Linking Silica Support Morphology to the Dynamics of Aminopolymers

Subscriber access provided by Eastern Michigan University | Bruce T. Halle Library

Article

Linking Silica Support Morphology to the Dynamics of Aminopolymers in Composites Jan-Michael Y. Carrillo, Matthew E. Potter, Miles A. Sakwa-Novak, Simon H. Pang, Christopher W Jones, and Bobby G. Sumpter Langmuir, Just Accepted Manuscript • Publication Date (Web): 11 May 2017 Downloaded from http://pubs.acs.org on May 15, 2017

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Langmuir is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 39

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

Langmuir

Linking Silica Support Morphology to the Dynamics of Aminopolymers in Composites Jan-Michael Y. Carrillo,∗,†,‡,k Matthew E. Potter,¶,§,k Miles A. Sakwa-Novak,¶ Simon H. Pang,¶ Christopher W. Jones,¶ and Bobby G. Sumpter†,‡ †Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States ‡Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States ¶School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States §Present address: School of Chemistry, University of Southampton, Southampton, SO17 1BJ, United Kingdom kCo-first authors that equally contributed to this work. E-mail: [email protected]

Abstract A combined computational and experimental approach is used to elucidate the effect of silica support morphology on polymer dynamics and CO2 adsorption capacities in aminopolymer/silica composites. Simulations are based on coarse-grained molecular dynamics simulations of aminopolymer composites where a branched aminopolymer, representing poly(ethylenimine) (PEI), is impregnated into different silica mesoporous supports. The morphology of the mesoporous supports varies from hexagonally packed

1

ACS Paragon Plus Environment

Langmuir

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

cylindrical pores representing SBA-15, double gyroids representing KIT-6 and MCM48, and cage-like structures representing SBA-16. In parallel, composites of PEI and the silica supports SBA-15, KIT-6, MCM-48 and SBA-16 are synthesized and characterized, including measuring their CO2 uptake. Simulations predict that a 3D pore morphology, such as those of KIT-6, MCM-48, and SBA-16, will have faster segmental mobility and have lower probability of primary amine and surface silanol associations, which should translate to higher CO2 uptake in comparison to a 2D pore morphology such as that of SBA-15. Indeed, it is found that KIT-6 has higher CO2 uptake than SBA-15 at equivalent PEI loading, even though both supports have similar surface area and pore volume. However, this is not the case for the MCM-48 support, which has smaller pores, and SBA-16, whose pore structure rapidly degrades after PEI impregnation.

Introduction The benchmark adsorption technologies used for CO2 capture from point sources are based on aqueous amine solutions. However, a drawback for using these well-established technologies is the energy intensive and highly corrosive process necessary to regenerate the amine solution. 1–4 An alternative method employs solid sorbents, which have lower heat capacities, and can hypothetically reduce the amount of energy required to regenerate the sorbent. Moreover, solid sorbent-based systems have been shown to possess high CO2 capacities, fast adsorption kinetics, and maintain these characteristics under realistic operating conditions. 5–11 One of the more common solid sorbents are composites of aminopolymers and ordered silica supports. Understanding the interplay between the aminopolymers with the silica support, and linking these relationships to performance to optimize the CO2 sequestration process, remains a challenge. Aminopolymers that are physically adsorbed into various silica supports through wet impregnation processes to form composites were pioneered by Song et al. 5 These amine-oxide

2


Page 2 of 39

Page 3 of 39

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

Langmuir

adsorbent materials are categorized as class 1 amine-oxide hybrid adsorbent materials and are considered among the most practical for use in industrial CO2 capture applications. 2,12 The other classes include amine-containing organosilanes that are covalently bonded to the support and in situ polymerized amine-containing monomers grafted on the silica support for classes 2 and 3, respectively. 13 Recently a new class (class 4) has been proposed by Wilfong et al., 14 which is a hybrid of classes 1 and 2, where aminosilanes, aminopolymers and silica are mixed in the design to provide a more robust composite. Various silica supports have been reported for wet impregnation with poly(ethylenimine). The morphology of these supports varies from two-dimensional (2D) hexagonally packed cylinders such as MCM-41 5,15,16 and SBA-15, 16–19 three-dimensional (3D) double gyroids such as MCM-48 16,19 and KIT-6, 16,20 and channel linked body centered cubic cages such as SBA-16. 16 It has been recognized that CO2 adsorption capacity increases as the pore volume of the mesoporous silica support is increased. 21 For example, the work by Son et al., 16 reported an increase in equilibrium CO2 adsorption capacity as pore diameter is increased for five different silica morphologies; cylindrical MCM-41 and SBA-15, double gyroid MCM-48 and KIT-6, and cage-like SBA-16. In addition, the work by Sayari et al., 15 looked into the CO2 capacity of standard MCM-41 against pore-expanded MCM-41 and found higher CO2 capacity for the latter. This larger CO2 capacity is attributed to the increased loading of the aminopolymer, made possible due to the larger pore volume brought about by the increase in pore diameter. Furthermore, in almost all cases, 3D structures outperform 2D structures. 16 However, the physical origin of why the adsorption capacity of aminopolymer/silica varies with the morphology of the porous support (i.e., cylindrical vs. double gyroid vs. cage-like pores) remains unclear. Additionally, while such ordered 2D and 3D structures have proven to be valuable models for deriving fundamental understanding of composite adsorbents, their costs for commercial deployment will be prohibitively high. Therefore, generating a broad understanding of the relationship between sorbent structure and performance across support materials with systematically varied properties is important for the translation of

3


Langmuir

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

the technology to commercial supports. It has been suggested, by neutron scattering experiments and coarse-grained molecular dynamics simulations, that amines attached to polymer segments located near the vicinity of pore walls have less propensity to adsorb CO2 . This is due to their limited mobility or slower polymer segmental dynamics, while bulk-like PEI found in the middle of the pores is the active species. 17,22 Also given the strong affinity of CO2 to the amine moieties, we can expect that the diffusion of CO2 across these composites is hindered by the motion of the polymer. 23 We can then infer that the penetration of CO2 through that bulk liquid is one of the major factors that sets the CO2 capacities of these composites. Hence, in this contribution, we extend the computational work described in ref. 22 to probe the influence of pore morphology to the polymer segmental dynamics through coarse-grained molecular dynamics simulations. We then link the dynamical trends observed in simulations with the CO2 adsorption capacities observed in experiments. Specifically, SBA-15, SBA-16, KIT-6 and MCM-48 were synthesized as supports for PEI impregnation. SBA-15, SBA-16 and KIT6 were synthesized to have similar pore diameters (roughly 8 nm), a situation that matches the simulations. While MCM-48, which is a double gyroid structure similar to KIT-6 but with a smaller pore diameter (roughly 3 nm), was selected to investigate the influence of pore size by contrasting results with KIT-6. A range of PEI loadings were used to further probe the interactions between the confined aminopolymer, the silica support and their influence on the adsorption of CO2 .

