Phenol Molecular Sheets Woven by Water Cavities in Hydrophobic Slit

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Phenol Molecular Sheets Woven by Water Cavities in Hydrophobic Slit Nanospaces Piotr Kowalczyk, Marek Wi#niewski, Artur Deditius, Jerzy Wloch, Artur Piotr Terzyk, Wendell P. Ela, Katsumi Kaneko, Paul A. Webley, and Alexander V. Neimark Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.8b02832 • Publication Date (Web): 17 Nov 2018 Downloaded from http://pubs.acs.org on November 23, 2018

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Phenol Molecular Sheets Woven by Water Cavities in Hydrophobic Slit Nanospaces

Piotr Kowalczyk*1, Marek Wiśniewski2, Artur Deditius1, Jerzy Wƚoch2, Artur P. Terzyk2, Wendell P. Ela1, Katsumi Kaneko3, Paul A. Webley4, and Alexander V. Neimark5

[1] School of Engineering and Information Technology, Murdoch University, 90 South Street, Murdoch 6150, Western Australia, Australia

[2] Physicochemistry of Carbon Materials Research Group, Faculty of Chemistry, N. Copernicus University in Toruń, 7 Gagarin St., 87-100 Toruń, Poland

[3] Center for Energy and Environmental Science, Shinshu University, 4-17-1, Wakasato, Nagano-City, 380-8553, Japan

[4] School of Chemical and Biomedical Engineering, University of Melbourne, Parkville, VIC 3010, Australia

[5] Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, 98 Brett Road, Piscataway, NJ 08854-8058, United States

E-mail: [email protected]

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Keywords Phenol adsorption, super-sieving effect, two-dimensional crystals, Molecular Dynamics simulations, percolating water cluster.


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Abstract

Despite extensive research over the last several decades, the microscopic characterisation of topological phases of adsorbed phenol from aqueous solutions in carbon micropores (pore size < 2.0 nm), which are believed to exhibit a solid and quasi-solid character, has not been reported. Here we present a combined experimental and molecular level study of phenol adsorption from neutral water solutions in graphitic carbon micropores. Theoretical and experimental results show high adsorption of phenol and negligible co-adsorption of water in hydrophobic graphitic micropores (super-sieving effect). Graphic processing unit-accelerated molecular dynamics simulations of phenol adsorption from water solutions in a realistic model of carbon micropores reveal the formation of two-dimensional phenol crystals with a peculiar pattern of hydrophilichydrophobic stripes in 0.8 nm supermicropores. In wider micropores, disordered phenol assemblies with water clusters, linear chains, and cavities of various sizes are found. The highest surface density of phenol is computed in 1.8 nm supermicropore. The percolating water cluster spanning the entire pore space is found in 2.0 nm supermicropore. Our findings open the door for the design of better materials for purification of aqueous solutions from nonelectrolyte micropollution.


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Introduction

Adsorption processes are playing a central role in water purification and clean-up from nonelectrolyte micropollution including toxic industrial chemicals, dyes, chlorine and chloramines, pesticides, pharmaceuticals, personal care products, and endocrine-disrupting chemicals, amongst others [1]. It has been estimated that ~80% of industrial water contaminates are phenolic derivatives [2]. Of these, most compounds are recognized as toxic carcinogens [2]. Thus, is it not surprising that phenol, a planar molecule with a hydroxyl group attached to the benzene ring, is a recommended probe for testing potential adsorbents for water purification and clean-up by adsorption processes [3, 4]. Nanoporous carbon adsorbents, such as granular activated carbons produced from natural precursors (GACs) and activated carbon fibres (ACFs) have been used in portable water purification systems and water treatment power plans for the production of clean drinking water [5, 6]. It is generally accepted that the wettability and the nanopore structure of carbon adsorbents are the most important properties for the optimization of their performance towards adsorptive removal of non-electrolyte contaminates [7-9]. Yet, the specifics of competitive solute-water adsorption in nanopores of the molecular size are still poorly understood. As a result, a “try it and see” approach rather than theory-informed design has been commonly used in search for advanced adsorbents. The cooperative effects of the nanopore size and wettability in adsorption of phenols are subjects of subsequent investigation [10, 11]. A variety of experimental methods have been used to study the mechanism of phenol adsorption from aqueous solutions at different pH, including amongst others, adsorption, calorimetry, Boehm titration, and X-ray photoelectron spectroscopy (XPS) analysis [12-14]. Although these methods provide a viable insight into the mechanism of phenol adsorption from aqueous solutions, they lack a detail analysis of the 4 ACS Paragon Plus Environment

