Trends in Solid Adsorbent Materials Development for CO2 Capture

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Review 2

Trends in Solid Adsorbent Materials Development for CO Capture Maryam Pardakhti, Tahereh Jafari, Zachary Tobin, Biswanath Dutta, Ehsan Moharreri, Nikoo Saveh Shemshaki, Steven L. Suib, and Ranjan Srivastava ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.9b08487 • Publication Date (Web): 22 Aug 2019 Downloaded from pubs.acs.org on August 23, 2019

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ACS Applied Materials & Interfaces

Trends in Solid Adsorbent Materials Development for CO2 Capture Maryam Pardakhtia, Tahereh Jafarib, Zachary Tobin c, Biswanath Dutta c, Ehsan Moharreri b, Nikoo S. Shemshakid, Steven Suib b,c,*, Ranjan Srivastavaa,* Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT 06269, United States a

b

Institute of Material Science, University of Connecticut, Storrs, CT 06269, United States

c

Department of Chemistry, University of Connecticut, Storrs, CT 06269, United States

Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, United States d

*Corresponding Authors: [email protected], [email protected] Keywords: CO2 adsorption and separation, carbon capture, porous materials, solid adsorbent, surface functionalization.

Table of Contents

1

2

Introduction ............................................................................................................................2 1.1

Climate Change ..............................................................................................................2

1.2

CO2 Emissions Mitigation..............................................................................................3

1.3

Overview of Classical Computational Studies of CO2 Adsorption..........................4

Materials for CO2 Capture ...................................................................................................5 2.1

Carbon Based Materials................................................................................................7

2.1.1. Activated Carbons (ACs) .......................................................................................7 2.1.2. Ordered Porous Carbons.......................................................................................9 2.1.3. Carbon Fibers ........................................................................................................11 2.1.4. Graphene................................................................................................................12 2.2

Silica/Alumina/Zeolite ..................................................................................................16

2.2.1

Silica........................................................................................................................16

2.2.2

Alumina and Nanoclays .......................................................................................21

2.2.3

Zeolite .....................................................................................................................23

2.3

Porous Crystalline Solids ............................................................................................26

2.3.1

Metal Organic Frameworks (MOFs)...................................................................26

2.3.2

Zeolite Imidazolate Framework (ZIFs)...............................................................35 1 ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

2.3.3 2.4 3

Covalent Organic Frameworks (COFs) and polymers ....................................36

Metal Oxides .................................................................................................................46

Conclusion and Future Perspective .................................................................................47

References...................................................................................................................................48

Abstract The United Nations (UN) recent report has warned about the excessive CO2 emissions and the necessity of making efforts to keep the increase in temperature below 2 °C. Current CO2 capture technologies are inadequate in contributing towards reaching that goal, and effective mitigation strategies must be pursued. In this work, we summarized trends in materials development for CO2 adsorption with focus on recent studies. We put adsorbent materials into four main groups of (I) carbon-based materials, (II) silica/alumina/zeolites, (III) porous crystalline solids, and (IV) metal oxides. Trends in computational investigations along with experimental findings are covered to find inform finding of promising candidates in light of practical challenges imposed by process economics. 1 1.1

Introduction Climate Change

Greenhouse gas emissions and anthropogenic CO2 emissions contribute to climate change1. This unwanted effect is one of the most challenging and urgent environmental issues facing the world today. Due to the increasing global population and the resulting elevated energy demands, CO2 emissions will continue to increase. Destruction of ecosystems, floods, and droughts are possible consequences of climate change that will adversely affect future generations. The Intergovernmental Panel on Climate Change (IPCC) has suggested that mitigation efforts should be implemented beyond those already in place. Otherwise, by the year 2100, warming will lead to severe risks, including species extinction, global and regional food insecurity, and constraints on human activities. Mitigation pathways require near-zero emissions of CO2 along with other greenhouse gases (GHG), which poses substantial technological challenges2. The U.S. National Oceanic and Atmospheric Administration (NOAA) reported that the concentration of atmospheric CO2 passed the red line of 400 ppm in 2016, reaching 414.7 ppm

2 ACS Paragon Plus Environment

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in May 2019. It is further projected to reach 500 ppm by 20503,4. This dramatic increase in CO2 in 2019 is equivalent to 40 billion tons per year, which as the leading source of greenhouse gases, has a tremendous impact on climate change. Consequently, most developed countries adopted the very first universal, legally binding global climate agreement to limit CO2 emission to reduce adverse effects. Various studies have pointed out that CO2 atmospheric levels should be controlled to a range of 350-450 levels5. About 45% of CO2 emissions are related to industrial and thermoelectric power plants through burning fossil fuels (coal, oil and natural gas)6. 1.2

CO2 Emissions Mitigation

CO2 emissions can be reduced by the development of new infrastructures for cleaner sources of energy (hydrogen, solar energy or nuclear power) as a long-term program. Carbon capture and storage (CCS) technologies provide immediate action to alleviate CO2 emissions by developing efficient materials for CO2 adsorption and storage. CCS technologies enable the industry to use fossil fuels while preventing CO2 emissions into the atmosphere. CCS starts with CO2 uptake from main source (power plants, refineries) followed by compression and transportation to the reservoirs for permanent storage. The bottleneck for this approach is the expensive CO2 capture step, which accounts for more than 60% of the whole CCS process cost7. There are various technologies to capture CO2, including absorption8, membrane technology9, cryogenic CO2 capture10, and adsorption11. The conventional approach of absorption by liquid amines demonstrates high efficiency, but suffers from corrosion, considerable energy loss, and inefficient regeneration12. However, CO2 capture by solid adsorbents offers benefits, such as high adsorption capacity, easy recovery, high uptake efficiency under humid conditions, easy handling, and materials stability13,14. Based on the type of CO2 production, there are three CO2 uptake processes: (1) pre-combustion capture, (2) oxy-fuel combustion, and (3) post-combustion capture15,16. Each process requires different operating conditions and optimization of the adsorbent materials. The requirement of pure oxygen for oxy-fuel combustion makes this a highly expensive process which is not competitive with the other gas capture technologies. The gas mixture of CO2/H2 must be separated in the pre-combustion process under high pressures up to 40 bar. Separation of CO2 from H2 is much easier than from N2 or O2. The separated H2 can be used as a clean source of energy, and the CO2 can be processed for storage. However, the precombustion process suffers from the high cost of equipment, high temperature, pressure, and low efficiency17. The more feasible capture methodology is post-combustion operation, which is



consistent with current power plants’ infrastructures16. The more challenging post-combustion adsorption takes place under atmospheric pressure and low CO2 concentration of 15%. CO2 capture by porous materials may go through pressure swing adsorption (PSA) and vacuum swing adsorption (VSA) in ambient temperature environments. They can be categorized under four circumstances (I) natural gas purification using PSA (CO2:CH4=10:90); (II) landfill gas separation using PSA (CO2:CH4=50:50); (III) landfill gas separation using VSA (CO2:CH4=50:50); and (IV) flue gas separation using VSA (CO2:N2=10:90). The first two cases undergo higher pressures of about 5 bar, whereas the latter two are under lower pressures of about 1 bar18. 1.3

Overview of Classical Computational Studies of CO2 Adsorption

Computational methods have been crucial for the investigation of porous materials properties and applications, by providing time and cost-effective alternatives to experimentation (especially for an extensive library of materials)19. Computational studies also help in the understanding of molecular interactions20. One of the most common methods for adsorption and separation is grand canonical Monte Carlo (GCMC) molecular simulation21,22. GCMC is widely used to simulate adsorption processes of gas molecules in crystalline porous materials. Adsorption studies benefit from GCMC simulation for evaluation of single gas uptake by an adsorbent, as well as selectivity of an adsorbent for a gas mixture. Importantly, such analysis can be simulated for various temperatures and pressures. With a grand canonical ensemble, the chemical potential, the volume, and the temperature of the adsorbate phase (gas phase) of the system are kept fixed. However, the number of molecules in the gas phase is free to fluctuate until the chemical potential in the adsorbent phase equals that of the adsorbate21,22. Monte Carlo (MC) simulation allows gas molecules to make various random moves, such as translations or rotations of existing molecules in the system, insertions of new gas molecules into the ensemble, or deletions of gas molecules from the ensemble. The Boltzmann statistic criteria determine whether the moves are accepted or not23. To carry out the simulation, atomic structures of adsorbate and adsorbent phases and force-field potentials are required. These structures are used to explain the bonding and nonbonding interactions between phases. More accurate force-field models lead to more robust adsorption simulations; however, they are limited by the high computational cost21,24,25. Molecular dynamics (MD) simulations investigate the time evolution of adsorption, usually at the femtosecond scale and are used for non-equilibrium conditions for studying the rate of adsorption21,22,25. The trajectory of a particle is calculated using Newton’s laws of motion. Kinetics


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of adsorption and diffusion properties of the adsorbate can be evaluated from MD simulations in studying non-equilibrium processes26.

Molecular simulations, supplemented by data science,

facilitate large-scale screening of porous materials in the realm of material discovery27–29. On the other hand, machine learning (ML) algorithms are beneficial for supervised prediction of adsorption capacity where enough data for structure and adsorption performance of porous materials is available. Given enough accuracy, machine learning-based methods are desirable compared to molecular simulations due to cost-effectiveness 2

Materials for CO2 Capture

Based on the adsorption condition (pre-combustion or post-combustion), different materials have been developed to obtain the highest efficiency for CO2 uptake. Historically activated carbons (ACs) and zeolites were among the first solid adsorbents applied for CO2 capture. However, many different materials such as metal organic frameworks (MOFs), polymers, and metal oxides have been recently designed to improve the CO2 adsorption efficiency. Figure 1 shows the increasing interest on CO2 capture studies focusing on solid materials. The following criteria are commonly used to evaluate CO2 uptake on solid adsorbents18. 

CO2 adsorption capacity under adsorption condition, 𝑁𝑎𝑑𝑠 𝐶𝑂2



Selectivity, 𝑆 =



Regenerability (%),𝑅 =



𝑑𝑒𝑠 working CO2 capacity, ∆𝑁𝐶𝑂2 = 𝑁𝑎𝑑𝑠 𝐶𝑂2 ― 𝑁𝐶𝑂2 = 𝐶𝑂2 𝑙𝑜𝑎𝑑𝑖𝑛𝑔 𝑎𝑡 𝑎𝑑𝑠𝑜𝑟𝑝𝑡𝑖𝑜𝑛 𝑝𝑟𝑒𝑠𝑠𝑢𝑟𝑒 ―

( )( ) 𝑥1

𝑥2

𝑦1

(∆𝑁

𝑦2

𝐶𝑂2

)

𝑁𝑎𝑑𝑠 𝐶𝑂2 × 100

𝐶𝑂2 𝑙𝑜𝑎𝑑𝑖𝑛𝑔 𝑎𝑡 𝑑𝑒𝑠𝑜𝑟𝑝𝑡𝑖𝑜𝑛 𝑝𝑟𝑒𝑠𝑠𝑢𝑟𝑒 𝑁𝑎𝑑𝑠 1 : Adsorbed component 1 (CO2) under adsorption condition 𝑁𝑎𝑑𝑠 2 : Adsorbed component 2 (N2 or CH4) under adsorption condition 𝑦1: mole fraction of component 1 (CO2) in gas phase 𝑦2: mole fraction of component 2 (N2 or CH4) in gas phase 𝑥1: mole fraction of component 1 (CO2) in adsorbed phase 𝑥2: mole fraction of component 2 (N2 or CH4) in adsorbed phase



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600 500 carbon-based materials Silica alumina zeolite polymer porous crystalline solids

400 300 200 100 0 2010

2011

2012

2013

2014

2015

2016

2017

2018

Figure 1. Number of publications on CO2 capture with various solid materials since 2010. Search in SciFinder with keywords of “CO2 capture” or “carbon dioxide capture” or “CO2 separation” or “CO2 uptake” and each solid adsorbent category in this study. To enhance CO2 adsorption, amine functionalization has been commonly used, either by post-synthesis grafting or impregnation during synthesis30. Introducing nitrogen onto a carbon surface improves the electron density and increases the basicity of the material, causing a stronger contact between the adsorbent and the CO2 molecule through Lewis acid/Lewis base interaction31. There has also been doping of nitrogen or other atoms into the network which poses certain advantages over amine functionalization, mainly stability and lack of leaching over regeneration cycles31. It is not trivial to exemplify the effect of N doping experimentally on materials with disordered pore architecture and complex surface chemistry (such as the presence of other functional groups). Wang and Yang et al. (2011) show that N doped carbons with lower surface areas adsorb more CO2 than pristine carbon materials that have relatively larger surface areas at 25 °C32. Kumar et al. (2015) employed Monte Carlo simulations to study the effect of N doped carbons with different pore geometries, and concluded that nitrogen doping has an effect on the pore architecture, leading to a change in how the CO2 molecule is adsorbed31. Adeniran et al. (2016) investigated CO2 adsorption in a series of carbon materials with varying pore sizes and varying nitrogen content, and concluded that micropores of 0.7 nm is optimal33. Sánchez-Sánchez et al. (2014) determined that at 25 °C nitrogen content is the main factor for CO2 adsorption, but at 0 °C the main factor is micropore volume34. Babu et al synthesized vertically aligned carbon nanotubes (VACNT) and integrated nitrogen atoms into the framework via N2 rf plasma treatment35. The materials being well-defined, with reproducible mesoporous pore structure and a chemically homogeneous surface were chosen to avoid the interfering influence of changing pore structure. There was a slight decrease in surface area with nitrogen incorporation, but the increased CO2


