Atomistic simulation of nanoporous layered double hydroxide materials and their properties. II. Adsorption and diffusion

Nanoporous layered double hydroxide (LDH) materials have wide applications, ranging from being good adsorbents for gases (particularly CO(2)) and liquid ions to membranes and catalysts. They also have applications in medicine, environmental remediation, and electrochemistry. Their general chemical composition is [M(1-x)(II)M(x)(III)(OH(-))(2)](x+)[X(nm)(m-)nH(2)O], where M represents a metallic cation (of valence II or III), and X(nm)(m-) is an m-valence inorganic, or heteropolyacid, or organic anion. We study diffusion and adsorption of CO(2) in a particular LDH with M(II)=Mg, M(III)=Al, and x approximately = 0.71, using an atomistic model developed based on energy minimization and molecular dynamics simulations, together with a modified form of the consistent-valence force field. The adsorption isotherms and self-diffusivity of CO(2) in the material are computed over a range of temperature, using molecular simulations. The computed diffusivities are within one order of magnitude of the measured ones at lower temperatures, while agreeing well with the data at high temperatures. The measured and computed adsorption isotherms agree at low loadings, but differ by about 25% at high loadings. Possible reasons for the differences between the computed properties and the experimental data are discussed, and a model for improving the accuracy of the computed properties is suggested. Also studied are the material's hydration and swelling properties. As water molecules are added to the pore space, the LDH material swells to some extent, with the hydration energy exhibiting interesting variations with the number of the water molecules added. The implications of the results are discussed.     

Testing predictions of macroscopic binary diffusion coefficients using lattice models with site heterogeneity

Quantitatively predicting mass transport rates for chemical mixtures in porous materials is important in applications of materials such as adsorbents, membranes, and catalysts. Because directly assessing mixture transport experimentally is challenging, theoretical models that can predict mixture diffusion coefficients using only single-component information would have many uses. One such model was proposed by Skoulidas, Sholl, and Krishna (Langmuir, 2003, 19, 7977), and applications of this model to a variety of chemical mixtures in nanoporous materials have yielded promising results. In this paper, the accuracy of this model for predicting mixture diffusion coefficients in materials that exhibit a heterogeneous distribution of local binding energies is examined. To examine this issue, single-component and binary mixture diffusion coefficients are computed using kinetic Monte Carlo for a two-dimensional lattice model over a wide range of lattice occupancies and compositions. The approach suggested by Skoulidas, Sholl, and Krishna is found to be accurate in situations where the spatial distribution of binding site energies is relatively homogeneous, but is considerably less accurate for strongly heterogeneous energy distributions.     

Ab initio parametrized MM3 force field for the metal-organic framework MOF-5

A new valence force field has been developed and validated for a particular class of coordination polymers known as nanoporous metal-organic frameworks (MOFs), introduced recently by the group of Yaghi. The experimental, structural, and spectroscopic data in combination with density functional theory calculations on several model systems were used to parametrize the bonded terms of the force field, which explicitly treats the metal-oxygen interactions as partially covalent as well as distinguishes different types of oxygens in the framework. Both the experimental crystal structure of MOF-5 and vibrational infrared spectrum are reproduced reasonably well. The proposed force field is believed to be useful in atomistic simulations of adsorption/diffusion of guest molecules inside the flexible pores of this important class of MOF materials.     

Nanoporous crystal 12CaO.7Al2O3: a playground for studies of ultraviolet optical absorption of negative ions

A novel nanoporous material 12CaO.7Al2O3 (C12A7) offers a possibility of incorporating large concentrations (>1021 cm-3) of a wide range of extraframework anions inside its nanopores. We have investigated, both experimentally and theoretically, optical absorption associated with several types of such anions, including F-, OH-, O-, O2-, O2-, and O22-, and assigned their optical absorption bands. It is demonstrated that the chemical identity and concentration of extraframework anions can be controlled by an appropriate treatment of "as grown" C12A7. We also show that the position of the adsorption edge is, in turn, determined by the chemical identity of the extraframework species and can be varied in the range of approximately 4-6 eV. We suggest that C12A7 is a unique host material, which can be used as a playground for studying negatively charged species that are unstable in other environments.     

