The importance of co-adsorption for applications of porous materials in gas separation has motivated fundamental studies, which have initially focused on the comparison of the binding energies of different gas molecules in the pores (i.e. energetics) and their overall transport. By examining the competitive co-adsorption of several small molecules in M-MOF-74 (M= Mg, Co, Ni) with in-situ infrared spectroscopy and ab initio simulations, we find that the binding energy at the most favorable (metal) site is not a sufficient indicator for prediction of molecular adsorption and stability in MOFs. Instead, the occupation of the open metal sites is governed by kinetics, whereby the interaction of the guest molecules with the MOF organic linkers controls the reaction barrier for molecular exchange. Specifically, the displacement of CO2 adsorbed at the metal center by other molecules such as H2O, NH3, SO2, NO, NO2, N2, O2, and CH4 is mainly observed for H2O and NH3, even though SO2, NO, and NO2, have higher binding energies (~70-90 kJ/mol) to metal sites than that of CO2 (38 to 48 kJ/mol) and slightly higher than water (~60-80 kJ/mol). DFT simulations evaluate the barriers for H2O->CO2 and SO2->CO2 exchange to be - 13 and 20 kJ/mol, respectively, explaining the slow exchange of CO2 by SO2, compared to water. Furthermore, the calculations reveal that the kinetic barrier for this exchange is determined by the specifics of the interaction of the second guest molecule (e.g., H2O or SO2) with the MOF ligands.
Towards Accurate and Scalable High-throughput MOF Adsorption Screening: Merging Classical Force Fields and Universal Machine Learned Interatomic Potentials
Enhancing Hydrogen Adsorption Ability of MOF-5 with Metal Node Exchange and Linker Functionalisation
Carl von Ossietzky Universität Oldenburg（奥尔登堡卡尔·冯·奥西茨基大学）；Friedrich-Schiller Universität Jena（耶拿弗里德里希·席勒大学）；Université de Montpellier, CNRS, ENSCM（蒙彼利埃大学，法国国家科学研究中心，国立化学学院）
Novel MOF-based polymer nanocomposite films were successfully prepared using Zr-based UiO-67 as a metal-organic framework (MOF) and polyurethane (PU) as a polymeric matrix. Synchrotron X-ray powder diffraction (SXRPD) analysis confirms the improved stability of the UiO-67 embedded nanocrystals and scanning electron microscopy images confirm their homogeneous distribution (average crystal size ~100-200 nm) within the 50-um thick film. Accessibility to the inner porous structure of the embedded MOFs was completely suppressed for N2 at cryogenic temperatures. However, ethylene adsorption measurem…
Microporous organosilicas assembled from polysilsesquioxane (POSS) building blocks are promising materials that are yet to be explored in-depth. Here, we investigate the processing and molecular structure of bispropylurea bridged POSS (POSS-urea), synthesised through the acidic condensation of 1,3-bis(3-(triethoxysilyl)propyl)urea (BTPU). Experimentally, we show that POSS-urea has excellent functionality for molecular recognition toward acetonitrile with an adsorption level of 74 mmol/g, which compares favourably to MOFs and zeolites, with applications in volatile organic compounds (VOC). The …
High-throughput screening of small-molecule adsorption in MOF
本论文采用高通量筛选技术结合最先进的van der Waals密度泛函理论，研究了H_2、CO_2、CH_4和H_2O四种重要分子在MOF-74-M（M = Be、Mg、Al、Ca、Sc、Ti、V、Cr、Mn、Fe、Co、Ni、Cu、Zn、Sr、Zr、Nb、Ru、Rh、Pd、La、W、Os、Ir和Pt）中的吸附性质。我们表明，高通量技术可以帮助加速储氢，碳捕获和气体分离的有效材料的开发和改进。构型吸附空间的探索使我们能够提取关键的信息，例如，水与CO_2对吸附"口袋"的竞争。“我们发现只有少数贵金属--Rh，Pd，Os，Ir和Pt--有利于CO_2的吸附，因此是有效的碳捕获材料的潜在候选者。我们的研究结果进一步揭示了H_2、CO_2、CH_4和H_2O在MOF结构中的结合特性的显著差异，表明这些纳米多孔材料可以成功地分离分子混合物。
Metal-organic framework (MOFs) are nanoporous materials that could be used to capture carbon dioxide from the exhaust gas of fossil fuel power plants to mitigate climate change. In this work, we design and train a message passing neural network (MPNN) to predict simulated CO$_2$ adsorption in MOFs. Towards providing insights into what substructures of the MOFs are important for the prediction, we introduce a soft attention mechanism into the readout function that quantifies the contributions of the node representations towards the graph representations. We investigate different mechanisms for …
Monolithic metal-organic frameworks (MOFs) represent a promising solution for the industrial implementation of this emerging class of multifunctional materials, due to their structural stability. When compared to MOF powders, monoliths exhibit other intriguing properties like hierarchical porosity, that significantly improves volumetric adsorption capacity. The mechanical characterization of MOF monoliths plays a pivotal role in their industrial expansion, but so far, several key aspects remain unclear. In particular, the fracture behavior of MOF monoliths has not been explored. In this work, …