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molecular configurations of the phenol-water mixtures in nanopores. Moreover, the methods of classical phenomenological thermodynamics have been commonly used for modelling and interpretation of adsorption isotherms [15-17]. However, the homogeneous representation of adsorbed phases by classical thermodynamics is questionable, when the sizes of pores and adsorbed molecules are similar. This is because of the molecular packing effects and strong lateral interactions in confining geometries [18, 19]. It is generally accepted [20-22] that adsorption of phenol from aqueous solutions on carbon adsorbents is maximized at neutral pH, when the nanopore blocking and co-adsorption of water molecules on the oxygen-containing functional groups (so-called “solvent effect”) is the lowest. In hydrophobic ultramicropores and narrow supermicropores with pore sizes 1.4 nm), the coadsorption of water is expected, however, both the composition and the structure of the adsorbed phenol-water mixtures is unknown. In hydrophobic mesopores (pore size > 2.0 nm), the adsorption of phenol is limited to spaces that are close to pore walls (e.g. contact and second adsorbed layers), whereas the remaining part of the mesopore is filled by water molecules [23]. The term “hydrophobic” is not precisely defined because all nanoporous carbon materials are oxidized to some extent upon their expose to air [24, 25]. Therefore, one can expect that the adsorption of phenol from aqueous solutions is either comparable or lower than the adsorption of pure phenol from the saturated vapor pressure at the same operating temperature. We have recently reported the super-sieving effect in phenol adsorption from aqueous solutions on nanoporous carbon beads synthesized from pure polymeric precursors [18]. In the current work, we investigate the microscopic mechanism of the super-sieving effect by combining the experimental results with graphic processing unit (GPU)-accelerated molecular dynamics simulations (GPU-MD) of phenol adsorption from aqueous solutions at neutral pH.


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Studied activated carbon samples and the experimental methods are described in section 2. To the best of our knowledge, the GPU-MD simulations of adsorption from aqueous solutions are reported for the first time. The details and description of the computed properties are given in section 3. Experimental and theoretical results are critically compared and discussed in section 4. Final conclusions are given in section 5. The study demonstrates the importance of the synergy between the experiment and atomistic level simulations in design and smart fabrication of novel nanoporous carbon adsorbents for purification and production of ultrapure water.

Materials and Methods

Materials

A sample of nanoporous carbon beads, NCB-8h, was prepared at Murdoch University by carbonization of acidic, gel-type cation exchange resin based on a styrene-divinylbenzene copolymer (Lanxess Lewatit, Germany) and subsequent activation with CO2. In the carbonization step, ∼2 g of precursor was placed in a ceramic crucible and carbonized at 650 °C for 1.5 h in a high-purity N2 steam (1.0 dm3/min, BOC, Australia) in a horizontal split-tube furnace. Then, the carbonized beads were activated with CO2 at 900 °C for 8 h in a high-purity CO2 steam (1.0 dm3/min, BOC, Australia) in a horizontal split-tube furnace. Norit granular activated carbon from Cabot Corporation (USA) was used as an industry benchmark.

Raman, XRD and SEM Measurements

Raman spectra of NCB-8h sample were recorded using the WITec alpha 300RA + confocal Raman imaging system at the Centre for Microscopy, Characterization and Analysis (CMCA), 6 ACS Paragon Plus Environment