Nanoporous Carbon Materials for Electrochemical Sensing

Nanoporous carbon materials are highly important materials for a wide array of applications. Here we show that nanoporous carbon can act as highly active materials for electrochemical sensing. We observed that nanoporous carbon material exhibits a faster heterogeneous electron transfer than graphite and pure carbon nanotubes. Nanoporous carbon exhibits a superior electrochemical performance for sensing of important biomarkers such as dopamine, ascorbic acid, uric acid, NADH, DNA bases, and forensic‐related compounds such as nitroaromatic explosives.     

Improving Internal Peptide Dynamics in the Coarse-Grained MARTINI Model: Toward Large-Scale Simulations of Amyloid- and Elastin-like Peptides

We present an extension of the coarse-grained MARTINI model for proteins and apply this extension to amyloid- and elastin-like peptides. Atomistic simulations of tetrapeptides, octapeptides, and longer peptides in solution are used as a reference to parametrize a set of pseudodihedral potentials that describe the internal flexibility of MARTINI peptides. We assess the performance of the resulting model in reproducing various structural properties computed from atomistic trajectories of peptides in water. The addition of new dihedral angle potentials improves agreement with the contact maps computed from atomistic simulations significantly. We also address the question of which parameters derived from atomistic trajectories are transferable between different lengths of peptides. The modified coarse-grained model shows reasonable transferability of parameters for the amyloid- and elastin-like peptides. In addition, the improved coarse-grained model is also applied to investigate the self-assembly of β-sheet forming peptides on the microsecond time scale. The octapeptides SNNFGAIL and (GV)(4) are used to examine peptide aggregation in different environments, in water, and at the water-octane interface. At the interface, peptide adsorption occurs rapidly, and peptides spontaneously aggregate in favor of stretched conformers resembling β-strands.     

Guest-specific diffusion anisotropy in nanoporous materials: Molecular dynamics and dynamic Monte Carlo simulations

For anisotropic nanoporous materials, guest diffusion is often reflected by a diffusion tensor rather than a scalar diffusion coefficient. Moreover, the resulting diffusion anisotropy may notably differ for different guest molecules. As a particular class of such systems, we consider an array of two types of channels, mutually intersecting each other, where the rates of diffusion in the different directions depend on the nature of the guest molecules. The simultaneous adsorption of two types of guest molecules is considered, as in technical applications of porous materials such as catalysis. A case study is presented in which atomistic molecular dynamics (MD) and coarse-grained dynamic Monte Carlo (DMC) simulations are compared and shown to yield qualitatively similar results for non-steady-state diffusion. The two techniques are complementary. MD simulations are able to predict the details of molecular propagation over distances of a few unit cells, whereas the evolution of sorption profiles over distances comparable with entire crystallites can be studied with DMC simulations. Consideration of these longer length and time scales is necessary for applications of such systems in chemical separations and heterogeneous catalysis.     

Towards an atomistic model for ORMOCER?-I: application of forcefield methods

ORMOCER^?s are an outstanding class of hybrid materials due to their tuneable properties, e.g. hardness, resistivity and refractive index. These materials are well-characterized with regard to their macroscopic properties, but understanding the system at the atomistic level still remains challenging. Understanding the material formation process at this level becomes especially important when three-dimensional nanoscale patterns are generated employing processes as laser-based multi-photon polymerization. We have developed an atomistic model based on the COMPASS forcefield to simulate the reference system ORMOCER^?-I. We chose representative compositions for the condensation reaction product as well as for the organically cross-linked polymerized product. In the first part of the study, the results of forcefield validation experiments and the development of the atomistic model for ORMOCER^?s are presented. The second part contains the results from molecular dynamics simulations at room temperature and under periodic boundary conditions, performed in order to test the feasibility of our model. The densities of the simulated materials are in very good agreement with experimentally determined densities for the unpolymerized as well as for the polymerized state, respectively.     

