Class Of Nanoporous Materials Research Articles

Advancing hydrogen storage predictions in metal-organic frameworks: A comparative study of LightGBM and random forest models with data enhancement

The escalating consumption of fossil fuels has given rise to a substantial upsurge in greenhouse gas concentrations and global temperatures, which, in turn, has triggered severe climate-related consequences. The critical imperative to reduce CO2 emissions and combat global warming has spurred extensive investigations into clean energy alternatives, with hydrogen emerging as a compelling zero-emission energy source. As a pivotal component of clean energy strategies, hydrogen requires designing compact, lightweight, and efficient storage systems. This study focuses on the development and evaluation of machine learning models for predicting the efficiency of Metal-Organic Frameworks (MOFs) in hydrogen storage, a key aspect of advancing clean energy technologies. MOFs, a class of nanoporous materials, show remarkable potential for hydrogen storage due to their high surface area and porosity. However, selecting the most suitable MOF for this application from a vast array of possible structures is a daunting task. In this context, machine learning algorithms offer an efficient alternative for predicting MOF suitability by considering their structural and chemical properties. We used ensemble learning methods, specifically Light Gradient Boosting Machine (LightGBM) and Random Forest (RF), to predict hydrogen uptake of MOFs based on a dataset of 219 experimentally tested samples. Two modeling scenarios were considered: one using the entire dataset, and the other involving strategic data pre-processing, including outlier removal and feature engineering. The results demonstrate that the measures taken to refine the dataset significantly enhance the predictive performance of the developed models, reducing prediction errors and improving overall goodness of fit. Specifically, the Mean Absolute Error (MAE) values for both the LightGBM and random forest models were reduced from 0.48 and 0.94, respectively, to 0.16 for both models, and the coefficients of determination (R2) increased substantially from 0.84 and 0.72 to 0.95, in both cases. Moreover, feature importance analysis unveiled that pressure-related features make the most significant contributions to the formation of tree ensembles during the model training process. A parametric sensitivity analysis was conducted revealing that H2 uptake in MOFs is most sensitive to changes in adsorption enthalpy, followed by surface area and temperature, while showing lower sensitivity to variations in pressure, consistent with established literature. These results underscore the pivotal role of data enhancement methods in refining machine learning models and can be instrumental in accelerating the development and optimization of MOF materials for clean energy applications.

Efficient adsorption separation of xylene isomers on Cu-BTC@Fe3O4 by appropriate activation methods

Metal-organic frameworks (MOFs) are a class of nanoporous materials. The development of efficient and environmentally friendly methods for activating MOFs is of great significance for its industrial application. In this work, nanoscale magnetic core-shell Cu-BTC@Fe3O4 was prepared through a secondary growth strategy. The effects of different activation solvents (dichloromethane and ethanol, respectively) and temperatures on the surface area, pore structures and the adsorption of xylene isomers on Cu-BTC@Fe3O4 were investigated. Ethanol as an activation solvent could more easily displace the precursors remaining in the channels of Cu-BTC@Fe3O4 than dichloromethane, while the temperature change has no significant influence on the pore structure. The adsorption separation of xylene isomers on Cu-BTC@Fe3O4 composite materials was studied using the batch vapor-phase adsorption, and liquid-phase breakthrough experiments. The activated Cu-BTC@Fe3O4 (CH2Cl2-200 ​°C ​− ​C2H5OH) material has the highest adsorption capacity of 210.26 ​mg ​g−1 for p-xylene (pX). Cu-BTC@Fe3O4 (C2H5OH) and Cu-BTC@Fe3O4 materials have excellent adsorption capacity for m-xylene (mX), with the values of 200.19 ​mg ​g−1 and 219.63 ​mg ​g−1, respectively, which is about 4 times higher than that of Cu-BTC@Fe3O4 (CH2Cl2). The adsorption capacity sequence of xylene on Cu-BTC@Fe3O4 (C2H5OH) and Cu-BTC@Fe3O4 materials is m-xylene (mX) ​> ​p-xylene (pX) ​> ​o-xylene (oX), and that of other materials is pX ​> ​mX ​> ​oX.