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adsorption was found to be greater than zeolites, carbon nanotubes, mesoporous carbon, or even nitrogen-doped mesoporous carbon35. Nitrogen is not the only element that increases CO2 adsorption when doped into carbon structures. Tascon et al proved that phosphorus and oxygen groups provide adsorption sites for CO2 molecules. Seema et al reported that sulfur-doped porous carbons can be more effective that undoped porous carbons, and even nitrogen-doped porous carbons36. Zhao et al. (2012) reported the introduction of potassium ions into porous carbons, which saw an increase in CO2 uptake and selectivity than nitrogen-doped porous carbons37. Ma et al. (2019) studied porous carbons doped with OH, Li, Na and K for both CO2 adsorption and CO2 selectivity in CO2/CH4 systems38. Lithium-doped porous carbons saw the highest CO2 adsorption, while potassiumdoped porous carbons saw the highest selectivity38. All alkali-doped systems had higher adsorption and selectivity than undoped porous carbons38. 2.1

Carbon Based Materials

Among various high-performing adsorbents, carbon-based materials make up a large proportion of adsorbents with several applications in catalysis, adsorption, and storage devices. Carbonbased materials provide several advantages, such as low-cost precursor materials and synthesis techniques, controllable textural properties of pore size and surface area, selective adsorption, hydrophobicity, high-temperature stability, and easy recovery39,40. 2.1.1. Activated Carbons (ACs) Many studies have shown activated carbons as promising adsorbents in the carbon capture process, due to abundant feedstock, low-cost materials, high available surface, and high adsorptive characteristics. The adsorptive properties and activation process of activated carbon can be attributed to the origin and composition of raw materials. Different precursors of activated carbon have been reported, including N-rich chitosan, which needs high-temperature calcination followed by either physical or chemical activation, bagasse41, rice husk42, palm fiber and shell43, coconut shell44, waste biomass45,46, and porous organic polymers47, among many others. Physically activated carbon materials have been treated with a gas stream of CO2, O2, or steam with simultaneous pyrolysis. However, chemically activated carbons have been processed with chemicals such as salts, base or acids. Table 1 summarizes some activated carbon with different sources and activation steps, with the focus on studies reporting since 2016. Most of the reported



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ACs for CO2 capture involve nitrogen doping or textural properties tuning, optimizing one or both together. Sethia and Sayari (2015) have developed super adsorbent ACs (CO2 capacity 5.39 mmol/g) for CO2 removal at 25oC and 1 bar with high selectivity of CO2 over N2. The activated carbon materials contain significant nitrogen content (5.07 mmol/g) with high surface area (1,317 m2/g) and large pore volume (0.27 cm3/g), resulting in high adsorption and selectivity. Both doped nitrogen and textural properties control the CO2 adsorption process, which is confirmed by fitted dual-site Langmuir modeling indicating two types of active sites. However, the role of ultramicropores is predominant48. Coromina et al. (2016) designed micro-porous ACs materials through a green and simple method from two natural inexpensive precursors of Jujun grass and Camellia japonica to obtain a highly porous AC46. Textural properties of these ACs were adjusted by modulating activation procedures (temperature and KOH/carbon ratio) which resulted in high adsorption capacity of obtained ACs for both pre-combustion (21.1 mmol/g at 20 bar) and post-combustion CO2 capture (5 mmol/g at 1 bar). However, the heat of adsorption was not reported. This information, if available, could shed light on the adsorption mechanism. Studies of CO2 adsorption equilibria and kinetics are useful for determining which type of CO2 adsorption (physisorption or chemisorption) dominates, as well as the adsorption isotherm models which are useful for precise simulation of CO2 based adsorption cooling and adsorbed gas storage systems49,50. Although nitrogen content and pore diameter significantly contributing to enhanced adsorption, the challenge in scaling up the synthesis of adsorbent materials remains to be addressed. Environmentally friendly methods such as using organic waste as a source of carbon is worth increased attention. Thermal stability and scale of the adsorption process needs to be fully studied for these materials. Table 1. List of various sources and activation type for activated carbons (ACs). Precursor Source Rice husk Delayed oil sands coke sea mango (cerbera odollam), SMAC Coca Cola waste

CO2 P Adsorption (bar) (mmol/g)

Activation Type

T (°C)

Chemical / phosphoric acid

30

1

5.43

chemical / KOH

50

0.66

5.63

phosphoric acid (H3PO4)

60

0.15

KOH

25

1


Other Modification

Ref.

Melaminenitrogenated Amine impregnation

42

0.52■

Aminemodification

52

5.22

-

53

51

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waste ionexchange resin

KOH

30

1

1.84■

-

54

α-D-glucose

Potassium oxalate/ less toxic than KOH

25

1

4.5

-

55

Peanut shaped packaging waste

KOH

25

1

4.2

-

56

Physical activation 25 1 2-3 under CO2 Physical activation Palm kernel shell 25 1 2.13 under CO2 gas stream ■ Adsorption unit is converted from [mg/g] as reported in original reference to [mmol/g]. Biomass waste

57

58

2.1.2. Ordered Porous Carbons Activated carbon materials have advantages such as thermal stability, low sensitivity to moisture, availability, and low cost. However, these materials are more suitable for high-pressure applications59. To improve low-pressure adsorption (pre-combustion), ACs are made and modified by tuning surface areas and pore sizes by synthesis of ordered porous carbons, and chemical modification of adsorbent surfaces60. There are various methods used for the synthesis of ordered mesoporous carbon (OMC) materials. Soft template and hard template methods have proven to be most promising for achieving high surface areas and narrow pore distributions61. The soft template method is based on self-assembly of block co-polymers, co-condensation, and carbonization. Using such an approach eliminates the need for introducing pre-synthesized templates and their subsequent removal. The hard template method is based on using silica nanostructures as the template, filling with carbon precursor followed by carbonization and subsequent template removal with NaOH or HF61. OMC adsorption capability may be further improved by morphological and chemical modifications. Micropore surface area and micropore volume are essential factors for CO2 adsorption62,63. Micropore volume is shown to be the most effective factor for low-temperature adsorption (273 K, 1 bar), while the surface composition is the dominant factor at higher temperatures or lower relative pressures for sulfur-doped carbon materials64. Various synthetic routes to make functionalized ordered mesoporous carbons have also been studied. Making nitrogen functionalized ordered mesoporous carbon is achieved by a variety of means, including using a nitrogen-containing organic reagent65, post-synthetic loading by dispersion of amine-containing reagents and subsequent heat treatment under N2 atmosphere66,67, post-synthetic loading by ammonia flow68, or a combination of nitrogen-containing reagents, followed by post-treatment69. While nitrogen incorporation may have side-effects on structural properties this can increase



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selective CO2 adsorption of carbon-based materials,70,71 even when no new porosity is created by the addition of N species35 (see Table 2). Nitrogen doping has been shown to be a promising method to enhance CO2 adsorption performance of carbon materials. Ashourirad et al. (2015) studied a series of highly porous nitrogen-doped carbon (CPCs) materials synthesized with nitrogen-rich benzimidazole-linked polymers (BILPs) activated by KOH. They reported characteristics of N-rich porous carbon materials (including quaternary/graphitic, pyrrolic, pyridinic, and pyridine N-oxide). At low pressures (1 bar and 298 K) CPC-550 (activated at 550K) showed the highest CO2 adsorption (5.8 mmol/g) among other CPCs and CO2/N2 selectivity of 59 at 298 K. At high pressures CPC700 showcased the highest CO2 uptake of 1.131 g/g at 298 K and 30 bar (see Table 3)72. Kumar et al. (2015) studied the ability of carbon slit-pores to take up CO2. Specifically, they looked at carbon slit-pores with pore widths ranging from 0.8-2.0 nm, as well as two disordered carbon structures RPC1 and RPC2 with slit-pore widths of 0.8 and 1.2 nm respectively. Here, the term “RPC” stands for “randomly placed carbon.” CO2 molecules were found to sit on slit structures better than disordered architectures. On the other hand, N-doping improved CO2/N2 selectivity while not significantly enhancing the CO2 uptake31 (see Table 2). The cost of preparation of highly engineered nanostructured adsorbent material and scalability of the process are the main challenges that need to be addressed. Moreover, high surface area and pore volume may lead to limited selectivity of CO2/N2 and CO2/CH472,73. Table 2. Ordered mesoporous carbon and CO2 uptake at ambient temperature and pressure conditions. OMC material

N-doped mesoporous carbon Activated Carbon Spheres (CS); nitrogen-doped CS Ordered Micromesoporous

Surface Area (m2/g)

494-1417

11471224

828

Pore Micropore Volume s Volume (cm3/g) (cm3/g)

0.310.47

0.15-0.4

Functionalization; Loading Tertiary N, Amino groups, quaternary N, pyridine-N-oxide; ~ Total elemental N up to 13 wt%

pyridinic and pyrrolic N 2.8-3.55 0.35-0.37 ~7% maximum N loading 0.71

0.33

None


CO2 adsorption (mmol/g) Ref. @ 298 K and 1.0 bar

2.8-3.2

65

3.7-4.1

63

3.01

62

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hybrid carbon nanosphere adsorbent (OM-CNS

2.1.3. Carbon Fibers Activated carbon fibers (ACFs) have been considered promising adsorbents due to their high specific surface area, narrow pore size distribution, and abundant micron size pores74. Narrow pore size distribution of ACFs leads to high adsorption capacity and rapid rates of adsorption40. The fibrous shape of ACFs offers easy handling in comparison with powders and granular materials39. Commercial ACFs modified by chemical activation using KOH have been evaluated for CO2 capture under atmospheric pressure39. The textural properties of ACFs were modulated by KOH concentration in which the optimum concentration of KOH maximized the surface area of carbon fibers. The effect of nitrogen doping on ACFs has been studied, which indicated that the CO2 uptake is mainly controlled by the porous structure of ACF. Nitrogen content increases the CO2 adsorption in a short period, which can be used for swing adsorption systems due to the short cycles75. Polyamide (PAN)-based activated carbon fibers (ACFs) were modified by randomly oriented carbon nanotubes (CNTs) by Chiang et al. (2017). CNT growth on ACFs reduced the specific surface area and pore volume of ACFs while improving the smoothness by increasing anchoring sites. Pretreatment of ACFs with cobalt acetate produced a carbonaceous adsorbent with nitrogen moieties of pyridine-like structures of six-member rings which improved the CO2 capacity. The isosteric heat of adsorption indicated physical adsorption, which is an advantage of CNT growth on ACFs (less than 80 KJ/mol)76. Wang et al. (2016) investigated the effect of pore size (pore diameter, 1.0-3.0 nm) and phase interactions by using GCMC simulations for ACs modified with functional groups of −COOH, −CO, −OH separately in an equimolar mixture of CO2/CH4 in a pressure range of 0.05-10 MPa. For AC materials, increasing the pore size at low and high pressures increased CO2 adsorption capacity while decreasing the CO2/CH4 selectivity. Activated carbon with a modified –COOH surface showed high selectivity for CO2/CH4 (55 with electrostatic interaction, at 0.25 MPa and 298 K) highlighting the importance of electrostatic interactions and surface chemistry at low pressures. With a pore size of 3.0 nm, adsorption capacity at 298 K and 3 MPa was reported as 1.93 mmol/g and CO2/CH4 selectivity of 3.6573. Biase et al. (2015) studied computational models of high surface area activated carbon Maxsorb (MSC-30, surface area= 3,000-3,400 m2/g) in CO2 adsorption performance and presented an MSC-30 model with optimized features. In the GCMC simulation, coronene platelets (CR) were



set up to represent MSC-30 at pressures between 0-25 bar and the role of parameters such as structural models and curvature, pore size, surface area, and functional groups (CR, coronene functionalized with two hydroxylic groups (CR-(OH)2), and coronene functionalized with three hydroxylic groups (CR-(OH)3)) were investigated. The reported model is CRNL-(OH)2 (corannulene functionalized with two hydroxylic groups with curvature structure, surface area= 3237 m2/g) that has a very close adsorption capacity as that of MSC-30 and so was suggested to be the representative of Maxsorb in structural modification studies77,78. 2.1.4.