Prediction of partition coefficients by multiscale hybrid atomic-level/coarse-grain simulations

Coarse-grain models are becoming an increasingly important tool in computer simulations of a wide variety of molecular processes. In many instances it is, however, desirable to describe key portions of a molecular system at the atomic level. There is therefore a strong interest in the development of simulation methodologies that allow representations of matter with mixed granularities in a multiscale fashion. We report here a strategy to conduct mixed atomic-level and coarse-grain simulations of molecular systems with a recently developed coarse-grain model. The methodology is validated by computing partition coefficients of small molecules described in atomic detail and solvated by water or octane, both of which are represented by coarse-grain models. Because the present coarse-grain force field retains electrostatic interactions, the simplified solvent particles can interact realistically with the all-atom solutes. The partition coefficients computed by this approach rival the accuracy of fully atomistic simulations and are obtained at a fraction of their computational cost. The present methodology is simple, robust and applicable to a wide variety of molecular systems.     

The multiscale coarse-graining method. X. Improved algorithms for constructing coarse-grained potentials for molecular systems

The multiscale coarse-graining (MS-CG) method uses simulation data for an atomistic model of a system to construct a coarse-grained (CG) potential for a coarse-grained model of the system. The CG potential is a variational approximation for the true potential of mean force of the degrees of freedom retained in the CG model. The variational calculation uses information about the atomistic positions and forces in the simulation data. In principle, the resulting MS-CG potential will be an accurate representation of the true CG potential if the basis set for the variational calculation is complete enough and the canonical distribution of atomistic states is well sampled by the data set. In practice, atomistic configurations that have very high potential energy are not sampled. As a result there usually is a region of CG configuration space that is not sampled and about which the data set contains no information regarding the gradient of the true potential. The MS-CG potential obtained from a variational calculation will not necessarily be accurate in this unsampled region. A priori considerations make it clear that the true CG potential of mean force must be very large and positive in that region. To obtain an MS-CG potential whose behavior in the sampled region is determined by the atomistic data set, and whose behavior in the unsampled region is large and positive, it is necessary to intervene in the variational calculation in some way. In this paper, we discuss and compare two such methods of intervention, which have been used in previous MS-CG calculations for dealing with nonbonded interactions. For the test systems studied, the two methods give similar results and yield MS-CG potentials that are limited in accuracy only by the incompleteness of the basis set and the statistical error of associated with the set of atomistic configurations used. The use of such methods is important for obtaining accurate CG potentials.     

Optimal allocation of replicas in parallel tempering simulations

We have studied the efficiency of parallel tempering simulations for a variety of systems including a coarse-grained protein, an atomistic model polypeptide, and the Lennard-Jones fluid. A scheme is proposed for the optimal allocation of temperatures in these simulations. The method is compared to the existing empirical approaches used for this purpose. Accuracy associated with the computed thermodynamic quantities such as specific heat is also computed and their dependence on the trial-exchange acceptance rate is reported.     

Advances in Porous Organic Polymers for Efficient Water Capture

Desiccant driven dehumidification for maintaining the proper humidity levels and atmospheric water capture with minimum energy penalty are important aspects in heat pumps, refrigeration, gas and liquid purifications, gas sensing, and clean water production for improved human health and comfort. Water adsorption by using nanoporous materials has emerged as a viable alternative to energy-intensive industrial processes, thus understanding the significance of their porosity, high surface areas, vast pore volumes, chemical and structural features relative to the water adsorption is quite important. In this review article, important features of nanoporous materials are presented, including zeolites, porous carbons, as well as crystalline and amorphous porous organic polymers (POPs) to define the interactions between the water molecules and the polar/non-polar functional groups on the surface of these nanoporous materials. In particular, focus is placed on the recent developments in POPs in the context of water capture as a result of their remarkable stability towards water and wide range of available synthetic routes and building blocks for their synthesis. We also highlighted recent approaches to increase the water sorption capacity of POPs by modifying their structure, morphology, porosity, and chemical functionality while emphasizing their promising future in this emerging area.     