Model and Simulation Details In this work, we used the simulation approach and the model of aminopolymer/silica composites developed by Carrillo et al. 22 Briefly, the branched aminopolymer PEI is coarse-grained and represented by 20 Lennard-Jones (LJ) beads connected such that there are 7 primary (1◦ ), 8 secondary (2◦ ), and 5 tertiary (3◦ ) amines (see inset in Figure 1) to simulate the

4


Page 4 of 39

Page 5 of 39

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

Langmuir

distribution of amines in the PEI used in the experiments. Each bead of the coarse-grained polymer represents a −CH2 −CH2 −NHx − moiety and the diameter of the LJ bead, σ, is approximately 3.5 ˚ A. The bead-to-bead interaction is represented by a shifted and truncated LJ potential,

ULJ =

 6 12 6 12  σ σ σ  4εb r + rcut − rσij − rcut ij

rij ≤ rcut

  0

rij > rcut

(1)

where rij is the distance between the ith and j th beads, σ is the bead diameter, rcut = 2.5 σ, is the cutoff distance, and εb is the well depth. The value of εb determines the solvent quality of the polymer in implicit solvent simulations, where εb = 1/3 kT (where kT is the thermal energy) denotes ideal solvent quality that results in a polymer structure described by a random walk. 24 For cases where εb > 1/3 kT , there exists a net attraction between LJ beads within the polymer resulting in a smaller polymer radius of gyration and denotes that the polymer is under poor solvent conditions. The solvent quality becomes poorer as the value of εb increases because of increasing bead-to-bead attractions. In this work, we used εb values of 1/3 kT and 3/2 kT representing both ideal and poor solvent qualities. The connectivity of the LJ beads in the branched polymer described in ref. 22 is maintained by the finite extensible nonlinear elastic (FENE) potential. 25 The silica support has associating surface beads (red beads in Figure 1) that have attractive LJ interactions with well depth εw = 2 kT with 1◦ amine beads (orange beads in Figure 1), which mimics the hydrogen bonding of OH groups in the silica support with the 1◦ amines in the polymer. The surface number density of the associating beads ρA is the same for different support morphologies. The procedure on how the models of the silica supports were prepared is described in the Supporting Information, which uses the parametric equations described by Wohlgemuth et al. 26 In this work we changed the morphology of the silica support to explore cylinders (e.g., SBA-15), double gyroid (e.g., KIT-6 and MCM-48), and linked cage-like (e.g., SBA-16) supports. (See Figure 1.) All simulations were performed 5


Langmuir

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

Page 6 of 39

using the LAMMPS 27 software package with GPU acceleration 28 at the Oak Ridge Leadership Computing Facility (OLCF). The system sizes (e.g., m, natom , and nR for the number of polymers, total number of LJ beads and number of surface reactive beads, respectively), dimensions (e.g., Lx , Ly , and Lz for simulation box dimensions in x, y and z directions, respectively) and other system properties (e.g., surface are and pore volume) are summarized in Table 1. Other system properties, such as average pore diameter and the ratio of pore surface area and pore volume, are presented in Table 2. The procedures for determining the textural properties in Tables 1 and 2, as well as confirmation of the XRD patterns and pore size distributions (PSD) of the supports, are presented in Figures S2 and S3 in the Supporting Information, respectively. All dynamical quantities calculated from the simulation trajectories are reported with reference to the dimensionless time unit, τ = σ(m/kT )1/2 , where m is the mass of a bead. Typically, τ is in the order of a nanosecond. 29 Further details of the molecular dynamics simulations are provided in ref. 22 Table 1: Simulation System Sizes and Dimensions. Structure Cylinders Double Gyroid Schoen IWP

Lx Ly Lz m natom nR * Surface Area (σ) (σ) (σ) (σ 2 ) 80 69.3 50 641 225910 14614 25384** 50 50 50 704 68667 7394 12842 56 56 56 897 103889 12858 22334

Pore Volume (σ 3 ) 64053 70412 89674

*Surface density, ρA = 0.576 σ −3 **Surface Area = 16 × 2πrcylinder × Lz ; rcylinder = 5.05σ

Table 2: Properties of Simulated Mesoporous Supports. Structure Cylinders Double Gyroid Schoen IWP

Average Pore Size Pore Surface Area/ Pore Volume ˚−1 ) (Diameter d, σ) (d, ˚ A) (γ, σ −1 ) (γ, A 9.24 ± 0.05 32.3 ± 0.2 0.396 0.113 9.20 ± 0.05 32.2 ± 0.2 0.182 0.052 9.24 ± 0.05 32.3 ± 0.2 0.249 0.071

6


Page 7 of 39

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

Langmuir

Cylinders

Double Gyroid

Schoen IWP

(e.g., SBA-15)

(e.g., MCM-48)

(e.g., SBA-16)

Impregnated polymer

Figure 1: Different morphologies of mesoporous supports: 2D arranged cylinders (left column), 3D periodic double gyroids (center column) and 3D cubic cage-like or Schoen IWP (right column). The mesoporous supports are represented as LJ beads (red and green beads in the bottom row) and have sites at the pore surface (red beads) that have attractive interactions with the 1◦ amines (orange beads) of the impregnated coarse-grained model of an aminopolymer. The inset shows the coarse-grained branched polymer described in ref. 22

7


Langmuir

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

Experimental Section Materials All chemicals were obtained from Sigma Aldrich and used as received without further purification.