Adsorption and diffusion of H2 and CO on UiO-66: A Monte Carlo simulation study

Metal-organic frameworks (MOFs) are a new class of nanoporous materials that have attracted much attention for the adsorption of small molecules, due to the large size of the cavities. In this study, we investigate the adsorption and diffusion of hydrogen (H2) and carbon monoxide (CO) guest molecules to the UiO-66 framework, as one of the most widely used MOFs, by using Monte Carlo simulation method. The results prove that an increment in the temperature decreases the amount of the adsorbed H2 and CO on the UiO-66 framework. While an enhancement of the pressure increases the amount of the adsorbed H2 and CO on the UiO-66 framework. Besides, the adsorption of H2 and CO on UiO-66 is the type I isotherm. The calculated isosteric heat for CO/UiO-66 is slightly higher than that of H2/UiO-66. The means of square displacement (MSD) value is less for CO molecule; hence, the movement of the guest molecule within the host cavity slows down and the guest molecule travels a shorter distance over a period of time. The guest molecule with higher molecular mass possesses less mobility, and therefore, it will have less permeability.

Identifying promising metal-organic frameworks for heterogeneous catalysis via high-throughput periodic density functional theory.

Metal-organic frameworks (MOFs) are a class of nanoporous materials with highly tunable structures in terms of both chemical composition and topology. Due to their tunable nature, high-throughput computational screening is a particularly appealing method to reduce the time-to-discovery of MOFs with desirable physical and chemical properties. In this work, a fully automated, high-throughput periodic density functional theory (DFT) workflow for screening promising MOF candidates was developed and benchmarked, with a specific focus on applications in catalysis. As a proof-of-concept, we use the high-throughput workflow to screen MOFs containing open metal sites (OMSs) from the Computation-Ready, Experimental MOF database for the oxidative C-H bond activation of methane. The results from the screening process suggest that, despite the strong C-H bond strength of methane, the main challenge from a screening standpoint is the identification of MOFs with OMSs that can be readily oxidized at moderate reaction conditions. © 2019 Wiley Periodicals, Inc.

High-Throughput Screening Approach for Nanoporous Materials Genome Using Topological Data Analysis: Application to Zeolites.

The materials genome initiative has led to the creation of a large (over a million) database of different classes of nanoporous materials. As the number of hypothetical materials that can, in principle, be experimentally synthesized is infinite, a bottleneck in the use of these databases for the discovery of novel materials is the lack of efficient computational tools to analyze them. Current approaches use brute-force molecular simulations to generate thermodynamic data needed to predict the performance of these materials in different applications, but this approach is limited to the analysis of tens of thousands of structures due to computational intractability. As such, it is conceivable and even likely that the best nanoporous materials for any given application have yet to be discovered both experimentally and theoretically. In this article, we seek a computational approach to tackle this issue by transitioning away from brute-force characterization to high-throughput screening methods based on big-data analysis, using the zeolite database as an example. For identifying and comparing zeolites, we used a topological data analysis-based descriptor (TD) recognizing pore shapes. For methane storage and carbon capture applications, our analyses seeking pairs of highly similar zeolites discovered good correlations between performance properties of a seed zeolite and the corresponding pair, which demonstrates the capability of TD to predict performance properties. It was also shown that when some top zeolites are known, TD can be used to detect other high-performing materials as their neighbors with high probability. Finally, we performed high-throughput screening of zeolites based on TD. For methane storage (or carbon capture) applications, the promising sets from our screenings contained high-percentages of top-performing zeolites: 45% (or 23%) of the top 1% zeolites in the entire set. This result shows that our screening approach using TD is highly efficient in finding high-performing materials. We expect that this approach could easily be extended to other applications by simply adjusting one parameter, the size of the target gas molecule.

Amorphous Porous Organic Cage Membranes for Water Desalination

Emerged as a new class of nanoporous materials, porous organic cages (POCs) possess salient features of solvent processability and water stability; thus, they are envisioned as promising membrane materials for water desalination. In this study, we propose a simulation protocol to construct atomic models of amorphous POC membranes and examine their desalination performance. Five membranes (AC1, AC2, AC3, AC16, and AC17) with similar cage structure but different periphery groups are considered. All the five membranes exhibit 100% salt rejection. In contrast to crystalline CC1 membrane, which is impermeable to water, AC1 has a water permeability Pw of 3.6 × 10–8 kg·m/(m2·h·bar). With increasing interconnected pores in AC2, AC3, AC16, and AC17, Pw increases. Due to the existence of hydroxyl groups in CC17 cages, AC17 exhibits the highest Pw of 3.17 × 10–7 kg·m/(m2·h·bar), which is higher than in commercial reverse osmosis membranes. Significantly, Pw is found to enhance in mixed AC3/AC17 and AC16/AC17 membran...