Graphene

Graphene, a relatively new synthetic allotropic carbonaceous material, has emerged to attract much attention due to its unique chemical and physical properties. These unique properties include large surface area (up to 2,630 m2/g), mechanical strength, chemical stability, and high thermal conductivity. Therefore, graphene has many applications including usage for supercapacitors, transistors, solar cells, touch panels, DNA sequencing, gas sensors, and for hazardous materials uptake79–81. However, bulk production of graphene suppresses its unique properties due to restacking of graphene layers80. Chandra et al. (2012) reported nitrogen-doping graphene through chemical activation of polypyrrole functionalized graphene sheets. The CO2 adsorption capability of nitrogen-doped graphene (NG) has been evaluated under atmospheric pressure and room temperature, revealing a large adsorption capacity of 4.3 mmol/g81. Kemp et al. (2013) carried out additional work on nitrogen-doped reduced graphene using polyaniline (PANI) to dope nitrogen homogeneously in porous graphene materials. The study demonstrated that a combination of N-content and pore size distribution control the CO2 adsorption. The high degree of reversibility and high selectivity of CO2 adsorption are the main advantages of the PANI doped graphene82. Investigation of CO2 adsorption on monolayer graphene on a silicon carbide substrate (001) at 30K by Takeuchi et al. (2017) showed low energy requirement for recovery (25-30 kJ/mol) indicating physisorption of CO2 on monolayer graphene83. Carbon-based materials performance in CO2 adsorption has been improved by functional groups increasing the electrostatic interactions. In a theoretical study, Xiao et al. (2015) used density functional theory (DFT) on bare graphene, P-substituted (phosphorus-substituted) graphene, and PH2-grafted functionalized structures to investigate CO2 adsorption with and without humidity. Although bare graphene does not show much activity in CO2 adsorption, adding functionalized groups improved attraction of CO2 molecules. The presence of humidity was also studied in the P-substituted and PH2-grafted structures. In their theoretical study as H2O and CO2 molecules


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interact with each other through C–O water electrostatic interactions, the presence of water in the system enhances CO2 adsorption84. Computational studies including molecular simulation and DFT improve the design of functionalized and doped carbon-based materials through investigation of favorable adsorption sites and interactions31,85,86. Wang et al. (2016) applied DFT to investigate the adsorption energy. Nitrogen doping creates more favorable adsorption sites on graphene for CO2 molecules and increases CO2 adsorption through enhancement of the adsorbate/adsorbent electrostatic interactions85. In this study amide and pyridine functional groups were reported as more effective than aniline and pyrrole functional groups due to higher energy of adsorption. Sulfur doping (Sdoping) increases the interaction between CO2 molecules and carbonaceous materials86,87. Li et al. (2017) studied the effect of sulfur doping on CO2 adsorption (at 300 K and 1 bar) in S-graphite planes. The adsorbent was S-graphite split pore, with two 3-D layers of graphene with different percentages of sulfur in the structure (7.94%- 33.12%). The case study was carried out in various pore sizes (H: plane distance) ranging from 0.6 – 1.1 nm. The CO2 uptake was investigated through GCMC simulation and DFT calculations. By increasing the sulfur content to 33.12%, the CO2 uptake of sulfur-doped graphite increased by 39.85% (51.001 mmol/mol) compared to the pristine graphite split. The improvement was also observed in the CO2/N2 selectivity of S-doped graphite with increasing sulfur amount. The phenomenon was explained through DFT calculations as stronger interactions occurring between S-graphene and carbon dioxide compared to the pristine graphite structure. In the presence of water, CO2 adsorption on S-graphite was higher than pristine graphite. Thus, S-graphite is a promising candidate for CO2 capture in humid conditions86. Synthesis reactions using sulfur has been disadvantaged from the toxic materials such as H2S, sulfuric acid, thiophene. Therefore, despite desirable adsorption capacities and selectivities, environmentally benign synthesis routes for these materials has remained a challenge. Two-dimensional polyaniline (C3N), the hole-free crystalline extension of graphene with orderly distributed nitrogen in the 2D lattice88, is another carbon material. It provides several advantages, such as excellent CO2 adsorption capacity due to the strong electrostatic interactions with CO2 molecules. C3N has several other advantages, including low cost, simple synthesis, environmentally benign impact, and doping flexibility, making this material a remarkable candidate for a wide range of applications 88. Li et al. (2017), using GCMC simulation and DFT calculations, investigated CO2 adsorption capacity and selectivity of C3N in gas mixtures of CO2/CO, CO2/H2, and CO2/CH4 at low pressures (0.15 and 1 bar) and 300 K. They observed significant CO2



Page 14 of 65

selectivity in C3N, with values of 15, 579, and 87 for CO2/CO, CO2/H2, and CO2/CH4 at 300 K and 0.15 bar, respectively and explained these data using calculations of the heat of adsorption where larger electric quadrupole moments and larger polarizability of CO2 molecules lead to a higher interaction with the C3N surface89. Details are provided in Table 4. Table 3. CO2 adsorption in selected carbon-based materials at low and high pressures. Material

Surface Pore Area Volume (m2/g) (cm3/g)

Density (g/cm3)

BILP-5

626

0.39

-

CPC-550a

1630

0.66

-

CPC-600a

2059

0.89

-

CPC-650a

2967

1.31

-

CPC-700a

3242

1.51

-

CPC-800a

2872

1.49

-

Slit (0.8 nm)

1297

0.387

2.01

N-slit (0.8 nm)

1289

0.401

2.02

Slit (1.2 nm)

1349

0.645

1.34

N-slit (1.2 nm)

1303

0.669

1.35

T (K)

P CO2 Uptake (bar) (mmol/g)

273 298 298 313 273 298 298 313 298 273 298 298 313 298 273 298 298 313 298 273 298 298 313 298 273 298 298 313 298 298 298 298 298 298 298 298 298

1.0 0.15 1.0 1.0 1.0 0.15 1.0 1.0 30 1.0 0.15 1.0 1.0 30 1.0 0.15 1.0 1.0 30 1.0 0.15 1.0 1.0 30 1.0 0.15 1.0 1.0 30 1 60 1 60 1 60 1 60


2.9 0.6 2.0 1.2 8.3 2.1 5.8 4.3 14.7 7.5 1.3 4.7 3.3 17.3 6.8 0.9 4.0 2.7 21.3 5.9 0.7 3.3 2.3 25.7 5.4 0.7 3.1 2.0 23.6 ~4.3 b ~4.5 b ~4.5 b ~4.5 b ~1.4 b ~9.5 b ~1.6 b ~10 b

Selectivity at 1 bar

Ref.

95 @ 273 K 36 @ 298 K

72

65 @ 273 K 59 @ 298 K

72

48 @ 273 K 26 @ 298 K

72

24 @ 273 K 17 @ 298 K

72

16 @ 273 K 12 @ 298 K

72

19 @ 273 K 15 @ 298 K

72

~ 22 b

31

~ 27 b

31

~ 7b

31

~ 7b

31

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RPC1

5861

2.834

0.30

N-RPC1

5823

2.815

0.30

RPC2

2993

1.156

0.60

N-RPC2

2910

1.407

0.60

298 298 298 298 298 298 298 298

1 60 1 60 1 60 1 60

~0.4 ~29.0 ~0.55 ~29.0 ~0.65 ~8.0 ~0.75 ~9.0

-

31

-

31

-

31

-

31

NG7 298 2.7 82 (activated at 700 979.6 0.440 1 9.07 273 5.8 °C) BILPs: benzimidazole-linked polymers. CPC: N-doped carbon. a N-doped carbon material synthesized from benzimidazole-linked polymers in temperature range of 500-800 °C. b GCMC simulation results. Table 4. CO2 adsorption of C3N at low pressures in pure and gas mixtures. Material

C 3N

T (K)

P (bar)

300 300 350 350

0.15 1.0 0.15 1.0

300 300

0.15 1.0

300 300

0.15 1.0

300 300

0.15 1.0

Selectivity @ 300K and 0.15

CO2 Uptake (mmol/g)

Ref.

bar

3.99 1.86 2.07 6.27 CO2/CO equimolar mixture: 3.10/ 0.20 5.16/ 0.53 CO2/H2 equimolar mixture: 2.51/ 0.004 4.1/0.03 CO2/ CH4 (0.43:0.57) mixture: 3.02/ 0.04 4.1 /0.03

89

CO2/CO: 15

89

CO2/H2 :597 CO2/CH4:87

89

89

Graphene-based membranes are energy-efficient for gas adsorption purpose. Their robustness under severe operating conditions makes them useful at large scales. The membrane performance is partly determined by pore size controlling the molecular sieving. MD simulations help investigating the separation mechanisms of gas mixtures such as CO2/N2 and CH4/CO2 through graphene-based membranes with small pore sizes

90–92.

Li et al. (2016) applied MD

simulations to not only study the selective adsorption of CO2 in mixture with N2 through graphene oxide (GO) membrane but also to understand the CO2/N2 adsorption mechanism and its permeability. The GO membrane sheet in the study contained randomly distributed hydroxyl and



epoxy groups. The high tendency of CO2 adsorption on GO layers was due to strong interactions (higher energy of adsorption) between GO and CO2 atoms. High degree of oxidation and large interlayer spacings in their study contributed to higher CO2 selectivity and permeability (lower permeability and CO2 selectivity) respectively. The highest selectivity was 24 with an interlayer spacing of 7.3 Å and a 40% oxidation rate. Higher selectivity was also observed in longer channels90. Khakpay et al. (2017) applied MD simulations to investigate concentration-dependent adsorption in CH4/CO2 mixtures in nanoporous graphene (NPG) and graphene oxide (NPGO) separation platforms. Functional groups led to higher CO2 adsorption capacity in graphene membranes as the oxygenated functional groups in the NPGO membrane showed higher CO2 adsorption capacity. CH4/CO2 selectivities in both NPG and NPGO membranes are as high as 5 and 6 respectively91. Investigating the utility of membrane technology for CO2 capture is an ongoing effort with challenges remaining in minimizing the high cost of membrane production in large scale. 2.2 2.2.1

Silica/Alumina/Zeolite Silica

Silica is one of the most abundant materials found in the world, existing in many different minerals in various environments. Silica exists commonly in nature as quartz, which makes up more than 10% of the earth crust. It is also the major component of sand, which is highly prevalent around the world. Silica can easily be synthesized with high surface area and porosity. It is possible to tune these properties through appropriate alterations in the synthesis process. In particular, mesoporous silica, with pores ranging from 2-50 nm, are used in a variety of applications, ranging from catalytic supports, drug delivery, energy storage, and molecular sieves. The Stöber process is a commonly used method to fabricate mesoporous silica nanoparticles. By reacting tetraethylorthosilicate with water in an alcoholic solvent, the precursor is hydrolyzed into small particles which then condense into the larger structure. Silica has shown promising activity as a support for CO2 adsorption systems. As a cheap, easily synthesized porous material, silica can act as a substrate to load with amines to trap and adsorb CO2. The type of porous silica used for CO2 adsorption has a pronounced effect on the performance of the combined adsorbent. Amorphous silica is a poor support for CO2 adsorption, due to a random array of pore sizes and shapes. The entire pore volume is not accessible to functionalizing agents and thus is not used. Ordered mesoporous silica is an excellent adsorbent


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support, not only because a much larger amount of the pore volume is accessible, but also because the characteristics of mesoporous silica, such as pore size, shape, or surface area, can easily be tuned via altering the synthesis. Mesoporous silica is commonly synthesized by forming an amorphous silica framework around an organic template. The template is then removed by either solvent extraction or calcination, leaving behind pores of defined shape and size93, examples of which are shown in Table 5. Table 5. Common Mesoporous Silica Support Characteristics [93]. Pore volume

Adsorbent

Surface Area (m2/g)

MCM-41

1229

1.15

2.7

SBA-15

950

1.31

6.6

KIT-6

895

1.22

6.0

HMS

561

1.44

9.8

(cm3/g)

Pore diameter (nm)

Functionalizing a mesoporous silica support with amine groups is an effective way to increase the effectiveness of CO2 adsorption. Primary and secondary amines all have affinities for CO2 shown in the following reactions6: CO2 + 2RNH2 → RNHCOO- +RNH3+ CO2 + 2R2NH → R2NCOO- + R2NH2+ The silica template reacts strongly with amines via the hydroxyls on the silica surface. The hydroxyl groups hydrogen bond with the amines, unraveling the amine chains and distributing them evenly throughout the silica framework. Different types of amines have different affinities for CO2 and selecting the right amine will affect the CO2 adsorption capacity of the material. Primary and secondary amines react more strongly with CO2 than tertiary amines, so silica loaded with primary or secondary amines will increase the possible loading of CO2. Maximizing the nitrogen weight percentage of the loaded amine increases the CO2 loading capacity93. There are two ways to load the silica framework with amine groups, amine impregnation and amine grafting. Amine impregnation involves physically mixing amines with the silica template by suspending porous silica into a solution of the amine of choice and a volatile solvent. The amine group impregnates the silica via diffusion into the pore space due to the concentration gradient and chemical affinity. Impregnation is followed by removal of the solvent by evaporation. Amine



grafting, or covalent linking of amine-containing compounds to the support, is advantageous compared to impregnated supports. The amine groups cannot be leached unless in a harsh chemical environment, making the adsorbent more stable, unlike impregnated materials94,95. Amine-functionalized silica adsorbents are commonly prepared through a two-step process. First, porous silica is synthesized by acidizing a solution of sodium silicate or tetraethyl orthosilicate using inorganic acid. Second, the synthesized porous silica is used as a substrate to support amines such as polyethylenimine (PEI), aminomethylpropanol (AMP), ethanolamine (MEA) and tetraethylenepentamine (TEPA) or to graft amino functional groups. Quant et al. (2017) have developed a one-step process for the grafting of amino functional groups, as the two-step method requires more energy to calcine the sample or more time to wash the silica surface before grafting. The one-step process was made possible by the co-condensation of silicon alkoxides and organosilanes. Mesoporous silica was prepared by mixing sodium silicate with 3aminopropyltriethoxysilane (APTES) through which pure CO2 was bubbled, acting as the acidic agent. Depending on CO2 concentration in the APTES solution, either a silica-gel adsorbent (SGA) or precipitated silica adsorbent (PSA) was formed. CO2 adsorption for PSA reached a maximum of 1.02 mmol/g at 50⁰C but abruptly dropped off at higher temperatures. CO2 adsorption for SGA reached a maximum of 0.80 mmol/g at 50⁰C.

However, adsorption levels slowly

decreased as temperature increased95. Commonly, mesoporous silica used for CO2 adsorption has a hierarchical porous structure.