Synthesis of silica supports SBA-15 synthesis SBA-15 was created from the recipe of Brunelli et al. 30 24.01 g of Pluronic P123 was initially dissolved in 630 mL of H2 O and 120 mL of concentrated hydrochloric acid (37 wt%) while rapidly stirring at 40 ◦ C to give a clear solution with white foam. Next, 52.68 g of tetraethoxysilane (TEOS) was added dropwise, after which the system was left to stir for 20 h at 40 ◦ C. The system was then aged under static conditions at 100 ◦ C for 24 h. The mixture was then filtered and washed with 6 L of deionized water. The white powder was subsequently dried at 75 ◦ C overnight prior to calcination. The powder was calcined by heating to 200 ◦ C at a rate of 1.2 ◦ C/min, holding for 1 h, and then increasing the temperature to 550 ◦ C at a rate of 1.2 ◦ C/min and holding for 4 h to yield a white powder. SBA-16 synthesis SBA-16 was created from the recipe of Kleitz et al. 31 with some minor modifications. First, 5.0 g of Pluronic F127 was dissolved in an acidic solution of 10.5 g concentrated HCl and 240 mL of deionized water inside of a 500 mL Erlenmeyer flask with a loose glass lid. Once dissolved, the temperature was raised to 45 ◦ C and 15 g of n-butanol was quickly added. The solution was stirred at that temperature for 1 h before 24 g TEOS was quickly added and the resultant mixture allowed to stir at 45 ◦ C for 24 h. The temperature was then increased to 90 ◦ C and the mixture was allowed to hydrothermally age under static conditions at that temperature for another 24 h. Following this aging, the resultant silica was immediately 8


Page 8 of 39

Page 9 of 39

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

Langmuir

filtered but not washed, and dried at 100 ◦ C for 24 h. Subsequently, the dried silica was slurried for 20 min with a mixture of 0.01 M HCl in ethanol and then filtered, dried at 75 ◦ C and calcined at 550 ◦ C for 2 h, with a 1.5 ◦ C/min ramp rate to that temperature from RT. KIT-6 synthesis KIT-6 was created from the recipe of Kleitz et al. 32 6.00 g of Pluronic P123 was put into a 1 L polypropylene bottle with 217 mL of deionized water and 11.8 mL of concentrated HCl. This system was closed and stirred at RT to dissolve the Pluronic P123. The system was heated to 35 ◦ C, and 6.00 g of n-butanol was added. The system was then closed and stirred at 35 ◦ C for a further 1 h. Next, 12.90 g of TEOS was added and the system was stirred for 24 h at 35 ◦ C. Following this, the stirring was stopped and the system heated to 100 ◦ C for 24 h. On removal and cooling, the system was filtered and calcined at a rate of 1 ◦ C/min up to 550 ◦ C, and held for 6 h. MCM-48 synthesis MCM-48 was created from the recipe of Doyle and Hodnett. 31 First, 5.00 g of cetyltrimethylammonium bromide and 0.5 g of sodium hydroxide were dissolved in 45 mL of deionized water. Then, 5.5 mL of TEOS was added to the solution, which was stirred at 35 ◦ C for 30 min, at which point a white solid formed. 33 The gel was then put into a PTFE-lined autoclave and heated at 150 ◦ C for 24 h. On removal and cooling the system was washed with 500 mL of deionized water and calcined at 650 ◦ C, at a rate of 2 ◦ C/min, and held for 6 h.

PEI impregnation Typically, 1.0 g of the above silica supports was initially stirred with 15 mL of methanol at room temperature for 1 h. A 20 mL solution of methanol containing either 670, 430 or 250 mg (as appropriate) of 800 MW branched PEI was added to the slurry and stirred for a 9


Langmuir

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

further 24 h at room temperature. The solvent was then removed under reduced pressure at 50 ◦ C to yield a white powder. The sample was then dried at 110 ◦ C for 12 h at 10 mbar. For the SBA-16 sorbents, two iterations of composites were prepared because structural degradation was observed in the materials. The second iteration of sorbents was prepared slightly differently than the above, meant to create more dilute conditions during preparation (i.e., more solvent per g silica and PEI). Here, 0.25 g of dried SBA-16 was dispersed in 20 mL of methanol. Separately, a given amount of PEI was dissolved in 10 mL of methanol. After stirring separately for 1 h, the PEI containing solution was added dropwise to the silica dispersion, and the resultant mixture stirred for 3 h before the solvent was removed and sorbent dried in the same manner as detailed above.

Characterization of silica supports and composites Nitrogen physisorption Nitrogen physisorption was performed on a Micrometrics Tristar 3020 instrument at 77 K. Samples were degassed for 12 h at 110 ◦ C prior to analysis. The data were analyzed using non local density functional theory (NLDFT) methods in the Quantachrome Versawin software package. Each silica sample was analyzed with the appropriate NLDFT kernel according to previous literature precedent. SBA-15 was analyzed with the cylinder model considering the adsorption branch of the isotherm. 34 SBA-16 was analyzed with the cylinder/sphere model considering the adsorption branch. 31,35 This model accounts for cylinders smaller than 5 nm and spheres larger than 5 nm, and is meant to capture the textural and geometric features of templated materials such as SBA-16. KIT-6 and MCM-48 were analyzed with the equilibrium model of cylindrical pores, considering the desorption branch of the isotherm. 36 Gravimetric CO2 adsorption Dry CO2 sorption capacities were measured using a TA instruments Q500 TGA using 10% CO2 in helium. Samples were pretreated under a 100 mL/min flow of helium at 110 ◦ C for 10


