Gas Adsorption In Porous Materials Research Articles

Active learning of alchemical adsorption simulations; towards a universal adsorption model.

Adsorption is a fundamental process studied in materials science and engineering because it plays a critical role in various applications, including gas storage and separation. Understanding and predicting gas adsorption within porous materials demands comprehensive computational simulations that are often resource intensive, limiting the identification of promising materials. Active learning (AL) methods offer an effective strategy to reduce the computational burden by selectively acquiring critical data for model training. Metal-organic frameworks (MOFs) exhibit immense potential across various adsorption applications due to their porous structure and their modular nature, leading to diverse pore sizes and chemistry that serve as an ideal platform to develop adsorption models. Here, we demonstrate the efficacy of AL in predicting gas adsorption within MOFs using "alchemical" molecules and their interactions as surrogates for real molecules. We first applied AL separately to each MOF, reducing the training dataset size by 57.5% while retaining predictive accuracy. Subsequently, we amalgamated the refined datasets across 1800 MOFs to train a multilayer perceptron (MLP) model, successfully predicting adsorption of real molecules. Furthermore, by integrating MOF features into the AL framework using principal component analysis (PCA), we navigated MOF space effectively, achieving high predictive accuracy with only a subset of MOFs. Our results highlight AL's efficiency in reducing dataset size, enhancing model performance, and offering insights into adsorption phenomenon in large datasets of MOFs. This study underscores AL's crucial role in advancing computational material science and developing more accurate and less data intensive models for gas adsorption in porous materials.

Development of dual‐model classical density functional theory and its application to gas adsorption in porous materials

AbstractClassical density functional theory (CDFT) is a useful theory in many fields. The basis of CDFT is spherical model and extending it to nonspherical molecules is a challenging issue due to the orientation/configuration of the molecules, which implies more complicated molecular models, and higher computational costs. In this work, we propose a dual‐model classical density functional theory (DM‐CDFT) to address this issue. The theory uses a more precise model (all‐atom model) and a simpler model (coarsening model) to construct the external and excess free energy functionals, respectively. By using this methodology, CDFT could handle orientation/configuration effects with low computational costs. The theory is examined by applying it to gas adsorption (such as C2H2/C2H4/C2H6 and toxic gases) in porous materials, and the predicted adsorption isotherms verify the accuracy of the theory. Additionally, the predicted density profile indicates that rotation entropy plays an important role in the adsorption of nonspherical molecules.

How Reproducible Are Isotherm Measurements in Metal–Organic Frameworks?

Scientific progress is severely impeded if experimental measurements are not reproducible. Materials chemistry and related fields commonly report new materials with limited attention paid to reproducibility. Here, we describe methods that are well suited to assessing reproducibility in these fields via retrospective analysis of reported data. This concept is illustrated by an exhaustive analysis of a topic that has been the focus of thousands of published studies, gas adsorption in metal–organic framework (MOF) materials. We show that for the well-studied case of CO2 adsorption there are only 15 of the thousands of known MOFs for which enough experiments have been reported to allow strong conclusions to be drawn about the reproducibility of these measurements. Our results have immediate implications for the characterization of gas adsorption in porous materials but, more importantly, demonstrate an approach to assessing reproducibility that will be widely applicable in materials chemistry.

Accurate van der Waals force field for gas adsorption in porous materials.

An accurate van der Waals force field (VDW FF) was derived from highly precise quantum mechanical (QM) calculations. Small molecular clusters were used to explore van der Waals interactions between gas molecules and porous materials. The parameters of the accurate van der Waals force field were determined by QM calculations. To validate the force field, the prediction results from the VDW FF were compared with standard FFs, such as UFF, Dreiding, Pcff, and Compass. The results from the VDW FF were in excellent agreement with the experimental measurements. This force field can be applied to the prediction of the gas density (H2 , CO2 , C2 H4 , CH4 , N2 , O2 ) and adsorption performance inside porous materials, such as covalent organic frameworks (COFs), zeolites and metal organic frameworks (MOFs), consisting of H, B, N, C, O, S, Si, Al, Zn, Mg, Ni, and Co. This work provides a solid basis for studying gas adsorption in porous materials. © 2017 Wiley Periodicals, Inc.

Accurate Evaluation of the Dispersion Energy in the Simulation of Gas Adsorption into Porous Zeolites.

The force fields used to simulate the gas adsorption in porous materials are strongly dominated by the van der Waals (vdW) terms. Here we discuss the delicate problem to estimate these terms accurately, analyzing the effect of different models. To this end, we simulated the physisorption of CH4, CO2, and Ar into various Al-free microporous zeolites (ITQ-29, SSZ-13, and silicalite-1), comparing the theoretical results with accurate experimental isotherms. The vdW terms in the force fields were parametrized against the free gas densities and high-level quantum mechanical (QM) calculations, comparing different methods to evaluate the dispersion energies. In particular, MP2 and DFT with semiempirical corrections, with suitable basis sets, were chosen to approximate the best QM calculations; either Lennard-Jones or Morse expressions were used to include the vdW terms in the force fields. The comparison of the simulated and experimental isotherms revealed that a strong interplay exists between the definition of the dispersion energies and the functional form used in the force field; these results are fairly general and reproducible, at least for the systems considered here. On this basis, the reliability of different models can be discussed, and a recipe can be provided to obtain accurate simulated adsorption isotherms.