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The University of Western Australia (UWA). We used the laser excitation wavelength of 532 nm. The Raman spectra were collected from 4 to 6 points chosen randomly on the surface of NCB-8h sample. The non-polarized Raman scattering spectra of Norit were investigated in the spectral range of 60-4500 cm-1 at Nicolaus Copernicus University (NCU). Raman spectra were recorded in the backscattering geometry using SENTERRA micro-Raman system using green laser operating at 532 nm. The laser beam was tightly focused on the sample surface through a 50x microscope objective. The position of the microscope objective with respect to the sample was piezoelectrically controlled (XY position). To prevent any damage of the sample, an excitation power was fixed at 2 mW. The resolution was 4 cm−1, CCD temperature 223 K, laser spot 2 μm in diameter, and total integration time 100 s (50 × 2 s) were used. X-ray powder scattering patterns (XRD) of NCB-8h sample was recorded using the Empyrean multi-purpose research diffractometer using Cu Kα radiation (λ = 0.15406 nm) at CMCA, UWA. Bulk powder of Norit sample was characterized by the XRD using Philips XPERT Pro diffractometer with CuKα1 radiation at NCU. Scanning electron microscope images (SEM) of NCB-8h sample were recorded using the Verios XHR SEM system at the CMCA, UWA. SEM studies of Norit were performed with Quanta 3D FEG (EHT = 30 kV) instrument at NCU. Samples were placed onto carbon tabs attached to aluminum SEM stubs. NCB-8h and Norit samples were analyzed in the microscope without coating treatment.

N2 Adsorption Measurements

The N2 adsorption-desorption isotherms on Norit and NCB-8h samples were measured at 77 K using the ASAP 2010 MicroPore System (Micromeritics, USA) at NCU. Before each measurement, carbon samples were desorbed in vacuum at 383 K for 3 h. Adsorption and structural parameters of Norit and NCB-8h samples were computed using the Brunauer7 ACS Paragon Plus Environment

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Emmett-Teller (BET) theory of multilayer adsorption [26], and general integral equation of adsorption implemented with local N2 adsorption isotherms computed from the classical nonlocal density functional theory (NLDFT) [27-29] (Fig. S2 in the Supporting Information).

Phenol Adsorption and Calorimetry Measurements

Phenol adsorption isotherms from water solutions (298 K, neutral pH) on NCB-8h and Norit samples was measured using UV-Vis spectrophotometer JASCO V-660 [30]. For each adsorption point, we collected the equilibrium concentration after 24 h and 48 h of equilibration at 270 nm. The enthalpy of immersion in water and in phenol solutions was measured at 298 K using a Tian-Calvet isothermal microcalorimeter [18]. The measurements for each carbon sample were repeated three times. The error was not larger than 0.5 mJ/m2. To gain insight into the mechanism of phenol adsorption from dilute aqueous solutions, we computed the adsorption energy distribution (AED) function using the method recommended in [31, 32],

𝑥𝑒𝑥𝑝(𝜀12/𝑅𝑇)

𝜀

𝜃𝑡(𝑐1) = ∫𝜀12,𝑚𝑎𝑥1 + 𝑥𝑒𝑥𝑝(𝜀12/𝑅𝑇)𝐹(𝜀12)𝑑𝜀12 12,𝑚𝑖𝑛

(1)

where 𝜃𝑡(𝑐) denotes the total fractional coverage of a solute, 𝐹(𝜀12) is the normalized distribution function, which characterizes the material heterogeneity in terms of the adsorption energy difference, 𝜀12 = 𝜀1 ― 𝜀2, between the solute (phenol, 𝜀1) and the solvent (water, 𝜀2), 𝑠𝑜𝑙 𝑥 = 𝑐1/𝑐𝑠𝑜𝑙 1 , where 𝑐1 and 𝑐1 is the equilibrium concentration and the solubility of phenol in

water, respectively, 𝑅 is the universal gas constant, and 𝑇 denotes temperature. The home-made


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implementation of the second order Tikhonov regularization method with the non-negative least-square algorithm was used for inversion of eq.1 [33]. Theoretical phenol-saturated capacity of studied carbon materials was computed using the pore side distribution 𝑓(𝐻) obtained from the NLDFT method from N2 (77 K) adsorption and the theoretical phenol capacities, 𝑁𝑡ℎ𝑒𝑜𝑟(𝐻) , simulated from constant pressure Gibbs ensemble Monte Carlo (MC) simulations [18],

𝑁𝑒𝑥𝑝𝑡.(𝑝/𝑝0) = ∫𝑁𝑁𝐿𝐷𝐹𝑇

( ,𝐻)𝑓(𝐻)𝑑𝐻 𝑝

𝑝0

(2)

(3)

𝑁𝑠𝑎𝑡. = ∫𝑁𝑡ℎ𝑒𝑜𝑟.(𝐻)𝑓(𝐻)𝑑𝐻

In the first step, we evaluated the pore size distribution function, 𝑓(𝐻), from eq. 2 using the second order Tikhonov regularization method with the non-negative least-square algorithm [33]. In the second step, phenol-saturated capacity was computed using eq. 3 and the pore size dependence of the MC simulated phenol-saturation capacity, 𝑁𝑡ℎ𝑒𝑜𝑟.(𝐻) [18]. Note that the theoretical phenol-saturated capacity computed from eqs. 2-3 corresponds to filling of carbon micropores with pure phenol.