Hierarchical silica particles are uniformly spherical,

nanoscale in size, and have a smooth surface, while having different pore sizes and morphologies that can be tuned. These characteristics make a hierarchical structure desirable for CO2 adsorption; however, synthesizing hierarchical mesoporous silica is complex, expensive and time-consuming. Zhao et al. (2017) synthesized silica with a trimodal mesoporous structure by physically mixing mesoporous SBA-15 and silica gel (HPS), which is simple, cheap and timesaving. The trimodal silica was used to prepare amine-functionalized adsorbents with TEPA. Adsorbents with different SBA-15/HPS and silica/amine ratios were prepared. Their CO2 adsorption capacities are shown below in Table 6 and compared to the characteristics of the sorbent, where the silica adsorbent is named, followed by the % grafting of TEPA. SHPS refers to a 1:1 ratio of SBA-15:HPS, 2SHPS is a 2:1 ratio and S2HPS is a 1:2 ratio96. Table 6. Effect of Surface Characteristics on CO2 Absorptivity of Amine-Functionalized Silica Supports [96]. Surface Area Pore Volume Pore Size CO2 adsorption Adsorbent (m2/g) (cm3/g) (nm) (mmol/g) HPS 40% 79.28 0.30 23 3.09


Page 18 of 65

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HPS 50%

42.15

0.19

23

4.26

61.72

0.44

6.1

2.94

28.70

0.2

-

4.1

SHPS 40%

104.37

0.63

23

3.18

SHPS 50%

34.62

0.32

23

4.61

93.42

0.76

23

3.27

54.24

0.48

23

5.05

92.95

0.52

23

3.14

30.12

0.26

23

4.63

SBA-15 40% SBA-15 50%

S2HPS 40% S2HPS 50% 2SHPS 40% 2SHPS 50%

Kishor et al. (2017) synthesized four different types of mesoporous silica: MCM-41, SBA-15, KIT16 & HV MCM-41, shown in Table 7. All four silica types were functionalized with PEHA. KIT-6 with no amine loading has 0.64 mol/kg at 30⁰C and 0.28 mol/kg 75⁰C adsorption capacity. With 40% amine loading, the adsorption capacity increased to 2.44 mol/kg at 30⁰C. With 60% amine loading, adsorption capacity further increased to 3.41 mol/kg at 75⁰C. Grafting more PEHA onto KIT-6 reduced CO2 adsorption due to the blocking of pores. Below 40% PEHA, the amine is homogenously distributed, and increasing the amine loading reduces active amine sites for adsorption by forming layers inside the silica channels. With an increase in temperature, viscosity of PEHA is decreased and the spacing between molecules is increased, exposing more active sites for adsorption. CO2 absorptivity of all four silica materials with 60% PEHA at 90 and 105⁰C at 1 bar are shown below, compared with their surface areas/pore volume before functionalization. Based on the absorptivity and characteristics of each material, higher pore volume improves the PEHA distribution inside the pore and thus the CO2 absorptivity97.



Page 20 of 65

Table 7. Characteristics and CO2 Adsorption of Functionalized Silica [97] Surface Area (m2/g)

Pore Volume (cm3/g)

Pore Size (nm)

CO2 Adsorption at 90 ⁰C and 1 bar (mmol/g)

KIT-6

857

1.25

6.6

4.08

CO2 Adsorption at 105 ⁰C and 1 bar (mmol/g) 4.48

SBA-15

853

1.23

6.6

3.97

4.5

MCM-41

1492

0.91

2.2

3.26

4.0

986

2.15

2.2

4.3

4.07

Adsorbent

HV MCM41

In theory, the presence of H2O during CO2 capture should improve amine adsorption efficiency due to the formation of carbonates and bicarbonates. However, as CO2 and H2O competitively adsorb and presence of H2O increases the possibility of amine leaching93. Fayaz et al. (2017) tested the effect of steam on CO2 adsorption for amine-grafted SBA-15 and for commercial silica (P10).

Both

silica

supports

were

grafted

with

3-[2-(2-aminoehtylamino)

ethylamino]-

propyltrimethoxysilane (Tri). The CO2 absorptivity was tested before exposure to steam and after 24 hours of exposure. The results for Tri-grafted SBA-15 are shown in Table 894. Steam treatment of functionalized SBA-15 reduced pore width, which increased resistance against diffusional mass transfer, and explaining the reduced CO2 adsorption. Prolonged steam treatment, up to 360 hours, led to blockage of pores and partial structural collapse of adsorbent. Grafted commercial silica showed higher hydrothermal stability than grafted synthesized SBA1594. Table 8. Effect of Steam Exposure on CO2 Adsorption of Mesoporous Silica [94] Sample SBA-15 SBA-15 24 h steam

CO2 Adsorption @ 25 ⁰C (mmol/g) 0.55



0.16

0.80

1.13

Amine incorporation into silica is one of the most effective methods in increasing CO2 interaction with the solid98–100. Lourenco et al. (2016) studied pristine and functionalized periodic mesoporous phenylene-silicas (Ph-PMO) through experimental investigation (up to 1000 KPa and T=298 K) and DFT calculations. They calculated the interaction energy of various group functionalized


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samples ( including -NH2, -NH, NO2 and SO3 ) with CO2 molecules and showed that although amine group in Ph-PMO structure led to smaller surface area and pore volume, it helped to reach higher CO2 capture as a result of higher CO2 adsorption affinity and interaction energy99. Amine functionalized SBA-15 led to higher CO2/CH4 selectivity in biogas up to a pressure of 1000 KPa at 25 °C. Marfa et al. (2018) experimentally and computationally (applied DFT calculation with meta-GGA approach) investigated CH4/CO2 separation using amine (APTES, TMMAP and 3DEAPTES) and diamine (N-[3-(trimethoxysilyl) propyl] ethylenediamine (N-3)]) functionalized SBA-15 materials. They reported CO2/CH4 selectivity of 15,000 in N-3@SBA-15 at low pressure (< 0.4 bar). At low pressures the high selectivity is due to CO2 chemisorption on the amine groups and low methane physisorption on the surface as the result of large pore size. At higher pressures, physisorption occurs from CO2 interaction with surface polar species100. Cation gating in zeolites contributes to gas separation efforts by providing the polar sites to attract polar molecules like CO2. The “trapdoor” role of cations is to limit the accessibility of pores based on the size and molecular electrostatic interactions. As a result, specific molecules such as CO2 can diffuse through materials, while other molecules cannot. In a recent study Coudert et al. (2017) applied ab initio molecular dynamics (AIMD) simulations and free energy studies to shed light on CO2 diffusion mechanisms through zeolite Na-RHO (3.80 Si/Al ratio) channel with narrow pores blocked by cations101.

CO2 was shown to enter the narrow pores, as the cation thermally

fluctuates in and out of the pore.79 Methane was studied as a control, as it lacks the strong adsorbate-zeolite interaction and was unable to squeeze through the pore despite the cation fluctuation.79 2.2.2

Alumina and Nanoclays

Aluminum oxide, also known as alumina, is a prominent mineral found worldwide. In 2018, the annual world production of alumina was about 130 million tons102. Alumina has found uses in the ceramic and material science disciplines due to its refractory capabilities. Alumina is synthesized from natural ores of aluminum hydroxide, namely bauxite, gibbsite, boehmite and diaspore. These compounds are purified by the Bayer process, where the ore is reacted with sodium hydroxide to purify the aluminum hydroxide, which is calcined to dehydrate the material and produce aluminum oxide103. Aluminum oxide, when functionalized, can act as a template for effective CO2 adsorption. Alumina materials commonly have high surface areas, large pore volumes, well-tailored meso-porosity, high crystallinity, and high thermal stability104. All the above characteristics are indicative of a



Page 22 of 65

material with high potential as a CO2 capture sorbent. Boehmite, a precursor to mesoporous alumina, through CO2 TPD, has shown high affinity for CO2104. Functionalizing mesoporous alumina would lead to even higher CO2 affinity. Feist et al. (2015) loaded γ-alumina with La2O3 to increase the CO2 adsorption capacity of γ-alumina. The loading of γ-alumina with La2O3 did not significantly change the surface area of the undoped γ-alumina, indicating the La2O3 does not block any alumina pores. CO2 adsorption capacity of Alumina with 0-7.5% of La2O3 is listed in Table 9105. Table 9. CO2 Adsorption of alumina with various La2O3 doping percentage [105]. La2O3 Doping (mol %) 0 2.5 3.5 7.5

CO2 Adsorption (μmol/g) 16.4 ± 0.6 36.8 ± 1.8 113 ± 9 92.8 ± 1.6

Gunathilake et al. (2016) synthesized an aluminum oxide material and grafted the system with (3cyanopropyl)-triethoxysilane and reacted it with hydroxylamine hydrochloride to convert the cyano groups into amidoxime groups. The CO2 adsorption of the material before and after hydroxylamine hydrochloride was measured at both 120 C and 25 C, with the results shown in Table 10. Samples were labeled Bh-CPX, where X denotes number of millimoles of CPTS organosilanes added in the synthesis. Samples were labeled Bh-AOX where X denotes the millimoles of CPTS in the synthesis, but these samples underwent post-synthesis modification to convert cyanopropyl (CP) groups to amidoxime(AO)104. Sakwa-Novak et al. (2014) grafted poly(ethylenimine) PEI onto mesoporous γ-alumina and exposed the material to varying times of steam treatment. CO2 adsorption of the material before and after was measured(see Table 11)106.

Table 10. CO2 Adsorption of Organosilane-Functionalized Boehmite at 1.2 atm [104]. Sample Bh* Bh-CP2 Bh-CP5 Bh-CP13 Bh-AO2 Bh-AO5 Bh-AO13

Surface Area (m2/g) 228 261 216 67 200 190 60

CO2 Adsorption @ 120 °C (mmol/g) 2.17 2.23 2.28 2.31 3.09 3.51 3.84


CO2 Adsorption @ 25 °C (mmol/g) 0.58 0.64 0.56 0.45 0.70 0.52 0.45

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Table 11. Effect of Steam on the CO2 Adsorption of PEI-Grafted Alumina [106] Surface Area Amine Loading CO2 Uptake @ 30 °C Sample (m2/g) (mmol N/g) (mmol/g) Untreated 38 7.81 1.71 sorbent 5 minutes 37 7.95 1.96 steam 1.5 hours 46 8.33 1.73 steam 12 hours 53 7.61 1.5 steam 24 hours 177 2.34 0.66 steam

2.2.3

Zeolite

Zeolites are a class of porous crystalline materials built of a periodic array of TO4 tetrahedra where T is represented by either aluminum or silicon93. While zeolites are found naturally, they are produced synthetically for industry. Commonly, zeolites are synthesized by heating aqueous solutions of alumina and silica with sodium hydroxide. Synthesized zeolites hold key advantages over natural occurring zeolites. Synthesis of zeolites offers immense control over the porosity and crystallinity of the material to a degree that cannot be found in nature. Since alumina and silica are extremely abundant materials, the theoretical supply of zeolite synthesis is unlimited. As of 2016, there were approximately 3 million tons of fabricated zeolites produced worldwide107. Zeolite frameworks are microporous, with pores on the order of 0.5-1.2 nm, forming networks of interconnecting channels or cages6. The resulting structure is a very stable material with high crystallinity, high surface area, and strong adsorption sites, making zeolites an attractive material to study in relation to CO2 adsorption108. In fact, zeolites have been extensively studied for CO2 adsorption. The microporosity of zeolites qualifies them as molecular sieves, which allows the selectivity of adsorption based on pore size59. Only molecules smaller than the pore size of the zeolite can be adsorbed. Due to the easily tunable pore size, zeolites can be tailored for the adsorption of CO2 based on the molecular sieving principle. The presence of aluminum atoms in the silicate-based framework increases the basicity of zeolites93. This effect is due to the lower electronegativity of aluminum compared to silicon. Addition of cations into the zeolite framework, such as Li, Na, or K, compensate for the negative framework charges from aluminum6. With decreased electronegativity of the added cations, the basicity of the zeolite increases. The higher



the base content of the zeolite, the higher the CO2 adsorption capacity93. Cations in the framework interact electrostatically with CO2 as well, attracting CO2 into the zeolite pores6. Certain zeolites exhibit the phenomenon of carbon gating, where CO2 can permeate the framework, but other compounds cannot. The gating phenomenon is commonly found in cationic zeolites where extra framework cations block the entrance of narrow pores. These pores are often connecting large cages to one another. Only CO2 can diffuse through the materials, bypassing the cations and moving from cage to cage. The gating effect gives high adsorption selectivities for CO2 over other small adsorbates, which is extremely useful when attempting to adsorb CO2 from a mixture of gases. Coudert et al. (2017) computationally studied the mechanism of CO2 adsorption into Na-RHO zeolite. Previously, the mechanism of carbon gating was believed to be based on the adsorbed CO2 molecule facilitating the movement of the cation out of the single 8ring (S8R) site. However, free energy calculations showed the free energy barrier of the cation movement is not significantly smaller when CO2 is present. By accounting for thermal motion and entropy at 298 K, the cation in the zeolite framework was shown to have a large amplitude of motion. About 3% of the time, the trapdoor is slightly ajar due to thermal motion. This opening is enough to allow CO2 to slide into the pores of the zeolite, and the free energy barrier for this movement is significantly reduced when the cation has moved. Other compounds, such as CH4, will not favorably diffuse into pores as the free energy barrier is much higher and so even when the trapdoor is open, movement will not occur101. Liu et al. (2017) tuned the pore structure and morphology of ZSM-5 by adding organosilanes to control pore growth. The zeolite ZSM-5 was studied because ZSM-5 has a high affinity for CO2 and is a high surface area crystalline zeolite. (3-aminopropyl) triethoxysilane (AMEO) and γ-chloropropyltriethoxysilane (CPTMO) were used as growth inhibitors for the synthesis of ZSM-5. These two functionalized ZSM-5 analogs were compared to a standard ZSM-5 zeolite. Surface area in Table 12 was determined by N2 sorption measurements. The SiO2/Al2O3 ratio was determined using X-ray fluorescence. CO2 adsorption sites were measured using CO2-TPD. The values in Table 13 represent the CO2 adsorption capacity of each sample in cm3/g, and these values were determined from CO2 adsorption isotherms. Using organosilanes to control and tune the pore size significantly increased the surface area, CO2 adsorption sites, and CO2 adsorption capacity. Organosilane samples were constructed of spherical aggregates of crystals, rough surfaces, and small particle sizes, while nonfunctionalized ZSM-5 had a smooth and angular surface. The increase in CO2 adsorption can also be attributed to the presence of mesopores in the functionalized ZSM-5 samples, which were


