With the advent of new synthesis and large-scale production technologies, nanostructured gas-adsorbent materials (GAM) like carbon nanocomposites and metal-organic frameworks are becoming increasingly more influential in our everyday lives. First-principles methods based on density functional theory (DFT) have been pivotal in establishing the rational design of GAM, a factor which has tremendously boosted their development. However, DFT methods are not perfect and due to the stringent accuracy thresholds demanded in modelling of GAM (i.e., exact binding energies to within ~0.01 eV) these techniques may provide erroneous conclusions in some challenging situations. Examples of problematic circumstances include gas-adsorption processes in which both electronic long-range exchange and nonlocal correlations are important, and systems where many-body energy and Coulomb screening effects cannot be disregarded. In this critical review, we analyse recent efforts done in the assessment of the performance of DFT methods in the prediction and understanding of GAM. Our inquiry is constrained to the areas of hydrogen storage and carbon capture and sequestration, for which we expose a number of unresolved modelling controversies and define a set of best practice simulation principles. Also, we identify the subtle problems found in the generalization of DFT benchmark studies performed in model cluster systems to real materials, and discuss effective approaches to circumvent them. The increasing awareness of the strengths and imperfections of DFT methods in the simulation of gas-adsorption phenomena should lead in the medium term to more precise, and hence even more fruitful, ab initio engineering of GAM.
Today, fast-growing energy demands and fuel resource depletion are among the hottest concerning issues that treating our world. So, a huge need is felt to find efficient, affordable and eco-friendly energy storage and production systems. Much current research effort proved that gaseous energy carriers such as CH4 and H2 seem to be the right choice for alternative fuel resources. However, the most important challenge with this new-faced resource is the comparatively low volumetric energy storage density. Fortunately, the high-pressure gas storage technique inside the porous media of solid adsor…
UT-Battelle, LLC（UT-巴特勒有限责任公司）；U.S. Department of Energy（美国能源部）
We investigate the graph-based convolutional neural network approach for predicting and ranking gas adsorption properties of crystalline Metal-Organic Framework (MOF) adsorbents for application in post-combustion capture of $\textrm{CO}_2$. Our model is based solely on standard structural input files containing atomistic descriptions of the adsorbent material candidates. We construct novel methodological extensions to match the prediction accuracy of classical machine learning models that were built with hundreds of features at much higher computational cost. Our approach can be more broadly a…
Computational studies addressing the adsorption of fluids in nano-porous materials mostly use ideal single crystal models of the adsorbent. While a few recent studies have tried to address the effects of inter-crystalline spacing on the adsorption of fluids in polycrystalline models of nano-porous materials, the effects of the orientational disorder in the polycrystalline adsorbent remain unexplored. Here we report the adsorption of SO$_2$, an industrially and environmentally important gas, in ZSM-22, a zeolite characterized by straight channel like pores. The simple pore geometry of ZSM-22 he…
First-Principles Investigation of Multimodal Toxic Gas Sensing in Carbon-Tuned hBN-Graphene Alloys: Chemiresistive, Work-Function, and Optical Responses
In this paper, we present a new implementation of the Multicomponent Potential Theory of Adsorption model. The proposed interpretation establishes a clear cut between parameters that depends on the adsorbent from those depending on the adsorbate, which leads to a better understanding of the parameters signification. The interdependence between pure isotherms is eliminated, which mean that each component can be individually finely adjusted. This new approach was tested against 14 datasets for a total of 510 experimental mixture adsorption data of CH4, CO2, N2, H2, O2, H2S, C2H6, C3H6 and C3H8 o…
Computational screening methods have been accelerating discovery of new materials and deployment of technologies based on them in many areas from batteries and alloys to photovoltaics and separation processes. In this review, we focus on post-combustion carbon capture using adsorption in porous materials. Prompted by unprecedented developments in material science, researchers in material engineering, molecular simulations, and process modelling have been interested in finding the best materials for carbon capture using energy efficient pressure-swing adsorption processes. Recent efforts have b…
COFAP: A Universal Framework for COFs Adsorption Prediction through Designed Multi-Modal Extraction and Cross-Modal Synergy
College of Science, College of Information and Electrical Engineering（科学学院，信息与电气工程学院）；China Agricultural University（中国农业大学）；Qingdao Institute of Software, College of Computer Science and Technology（软件研究所，计算机科学与技术学院）；China University of Petroleum (East China)（中国石油大学（华东））；Weifang university（潍坊大学）；College of Environmental Science and Engineering（环境科学与工程学院）；North China Electric Power University（华北电力大学）；College of Science（科学学院）