Simulation Methodology

We used a model of Madagascar graphite (6 layers, each wall has the dimensions x = z = 4.396 nm, y = 2.0, 4.0 nm) reconstructed from experimental wide-angle X-ray scattering measurement and the hybrid reverse Monte Carlo simulation method [34]. The simulation box was constructed as follows. Two Madagascar graphite crystals were placed in a box to form the opposite pore walls. The walls were movable to control the effective pore widths (Heff, as 9 ACS Paragon Plus Environment

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shown in Fig. 1). Next, two virtual repulsive walls were placed at the top and the bottom of each slit-shaped pore (see violet planes in Fig. 1) excepting the entrance to a pore. The boxes (x = z = 4.396 nm, y = 9.030 nm) containing equilibrated water-phenol mixtures were placed above and below the pore box. Each box contained 120 phenol and 5103 water molecules, respectively (the concentration equal to 10.90 % mass). Those boxes were prepared by the equilibration of the phenol - water mixtures using the SPC/E water molecules [35] and Variable Langevin integrator/thermostat, together with the stochastic Andersen barostat (1 bar). The OPLSAA parameters for phenol were taken from the TINKER package [36]. For the water - carbon interaction the parameters proposed by Werder et al. were applied [37]. Simulations of phenol adsorption (T = 323 K, N,V,T ensemble) were performed for each carbon pore for a single point constant phenol equilibrium concentration equal to 10.90 % mass. The OpenMM 7.01, a high-performance toolkit for molecular simulations was applied (GPU-MD) [38]. The equilibration time was equal to 10.5 ns. The simulation is performed in steps by consecutive equilibration of the outside mixture containers with the pore. At each step, during simulation phenol molecules fill the nanopore and the phenol pressure (or concentration) in outside containers reduces down to the equilibrium concentration corresponding to the accumulated amount of phenol in the pore. On the next steps, phenol solution containers were replaced by the new ones containing the same prepared 10.9% mixture, and the equilibration is repeated. The boxes are replaced until the number of molecules in the nanopore was constant, and adsorption was calculated, assuming that the molecule is inside a nanopore if its center of mass is inside (Fig. S3 in the Supporting Information). The Variable Langevin integrator with time step equal to 2 fs was used in all the above simulations. Simulations were performed for the pores widths Heff (nm) = 0.8, 1.05, 1.3, 1.55, 1.8, 2.05, 2.3, 2.8, 3.3 and 3.8.


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To characterize the structural ordering of confined phenol and water molecules, we computed the angular order parameter, 𝑆(𝛼), from the following expression [39, 40],

𝑆(𝛼) = 〈𝑃2(𝑐𝑜𝑠𝛼)〉 =

〈

3𝑐𝑜𝑠2𝛼 ― 1 2

〉

(4)

where  denotes the angle between the graphitic pore wall normal and the plane vector of the adsorbed molecule (Fig. S4 in the Supporting Information). The bracket means that the order parameters were averaged over all configurations recorded during the GPU-MD simulations. If all the adsorbed molecules are perpendicular to the graphitic pore walls, 𝑆 = 1.0. In contrast, 𝑆 = ―0.5 indicates that all adsorbed molecules are parallel to the graphitic pore walls. The isotropic distributions of adsorbed molecules orientation in carbon micropores correspond to 𝑆 = 0. Additionally, we computed the local phenol and water density profiles [41].


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Figure 1. Slit-shaped carbon nanopore model with the Madagascar graphite walls (left panel), and the simulation box before GPU-MD equilibration (right panel, two boxes with equilibrated phenol solutions, virtual repulsive walls and a slit-shaped carbon nanopore). Note that the graphics collected in this figure, and Fig. 5 are created using the VMD program [42].