Iodine Gas Adsorption in Nanoporous Materials: A Combined Experiment–Modeling Study

Here, we present a combined experimental and Grand Canonical Monte Carlo (GCMC) modeling study on the adsorption of iodine in three classes of nanoporous materials: activated charcoals, zeolites, and metal–organic frameworks (MOFs). Iodine adsorption profiles were measured for the first time in situ, with a uniquely designed sorption apparatus. It was determined that pore size and pore environment are responsible for a dynamic adsorption profile, correlated with distinct pressure ranges. At pressures below 0.3 atm, iodine adsorption is governed by a combination of small pores and extra-framework components (e.g., Ag+ ions in the zeolite mordenite). At regimes above 0.3 atm, the amount of iodine gas stored relates with an increase in pore size and specific surface area. GCMC results validate the trends noted experimentally and in addition provide a measure of the strength of the adsorbate–adsorbent interactions in these materials.

LCA of Starch Aerogels for Biomedical Applications

Aerogels are a special class of nanoporous materials with increasing interest in biomedical and pharmaceutical applications due to their open pore structure and high surface area. Among them, polysaccharide aerogels are biodegradable and biocompatible and, therefore, can be used as carriers for drug delivery systems. In this work, an analysis of their production from the environmental point of view was made, following a Life Cycle Assessment (LCA) approach with the aim of reducing the total emissions. Maize starch aerogels were produced on a pilot scale using a three-step process: first, the gel is prepared using an aqueous solution, then water is replaced by ethanol forming an alcogel and finally, carbon dioxide at supercritical conditions is used as non-solvent to dry the gel and obtain the aerogel. The materials and energy consumptions were determined and the emissions to air, soil and water due the aerogel production were evaluated; all data were normalized to the functional unit (1 g of final aerogel). The environmental analysis was conducted using SimaPro 8.0.4 software and the data for the life cycle inventory were experimentally measured or recovered from the Ecoinvent database.

Design of nanoporous materials with optimal sorption capacity

Modern technological advances have enabled one to manufacture nanoporous materials with a prescribed pore structure. This raises a possibility of using controllable pore-scale parameters (e.g., pore size and connectivity) to design materials with desired macroscopic properties (e.g., diffusion coefficient and adsorption capacity). By relating these two scales, the homogenization theory (or other upscaling techniques) provides a means of guiding the experimental design. To demonstrate this approach, we consider a class of nanoporous materials whose pore space consists of nanotunnels interconnected by nanotube bridges. Such hierarchical nanoporous carbons with mesopores and micropores have shown high specific electric double layer capacitances and high rate capability in an organic electrolyte. We express the anisotropic diffusion coefficient and adsorption coefficient of such materials in terms of the tunnels' properties (pore radius and inter-pore throat width) and their connectivity (spacing between the adjacent tunnels and nanotube-bridge density). Our analysis is applicable for solutes that undergo a non-equilibrium Langmuir adsorption reaction on the surfaces of fluid-filled pores, but other homogeneous and heterogeneous reactions can be handled in a similar fashion. The presented results can be used to guide the design of nanoporous materials with optimal permeability and sorption capacity.

Screening Materials Relevant for Energy Technologies.

In this short review, some recent advances are discussed in the development of computational techniques to perform large-scale screening of materials for energy-related applications. We focus on carbon capture and methane storage in different classes of nanoporous materials. We show how these screening studies can identify whether economic targets for particular processes can be reached.

Simulation and modelling of MOFs for hydrogen storage

Metal organic frameworks (MOFs) have received significant attention in recent years both from academia and industry since this new class of nanoporous materials has many potential advantages over traditional nanoporous materials in gas storage and separation applications. Hydrogen storage has been one of the most widely investigated applications of MOFs and recent experimental studies have shown that several MOFs are promising for hydrogen storage at low temperatures and moderate pressures. It is not practical to test every single MOF in the laboratory for hydrogen storage using experimental methods due to the very large number of existing MOF materials in the literature. Efforts to estimate the hydrogen storage performance of MOFs using molecular simulations and theoretical modelling play a very important role in identifying the most promising materials prior to extensive experiments. We review the current state of the art in molecular simulations and modelling of MOFs for hydrogen storage, compare experimental measurements and simulation predictions for hydrogen uptake of widely studied MOFs, discuss the main reasons for the discrepancy between experiments and simulations, and address the importance of developing theoretical models to predict the hydrogen storage performance of MOFs based on structural properties of materials prior to computationally demanding molecular simulations.