Page 10 of 39

Page 11 of 39

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

Langmuir

3 h. The CO2 uptake was then measured from the gain in mass after subsequent exposure to 10% CO2 in helium, at 30 ◦ C, flowed at 90 mL/min for 6 h, with a 10 mL/min balance helium flow. Organic content of sorbent The PEI content of the samples was measured using a Netzsch STA409PG TGA. The weight loss between 120 ◦ C to 900 ◦ C, under a combined flow of 90 mL/min of air and a 30 mL/min of nitrogen, was used to estimate the organic content in the sorbents. The data were collected between 25 and 900 ◦ C at a heating at a rate of 10 ◦ C/min. PEI content was taken as the mass loss between 120 ◦ C and 900 ◦ C, after correcting for mass loss from residual surfactant or strongly bound water left on the bare silica. Powder X-ray diffraction Powder XRD patterns were obtained by use of a PANalytical X’Pert diffractometer with a CuKα X-ray source. The XRD patterns for the different silica supports are presented in Figure S5 in the Supporting Information. Microscopy Scanning electron microscopy (SEM) was performed on a Hitachi SU8230 with cold field emission gun at 1 kV accelerating voltage and 2 µA emission current. Transmission electron microscopy (TEM) was performed on a FEI Tecnai F30 with thermally-assisted field emission gun at 300 kV accelerating voltage. TEM and SEM images are presented in Figure S6 in the Supporting Information.

11


Langmuir

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

Page 12 of 39

Results and Discussion Simulation results The pair distribution as a function of space and time or the Van Hove 37 correlation function, G(r, t), of polymer beads is a means of quantifying the dynamics of the polymer segments in the bulk and impregnated into a silica support. The spatial Fourier transform of G(r, t) is the intermediate dynamic structure factor that consists of the self, Fs (q, t), and the distinct, Fd (q, t), parts. Here q is the magnitude of the wave vector transfer and is related to the pair distance r as q = 2π/r. We are interested in the self part of the intermediate dynamic structure, which is related to the scattering intensity, I(q, ω), obtained from quasi-elastic neutron experiments (QENS) experiments and pertains to the correlations of individual beads to itself. 22 In the simulations, Fs (q, t) is directly computed from the trajectories of the LJ beads in the coarse-grained molecular dynamics simulations as, * N + X 1 e i q~·(~ri (t)−~ri (0)) Fs (q, t) = N i

(2)

where N is the total number of polymer LJ beads, ~q is the wave vector transfer and ~r is the position vector. The dynamics of the LJ beads inside the different mesoporous supports can then be compared based on how rapid Fs (q, t) decays, where a faster decay would mean faster loss of spatial correlation and pertains to faster bead dynamics. In Figure 2, the Fs (q, t) of the LJ beads within cylinders, double gyroid and cage-like IWP mesoporous supports are presented at different values of q, which range from 1 to 6 σ −1 and is equivalent to length scales in between the size of the pore diameter, d and the bead diameter σ. Rapid decay is observed for the LJ beads inside the cage-like IWP mesoporous supports at all values of q considered and up to time scales below 103 τ . After which, there is a slowing down of the decay and the decay of the LJ beads within the double gyroid mesoporous supports is more rapid. These subtle details are not revealed just by examining the value of the ratio between the pore surface area and pore volume or γ (see Table 2), where 12


Page 13 of 39

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

Langmuir

we expect a lower value would result in faster dynamics if the pore radius is kept constant. This can be attributed to the effect of the 3D morphology of the mesoporous support, which indicates that the dynamics inside the cage in the cage-like IWP structure is faster than those of the double gyroid. However, at longer time scales where the beads at the middle of the cage approach the cage wall or the channels connecting the cage, the dynamics slows down relative to the double gyroid. The Fs (q, t) for the beads inside cylindrical pores have the slowest decay, reflective of the 2D nature of the morphology and the high value of γ. We have previously shown that we can fit the Fs (q, t) of aminopolymers impregnated into a cylindircal pore with the sum of three exponential decay functions with three characteristic relaxation times, representing the motions of beads belonging to unadsorbed polymers, beads in a polymer that are attached to adsorbed primary amine beads, and adsorbed primary amine beads. 22 Intuitively, to explain the hopping dynamics of the polymer beads in the cagelike supports, we can add another process by adding one more exponential decay function in the fitting equation, representing the motion of beads hopping from one IWP cage to another (see Figure S4 in the Supporting Information). The longest relaxation time obtained from the fit is around 104 τ , which estimates the relaxation time of the cage-hopping process. Here, we comment on the precision of the data obtained in the calculation of the Fs (q, t) used in the fitting procedure. The error bars shown in Figure S4 represents one standard error of the mean (SE) in both directions of the y-axis. The SE indicates how precisely the data √ point is calculated and is related to the standard deviation (SD) as SD/ nens , where nens is the number of samples in the ensemble average. The error bars in Figure S4 only become as large as the figure symbols in the Fs (q, t) = 10−5 range, thus these numbers are still meaningful at this range. The small value of the SE is possible by using a large sample size for the ensemble. In addition, all calculations were done at double-precision floating-point accuracy. To further explore the effects of the morphology on the dynamics of the beads inside the mesoporous supports, in Figure 3 we calculated the partial radial distribution function,

13


Langmuir

Fs (q, t)

100

q = 1.0σ −1

q = 2.0σ −1

100

10−1

10−1

10−2

10−2

10−3

10−3

10−4

Cylinder Double Gyroid IWP

10−5 10−1

100

101

102

10−4 103

100

Fs (q, t)

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

Page 14 of 39

104

105

10−1

100

101

102

q = 4.0σ −1

103

104

10−5 105

q = 6.0σ −1

100

10−1

10−1

10−2

10−2

10−3

10−3

10−4

10−4

10−5 10−1

100

101

102

103

104

105

10−1

100

t[τ ]

101

102

103

104

10−5 105

t[τ ]

Figure 2: Self intermediate dynamic structure factor, Fs (q, t), of monomer beads inside cylinders (red squares), double gyroid (black circles) and cage-like IWP (blue triangles) mesoporous supports at different values of q. Error bars (SE) are of the same size as data points.