Results and Discussions

Figure 2a, 2b and Figure S1 in the Supporting Information displays scanning electron microscopy (SEM) images of the surface of Norit and NCB-8h sample. The surface morphology of the Norit activated carbon is quite different compared to the NCB-8h carbon sample produced from a synthetic precursor. The surface of the Norit is very rough with the heterogeneous structure of macro- and mesopore entrances that are directly connected to the exterior (Fig. 2a and Fig. S1 in the Supporting Information). Micropores are therefore predominantly connected to irregular mesopores, as in the classical tree-pore model of


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disordered porous carbons [43]. In contrast, the micropore entrances at the surface of the NCB8h spherical beads are directly connected to the exterior, which is typical for activated carbon fibres produced from polymeric precursors (so-called cylindrical pore model [33]). The Raman spectral examination of both carbon materials display two overlapping broad bands locating at 1350 and 1590 cm-1 (Fig. 2c). Such feature is associated with the disordering of the samples (D band) and stretching vibration in the aromatic planes (G band), respectively, and confirm that both carbon samples consists of nanometre-scale graphitic crystallites embedded in the disordered carbon matrix. For Norit and NCB-8h samples, the in-plane size of graphitic crystallites, 2.1-2.2 nm, computed from the Ferrari-Robertson equation are comparable (Table 1) [44]. It is not surprising because the carbonization and activation of carbon precursors at 800-900 0C should generate similar sizes of graphite nanocrystallites. To induce a further growth of graphitic crystallites, significantly higher temperatures are necessary [45]. X-ray diffraction (XRD) patterns shown on Fig. 2d are dominated by intensities of (002) and (100) peaks. For both Norit and NCB-8h samples, the (002) diffraction peaks are broadened and shifted to lower angles as compared to (002) diffraction peak of graphite, indicating larger interlayer spacing between graphitic planes of nano-crystallites than those of graphite [46]. Indeed, an average interlayer spacing (d002) computed for Norit and NCB-8h is 0.361 and 0.399 nm, respectively, and it is greater than graphite spacing of 0.335 nm (Table 1). These structural characteristics are typical for turbostratic carbonaceous materials [47]. This observation justifies to some extend the use of the simplistic carbon slit-shaped pore model employed for the pore size distribution analysis and in computer simulations (Fig. 1) [48-50].


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Sample

La

d002

(nm)

(nm)

SBET (m2/g)

NCB-8h

2.2

0.399

Norit

2.1

0.361

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aBET (mmol/g)

Stot (m2/g)

Smeso (m2/g)

Smicro (m2/g)

902

9.2

1186

-

1186

830

8.5

894

88

806

Table 1. Crystallographic (interlayer spacing d002), crystallite (in-plane sizes of graphitic crystallites La) and nanopore parameters estimated from the Raman, XRD scattering, and N2 adsorption (77 K) measurements. The total (Stot), mesopore (Smeso) and micropore (Smicro) specific surface areas were estimated from N2 adsorption isotherms and NLDFT method (Fig. S2 in the Supporting Information). For comparison, the specific surface areas (SBET) and monolayer capacities (aBET) of carbon samples were evaluated from N2 adsorption isotherms and the Brunauer-Emmett-Teller (BET) method.


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Figure 2. SEM image of the (a) Norit activated carbon and (b) NCB-8h sample activated using CO2 at 900 0C for 8h. (c) Raman spectra and (d) XRD diffraction patterns recorded for NCB8h and Norit carbon samples.

Figure 3a presents, measured volumetrically, experimental N2 adsorption-desorption isotherms at 77 K on Norit and NCB-8h. The isotherm measured for NCB-8h is typical for microporous materials (type I isotherm following to IUPAC) [51], however for Norit a mixture type between I and IV is observed. The Norit sample is structurally heterogonous activated carbon with NLDFT specific surface area of 894 m2/g, and the total pore volume at p/p0 = 0.98 is 0.56 cm3/g (Table 1 and Fig. 1a). The pore size distribution of Norit has a broad range of micropores ranges from ultra- to supermicropores (Fig. 3b and Fig. S2 in the Supporting Information). Moreover, an increase in N2 adsorption in the classical BET range (0.05-0.25 15 ACS Paragon Plus Environment