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responsible for facilitating CO2 diffusion and transfer through the framework and which increased the surface area109. To achieve gas separation efficiency, two units are required, a bulk separator and a purifier. Han et al. (2017) combined both units into a single hybrid process by packing a FAU-zeolite membrane with zeolite 5A pellets to separate CO2 from a mixture of CO2 and CH4. The zeolite 5A pellets handled the bulk separation and FAU-zeolite dealt with the purification. Packing the zeolite membrane with zeolite pellets enhanced the interfacial contact between the membrane and gas phase. As a result the separation of CO2 and CH4 is greater with zeolite 5A pellets packed into the FAU-zeolite membrane than with just the membrane110. Song et al. (2018) designed another material with gas separation efficiency in mind, regarding separation of CO2 and N2. Zeolites with relatively small micropores have shown decent CO2/N2 separation but the gas diffusion through the material was slow and limiting. Zeolites with larger micropores have higher CO2 adsorption but low CO2/N2 separation efficiency. Zeolite 5A is a larger micropore zeolite. Molecular layer deposition was used to coat zeolite 5A with an ultrathin layer of TiO2. The deposited TiO2 layer increased selectivity of CO2 and N2 separation by narrowing the zeolite pore mouth. Misalignment of the deposited layer and the zeolite pores is the cause of the increased selectivity and can be tailored by coating thickness. Zeolite 5A with an optimized TiO2 layer displayed CO2 adsorption capacity of 1.62 mmol/g and CO2 N2 selectivity of 70 mmol/g at 0.5 bar and room temperature111. Table 12. Characteristics of Functionalized ZSM-5 [109]. Sample CPTMO AMEO ZSM-5

Surface Area (m2/g)

SiO2/Al2O3

438 405 383

26 25.5 25

CO2 Adsorption Sites (μmol/g) 1,505 846 832

Table 13. CO2 Adsorption Capacity (mmol/g*) at Different Temperatures and 1 bar [109]. Sample 0⁰C 12.5⁰C 25⁰C CPTMO 2.62 2.31 1.97 AMEO 2.55 2.26 1.92 ZSM-5 2.39 2.11 1.82 3 * Unit is converted from [cm /g] to [mmol/g] (considering STP condition).


50⁰C 0.79 0.61 0.50


2.3

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Porous Crystalline Solids

Porous crystalline materials such as metal-organic frameworks (MOFs), zeolite imidazolate frameworks (ZIFs) and covalent organic frameworks (COFs) are more recent classes of porous materials with incredible tunability. These materials, either through synthesis or computational designs, have been gaining traction in the CO2 adsorbent research community to accelerate the search for the rational design of adsorbent materials 112. 2.3.1

Metal Organic Frameworks (MOFs)

Metal organic frameworks (MOFs), a class of crystalline porous materials, were introduced in 1995113 with a wide range of applications from purification114–117, separation118–120, and adsorption121,122 to catalysis123–126. A typical MOF structure is the result of self-assembly of metalcontaining clusters and organic linkers, creating a reticular network. The schematic structure of M-MOF-74, shown in Figure 2, is redrawn from reference110. M2O2(CO2)2 clusters along with DOT (2,5-dioxidoterephthalate) linkers are used to build a highly porous crystal structure.

DOT (2,5-dioxidoterephthalate)

M2O2(CO2)2

M-MOF-74

Figure 2. Schematic representation of a MOF building units. Mg-MOF-74 has shown exceptional CO2 adsorption capacity. M in M2O2(CO2)2 and M-MOF-74 denotes for Zn, Co, Ni, and or Mg. Redrawn from reference [117]. One of the most interesting aspects of the reticular network of MOFs is the tunable void space in the structure. Control over the size and geometry of a MOF is achieved by specifying the metal cluster and organic linker type along with the functional groups, leading to design and synthesis of more than 81,000 MOFs to date in the Cambridge Structural database (CSD).127 These materials all possess high surface areas of more than 10,000 m2/g128–130 and pore volumes of more than 5 cm3/g131. In addition to their high surface area, the bridged/intertwined porous structure of MOFs has made this solid material a welcoming host of gas or liquid molecules. On the other hand, gas molecules can be removed from the system due to the stable structure of


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MOFs. These specific features of MOFs (which contribute to adsorption-related applications), are the main reason for studying these porous materials in gas separation6,132,133.. Several factors such as functional groups (like amine group)134–139, open metal sites (OMSs)140, and pore properties significantly contribute to CO2 uptake performance of MOFs141. Extensive reviews reported both experimental and computational investigations of CO2 adsorption/desorption using MOFs17,142,143. The focus here is on the most recent CO2 capture studies on MOFs. 2.3.1.1. Metal type and open metal sites Metal site type in MOFs controls electrostatic interactions. The most recently studied MOFs, such as M-MOF-74 (M: metal like Mg, Co) and HKUST-1, with high CO2 adsorption capacity have metals such as Mg, Zn, and Co in their structure. Developing new structures require open metal sites of various metal ions in the structure144. Ethiraj et al. (2016) synthesized a cerium-based MOF with MOF-76 topology (MOF-76-Ce) proposing an easy synthesis method for MOFs with high thermal stability overcoming the challenge in gram-scale production where. desolvated MOF76-Ce-ds (activated at 250 °C with SBET= 754 m2/g) had shown15 wt% (4 mmol/g) CO2 adsorption capacity at 25 °C and 1.1 bar145. Asgari et al. (2018) synthesized M-BTT MOF (M= Cr, Mn, Fe, and Cu; BTT3− = 1,3,5-benzenetristetrazolate) with an experimental surface area in the range of 1,700-2,050 m2/g. Although Mn-BTT had higher surface area and pore volume, Cr-BTT showed higher CO2 adsorption capacity, ~4.5 mmol/g at 298 K and 1 bar. The DFT analysis showed the behavior of open metal sites in the interaction with CO2 molecules at low pressures of 0-1 bar and 298 K, revealing Cr-BTT had the highest number of open metal sites among the samples146. Zirconium metal in the structure of MOFs brings the benefits of high heat and moisture stability, which was shown to boost CO2 uptake147. Chen et al. (2016) introduced a moisture-stable threedimensional MOF with zirconium metal and −NH2 functionalized tetrazole pillars (SBET = 312 m2/g and pore volume = 0.17 cm3/g). The CO2 adsorption capacity was about 2.25 mmol/g with high CO2/N2 (127) and CO2/CH4 (131) selectivity at 298 K and 1 bar. Based on their computational analysis, the polar structure of the new MOF enhances CO2 capture148. In another study, a novel class of metallocyclam Zr-MOFs, VPI-100 (Cu) and VPI-100 (Ni) (VPI = Virginia Polytechnic Institute), were synthesized and tested for CO2 uptake and catalytic activities. The reported surface areas for the two materials were 398 and 344 m2/g, respectively. Extraordinary chemical stability was demonstrated by change of pH in the solution (by using different solvents such as phosphate, water, NaOH, 1M HCl, 6M HCl, and 8M HNO3). CO2 adsorption capacity of VPI100(Cu) at 296 K and 1 atm was 3.76 wt% (19.15 cm3/g at STP, 0.85 mmol/g) while in the Ni



Page 28 of 65

monologue case was 2.70 wt% (13.79 cm3/g at STP, 0.62 mmol/g149. To increase CO2 uptake on Zr-MOFs under post-combustion conditions, Li et al. (2018) studied the structure and performance of porphyrinic Zr-MOFs (known as PCN-X) by incorporating extra open metal sites of Fe+3 and Al+3. The addition of the extra sites led to a 22.1% and a 112.2% increases of CO2 adsorption compared to the pristine PCN-X at 1 bar and 298 K. Although PCN-X-100%-Fe had lower surface area compared to the pristine PCN-X (SBET 441 vs. 955 m2/g), higher CO2 adsorption was observed indicating that higher surface area did not guarantee higher adsorption capacity. Extra open metal sites provided additional interactions between host and guest molecules and increased the CO2 adsorption capacity in PCN-X-100%-Al to ~1.75 mmol/g @298 K and 1 bar150 (See Table 14). 2.3.1.2. Functionalized MOFs Making of composite MOFs leads to considerable thermal stability and highly ordered channels. They are built by assembling an agent, such as mesoporous silica or graphite oxide, with MOF structures. These types of MOF composites show an increase in MOF performance for CO2 adsorption and separation151–153. Chen et al. (2017) presented a modified HKUST-1 MOF structure (HKUST-1@SBA-15) which was designed to build MOFs on silica supports by different SBA-15 contents. The composite (labeled as HS-1 with 1 wt% of SBA-15) showed higher surface area (SBET:1745 vs.1466 m2/g) and additional micropores leading to higher CO2 adsorption compared to the pure MOF (4.85 vs. 4.19 mmol/g at 298 K and 1.0 bar)151 as shown in Table 14. Table 14. CO2 adsorption of HKUST-1 and its SBA-15 composites at low pressure (1 bar). SBET Micropore T P CO2 Uptake (m2/g) Volume (m3/g) (K) (bar) (mmol/g)* HKUST-1 1466 0.59 298 1 4.2 HS-0.5 1575 0.65 298 1 4.5 HS-1 1745 0.70 298 1 4.8 HS-1.5 1619 0.66 298 1 4.6 HS-2 1581 0.64 298 1 4.4 HS-2.5 1503 0.62 298 1 4.2 HS-3 1458 0.60 298 1 4.0 HKUST denotes Hong Kong University of Science and Technology. * Unit is converted from [cm3/g] to [mmol/g] (considering STP condition). Material

Ref.

151

Polar functionalities in MOFs contribute to higher CO2 uptake. Zheng et al. (2016) developed HNUST-5, an acylamide-functionalized MOF with rht-type network with open copper sites154,155. The CO2 uptake capability of HNUST-5 at 273 and 298 K in a wide range of pressures (up to 40


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bar) was studied and compared to some other acylamide-functionalized MOFs with high porosity such as Cu-FTDTT, NJUBai-23, HNUST-3, Cu-TPBTM, NJU-Bai9, NJU-Bai22 (see Table 14,16). Liao

et.

al.

(2016)

studied

CO2

adsorption

performance

of

the

small-pore

MOF

[Mg2(dobdc)(N2H4)1.8] modified by hydrazine (N2H4). CO2 single-component isothermal uptake at low pressures (0.4-150 mbar) and a wide range of temperatures (298-328K) was evaluated. To validate the practicality of the introduced structure under dynamic mixed-gas conditions, the presence of CO2/N2 mixtures in dry and humid conditions was studied. Application of this scenario demonstrated that the introduced hydrazine modified MOF had higher CO2 uptake compared to its non-modified structure [Mg2(dobdc)]156. Recently Zheng et al. (2018) synthesized HNUST-7 and reported gas uptake capacity in a pressure range from 0-35 bar for methane and nitrogen as well as carbon dioxide. HNUST-7 is a functionalized MOF designed by diisophthalate ligands with linking acylamide groups and dicopper paddlewheel clusters (which is highly porous NbO-type MOF-505 analogue) and has CO2 capture capacity of about 22 mmol/g at 273 K and 20 bar157. Bai et al. (2016) incorporated amide groups into NJU-Bai21 MOF ([Cu2(PDAD)(H2O)]n, H4PDAD=5,5′‐(pyridine‐3,5‐dicarbonyl)bis(azanediyl)diisophthalic acid , also known as PCN-124) to synthesize quasi-mesoporous NJU-Bai22 and mesoporous NJU-Bai-23. These two amidemodified structures (NJU-Bai22 and 23) showed higher CO2 storage capacity at high pressures (23.7 and 32.5 mmol/g at 298 K at 40 bar respectively) and higher thermal stability158. They later introduced NJU-Bai35 with exceptional CO2/N2 selectivity of 275.8 at 298 K and 1 bar159.CO2 capture on HNUST-3 (the porous oxalamide-functionalized MOF) at pressures ranging from 0-20 bar also showed that the performance is higher than some high-surface area MOFs such as MOF5 (20.2 vs. 19.0 mmol/g) at 298 K and 20 bar160. Although functional groups may lead to lower surface area, it is shown that they are worth implementing if leading to higher electrostatic interactions and consequently increasing the CO2 adsorption capacity. This behavior was observed by polyethyleneimine (PEI) functional groups in the previously introduced MIL-101 structure161,162. Loadings of PEI consistently led to higher adsorption specifically at low pressures. In a recent study, Gaikwad studied a multi-step improvement of adding new open metal sites and PEI functional groups. The results showed that functional groups decrease the surface area but contribute to higher adsorption capacities at low pressures163. A summary of some of the recently studied MOFs including the HNUST family and the NJU-Bai family is shown in Tables 15 and 16. 2.3.1.3. Molecular sieving



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Proper tuning of the MOF structure promotes CO2 (3.3Å) molecules entering the adsorbent pore while preventing N2 (3.64 Å) and CH4 (3.8 Å) molecules. Designing themicropores structure with high stability and regenerability is a challenging task164. Chen et al. (2016) synthesized squared lattice network of Qc‐5‐Cu‐sql‐β ([Cu(quinoline‐5‐carboxyate)2]n (Qc‐5‐Cu)) with a pore size of 3.3 Å and water resistant structure. It exhibited high CO2 uptake capacity of 2.17 mmol/g at 293 K and 1 bar compare to 0.06 and 0.01 mmol/g uptake of CH4 and N2 respectively164. SIFSIX-14-Cu-i (SIFSIX = hexafluorosilicate, 14 = 4,4′- azopyridine, i = interpenetrated) is another copper coordinated network (pore size 3.4 Å and thermal stability of up to 200 °C) studied for molecular sieving purposes which showed CO2/CH4 selectivity of 46.2 at 1 bar165. Table 15. CO2 adsorption on various MOFs at low and high pressures. Pore SBET T P CO2 Uptake Material Volume Selectivity (m2/g) (K) (bar) (mmol/g) 3 (cm /g) PCN-X 855 0.72 298 1 ~0.8* PCN-X441 0.28 298 1 ~0.99* 100%Fe PCN-X774 1.36 298 1 ~1.75* 100%Al CO2/CH4: 7.9 273 20 22.47 HNUST-3 2412 0.99 CO2/N2: 26.1 298 20 20.2 @ 298 K CO2/CH4: 6.29 HNUST-4 1136 0.458 273 1 4.5 CO2/N2: 29.88 @ 273 K 273 1 4.3 CO2/N2: 32.5 298 1 2.5 3643 CO2/CH4: 7.3 HNUST-5 1.46 273 36 38.9 @ 273 K 298 36 24.9 CO2/N2: 30.3 HNUST-6 1093 0.455 273 1 4.99* CO2/CH4: 6.6 CO2/CH4: 6.92 CO2/N2 :22.39 @273 K 273 30 26.1 HNUST-7 2804 1.11 298 30 19.4 CO2/CH4: 5.40 CO2/N2: 18.64 @ 298 K HNUST denotes Hunan University of Science and Technology. *Unit is converted from [cm3/g] to [mmol/g] (considering STP condition).