Structure and electrons in mayenite electrides

One major goal in materials chemistry is to find inexpensive compounds with improved capabilities. Stable inorganic electrides, derived from nanoporous mayenite [Ca12Al14O32]O, are a new family that has very interesting properties such as electronic conductivity combined with transparency. However, an intriguing fundamental problem is to understand the structures of these cubic materials and to characterize their free-electron loadings. Here we report an accurate structural study for three members of the series [Ca12Al14O32]O(1-delta)e(2delta) (delta = 0, 0.15, and 0.45), from single-crystal low-temperature synchrotron X-ray diffraction. The complex structural disorder imposed by the presence of the oxide anions into the mayenite cages has been unravelled. Furthermore, the final electron density map for delta = 0.45 black mayenite has shown electron density localized into the center of the cages, which is the first experimental proof of their electride nature. The reported structural findings challenge theorists to improve predictive models in this new family of materials.     

Functional organic materials based on polymerized liquid-crystal monomers: supramolecular hydrogen-bonded systems

Functional organic materials are of great interest for a variety of applications. To obtain precise functional properties, well-defined hierarchically ordered supramolecular materials are crucial. The self-assembly of liquid crystals has proven to be an extremely useful tool in the development of well-defined nanostructured materials. We have chosen the illustrative example of photopolymerizable hydrogen-bonding mesogens to show that a wide variety of functional materials can be made from a relatively simple set of building blocks. Upon mixing these compounds with other reactive mesogens, nematic, chiral nematic, and smectic or columnar liquid-crystalline phases can be formed that can be applied as actuators, sensors and responsive reflectors, and nanoporous membranes, respectively.     

Argon and krypton adsorption on templated mesoporous silicas: molecular simulation and experiment

In this work we report molecular simulation results for argon and krypton adsorption on atomistic models of templated mesoporous silica materials. These models add atomistic levels of detail to mesoscale representations of these porous materials, which were originally generated from lattice Monte Carlo simulations mimicking the synthesis process of templated mesoporous silicas. We generate our atomistic pore models by carving out of a silica block a ‘mathematically-smooth’ representation of the pores from lattice MC simulations. Following that procedure, we obtain a model material with mean mesopore and micropore diameters of 5.4 nm and 1.1 nm, respectively (model A). Two additional model materials were considered: one with no microporosity, and with mesopores similar to those of model A (model B), and a regular cylindrical pore (model C). Simulation results for Ar and Kr adsorption on these model materials at 77 K and 87 K shows that model A provides the best agreement with experimental data; however, our results suggest that fine-tuning the microporosity and/or the surface chemistry (i.e., by decreasing the density of OH groups at the pore surface) of model A can lead to better agreement with experiments. The filling of the mesopores in model materials A and B proceeded via a classical capillary condensation mechanism, where the pores fill at slightly different pressures. This observation contrasts with what was observed in our previous study (Coasne, et al. in Langmuir 22:194–202, 2006), where we considered atomistic silica mesopores with an important degree of surface roughness at length scales below 10 Å, for which we observed a quasi-continuous mesopore filling involving intermediate phases with liquid-like “bridges” and gas-like regions. These results suggest that pore surface roughness, and other morphological features such as constrictions, play an important role in the mechanism of adsorption and filling of the mesopores.     