14


Page 15 of 39

g(r), of the contacts between 1◦ amine beads and pore surface associating beads (red beads in Figure 1). This function gives the density probability for a pore surface associating bead to have a 1◦ amine neighbor at a given distance r. Higher intensities for the first coordinate peak are observed for g(r) in cylinders, followed by double gyroid and then by cage-like IWP, which indicates that associating beads in cylinders have the highest probability to be in contact with a 1◦ amine. This trend agrees with the trend for Fs (q, t) at short t and is indicative that when more 1◦ amine beads are adsorbed on the surface, this results in slower segmental dynamics. 8.0 Cylinder Double Gyroid IWP

6.0

g(r)

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

Langmuir

4.0

2.0

0.0

100

101

r[σ] Figure 3: Partial radial distribution function, g(r), of 1◦ amine beads with associating surface beads for branched polymers impregnated into cylinders (red squares), double gyroid (black circles) and cage-like IWP (blue triangles) mesoporous supports. Furthermore, we calculated the mean square displacement of 1◦ amine beads, MSD1◦ , of the branch polymer in the bulk and in confinement (see Figure 4). The transition from the ballistic regime (power law = 2) to the diffusive regime (power law = 1) is more abrupt in the bulk than to those of the confined polymers with notably short sub-diffusive regime in between the two regimes. The polymers confined in the IWP has the longest duration of the transition from the sub-diffusive to diffusive regimes, occurring at around 104 τ . This long transition is indicative of caging of the primary beads. The time of occurrence of the transition from the sub-diffusive to the diffusive regime is in agreement with the estimated 15


Langmuir

value of the longest characteristic time obtained by fitting the Fs (q, t) of the polymer beads at q = 6.0σ −1 (or at the length scale of bead) with the sum of four exponential decay functions as described in Figure S4 in the Supporting Information. 104

MSD1◦ [σ 2 ]

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

Page 16 of 39

Cylinder Double Gyroid IWP Bulk

103 102 101

1

t90,cyl ) regardless of solvent quality. The ratio of the characteristic times between the double gyroid and the large cylinder, t90,DG /t90,cyl , is an indicator of the relative decrease of the dynamics of the beads in the double gyroid support relative to the beads inside the large cylinder. The inset in Figure 10 demonstrates that the characteristic time in the double gyroid is ∼ 20% larger than that of the large cylinder for εb = 1/3 kT . In comparison, this is increased to ∼ 40% when εb is increased to 3/2 kT and can be attributed to the clogging of the double gyroid pore. With these results, we have demonstrated that an increase in the viscosity of the impregnated aminopolymer drastically decreases the dynamics of the polymer especially in smaller pores where the aggregating polymer can easily clog the pore, thus providing a probable explanation for why the PEI/MCM-48 has a lower CO2 uptake than the PEI/SBA-15 aminopolymer/silica composite at high PEI loadings. Again, we remind the reader that the coarse-grained molecular dynamics approach taken in ref. 22 and extended in this work can only provide qualitative agreements with experimental results. Despite this we are still able to gain valuable insights into optimal sorbent design where the simulations suggest that aside from pore size, pore morphology also affects CO2 uptake by changing the interplay between the interaction of 1◦ amines to surface silanols and the aggregation PEI segments.

Summary In this work we have used the coarse-grained model and molecular dynamics simulations approach described in ref. 22 and extended the procedure to investigate the effect of the mesoporous support morphology on the dynamics of the impregnated branched polymer. The results show subtle details in the dynamics of the polymers that can be attributed to the morphology of the mesoporous support. Specifically, if the pore diameter is equivalent, the polymer dynamics of a 3D periodic structure (e.g., double gyroid/MCM-48 and cage-like

27


Langmuir

105 Double Gyroid Cylinder

4

10

= 3

t90,DG /t90,cyl

kT

kT

10

εb = 1/3kT εb = 3/2kT

1.8

3

0

2.0

1

101

2

102

=

t90 [τ ]

εb

103 εb

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

Page 28 of 39

1.6 1.4 1.2 1.0 1

2

3

q

4

10−1 −1 10

5

6

100

101

q[σ] Figure 10: Characteristic time, t90 of the Fs (q, t) monomer beads inside large cylinders (magenta sqaures) and double gyroid (black circles) mesoporous supports at different values of q and solvent quality (εb ). Error bars (SE) are of the same size as data points.

28


Page 29 of 39

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

Langmuir

IWP/SBA-16) is generally faster than those of 2D structures (e.g., cylinders/SBA-15) and can be attributed to higher pore surface area to pore volume ratio, γ, of the 2D morphology (more surface contacts). Furthermore, the cage-like IWP support (e.g., SBA-16) is predicted to have faster dynamics than the double gyroid (e.g., MCM-48) support at shorter time scales because the cages provide a more “bulk-like” environment in comparison to the channels found in the double gyroid. However at longer time scales, this trend is reversed as the dynamics of the polymer in the cage-like IWP are obstructed by the cage wall and its dynamics are mostly due to the movement of the polymer in the narrower channels linking the cages (hopping from one cage to another). Unfortunately, we were unable to fully test this hypothesis with SBA-16, as the impregnated PEI catalyzed the degradation of the silica structure, making a quantitative characterization unfeasible. The synthesized KIT-6, which have approximately the same textural properties as the SBA-15, silica supports used in the aminopolymer composites, supports the simulation inference that PEI impregnated in double gyroids has faster dynamics and has more exposed primary amines that can readily adsorb CO2 . Hence the observed higher CO2 uptake by KIT-6 relative to SBA-15 containing cylindrical pores. In addition, we have synthesized PEI/MCM-48 (double gyroid support) aminopolymer/silica composites and observed better CO2 uptake by the PEI/SBA-15 despite its 2D morphology. Our simulations demonstrate the compounding effect of a smaller pore size and higher PEI viscosity on the dynamics of the aminopolymer in MCM-48 supports. They show that not only does the smaller pore size in the MCM-48 support lead to a higher γ value that slows down polymer dynamics, but also the presence of CO2 , which is known to increase the viscosity of PEI by facilitating cross-linking of amine groups, causes aggregation of the polymer that can easily clog the narrow pores in the MCM-48 support. Both slowing down of the polymer dynamics due to more surface contacts and the clogging of the pores likely contribute to the lower CO2 uptake in MCM-48 supports. Finally, we envision further improvements in sorbent design through the application

29


Langmuir

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

of our combined computational and experimental approach to alternative polymer/silica composite systems, such as systems with additives that enhance the CO2 adsorption process or to systems that contains both grafted and impregnated polymers, such as class 4 systems.