The Potential Applications of Nanoporous Materials for the Adsorption, Separation, and Catalytic Conversion of Carbon Dioxide

Carbon capture and storage (CCS) technologies aiming at tackling CO2 emission have attracted much attention from scientists of various backgrounds. Most CCS systems require an efficient adsorbent to remove CO2 from sources such as fossil fuels (pre‐combustion) or flue gas from power generation (post‐combustion). Research on developing efficient adsorbents with a substantial capacity, good stability and recyclability has grown rapidly in the past decade. Because of their high surface area, highly porous structure, and high stability, various nanoporous materials have been viewed as good candidates for this challenging task. Here, recent developments in several classes of nanoporous materials, such as zeolites, metal organic frameworks (MOFs), mesoporous silicas, carbon nanotubes, and organic cage frameworks, for CCS are examined and potential future directions for CCS technology are discussed. The main criteria for a sustainable CO2 adsorbent for industrial use are also rationalized. Moreover, catalytic transformations of CO2 to other chemical species using nanoporous catalysts and their potential for large scale carbon capture and utilization (CCU) processes are also discussed. Application of CCU technologies avoids any potential hazard associated with CO2 reservoirs and allows possible recovery of some running cost for CO2 capture by manufacturing valuable chemicals.

Molecular Simulations of Hydrogen Storage on Several Nanoporous Zeolites

Zeolites belong to a most prominent class of nanoporous materials which have been considered as potential sorbents for hydrogen storage. The adsorption of hydrogen molecules on MFI, MOR and LTA zeolites, which encompass a range of different pore structure and chemical composition, has been simulated employing Grand Canonical Monte Carlo (GCMC) method. We compare their capacities of hydrogen storage at different temperatures and pressures. The results show that the adsorbed amounts is in order of LTA>MOR>MFI at the same condition. The effects of pore structure of zeolites, temperature and pressure on the hydrogen adsorption has been examined. The results clearly show that: (1) the temperature effect on the adsorption decreases with decreasing in the number of hydrogen molecules adsorbed. (2) A large volume of micropores and a suitable diameter near to the kinetic diameter of a hydrogen molecule are important for improving the hydrogen-storage capacity of zeolites. Based on this, we can conclude that the LTA zeolite with a large pore volume and a suitable channel diameter exhibits a most efficient hydrogen storage capacity than MOR and MFI zeolites.

Molecular Dynamics Simulation of Water and Ions in Nanopores of Lysozyme Protein Crystal

Highly porous cross-linked protein crystals are a novel class of nanoporous materials with vast applications in biocatalysis and selective separation membranes. Long time equilibrium molecular dynamics (MD) simulations were performed to study the behavior of water and ions in the nanopores of lysozyme protein crystals. Pore size profile along different axes showed that the main pores lie along the z-axis consisting of an anisotropic structure. The morphology of pore network and pore sizes, influence water dynamics in protein crystals. Transport properties of water molecules were investigated under two diffusion regimes around protein surface, i.e. surface and core zone. Results showed that water molecules near the surface zone had the anomalous diffusion behavior while the behavior in the core zone was diffusive. Moreover, an anisotropic diffusion behavior was occurred along different axes in accordance to experimental predictions. Simulations demonstrated that nearly 16 percent of water molecules have the residence time above 100 ps at the first hydration layer around the protein crystal, while 3.3 percent of those remain in the cavities over a longer time of about 1400 ps. The behavior of chloride counter ions in the first hydration layer around the protein crystal or on the specific residues of the crystal was investigated as well. The simulation results were in a good agreement with the previous theoretical studies and experimental data. This study provides valuable insights into understanding the transport phenomena in the protein crystals in view of the nature of solvent-protein and ion-protein interactions.

Storage and separation applications of nanoporous metal–organic frameworks

This Highlight explores the progress and perspective in studies of metal–organic frameworks (MOFs), a new class of nanoporous materials, particularly suited for storage and separation applications related to energy utilization and environmental remediation. Since the discovery of the first MOF compound, hundreds of different MOFs have been developed and reported. MOFs are generally synthesized by self-assembly of metal ions/clusters as coordination centers and organic ligands as linkers. They possess intriguing chemical and physical properties and are structurally tunable, thermally stable and mechanically sound. MOFs are increasingly proving to be a superior class of materials for state-of-the-art applications in crystal engineering, chemistry, and materials science. In this Highlight, we present general routes for MOFs synthesis, discuss reticular design of their pore structures, and show some of their remarkable applications, especially in the areas of storage and separation.