Efficiently mapping structure-property relationships of gas adsorption in porous materials: application to Xe adsorption.

Designing better porous materials for gas storage or separations applications frequently leverages known structure-property relationships. Reliable structure-property relationships, however, only reveal themselves when adsorption data on many porous materials are aggregated and compared. Gathering enough data experimentally is prohibitively time consuming, and even approaches based on large-scale computer simulations face challenges. Brute force computational screening approaches that do not efficiently sample the space of porous materials may be ineffective when the number of possible materials is too large. Here we describe a general and efficient computational method for mapping structure-property spaces of porous materials that can be useful for adsorption related applications. We describe an algorithm that generates random porous "pseudomaterials", for which we calculate structural characteristics (e.g., surface area, pore size and void fraction) and also gas adsorption properties via molecular simulations. Here we chose to focus on void fraction and Xe adsorption at 1 bar, 5 bar, and 10 bar. The algorithm then identifies pseudomaterials with rare combinations of void fraction and Xe adsorption and mutates them to generate new pseudomaterials, thereby selectively adding data only to those parts of the structure-property map that are the least explored. Use of this method can help guide the design of new porous materials for gas storage and separations applications in the future.

Experimental study of deformation rules during the process of gas adsorption and desorption in briquette coal

Gas is one of the most important factors which causes coal and gas outburst and can influence the mechanical characteristics of coal. Coal itself is a kind of elastic carbonaceous material which can swell and shrink under the influence of gas adsorption and desorption. Solid deformations influence the porosity of coal which also changes its adsorption and desorption capability. Gas pressure due to gas adsorption in porous materials is the cause of elastic deformation of coal, which can be assessed by direct experimental measurements. In this paper, briquette coal samples are made with different sizes of coal particles and the deformations are tested during the process of gas adsorption and desorption in samples under different gas pressures. The results show that coal swells during gas adsorption and shrinks during desorption. Deformation of different coal samples under different gas pressures is variable. It is further observed that deformation of coal is proportional to gas pressure and particle size. Also, deformation is not recoverable and residual deformation develops. The relationship between residual deformation and gas pressure is derived. This study helps to reveal the damage mechanism of pore gas in cola mass.

Use of the Grand Canonical Transition-Matrix Monte Carlo Method to Model Gas Adsorption in Porous Materials

We present grand canonical transition-matrix Monte Carlo (GC-TMMC) as an efficient method for simulating gas adsorption processes, with particular emphasis on subcritical gas adsorption in which capillary phase transitions are present. As in other applications of TMMC, the goal of the simulation is to compute a particle number probability distribution (PNPD), from which thermophysical properties of the system can be computed. The key advantage of GC-TMMC is that, by appropriate use of histogram reweighting, one can generate an entire adsorption isotherm, including those with hysteresis loops, from the PNPD generated by a single GC-TMMC simulation. We discuss how to determine various thermophysical properties of an adsorptive system from the PNPD, including the identification of capillary phases and capillary phase transitions, the equilibrium phase transition, other free energies, and the heat of adsorption. To demonstrate the utility of GC-TMMC for studies of adsorption, we apply the method to various sy...

Analytical representation of micropores for predicting gas adsorption in porous materials

A straightforward method for the prediction of the gas storage capabilities of porous materials has been established. The Topologically Integrated Mathematical Thermodynamic Adsorption Model (TIMTAM) combines analytical surface potential energies with classical physisorption thermodynamics in a computationally inexpensive fashion. Experimental and simulated isotherms from leading sorbent candidates such as metal–organic frameworks (MOFs), zeolitic imidazolate frameworks (ZIFs), carbon nanotubes and activated carbons have been used to verify the model. Furthermore, the effect of pore size and shape upon gas storage characteristics is explored using the TIMTAM routine.

The role of water in the performance of biofilters: Parameterization of pressure drop and sorption capacities for common packing materials

The presence of water in a biofilter is critical in keeping microorganisms active and abating pollutants. In addition, the amount of water retained in a biofilter may drastically affect the physical properties of packing materials and packed beds. In this study, the influence of water on the pressure drop and sorption capacities of 10 different packing materials were experimentally studied and compared. Pressure drop was characterized as a function of dynamic hold-up, porosity and gas flow rate. Experimental data were fitted to a mathematical expression based on a modified Ergun correlation. Sorption capacities for toluene were determined for both wet and dry materials to obtain information about the nature of interactions between the contaminant, the packing materials and the aqueous phase. The experimental sorption capacities of materials were fitted to different isotherm models for gas adsorption in porous materials. The corresponding confidence interval was determined by the Fisher information matrix. The results quantified the dynamic hold-up effect resulting from the significant increase in the pressure drop throughout the bed, i.e. the financial cost of driving air, and the negative effect of this air on the total amount of hydrophobic pollutant that can be adsorbed by the supports. Furthermore, the results provided equations for ascertaining water presence and sorption capacities that could be widely used in the mathematical modeling of biofilters.