Supporting Information Available Details on how the supports are modeled and characterized in the simulations and the characterization of synthesized silica supports in the experiments are presented in the Supporting Information.

This material is available free of charge via the Internet at http:

//pubs.acs.org/.

Acknowledgement This work is supported by the Center for Understanding and Control of Acid Gas-Induced Evolution of Materials for Energy (UNCAGE-ME), an Energy Frontier Research Center funded by U.S. Department of Energy (US DoE), Office of Science, Basic Energy Sciences (BES) under Award no. DE-SC0012577. Computational aspects of this work were performed at the Center for Nanophase Materials Sciences (CNMS), a DOE Office of Science User Facility. This research used resources of the Oak Ridge Leadership Computing Facility (OLCF) at the Oak Ridge National Laboratory (ORNL), which is supported by the Office of Science of the U.S. DoE under Contract No. DE-AC05-00OR22725.

References (1) Wang, M.; Lawal, A.; Stephenson, P.; Sidders, J.; Ramshaw, C. Post-combustion Co2 Capture with Chemical Absorption: A State-of-the-art Review. Chem. Eng. Res. Des. 2011, 89, 1609–1624.

30


Page 30 of 39

Page 31 of 39

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

Langmuir

(2) Bollini, P.; Didas, S. A.; Jones, C. W. Amine-Oxide Hybrid Materials for Acid Gas Separations. J. Mater. Chem. 2011, 21, 15100–15120. (3) Lu, W.; Sculley, J. P.; Yuan, D.; Krishna, R.; Wei, Z.; Zhou, H.-C. Polyamine-Tethered Porous Polymer Networks for Carbon Dioxide Capture from Flue Gas. Angew. Chem. Int. Ed 2012, 51, 7480–7484. (4) Jande, Y.; Asif, M.; Shim, S.; Kim, W. Energy Minimization in Monoethanolaminebased CO2 Capture Using Capacitive Deionization. Int. J. Energy Res. 2014, 38, 1531– 1540. (5) Xu, X.; Song, C.; Andresen, J. M.; Miller, B. G.; Scaroni, A. W. Novel Polyethylenimine-Modified Mesoporous Molecular Sieve of MCM-41 Type as HighCapacity Adsorbent for CO2 Capture. Energy Fuels 2002, 16, 1463–1469. (6) Qi, G.; Fu, L.; Giannelis, E. P. Sponges with Covalently Tethered Amines for HighEfficiency Carbon Capture. Nat. Commun. 2014, 5 . (7) Hicks, J. C.; Drese, J. H.; Fauth, D. J.; Gray, M. L.; Qi, G.; Jones, C. W. Designing Adsorbents for CO2 Capture from Flue Gas-Hyperbranched Aminosilicas Capable of Capturing CO2 Reversibly for CO2 Capture from Flue Gas-Hyperbranched Aminosilicas Capable of Capturing CO2 Reversibly. J. Am. Chem. Soc. 2008, 130, 2902–2903. (8) Fauth, D.; Gray, M.; Pennline, H.; Krutka, H.; Sjostrom, S.; Ault, A. Investigation of Porous Silica Supported Mixed-Amine Sorbents for Post-Combustion CO2 Capture. Energy Fuels 2012, 26, 2483–2496. (9) Fan, Y.; Kalyanaraman, J.; Labreche, Y.; Rezaei, F.; Lively, R. P.; Realff, M. J.; Koros, W. J.; Jones, C. W.; Kawajiri, Y. CO2 Sorption Performance of Composite Polymer/Aminosilica Hollow Fiber Sorbents: An Experimental and Modeling Study. Ind. Eng. Chem. Res. 2015, 54, 1783–1795.

31


Langmuir

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

(10) Xu, X.; Song, C.; Miller, B. G.; Scaroni, A. W. Influence of Moisture on CO2 Separation from Gas Mixture by a Nanoporous Adsorbent Based on Polyethylenimine-Modified Molecular Sieve MCM-41. Ind. Eng. Chem. Res. 2005, 44, 8113–8119. (11) Zhang, W.; Liu, H.; Sun, C.; Drage, T. C.; Snape, C. E. Performance of Polyethyleneimine–Silica Adsorbent for Post-Combustion CO2 Capture in a Bubbling Fluidized Bed. Chem. Eng. J. 2014, 251, 293–303. (12) Choi, S.; Drese, J. H.; Jones, C. W. Adsorbent Materials for Carbon Dioxide Capture from Large Anthropogenic Point Sources. ChemSusChem 2009, 2, 796–854. (13) Li, W.; Choi, S.; Drese, J. H.; Hornbostel, M.; Krishnan, G.; Eisenberger, P. M.; Jones, C. W. Steam-Stripping for Regeneration of Supported Amine-Based CO2 Adsorbents. ChemSusChem 2010, 3, 899–903. (14) Wilfong, W. C.; Kail, B. W.; Jones, C. W.; Pacheco, C.; Gray, M. Spectroscopic Investigation of the Mechanisms Responsible for the Superior Stability of Hybrid Class 1/Class 2 CO2 Sorbents: A New Class 4 Category. ACS Appl. Mater. Interfaces 2016, 8, 12780–12791. (15) Franchi, R.; Harlick, P.; Sayari, A. A high capacity, water tolerant adsorbent for CO 2: diethanolamine supported on pore-expanded MCM-41. Stud. Surf. Sci. Catal. 2005, 156, 879–886. (16) Son, W.-J.; Choi, J.-S.; Ahn, W.-S. Adsorptive Removal of Carbon Dioxide using Polyethyleneimine-Loaded Mesoporous Silica Materials. Microporous Mesoporous Mater. 2008, 113, 31–40. (17) Holewinski, A.; Sakwa-Novak, M. A.; Jones, C. W. Linking CO2 Sorption Performance to Polymer Morphology in Aminopolymer/Silica Composites through Neutron Scattering. J. Am. Chem. Soc. 2015, 137, 11749–11759.