Comparative Molecular Simulation Study of CO2/N2 and CH4/N2 Separation in Zeolites and Metal−Organic Frameworks

In this work, a systematic molecular simulation study was performed to compare the separation of CO2/N2 and CH4/N2 mixtures in two different classes of nanoporous materials, zeolites, and metal-organic frameworks (MOFs). For this purpose, three zeolites (MFI, LTA, and DDR) and seven MOFs (Cu-BTC, MIL-47 (V), IRMOF-1, IRMOF-12, IRMOF-14, IRMOF-11, and IRMOF-13) were chosen as the representatives to compare. On the basis of the validated force fields, both adsorption selectivity and pure CO2 and CH4 adsorption isotherms were simulated. The results show that although MOFs perform much better for gas storage, their separation performance is comparable to zeolites; for the systems with the preferable component having a larger quadrupolar moment, both zeolites and MOFs can enhance the separation selectivity, and in contrast they both reduce the selectivity. In addition, we show that ideal adsorbed solution theory (IAST) gives a very reasonable prediction of the mixture adsorption isotherms both in zeolites and in MOFs if the pure component isotherms are known. We demonstrate that the difference in quadrupolar moment of the components is an important property that has to be considered in the selection of a membrane material.

Progress, Opportunities, and Challenges for Applying Atomically Detailed Modeling to Molecular Adsorption and Transport in Metal−Organic Framework Materials

Metal−organic framework (MOF) materials are a class of nanoporous materials that have many potential advantages over traditional nanoporous materials for adsorption and other chemical separation technologies. Because of the large number of different MOFs that exist, efforts to predict the performance of MOFs using molecular modeling can potentially play an important role in selecting materials for specific applications. We review the current state-of-the-art in the molecular modeling and quantum mechanical modeling of MOFs. Quantum mechanical calculations have been used to date to examine structural and electronic properties of MOFs and the calculation of MOF−guest interactions. Molecular modeling calculations using empirical classical potential calculations have been used to study pure and mixed fluid adsorption in MOFs. Similar calculations have recently provided initial information about the diffusive transport of adsorbed fluids in MOFs.

Design Requirements for Metal-Organic Frameworks as Hydrogen Storage Materials

Storing an acceptable density of hydrogen in porous materials by physisorption at room temperature and reasonable pressures is a challenging problem. Metal-organic frameworks (MOFs) are a new class of nanoporous materials that have shown early promise for meeting this goal. They have extremely large specific surface areas, but the heats of adsorption to date are too low to provide significant storage at room temperature. In this work, molecular simulations are used to provide guidelines for the design of MOFs for hydrogen storage. To learn how much the heat of adsorption must be increased to meet current targets, we artificially increase the hydrogen/MOF Lennard-Jones attraction. The correlation of the amount of hydrogen adsorbed with the heat of adsorption, the surface area, and the free volume is revisited. We also review the distinction between excess and absolute adsorption and show that comparing the density of hydrogen within the free volume of materials provides useful insight. The simulation resul...

Nanoporous materials.

The current review article attempts to cover the field of nanoporous materials, thereby materials with voids of the order of 1 nm to 100 nm or even larger. Concepts, that have an effect on a more general basis, are introduced and the common features among the different classes of nanoporous materials are demonstrated enabling understanding their formation and stability. It is seen that the most successful method to produce nanoporous materials made by design is to imprint a template structure into a functional inorganic or even organic network. Further, the manuscript gives an introduction to state of the art overview for microporous, mesoporous and macroporous materials, while the preference lies on ordered pore structures. Further, it is demonstrated how important but also demanding the use of modern analytical techniques are. This makes the field of nanoporous materials truly interdisciplinary with aspects of inorganic chemistry, polymer science, colloid chemistry, physical chemistry, analytical chemistry and chemical engineering.

Structural and Motional Features of a Layered Sodium Hydrous Silicate as Revealed by Solid State NMR

An approach for the investigation of layered alkali metal polysilicate hydrous materials is presented by choosing complementary multinuclear NMR methodologies. New insights into the structural and motional features of magadiite, a layered sodium silicate hydrate, have been gained using 1H, 2H, 29Si and 23Na one- and two-dimensional NMR experiments. Complementary 1H MAS single- and double-quantum studies have proven to be powerful tools in a clear recognition of the nature of hydrous species involved in hydrogen bonding. 1H and 2H MAS experiments permitted us to determine the extent of the mobility of water molecules and provided corroborating evidences of an intralayer, strongly hydrogen bonded character of silanol groups. On the basis of a novel strategy in the analysis of the cross polarization dynamics, it appeared that magadiite contains two types of structurally different Q(3) tetrahedra, as well as two types of sodium ions. The strategy applied in this work might be useful to obtain structural and motional information in the related layered alkali metal silicates, as well as in other classes of nanoporous materials.