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p/p0) and the sorption hysteresis loop indicates the presence of narrow mesopores (Fig. 3a). The specific surface area of mesopores 88 m2/g is calculated from N2 adsorption isotherm and NLDFT method (Table 1 and Fig. S2 in the Supporting Information). NBC-8h exhibited a predominant microporosity with a NLDFT specific surface area of 1186 m2/g, and the total pore volume at p/p0 = 0.98 is 0.45 cm3/g (Table 1 and Fig. 1a). The NLDFT pore size distribution function for NCB-8h is qualitatively similar to that computed for Norit. However, for NCB-8h carbon ultramicropores of uniform pore size 2.25 nm the surface density of adsorbed phenol reaches an asymptotic 20 ACS Paragon Plus Environment

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value. This indicates that the mechanism of the phenol adsorption in mesopores and on the flat graphite surface is the same. While this is not surprising per se, it is remarkable that the monolayer confinement stabilizes the two-dimensional phenol crystals with a peculiar pattern of hydrophilic-hydrophobic stripes (Fig. 5a). Static self-assembly between adsorbed phenol molecules does explain the formation of hydrophobic-hydrophilic stripes. To the best of our knowledge this is the first observation of the self-assembled phenol crystals stabilized by the monolayer confinement. From the variation of the local density profile and order parameter in 0.8 nm supermicropore, we concluded that phenol molecules are compressed in the middle of the micropore and their preferential orientations are parallel to the pore walls (Fig. 6). Furthermore, we found that phenol crystal defects are filled with water single molecules only (Fig. 7a). The water molecules are adsorbed closer to the pore walls compared to phenol and their preferential orientations are parallel to the pore walls (Fig. 6 and 7a). A peculiar configuration of water molecules in the adsorbed layer can be explained by constraints that are imposed by the two-dimensional phenol crystal (Fig. 7a). Two contact layers of phenol are found in a wider 1.0 nm micropore (Fig. 6). There is, however, a fraction of phenol molecules that are adsorbed close to the pore centre. Interestingly, small water clusters (e.g. monomers, dimers, trimers, and small chain-like water clusters) are preferentially co-adsorbing at phenol contact layers including spaces close to the pore walls and the pore centre. That is why the water local density profile is somehow broader as compared to the phenol density profile (Fig. 6). Snapshots of the GPU-MD simulations reveal that small water clusters are isolated (Fig. 7b). They do not exclude the pore volume for phenol but they fill the defects between adsorbed phenol molecules (Fig. 6). Inside 1.8 nm micropore, the water clusters with different sizes and morphologies are found around the pore centre (Figs. 5-6). Two layers of phenol are adsorbed on pore walls, as shown on the local density profile (Fig. 6). As expected, water molecules have random orientations with an exception of water co-adsorbing in phenol layers. The water


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clusters are growing in 1.8 nm supermicropores, however, they do not form a percolating network. In 2.0 nm supermicropore the liquid-like isotropic water is filling the spaces close to the pore centre, whereas phenol molecules are adsorbed close to the pore walls with preferential flat orientations (Figs. 5, 6, 7b). Moreover, we observe the formation of the percolated cluster of water molecules spanning the whole space of the pore (Fig. 5, 7b). In narrow mesopores (pore size 2.25 nm), the surface density of adsorbed phenol reaches an asymptotic value corresponding to the adsorption of phenol from water solutions on two independent graphitic surfaces (Fig. 5). Taking into account the GPU-MD simulation results, we concluded that the maximum enhancement of the surface density of phenol in 1.8 nm supermicropore is 23% greater as compared to an open graphite surface (Fig. 5). The highest selectivity of phenol over water is theoretically predicted in narrow supermicropores, which is an important factor for design and pore engineering of novel carbon adsorbents for production of ultrapure water.


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Figure 5. The surface density of phenol adsorbed from aqueous solutions at 323 K and neutral pH computed from GPU-MD simulations. Middle panels show the equilibrium snapshots of phenol-water mixtures adsorbed in 0.8 (a), 1.0 (b), 1.8 (c), and 2.0 nm (d) graphitic micropores at the given conditions (water molecules are brighter). The structure of water monomers, clusters, cavities, and percolating cluster is highlighted in the bottom panels.


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Figure 6. The variation of the local density (left panels) and order parameter (right panels) of phenol and water adsorbed in 0.8, 1.0, 1.8, and 2.0 nm graphitic micropores at 323 K and neutral pH computed from GPU-MD simulations.