32


Page 32 of 39

Page 33 of 39

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

Langmuir

(18) Sanz, R.; Calleja, G.; Arencibia, A.; Sanz-Perez, E. CO2 Adsorption on Branched Polyethyleneimine-Impregnated Mesoporous Silica SBA-15. Appl. Surf. Sci. 2010, 256, 5323–5328. (19) Gargiulo, N.;

Caputo, D.;

Colella, C. Preparation and Characterization of

Polyethylenimine-modified Mesoporous Silicas as CO2 Sorbents. Stud. Surf. Sci. Catal. 2007, 170, 1938–1943. (20) Liu, Y.; Shi, J.; Chen, J.; Ye, Q.; Pan, H.; Shao, Z.; Shi, Y. Dynamic Performance of CO2 Adsorption with Tetraethylenepentamine-Loaded KIT-6. Microporous Mesoporous Mater. 2010, 134, 16–21. (21) Sakwa-Novak, M. A.; Holewinski, A.; Hoyt, C. B.; Yoo, C.-J.; Chai, S.-H.; Dai, S.; Jones, C. W. Probing the Role of Zr Addition versus Textural Properties in Enhancement of CO2 Adsorption Performance in Silica/PEI Composite Sorbents. Langmuir 2015, 31, 9356–9365. (22) Carrillo, J.-M. Y.; Sakwa-Novak, M. A.; Holewinski, A.; Potter, M. E.; Rother, G.; Jones, C. W.; Sumpter, B. G. Unraveling the Dynamics of Aminopolymer/Silica Composites. Langmuir 2016, 32, 2617–2625. (23) Zhang, R.; Schweizer, K. Statistical Mechanical Theory of Penetrant Diffusion in Polymer Melts and Glasses. Macromolecules 2016, 49, 5727–5739. (24) Grest, G. S.; Murat, M. Structure of Grafted Polymeric Brushes in Solvents of Varying Quality: a Molecular Dynamics Study. Macromolecules 1993, 26, 3108–3117. (25) Kremer, K.; Grest, G. S. Dynamics of Entangled Linear Polymer Melts: A MolecularDynamics Simulation. J. Chem. Phys. 1990, 92, 5057–5086. (26) Wohlgemuth, M.; Yufa, N.; Hoffman, J.; Thomas, E. L. Triply Periodic Bicontinuous

33


Langmuir

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

Cubic Microdomain Morphologies by Symmetries. Macromolecules 2001, 34, 6083– 6089. (27) Plimpton, S. Fast Parallel Algorithms for Short-Range Molecular Dynamics. J. Comput. Phys. 1995, 117, 1–19. (28) Brown, W. M.; Wang, P.; Plimpton, S. J.; Tharrington, A. N. Implementing Molecular Dynamics on Hybrid High Performance Computers–Short Range Forces. Comput. Phys. Commun. 2011, 182, 898–911. (29) Carrillo, J.-M. Y.; Sumpter, B. G. Structure and Dynamics of Confined Flexible and Unentangled Polymer Melts in Highly Adsorbing Cylindrical Pores. J. Chem. Phys. 2014, 141, 074904. (30) Brunelli, N. A.; Didas, S. A.; Venkatasubbaiah, K.; Jones, C. W. Tuning Cooperativity by Controlling the Linker Length of Silica-Supported Amines in Catalysis and CO2 Capture. J. Am. Chem. Soc. 2012, 134, 13950–13953. (31) Kleitz, F.; Czuryszkiewicz, T.; Solovyov, L. A.; Lindén, M. X-ray Structural Modeling and Gas Adsorption Analysis of Cagelike SBA-16 Silica Mesophases prepared in a F127/Butanol/H2 O System. Chem. Mater. 2006, 18, 5070–5079. (32) Kleitz, F.; Choi, S. H.; Ryoo, R. Cubic Ia3d Large Mesoporous Silica: Synthesis and Replication to Platinum Nanowires, Carbon Nanorods and Carbon Nanotubes. Chem. Commun. 2003, 2136–2137. (33) Doyle, A.; Hodnett, B. Stability of MCM-48 in Aqueous Solution as a Function of pH. Microporous Mesoporous Mater. 2003, 63, 53–57. (34) Ravikovitch, P. I.; Neimark, A. V. Characterization of Micro- and Mesoporosity in SBA-15 Materials from Adsorption Data by the NLDFT Method. J. Phys. Chem. B 2001, 105, 6817–6823. 34


Page 34 of 39

Page 35 of 39

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

Langmuir

(35) Ravikovitch, P. I.; Neimark, A. V. Density Functional Theory of Adsorption in Spherical Cavities and Pore Size Characterization of Templated Nanoporous Silicas with Cubic and Three-Dimensional Hexagonal Structures. Langmuir 2002, 18, 1550–1560. (36) Kleitz, F.; Bérubé, F.; Guillet-Nicolas, R.; Yang, C.-M.; Thommes, M. Probing Adsorption, Pore Condensation, and Hysteresis Behavior of Pure Fluids in Three-Dimensional Cubic Mesoporous KIT-6 Silica. J. Phys. Chem. C 2010, 114, 9344–9355. (37) Van Hove, L. Correlations in Space and Time and Born Approximation Scattering in Systems of Interacting Particles. Phys. Rev. 1954, 95, 249. (38) Kruk, M.; Jaroniec, M.; Ko, C. H.; Ryoo, R. Characterization of the Porous Structure of SBA-15. Chem. Mater. 2000, 12, 1961–1968. (39) Hoang, V.-T.; Huang, Q.; Eic, M.; Do, T.-O.; Kaliaguine, S. Structure and Diffusion Characterization of SBA-15 Materials. Langmuir 2005, 21, 2051–2057. (40) Doi, Y.; Takai, A.; Sakamoto, Y.; Terasaki, O.; Yamauchi, Y.; Kuroda, K. Tailored Synthesis of Mesoporous Platinum Replicas Using Double Gyroid Mesoporous Silica (KIT-6) with Different Pore Diameters via Vapor Infiltration of a Reducing Agent. Chem. Commun. 2010, 46, 6365–6367. (41) Grudzien, R. M.; Grabicka, B. E.; Jaroniec, M. Effective Method for Removal of Polymeric Template from SBA-16 Silica Combining Extraction and Temperature-Controlled Calcination. J. Mater. Chem. 2006, 16, 819–823. (42) Kim, T.-W.; Ryoo, R.; Kruk, M.; Gierszal, K. P.; Jaroniec, M.; Kamiya, S.; Terasaki, O. Tailoring the Pore Structure of SBA-16 Silica Molecular Sieve through the Use of Copolymer Blends and Control of Synthesis Temperature and Time. J. Phys. Chem. B 2004, 108, 11480–11489.