Ref.

150

160

166

154

167

157

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Table 16. CO2 adsorption on various MOFs at low and high pressures. Pore volum SBET T P CO2 Uptake Material e Selectivity Ref. (m2/g) (K) (bar) (mmol/g) (cm3/g ) 273 1 NJU-Bai20 2221 6.13*3.05* CO2/CH4 =3.9 @ 1 bar 298 1 NJU-Bai21 273 1 1979 9.28*5.17* CO2/CH4 =7.8 @ 1 bar 158 (PCN-124) 298 1 NJU-Bai22 2177 1.17 298 40 23.74■ CO2/CH4 =6.7 @ 1 bar NJU-Bai-23 2519 1.75 28 40 28.8 CO2/CH4 =5.8 @ 1 bar CO2/N2 (0.15:0.85) = 168 NJU-Bai32 751 298 0.15 1.08* 70.5 @ 298 K and 1 bar CO2/N2 (0.15:0.85) = 58.7@ 273 K and 1 bar CO2/CH4 (1:1) = 9.7 @ 273 K and 1 bar 273 0.15 169 NJU-Bai33 884.8 0.35 1.81*0.97* CO2/N2 (0.15:0.85= 40.3 298 0.15 @ 298 K and 1 bar CO2/CH4 (1:1) = 8.9 @ 298 K and 1 bar CO2/N2 (0.2/ 0.8) =275.8 273 ~4.5 @298 159 NJU-Bai35 862.8 1 298 ~3.3 CO2/CH4 (0.5:0.5) =11.6 @298 SNU-50 273 1 5.36 {[Cu2(bdcppi)(d 170 1 3.6 2300 1.08 298 mf)2]⋅10DMF⋅2H 298 46 17.1 2On CO2/CH4 (8.6) Cu3(BTB6−) 3288 1.77 298 1 ~2.5 CO2/N2 (34.3) 155 20 25.2 6 Cu3(TATB −) 3360 1.91 298 Cu-TPBTM

3160 1.268

273

20

27.58

CO2/N2: 26.1 @ 298 K

171

MOF-76-Ce-ds

754

298

1.1

4.0

CO2/N2: 15.4 @atmospheric condition

145

0.3

298 0.4 × 10 ―3 328 0.4 × 10 ―3 313 0.1 298 0.001

3.89 1.04 4.97 4.30

-

156

0.57

313 298

0.15 1.0

5.288.6

-

-

298

1

~2

CO2/N2 (15:85): 26.6 @100 kPa

Mg2(dobdc)(N2H 4)1.8 ;(dobdc4− = 1,41012 dioxido-2,5benzenedicarbox ylate Mg-MOF-74 1800 MOF-505-K*

977

-


172,17 3 174


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CO2/CH4 (50:50): 5.5 @100 kPa NJU-Bai denotes Nanjing University Bai group. ■ Unit is converted from [mg/g] to [mmol/g] (considering STP condition). * Unit is converted from [cm3/g] to [mmol/g] (considering STP condition). 2.3.1.3. Computational Modeling of MOFs Computational investigations provide molecular-level insight in the adsorption process and have been applied and reported in recent studies175,176. Regularity and designability of MOFs with a variety of choices to build the structure make them a suitable subject for molecular simulations177. The efforts have been widely implemented through GCMC simulations22 to study and estimate gas uptake on MOFs, either through exclusive or open-access software packages such as MuSiC and RASPA178–180. An advantage of computational studies in CO2 capture is examining the competition among CO2 molecules and others in gas mixtures, as well as molecule exchange sites with the host. Density functional theory (DFT) studies provides information on the energy barriers in adsorption competition among molecules. For example, Mg-MOF-74 (also known as CPO-27-Mg or Mg2(dobdc) where dobdc4− = 1,4-dioxido-2,5-benzenedicarboxylate)172 with open metal sites has a considerable quadrupole moment and high polarizability. This material has shown high CO2 adsorption capacity181,182. Understanding the adsorption of gas molecules on MgMOF-74, and MOFs in general at the molecular level requires investigations using methods such as DFT methods. Tan et al. (2015) investigated the adsorption mechanism of a variety of gas molecules such as H2O, NH3, NO, NO2, N2, O2 and CO2 on M-MOF-74 (M= Mg, Co, and Ni). The kinetics and mechanism of co-adsorption were studied through DFT calculations, revealing that, in addition to open metal sites, there are interactions with other guest molecules and the host structure effecting CO2 adsorption. Moreover, such interactions may lead to displacement of CO2 with other gas molecules such as H2O. In the case of water, oxygen atoms in H2O near metal sites led to weakening of the interaction between CO2 and the host and possibly displacing CO2 with H2O molecules as a result of hydrogen bonding to the organic linkers 183. To understand the role of amine functional groups on carbon capture performance of MOFs and to validate experimental observations with more effective intuition Lee et al. (2018) implemented DFT calculation on mmen (N,N′-dimethylethylenediamine) functionalized M2(dobpdc) type MOFs (M= Mg, Mn, Fe, Co, Zn; dobpdc = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate). The results elucidated binding energies among CO2 molecules and adsorption sites on these five MOFs as well as their electrostatic interactions. For instance, with calculation of enthalpy of adsorption of functionalized


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and non-functionalized MOFs, amine group-functionalized (mmen) M2(dobpdc) MOFs are more effective adsorbents even in the presence of water184. 2.3.1.4. MOF Databases Increasing computational power and designability of MOFs led researchers in the field of computational chemistry to build a large database of MOFs and boost material discovery. However, MOF databases could include an astronomical number of structures without considering limits and constraints185,186. The hypothetical MOF (hMOF) database, which includes 137,396 porous structures (available at http://hmofs.northwestern.edu/hc/crystals.php) was introduced by Wilmer et al. (2012). The database was computationally designed with 102 building blocks to generate known synthesized MOFs at the time of study. The designers limited the database generation procedure with constraints such as allowing only one type of inorganic building block, two types of organic building blocks, and one kind of functional group186. Since then, the hMOFs database has been analyzed and computationally screened for different separation and storage properties for gases such as methane, CO2, and hydrogen to identify high performing candidates for future experimental studies. In fact, the size and variety of the hMOFs database created the opportunity to apply machine learning algorithms to predict the performance of adsorption of each MOF. ML studies mostly took advantage of structural properties such as void fraction, pore size, surface area, and density as well as chemical properties to investigate the uptake capacity of adsorbent in different gas adsorption applications187–190. In the case of CO2 adsorption, porous materials such as MOFs can be used in pressure swing adsorption (PSA) and vacuum swing adsorption (VSA) in ambient temperature environments. Wilmer et al. (2012) studied four different cases of CO2 adsorption in a gas mixture on an hMOFs database using GCMC simulation: (1) natural gas purification using PSA (CO2:CH4=10:90); (2) landfill gas separation using PSA (CO2:CH4=50:50); (3) landfill gas separation using VSA (CO2:CH4=50:50); and (4)flue gas separation using VSA (CO2:N2=10:90). The first two cases undergo higher pressures of about 5 bar, whereas the latter two are under lower pressures of about 1 bar191. Fernandez et al. (2013) used the results of Wilmer’s work to apply a support vector machine (SVM) algorithm and predict hMOFs capacity in CO2 adsorption. They used structural features as well as a proposed descriptor called the atomic property weighted radial distribution function (APRDF) to predict CO2 capture capacity of hMOFs. The accuracy of the model in flue gas separation (at 0.1 bar and 298 K) and natural gas separation (at 0.5 bar and 298 K) cases are reported with R2=0.673 and R2=0.735 respectively192. Recognizing high performing MOFs among a large library of hMOFs has been also tested through a machine learning classification method. Fernandez et



al. (2016) used quantitative structure−property relationship (QSPR) models, along with the structural features such as surface area, pore size, and void fraction to filter high performing MOFs at low pressures to predict CO2 adsorption capacity, reaching an accuracy of 94.5%188,193. The Computation-Ready Experimental MOF (CoRE MOF) database was extracted from experimentally synthesized MOFs available in the Cambridge structural database (CSD). The CoRE MOF database, reported by Chung et al. (2014), refined synthesized MOFs by processing of structures through (1) desolvating the structures (using the graph-labeling algorithm), (2) removing additional solvent molecules from the structure, (3) neutralizing overall charge of each MOF structure, and (4) retaining interpenetrated structures. The authors mentioned that the database does not include all MOF structures available in the CSD (more than 600K at the time of writing the current article) due to the challenge of implementing all the steps mentioned above. Instead they eventually reported on 4,764 MOF structures and their properties, such as void fraction, limiting pore diameters, and maximum pore diameters. The CoRE database is available online at http://dx.doi.org/10.11578/1118280. The database shows similarities between synthesized MOF properties and their methane deliverable capacity when compared to the corresponding properties of the hMOF database. However, the CoRE MOF database is more topologically diverse than the hMOF database due to structurally limited unites used in building hypothetical MOF databases185. Nazarian et al. (2016) assessed over 800 various CoRE MOFs with their experimental and DFT-optimized structures. They observed structural properties such as pore size, unit cell length and angles, unit cell volume, and helium void fraction undergo up to 10% change after energy minimization. They also reported that energy minimization of the structure does not have a significant effect on the methane uptake. However, only a 5% change for CO2 adsorption was observed leading to the conclusion that structural optimization has poor correlation with the gas uptake194. Qiao et al. (2016) applied molecular simulations on the 4,764 CoRE MOFs to evaluate CO2 separation in flue gas (CO2/N2:15/85) and natural gas (CO2/CH4:50/50) at ambient temperature195. They considered adsorption performance criteria such as adsorption selectivity (S), adsorption capacity 𝑁𝐶𝑂2), working capacity (∆𝑁𝐶𝑂2), and regenerability (R). Type of metal (alkali, alkaline, lanthanide, and transition) also plays an important role. Based on S, R and ∆𝑁𝐶𝑂2 values, most of the high-performing CoRE MOFs for CO2 capture have lanthanide metal atoms in their structure while alkali-MOFs showed the lowest performance. The 15 highest performing CoRE MOFs have ∆𝑁𝐶𝑂2>70 cm3/cm3, S>100, and R>70% for CO2/N2 and ∆𝑁𝐶𝑂2>100 cm3/cm3, S>9, and R>60% for CO2/CH4 separation195.


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Li et. al. (2016) investigated the presence of water (RH = 80%) on CO2/H2O selectivity performance on the MOFs present in the CoRE database. The screening process for the CO2/H2O mixture is a challenging task. The presence of water in the system increases the computational cost of the GCMC simulation. To make the analysis more tractable, for the first stage of screening, the Henry’s laws constants between CO2 and H2O were calculated and used as the criterion to identify high performing MOFs. Fifteen MOFs stood above the rest, and two of them went through GCMC simulation. The first was CO2/N2 (CO2/N2 = 1:9) and the second was CO2/H2O. Both were done under post-combustion CO2 capture conditions (1 bar and 298 K)196. While a primary purpose of implementation of molecular simulation on the large library of MOFs is to identify the best performing candidates, dealing with the expensive simulation costs is generally prohibitive. Methods such as machine learning and genetic algorithms (GA) have been used to tackle this issue. Chung et al. (2016) screened hMOF databases for CO2 separation in pre-combustion processes by implementation of a GA on the hMOF database to search among the building blocks. Only those with the highest performance were simulated and as the result the computational cost was reduced. To validate the procedure, the highest performing candidates were synthesized, and showed good agreement between experiment and simulation. The method was also successful in screening the CoRE MOFs database which is a synthesized library of MOFs with the available synthesis protocol197. 2.3.2

Zeolite Imidazolate Framework (ZIFs)

ZIFs, a subgroup of MOFs with isomorphic pore topology corresponding to zeolite structures, are built with tetrahedrally-coordinated transition metal ions such as Fe, Co, Cu, Zn (replacing the Si atoms in zeolites) connected by imidazolate linkers (replacing bridging oxides in zeolites). The metal-imidazolate-metal angle in ZIFs is similar to the Si-O-Si angle of zeolites. ZIFs have large surface area and high heat tolerance, which makes them a promising subject for carbon capture studies198–202. Along with experimental studies, there are efforts to design new materials. Lin et al. generated a large database of ZIFs that includes more than 300,000 of predicted structures (2012). This library of ZIFs structures was studied for carbon dioxide capture and storage. The criteria for ZIF performance was Henry’s coefficient and the heat of adsorption. Additionally, the effect on parasitic energy was used as the representative of electricity consumption in carbon capture processes in industry203. This database was also investigated for gas separation studies specifically for methane storage204,205.