Hydrogen storage in nanoporous carbon materials: myth and facts

We used Grand canonical Monte Carlo simulation to model the hydrogen storage in the primitive, gyroid, diamond, and quasi-periodic icosahedral nanoporous carbon materials and in carbon nanotubes. We found that none of the investigated nanoporous carbon materials satisfy the US Department of Energy goal of volumetric density and mass storage for automotive application (6 wt% and 45 kg H(2) m(-3)) at considered storage condition. Our calculations indicate that quasi-periodic icosahedral nanoporous carbon material can reach the 6 wt% at 3.8 MPa and 77 K, but the volumetric density does not exceed 24 kg H(2) m(-3). The bundle of single-walled carbon nanotubes can store only up to 4.5 wt%, but with high volumetric density of 42 kg H(2) m(-3). All investigated nanoporous carbon materials are not effective against compression above 20 MPa at 77 K because the adsorbed density approaches the density of the bulk fluid. It follows from this work that geometry of carbon surfaces can enhance the storage capacity only to a limited extent. Only a combination of the most effective structure with appropriate additives (metals) can provide an efficient storage medium for hydrogen in the quest for a source of "clean" energy.     

Molecular modeling on the binary blend compatibility of poly(vinyl alcohol) and poly(methyl methacrylate): an atomistic simulation and thermodynamic approach

Computer simulations play an important role in designing new polymers as well as in predicting properties of existing polymers. In this paper, the blend compatibility of poly(vinyl alcohol) (PVA) with poly(methyl methacrylate) (PMMA) was studied over the wide range of compositions allowed by the atomistic and mesoscopic simulation methods. The Flory-Huggins interaction parameter, chi, of the blends computed using the atomistic simulation confirmed the blend compatibility for compositions containing >60 wt % of PVA. This observation was further supported by differential scanning calorimetric experiments. Solubility parameters of the polymers obtained from the simulation procedure were in good agreement with those of the literature data. Simulation results were further supported by the spectral and solution property measurements. From the atomistic simulations, chi versus concentration plots were constructed, which showed trends similar to those experimentally measured melting temperature versus concentration. The chi values for the blends, which satisfied the criteria of miscibility of two polymers by the atomistic simulation, agreed quite well with the solubility criteria related to order parameters calculated from the mesoscopic simulation. Kinetics of phase separation was examined via density profiles calculated using the MesoDyn approach for incompatible blends. The length and time scales spanned by these simulations were found to be relevant to the real application scales. The free energy computed in the mesoscopic simulation for blends reached equilibrium, particularly when the simulation was performed at a higher time step, indicating the stability of the blend system at certain compositions.     

Molecular simulations for energy, environmental and pharmaceutical applications of nanoporous materials: from zeolites, metal-organic frameworks to protein crystals

Nanoporous materials have widespread applications in chemical industry, but the pathway from laboratory synthesis and testing to practical utilization of nanoporous materials is substantially challenging and requires fundamental understanding from the bottom up. With ever-growing computational resources, molecular simulations have become an indispensable tool for material characterization, screening and design. This tutorial review summarizes the recent simulation studies in zeolites, metal-organic frameworks and protein crystals, and provides a molecular overview for energy, environmental and pharmaceutical applications of nanoporous materials with increasing degree of complexity in building blocks. It is demonstrated that molecular-level studies can bridge the gap between physical and engineering sciences, unravel microscopic insights that are otherwise experimentally inaccessible, and assist in the rational design of new materials. The review is concluded with major challenges in future simulation exploration of novel nanoporous materials for emerging applications.     

General description of the adsorption of proteins at their iso-electric point in nanoporous materials

A simple but remarkably precise geometric pore-filling model is proposed and experimentally validated for the adsorption of proteins at their iso-electric point (pI) in nanoporous materials. Three different globular proteins-lysozyme, myoglobin, and bovine serum albumin-are used as model proteins to study protein adsorption on two types of ordered mesoporous materials-silica and carbon-which allows us to study the effects of protein and surface structure on the protein adsorption mechanism. The geometric pore-filling model confirms that proteins are closely packed inside the pore channels of mesoporous materials, leading to an exceptionally large protein loading capacity. A relationship for the amount of adsorbed protein as a function of protein size, nanopore volume, and pore diameter is derived. The pore space gradually fills up to complete packing of the available pore space at the highest protein concentration. The high precision of the geometric pore-filling model demonstrates its utility to predict the protein adsorption capacity of ordered nanoporous materials.