35


Langmuir

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

(43) Alfredsson, V.; Anderson, M. W. Structure of MCM-48 Revealed by Transmission Electron Microscopy. Chem. Mater. 1996, 8, 1141–1146. (44) Walters, M. S.; Lin, Y.-J.; Sachde, D. J.; Edgar, T. F.; Rochelle, G. T. Control Relevant Model of Amine Scrubbing for CO2 Capture from Power Plants. Ind. Eng. Chem. Res. 2016, 55, 1690–1700. (45) Aaron, D.; Tsouris, C. Separation of CO2 from Flue Gas: a Review. Sep. Sci. Technol. 2005, 40, 321–348. (46) Sayari, A.; Belmabkhout, Y.; Serna-Guerrero, R. Flue Gas Treatment via CO2 adsorption. Chem. Eng. J. 2011, 171, 760–774. (47) Samanta, A.; Zhao, A.; Shimizu, G. K.; Sarkar, P.; Gupta, R. Post-Combustion CO2 Capture Using Solid Sorbents: a Review. Ind. Eng. Chem. Res. 2011, 51, 1438–1463. (48) Alkhabbaz, M. A.; Bollini, P.; Foo, G. S.; Sievers, C.; Jones, C. W. Important Roles of Enthalpic and Entropic Contributions to CO2 Capture from Simulated Flue Gas and Ambient Air Using Mesoporous Silica Grafted Amines. J. Am. Chem. Soc. 2014, 136, 13170–13173. (49) Yoo, C.-J.; Lee, L.-C.; Jones, C. W. Probing Intramolecular versus Intermolecular CO2 Adsorption on Amine-Grafted SBA-15. Langmuir 2015, 31, 13350–13360. (50) Roque-Malherbe, R.; Polanco-Estrella, R.; Marquez-Linares, F. Study of the Interaction between Silica Surfaces and the Carbon Dioxide Molecule. J. Phys. Chem. C 2010, 114, 17773–17787. (51) Belmabkhout, Y.; Serna-Guerrero, R.; Sayari, A. Adsorption of CO2 from Dry Gases on MCM-41 Silica at Ambient Temperature and High Pressure. 1: Pure CO2 Adsorption. Chem. Eng. Sci. 2009, 64, 3721–3728.

36


Page 36 of 39

Page 37 of 39

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

Langmuir

(52) Mello, M. R.; Phanon, D.; Silveira, G. Q.; Llewellyn, P. L.; Ronconi, C. M. AmineModified MCM-41 Mesoporous Silica for Carbon Dioxide Capture. Microporous Mesoporous Mater. 2011, 143, 174–179. (53) Heydari-Gorji, A.; Belmabkhout, Y.; Sayari, A. Polyethylenimine-Impregnated Mesoporous Silica: Effect of Amine Loading and Surface Alkyl Chains on CO2 Adsorption. Langmuir 2011, 27, 12411–12416. (54) Pinto, M. L.; Mafra, L.; Guil, J. M.; Pires, J.; Rocha, J. Adsorption and Activation of CO2 by Amine-Modified Nanoporous Materials Studied by Solid-State NMR and 13CO2 Adsorption. Chem. Mater. 2011, 23, 1387–1395. (55) Knöfel, C.; Martin, C.; Hornebecq, V.; Llewellyn, P. L. Study of Carbon Dioxide Adsorption on Mesoporous Aminopropylsilane-Functionalized Silica and Titania Combining Microcalorimetry and in situ Infrared Spectroscopy. J. Phys. Chem. C 2009, 113, 21726–21734. (56) Didas, S. A.; Kulkarni, A. R.; Sholl, D. S.; Jones, C. W. Role of Amine Structure on Carbon Dioxide Adsorption from Ultradilute Gas Streams such as Ambient Air. ChemSusChem 2012, 5, 2058–2064. (57) Zelenak, V.; Halamova, D.; Gaberova, L.; Bloch, E.; Llewellyn, P. Amine-Modified SBA-12 Mesoporous Silica for Carbon Dioxide Capture: Effect of Amine Basicity on Sorption Properties. Microporous Mesoporous Mater. 2008, 116, 358–364. (58) Kim, H.-J.; Chaikittisilp, W.; Jang, K.-S.; Didas, S. A.; Johnson, J. R.; Koros, W. J.; Nair, S.; Jones, C. W. Aziridine-Functionalized Mesoporous Silica Membranes on Polymeric Hollow Fibers: Synthesis and Single-Component CO2 and N2 Permeation Properties. Ind. Eng. Chem. Res. 2014, 54, 4407–4413. (59) Wilfong, W. C.; Srikanth, C. S.; Chuang, S. S. In Situ ATR and DRIFTS Studies

37


Langmuir

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

of the Nature of Adsorbed CO2 on Tetraethylenepentamine Films. ACS Appl. Mater. Interfaces 2014, 6, 13617–13626. (60) Turgman-Cohen, S.; Giannelis, E. P.; Escobedo, F. A. Transport Properties of Amine/Carbon Dioxide Reactive Mixtures and Implications to Carbon Capture Technologies. ACS Appl. Mater. Interfaces 2015, 7, 17603–17613.

38


Page 38 of 39

Page 39 of 39

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

Langmuir

Graphical TOC Entry

39


Linking Silica Support Morphology to the Dynamics of Aminopolymers

Recommend Documents