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Figure 7. Snapshots of the equilibrium phenol-water mixtures adsorbed in 0.8 (a) and 2.0 (b) nm supermicropores obtained from GPU-MD simulations. Monomer (a) and percolating water cluster spanning the entire pore space (b) is highlighted by rectangular boxes.

Conclusions

In this work, we investigated the mechanism of phenol adsorption from aqueous solutions (293 K, neutral pH) on two representative samples of activated carbons, namely, nanoporous carbon beads NCB-8h and granular activated carbon Norit from Cabot. For both carbon samples, we found the low value of the enthalpy of immersion in pure water 44-45 mJ/m2, which indicate a strongly hydrophobic character of carbon micropores. The supersieving effect in phenol adsorption from aqueous solutions at neutral pH in Norit and NCB-8h carbon samples is confirmed based on the combined theoretical and experimental results. However, from the recent development of the theory of super-sieving effect in phenol 25 ACS Paragon Plus Environment

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adsorption from aqueous solutions, we found that the distribution of the phenol adsorption capacity in Norit and NCB-8h is very different. For Norit, only 100 mg/g of phenol is adsorbed in ultramicropores (pore size < 0.6 nm), whereas 200 mg/g of phenol is adsorbed in ultramicropores of NCB-8h. Both theoretical and experimental saturation phenol capacity of NCB-8h is 50 mg/g higher than Norit. To gain insights into microscopic mechanism of super-sieving effect in phenol adsorption from aqueous solutions, we implemented and simulated the phenol adsorption from neutral water solutions in model slit-shaped graphitic carbon nanopores using molecular dynamics on a graphics processing units. GPU-MD simulations revealed that adsorption and structural ordering of phenol-water mixtures in hydrophobic carbon micropores depend strongly on the pore size. In 0.8 nm supermicropore, a static self-assembly of phenol molecules into two-dimensional crystal with a peculiar pattern of hydrophilic-hydrophobic stripes is stabilized by the monolayer confinement at ambient temperatures. Irregular water clusters (e.g. monomers, dimers and trimers) and short linear water chains are found in 1.8 nm supermicropore. However, the simulated snapshots showed that the co-adsorbing water is below the percolation threshold. Additionally, in 0.8 nm supermicropore, we predicted the highest surface density of phenol that is 23% grater as compared to that on a graphite surface. Further growing of water clusters result in the formation of the percolating water cluster spanning the entire pore space of 2.0 nm supermicropore. In narrow mesopores (pore size 2.25 nm) the surface density of adsorbed phenol reaches an asymptotic value that corresponds to adsorption on two independent graphite surfaces. The super-sieving effect in phenol adsorption from aqueous solutions in hydrophobic carbon micropores is explained by analyzing the structure of co-adsorbed water. We found that small clusters (e.g. monomers, dimers and trimers) and short-linear water chains do not exclude pore volume for phenol adsorption significantly. Interestingly, the percolating water cluster is


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found in 2.0 nm supermicropore. In mesopores, the liquid-like water excludes the significant part of the pore volume for adsorption of phenol. Our findings show that GPU-MD simulations combined with the pore size distribution analysis can be used for theory informed synthesis of advanced materials for water purification and

clean-up

from

non-electrolyte

micropollution.

Narrow

supermicropores

and

ultramicropores are desirable for production of ultrapure water due to the highest selectivity of phenol over the water (e.g. formation of two-dimensional phenol crystals). The highest uptake of phenol per surface area of pore walls is found in 1.8 nm supermicropores. The optimization of adsorption properties can be achieved by tuning the hydrophobicity and pore size in the ultramicropore range as confirmed by the superior phenol-adsorption performance for NCB8h samples.

Supporting Information

High magnification SEM image of the surface of the Norit activated carbon, fitting of the experimental N2 adsorption isotherms (77 K) by NLDFT method, NLDFT cumulative pore size distributions, variation of the phenol adsorption with GPU-MD run, schematic diagram showing a definition of the angle between the graphitic pore wall normal and the plane vector of the adsorbed phenol, the variation of the local density profiles and order parameter computed from GPU-MD simulations.

Acknowledgment

P. K. acknowledges the financial support from the Murdoch University start-up grant: Nanopore controlled synthetic carbons for interfacial separations and catalysis (11701). The 27 ACS Paragon Plus Environment

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work was partially supported by Grant-in-Aid for Scientific Research (B) (17H03039) and the JST OPERA project.

References

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