Ban et al. (2018) studied cavity occupancy on the highly stable MOF (ZIF-8) for increasing CO2 adsorption selectivity in membranes. The room temperature ionic liquids (RTILs) used as cavity occupant were imidazolium-based [bmim][Tf2N] to control the cage size of ZIF-8 between CO2 and N2. They observed a greater than five-fold increase in CO2/N2 and CO2/CH4 selectivity in the fine-tuned ZIF-8 ( IL@ZIF-8), despite reducing surface area and pore volume206. In a study on complimentary effects of ZIF-8 and GO, mixing both fillers in a mixed matrix membrane showed higher CO2 selectivity, and permeability, as well as improved mechanical stability207. A big challenge in commercializing MOFs and their subgroups is the synthesis procedure which either has high cost or environmental concerns. One of the alternatives for the solvothermal synthesis procedure is using aqueous solutions, which is more commercial friendly and has low toxicity concerns. Ramos-Fernandez et al. (2018) provided an easy synthesis procedure in aqueous solution at room temperature for ZIF-93 that demonstrated high thermal and chemical stability. The surface area and pore volume are 604 m2/g and 0.46 cm3/g respectively. The CO2 adsorption capacity of ZIF-93 at 303 K was reported as 180 cm3/g and 35 cm3/g at 30 bar and 1 bar respectively. Almost no N2 adsorption on ZIF-93 in the binary mixture of CO2/N2 (25 : 75) was observed. Their method is promising for scale-up201. 2.3.3

Covalent Organic Frameworks (COFs) and polymers

COFs, first reported by Yaghi in 2005208, are a another class of crystalline materials with selforganized porous structures. Their structures are built of organic building blocks linked by strong covalent bonds from elements such as hydrogen, boron, carbon, nitrogen, and oxygen with surface area as high as 4,210 m2/g (reported for COF-103)209–212. These lightweight covalently bonded elements give the COF structures low densities and high thermal stabilities (400-500 C), while embracing the merits of MOFs, including high CO2 adsorption capacity and selectivity. COFs have been tested for applications such as gas separation and storage213–218. Liu et al. (2010) reported separation performance of synthesized materials including six MOFs (IRMOF-1, 8, 10, 14, 16, Cu-BTC) and six COFs (COF-6, 8, 10, 102, 103, 105) in a binary mixture of CH4/CO2/H2 at low pressures (up to 2 bar) and 298 K. They concluded that both categories of porous materials have similar performance. CO2/CH4 selectivity at low pressures for all the cases were between 14, except for Cu-BTC which demonstrated selectivity of approximately 8 at 2 bar219. Extensive studies on COFs have led to a number of review studies in the recent years. Zeng et al. (2016) reviewed different types of COFs such as boron-based, triazine-based, imine-based and


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boron/imine-based COFs. The highest surface area was reported for COF-102 at 3,620 m2/g; CO2 adsorption was 1.53 mmol/g at low pressures (at 273 K and 1 bar)220. Lower surface area was reported for FCTF-1–600 at 1535 m2/g, with the highest CO2 adsorption of 5.57 mmol/g220. COFs performance is strongly dependent on the synthesis method in which the structure develops. Olajire (2017) reviewed recent synthesis methods for different types of COFs (boronbased, covalent triazine-based framework (CTF), imine-based, and multiple-component COFs) with the focus on their application in CO2 capture221. A detailed review on COFs is provided by Lohse et al. (2018) covering chemistry/geometry, synthesis methods, and applications of COFs222. Metal doping and amine functionalization of COFs have shown enhancement in CO2 adsorption performance by increasing the interactions between the COF structure and guest molecules223. Lan et al. (2010) studied the doping effects of alkali (Li, Na, and K), alkaline-earth (Be, Mg, and Ca), and transition metals (SC and Ti) by calculating binding energies of CO2 molecules with three-dimensional (3D) COFs, COF-102 and COF-105. DFT calculations on the transition metal doping in their work showed that metal doping led to strong bonds between CO2 and metal cations. Thus, a high possibility of chemisorption occurs as the binding energy exceeds 20 kJ/mol. However, Li-doping among all alkaline and alkali metals had the higher binding energy in the physisorption limit. As a result, CO2 adsorption on Li-doped COFs was studied with GCMC simulations. Compared to COF-102 and pristine COF-105, Li-doped COF-105 has higher CO2 adsorption capacities reaching values of 7.81, 21.5, and 51.4 mmol/g at 298 K at pressures of 1, 10 and 40 bar, respectively224. However, this new class of porous materials requires further extensive study to fully understand the synthesis procedures required to build various structures and performance enhancement conditions, such as functionalizing methods. Gao et al. (2018) provided a solvent control method to synthesize built-in functionalization of two 2D-COFs, TPECOF-1, and TPE-COF-2 (TPE: tetraphenylethane). The first had a surface area of 1,535, while the second was 2,168 m2/g respectively. The CO2 adsorption performance of these two COFs at low pressures (up to 1 bar) was investigated.

The highest adsorption was reported to be

approximately 5.39 mmol/g at 1 bar and 273 K for TPE-COF-2225 as shown in Table 17. COFs and CTFs are subclasses of porous organic polymers (POPs). CTFs and their functionalized structures have received attention specifically in CO2 capture, where the synthesis, properties, and gas uptake capacities of new or modified CTFs have been reported. Synthesis temperature is a factor that has a large effect on surface area. The higher the synthesis



temperature, the higher the surface area. Thus, synthesis of new CTFs in different temperature environments leads to different properties that effect the material performance for CO2 capture. Hug et al. (2015) evaluated CO2 uptake capacity of four nitrogen-rich CTFs with the monomers of 5,5′-dicyano-2,2′-bipyridine32 (bipy-CTF), 1,4-dicyanobenzene20,22 (CTF1), pyrimidine-2,5dicarbonitrile (pym-CTF) and 2,6-dimethylpyridine-3,5-dicarbonitrile (lutCTF). They evaluated the CTFs under different synthesis temperatures (300-600 ºC) and observed the highest surface area and CO2 uptake capacity (at 273 K and 1 bar) at the highest synthesis temperature of 600 ºC. They reported CO2 uptake capacity in descending order as bipy-CTF600 (5.58 mmol/g) > lutCTF600 (4.49 mmol/g) > CTF1-600 (4.36 mmol/g) > pym-CTF600 (3.34 mmol/g)226. Wang et al. (2018) studied a set of CTFs, DCBP-CTF-1, DCBP-CTF-2, F-DCBP-CTF-1, and FDCBP-CTF-2. The two latter CTFs are fluorine functionalized and synthesized with linkers of 2,2′,3,3′,5,5′,6,6′-octafluoro-4,4′-biphenyldicarbonitrile at 400 ºC with ZnCl2 /monomer ratios of 5 and 10 respectively. These two materials showed higher nitrogen content, surface area, CO2 adsorption, and CO2/N2 selectivity (see Table 16). Fluorine modified CTFs enhanced the materials performance in terms of CO2 uptake and CO2/N2 selectivity despite being barely affected in the presence of water due to fluorine hydrophobicity227. Jena et al. (2018) presented the first modification of CTFs with acetylacetonate groups. They introduced four different acac-CTFs (acac-CTF-5-400, acac-CTF-10-400, acac-CTF-5-500, and acac-CTF-10-500) synthesized with a nitrile linker ( 4,4′-malonyldibenzonitrile) at two different temperatures (400 and 500 ºC) and linker to ZnCl2 molar ratios of 1:5 and 1:10. The BET surface area in descending order was found to be acac-CTF-10-500(1,626 m2/g) > acac-CTF-5-500 (1,556 m2/g) > acac-CTF-10-400 (1,150 m2/g) > acac-CTF-5-400 (1,131 m2/g). Along with reporting CO2/N2 selectivity, they also tested CO2 uptake capacity of the samples at low pressures (0-1 bar) and 273 and 298 K. Although acacCTF-5-500 has lower surface area and pore volume than acac-CTF-10-500, this material showed higher CO2 uptake capacity at both temperatures and more effective CO2/N2 selectivity228 (see Table 16). Dey et al. (2017) studied CTFs constructing combination of nitrile linkers and their performance on CO2 adsorption capacity. They separately synthesized tetrakis(4-cyanophenyl) ethylene (M/PCTF-1) monomer to either terephthalonitrile (M1/CTF-1), tetrafluoroterephthalonitrile (M2/FCTF-1), 4,40-biphenyldicarbonitrile (M3), or 1,3,5-benzenetricarbonitrile (M4/CTF-0) to form four combinations of nitrile-rich CTFs of MM1, MM2, MM3, and MM4 through ionothermal methods (ZnCl2, 400 °C). They showed that by tuning the monomer ratios the micropore volume


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accessible to CO2 is tailored resulting in enhanced uptake229. Zeng et al. (2018) applied GCMC and MD simulations to study the kinetics of CO2 adsorption on five COFs (modified either with triazine or pyromellitic dianhydride (PMDA)), TS-COF-1 (*TS: task specific), TS-COF-2, PI-COF1, PI-COF-2 (* PI: polyimide), and PI-COF-3230. The GCMC simulation results showed that PICOF-3 (with the pore size of 53Å) had the highest CO2 adsorption capacity at 1 bar (> 500 mmol/g). To investigate the possible improvement of adsorption performance and selectivity, they performed GCMC and MD simulations on pristine and -NH2 functionalized structures. They reported that adding -NH2 groups was the reason behind the enhancement for the adsorption capacity and selectivity231. Coordination polymer networks (CPNs), also referred to as porous coordination polymers (PCPs), are another group of crystalline porous materials inspired by MOFs. The elementary units are metal ions and organic or inorganic linkers attached with covalent bonds. The structures are capable of being tailored in one, two, or three dimensions based on the type and coordination of ligands (see Figure 3). The drivers for these choices are based on their ultimate application, such as gas storage and separation232–235. In 2015, Neti et al. synthesized phthalocyanine porous polymer (CPP) by reacting tetraazidophthalocyanine nodes and bisamine diethynylbenzene linkers. The BET surface area and total pore volume were reported as 579 m2/g and 0.71 cm3/g. The CO2 adsorption for CO2:CH4 mixture at low pressure (1 bar) was reported as 3.57 mmol/g (15.7 wt%) at 273 K and 2.27 mmol/g (10 wt%) at 298 K. In addition to the high adsorption capacity, CPP showed high selectivity: CO2/N2=94 and CO2/CH4= 12.8. The non-functionalized structure of CPP performed better than another polymer that was studied, benzimidazole-linked porphyrin-based porous polymer, referred to as PBILP (surface area = 557 m2/g). PBILP has a CO2 adsorption capacity of 2.76 mmol/g (12.1 wt%). The selectivity values at 273 K and 1 bar are also lower than CPP, CO2/CH4 = 7.2, and CO2/N2 =72236,237. Sun et al. (2015) synthesized four types of polymers with chloromethylbenzene and various diamines (NUT-1, NUT-2, NUT-3, and NUT-4). They reported the performance for CO2, CH4, and N2 on polymers at 273 and 298 K at low pressures (0-1 bar)238. (see Table 17) Microporous organic polymers are competitive with zeolites and activated carbon in gas adsorption applications. These materials not only possess low density and high surface area but also exceptional thermal stability. To achieve acceptable adsorption performance in microporous organic polymers, like nanoporous materials, functionalization is required to enhance the



interaction between adsorbate and adsorbate. Sun et al. (2016 & 2017) synthesized a group of thiophene-based conjugated microporous polymers (ThPOPs). ThPOPs contain sulfur atoms on their surface that contribute to the creation of dipole-quadrupole interactions with CO2 molecules and increase CO2 adsorption capacity of ThPOPs239,240. Amine functionalization of porous organic polymers was studied on polydivinylbenzene (PDVB)241,242. Jafari et al. (2017) modified PDVB by adding vinyl imidazole (VI) and vinyl triazole (VT) to the structure through microwave assisted synthesis methods to increase CO2 capture capacity from 1.2 mmol/g (PDVB) to 2.65 mmol/g (PDVB-VT)241. Conjugated microporous polymers (CMPs) have amorphous structures with low density and high chemical stability due to strong covalent bonds. These types of polymer networks that are formed through extension of π-conjugation in the polymeric network have been studied experimentally and computationally through GCMC and MD simulations. Suresh et al. (2014) s tetraphenylethene (TPE)-based CMP and evaluated its CO2 uptake capacity. They reported the BET surface area, pore size, and pore volume as 854 m2/g, 10.8 Å, and 0.57 cm3/g respectively. The CO2 uptake at 1 atm and 195 K was reported to be 7.3 mmol/g (32.4 wt%) which indicates good agreement between the experimental and computational results243. In another study, Bonakala et al. (2015) computationally examined perfluorinated amorphous polymer properties and its CO2 uptake capacity. The study reports a 10% increase of CO2 adsorption in the fluorine substituted tetraphenylethylene-based conjugated microporous polymer, TPE-FCMP, compared to its hydrogenated counterpart. The MD simulated properties reported pore diameter: 3.681 Å, density: 0.89 g/cm3 and surface area: 867 m2/g. GCMC isothermal adsorption simulation at 195K and 1 bar shows more than 35 wt% CO2 uptake244. Guest molecules can cause the host network to undergo structural changes, which will affect the adsorption capacity. Meza-Morales et al. (2016) used computational studies to study structural changes in a series of coordination polymer ligands (CPLs) such as CPL-2, CPL-4, and CPL-5 in the vicinity of CO2 molecules at 195 K and pressures up to 10 atm. The change in the unit cell and ligand rotation are two main framework changes, where the latter leads to larger pore volume and consequently higher CO2 adsorption245. A list of COFs along with their characteristics and CO2 adsorption is given in Table 17.


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1D network

Linear chain

Zigzag chain

Double chain

Fish-bone

Ladder

Railroad

Helix

2D network

Rectangular grid

Square grid

Rhombic grid

Honeycomb grid

Brick wall

Herringbone

CdSO4

Octahedral

3D network

ThSi2

PtS

Diamond

NbO

Figure 3. Schematic representation of 1D, 2D and 3D coordination polymer motifs. Redrawn from references [233,235].



Table 17. reported CO2 adsorption performance of COFs at low and high pressures.


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Material

Pore SBET Size (m2/g) (Å)

COF-1

750

COF-5

T (K)

-

1670 2.7 nm

-

-

COF-6

750

0.9 nm

-

-

COF-8

1350 1.6 nm

-

-

COF-10

1760 2.6 nm

-

-

TDCOF-5

2497

-

1.3

-

CTF-1

746 791 536

1.2 nm

0.4

-

PCTF-3 PCTF-4 PCTF-5 PCTF-7

641 1090 1183 613

-

0.44 0.75 0.70 0.36

-

FCTF-1

662

-

-

-

FCTF-1-600* *Synthesized at 600 °C

1535

-

-

-

COF-102

3620 1.2 nm

1.55

0.41

-

-

1.54

0.38

273 298

COF-103

-

-

4210 1.2nm

P (bar)

CO2 adsorption (mmol/g)

CO2/N2 Ref. Selectivity

273 1.0 2.27■5.22■ 273 55 273 1.0 1.38■19.75■ 273 55 273 1.0 3.79■7.04■ 273 55 273 1.0 1.47■14.3■ 273 55 273 1.0 1.2■22.93■ 273 55 273 1.0 2.09■ 273 0.50 0.1 IAST: 20 273 2.47 1.00.1 Breakthrou 298 0.21 1.0 gh: 18 298 1.41 1.0 2.19* 273 25 1.0 2.32* 273 26 1.0 2.61* 273 32 273 1.0 2.19* 41 273 0.1 1.76 IAST: 31 273 1.0 4.67 Breakthrou 298 0.1 0.92 gh: 77 298 1.0 3.21 273 0.1 1.40 IAST: 19 273 1.0 5.53 Breakthrou 298 0.1 0.68 gh: 152 298 1.0 3.41 273 1 1.53* 298 55 27.48* 1 9.34* 298 40 30.86*

0.32

Li-doped COF-102

0.9 nm

Densit Pore y Volume (g/cm3 3 (cm /g) )

COF-105

-

-

-

0.18

298

Li-doped COF-105

-

-

-

-

298

1 55 30 1 40


1.71*27.26*

-

82 (simulated) 7.86* 51.79*

-

221

221

221

221

221 246

247–249

250 250 250 250

247

247

209,220

220

209,220

209,220, 251

209,220


COF-108

-

-

-

0.17

298

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209,220,

96 251 30 (simulated) 225 273 1 atm 3.14* 225 273 1 atm 5.34* 252 1 273 4.38* 29.3 252 1 273 4.14* 33.1 252 1 273 3.88* 21.2 format in [mg/g] to [mmol/g] (considering STP

TPE-COF-1 1535 1.65 TPE-COF-2 2168 2.14 CTF-BIB-1 1636 0.96 CTF-BIB-2 1714 0.99 CTF-BIB-3 2088 1.10 ■ Unit is converted from its originally presented condition). * Unit is converted from its originally presented format in [cm3/g] to [mmol/g] (considering STP condition). ▲ Unit is converted from its originally presented format in [wt%] to [mmol/g].


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Table 17, cont’d. reported CO2 adsorption performance of COFs at low and high pressures. Densit Pore Pore SBET y T Material Size Volume 3 (m2/g) (g/cm (K) (Å) (cm3/g) ) 273 DCBP-CTF-1 2437 1.48 298 273 DCBP-CTF-2 2036 2.26 298 273 F-DCBP-CTF-1 1574 1.5 298 273 F-DCBP-CTF-2 1126 1.56 298 273 acac-CTF-5-400 1131 0.90 298 273 acac-CTF-10-400 1150 0.95 298 273 acac-CTF-5-500 1556 1.20 298 273 acac-CTF-10-500 1626 1.60 298

P (bar) 1 1 1 1 1 1 1 1

CO2 adsorption (mmol/g) 3.65 2.07 3.31 1.84 5.98 3.82 5.23 3.16 2.87 1.89 3.06 1.96 3.30 1.97 3.16 1.91

CO2/N2 Ref. Selectivity 13

227

21

227

31

227

22

227

38

228

20

228

46

228

21

228

MM1

1800

-

1.11

-

273

1

3.68

25

229

MM2

1360

-

0.67

-

273

1

4.70

44

229

MM3

1884

-

1.52

-

273

1

2.62

16

229

MM4

1407

-

0.78

-

273

1

3.40

32

229

NUT-1

99.9

3.6

0.073

-

298

1

1.43■

10140

238

NUT-2

70.0

4.3

0.064

-

298

1

0.99■

3140

238

NUT-3

42.4

4.1

0.042

-

298

1

0.64■

590

238

NUT-4

26.9

4.0

0.025

-

298

1

0.40■

110

238

ThPOP-1

1050

-

0.69

-

273

1

3.41▲

-

239

ThPOP-2

160

-

0.27

-

273

1

0.91▲

-

239

0.27

-

273

1

1.78▲

-

240

0.93

-

273

1

3.48▲

-

240

1.12

-

273

1

2.84▲

-

240

ThPOP-3 ThPOP-4 ThPOP-5

0.58,1. 75 0.50,0. 1060 58 350

1300

0.59

240 ThPOP-6 1320 0.59 1.40 273 1 3.0▲ ■ Unit is converted from its originally presented format in [mg/g] to [mmol/g] (considering STP condition). * Unit is converted from its originally presented format in [cm3/g] to [mmol/g] (considering STP condition). ▲ Unit is converted from its originally presented format in [wt%] to [mmol/g].



2.4

Metal Oxides

Like the various MOFs mentioned above, different metal oxides can be used directly as an adsorbent to capturing gaseous CO2. Selection of these metal oxides are done so that the final carbonized material is thermodynamically stable253. In this regard, both CaO and MgO have shown promising activity by forming insoluble carbonates upon CO2 fixation254–257. Moreover, the high abundance, low toxicity, and cost-effectiveness of these materials have invoked tremendous interest among researchers to enhance their sorption capacity. Mayorga et al. (2001) reported a sorption capacity of 0.13 mmol/g (0.57 wt%) for MgO under moderate temperatures and dry environments258. To date, various approaches have been made to enhance this activity. Bhagiyalakshmi et al. (2010) synthesized carbon templated mesoporous MgO. The mesoporosity enhanced CO2 adsorption capacity up to 1.81 mmol/g (8 wt%) at 298 K and 2.27 mmol/g (10 wt%) at 373 K, whereas the non-porous MgO only displayed 0.23-45 mmol/g (1–2 wt%) of adsorption at 298 K under atmospheric pressure259. Similarly, Han et al. (2012) introduced the concept of meso-porosity with MgO. Specifically, they developed a composite material in a facile coprecipitation method to trap CO2 from flue gas at high temperature (423–673K). Homogeneous distribution of the microcrystalline MgO nanoparticles on the alumina framework further enhanced the active surface area. This increased the CO2 adsorption capacity of the material to 1.75 mmol/g (7.7 wt%) and 2.98 mmol/g (13.1 wt%) in the absence or presence of water vapor at 473 K260. These results inspired the researchers to explore the effect of physisorption instead of chemisorption. In 2012, Slostowki et al. reported the effect of strong reducibility of CeO2 to capture CO2 (5 wt%)261, whereas Pham et al. displayed the effect of oxygen vacancy for the same material to capture only up to 0.91 mmol/g (4 wt%)262. To enhance the surface area and active site density, several other strategies were conceived. They included CaO-based pellets as cores and different mesoporous metal oxides (e.g. alumina, ceria, and yttrium-stabilized zirconia) as shells263. This material morphology enhanced their stability enabling use over 20 times for CO2 uptake264. Bhatta et al. (2016) reported layered double hydroxide (LDH) multi-walled carbon nanotubes with an adsorption capacity of 1.12 mmol/g at 300 °C under a total pressure of 1 bar and 10 cycles265. These LDH materials are known for their good thermal stability, relatively faster CO2 adsorption kinetics, and moderate regeneration temperature.

All of these properties are factors that

contribute to high CO2 adsorption affinity266–268. Moreover, promotion with K2CO3 by Li et al. (2013) (to uptake 1.93 mmol/g at 300 °C and 1 atm)269,270 , and Na2CO3 and Mg/Al ratio of 20 by Kim et al. (2016) (to uptake 9.27 mmol/g at 240 °C and 1 atm)271 showed the effectiveness of this protocol.


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These results inspired the incorporation of alkali metal ions (salts) into the MgO framework, which increased the basicity of the material by enhancing surface defects and positive charge density. The effect of increased basicity was reflected when Liu et al. reported an enhancement of CO2 sorption capacity greater than 1.9 mmol/g (8.36 wt%) at 573 K, for their alkali-metal carbonate (Cs2CO3) doped MgO materials272,273. Several MgO and CaO based materials were developed by incorporating alkali metal ions to further enhance the sorption capacity under mild operational conditions. Harada et al. reported alkali metal nitrates/nitrites coated MgO274 with CO2 uptake up to 15.7 mmol/g (under pressure of 1 bar at 340 °C). Qiao et al. (2017) reported Li/Na/K based MgO (10 mol% (Li0.3Na0.6K0.1)NO3.MgO) with adsorption of 16.8 mmol/g (at 1 atm and 300 °C)275. Metal oxide adsorption of CO2 via chemical reaction is relatively slow, while the desorption process requires high temperatures (above 670 K) and is energy intensive. Although metal oxides have high adsorption volume, the technology requires further development in terms of regeneration and energy consumption6. 3

Conclusion and Future Perspective

Adsorption with porous solids is a promising technology, reducing the energy requirement for regeneration compared to the currently widely used scrubbing technology for post-combustion carbon capture. Modification methods such as amine functionalization and optimization of textural properties enhance CO2 adsorptive properties. Porous materials with narrow pores doped with CO2-philic heteroatoms are desirable for post-combustion carbon capture processes. To improve economics and practical usage, thermal stability, moisture resistance, and low cost are necessary for solid adsorption technology to compete with state-of-the-art scrubbing. Silica and zeolites with fast adsorption/desorption kinetics at their current stage of development have limited application. These materials suffer from their high moisture sensitivity, which increases the regeneration cost. Carbon based adsorbents offer advantages of high stability and low cost of precursors, notwithstanding low selectivity and relatively low adsorption capacity. Attempts in developing biomass-based CO2 adsorbents has aimed to use low-cost and sustainable adsorbent materials. Research is needed to improve their capacity by efficient activation processes. MOFs are highly ordered micro-crystalline materials with a high potential for rational design and screening. While their large-scale production and utilization are costly, they display high selectivity and capacity for CO2 adsorption. COFs have the advantages of high adsorption capacity and selectivity. However, they are constrained by their high dependency on their synthesis conditions, which are more complicated and expensive compared to other adsorbents. General research trends in COFs and porous polymers have been on functionalizing the surface with nitrogen-containing groups to



increase uptake and selectivity. Additional functionalization includes the addition of fluorine to introduce hydrophobicity and stability. Metal oxides have shown very high adsorption capacities but require high-temperature regeneration processes. We recommend determining CO2 uptake characterization of materials under varied pressures and temperatures to examine their regenerability in adsorption/desorption cycles. These include temperature swing adsorption (TSA), pressure swing adsorption (PSA) and the combination of both. Generally at low pressures, surface chemistry dominates the interactions and favors CO2 selectively, while at high pressure physisorption is prevalent. We have highlighted various conditions at which adsorption and desorption occurs along with selectivity to provide insight into materials rational design for withstanding regeneration conditions. Here, various performance metrics have been suggested for consideration in future research for materials discovery besides CO2 adsorption capacity and selectivity. These metrics include synthesis simplicity, thermal stability, and moisture stability. Among factors contributing to adsorption performance, the most important properties are microporous surface area, nitrogen and fluorine functionalization, and structural flexibility. For certain crystalline material classes, large databases of crystal information are being generated, and computational screening studies are emerging to facilitate adsorbent material discovery. More research needs to be done on environmentally friendly sources of adsorbents. Such sources include agricultural residues, industrial food and beverage waste, and biomass-based adsorbents to address the economics and environmental aspects of adsorbent manufacturing.

Acknowledgements This material is based upon work supported by the Department of Energy, Office of Science, Office of Basic Energy Sciences, under Award Number DE-FG02-86ER13622-A000. We also acknowledge General Electric for supporting this work under a GE Fellowship for Innovation.

References (1) (2) (3)

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