In a world where capture and separation processes represent above 10% of global energy consumption, novel porous materials, such as Metal-Organic Frameworks (MOFs) used in adsorption-based processes are a promising alternative to dethrone the high-energy-demanding distillation. Shape and size tailor-made pores in combination with Lewis acidic sites can enhance the adsorbate-adsorbent interactions. Understanding the underlying mechanisms of adsorption is essential to designing and optimizing capture and separation processes. Herein, we analyze the adsorption behaviour of light hydrocarbons (met…
The increasing CO2 level is a critical concern and suitable materials are needed to capture such gases from the environment. While experimental and conventional computational methods are useful in finding such materials, they are usually slow and there is a need to expedite such processes. We use Atomistic Line Graph Neural Network (ALIGNN) method to predict CO2 adsorption in metal organic frameworks (MOF), which are known for their high functional tunability. We train ALIGNN models for hypothetical MOF (hMOF) database with 137953 MOFs with grand canonical Monte Carlo (GCMC) based CO2 adsorpti…
The large number of possible structures of metal-organic frameworks (MOFs) and their limitless potential applications has motivated molecular modelers and researchers to develop methods and models to efficiently assess MOF performance. Some of the techniques include large-scale high-throughput molecular simulations and machine learning models. Despite those advances, the number of possible materials and the potential conditions that could be used still pose a formidable challenge for model development requiring large data sets. Therefore, there is a clear need for algorithms that can efficient…
Density Functional Theory Meta-GGA+U Study of Water Incorporation in the Metal Organic Framework Material Cu-BTC
利用密度泛函理论在meta-GGA +U水平上研究了金属有机骨架材料Cu-BTC的吸水性，最高可达3.5 H $_2$ O/Cu离子.水分子的稳定排列显示氢键水分子的链和在高浓度下形成封闭笼的趋势。水分子团簇主要通过水-水氢键和铜-水-氧相互作用的结合而稳定。通过范德华相互作用、水-水键合的电场增强以及水与骨架氧的氢键合进一步增强稳定性。我们假设形成这种稳定簇的趋势解释了水对Cu-BTC和具有暴露金属位点的相关MOF的特别强的亲和力。
Diamine-appended metal{organic frameworks (MOFs) of the form Mg2(dobpdc)(diamine)2 adsorb CO2 in a cooperative fashion, exhibiting an abrupt change in CO2 occupancy with pressure or temperature. This change is accompanied by hysteresis. While hysteresis is suggestive of a firstorder phase transition, we show that hysteretic temperature-occupancy curves associated with this material are qualitatively unlike the curves seen in the presence of a phase transition; they are instead consistent with CO2 chain polymerization, within one-dimensional channels in the MOF, in the absence of a phase transi…
Combined Experimental and Theoretical Studies on Iodine Capture of Zr-based Metal-Organic Frameworks: Effect of N-functionalization and Adsorption Mechanism
We study the energetic stability and structural features of bimetallic metal-organic frameworks. Such heterometallic MOFs, which can result from partial substitutions between two types of cations, can have specific physical or chemical properties used for example in catalysis or gas adsorption. We work here to provide through computational chemistry a microscopic understanding of bimetallic MOFs and the distribution of cations within their structure. We develop a methodology based on a systematic study of possible cation distributions at all cation ratios by means of quantum chemistry calculat…
A generative artificial intelligence framework based on a molecular diffusion model for the design of metal-organic frameworks for carbon capture
Data Science and Learning Division, Argonne National Laboratory（阿贡国家实验室数据科学与学习分部）；Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校生物物理学与定量生物学中心）；Multiscale Materials and Manufacturing Lab, University of Illinois Chicago（芝加哥伊利诺伊大学多尺度材料与制造实验室）；Department of Materials Science and Engineering, Northwestern University（西北大学材料科学与工程系）；Department of Computer Science, University of Chicago（芝加哥大学计算机科学系）；Department of Physics, University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校物理系）
本文提出GHP-MOFassemble生成式AI框架，基于分子扩散模型设计高CO2吸附容量且可合成的MOFs，经多步筛选验证，所得前六种MOFs的CO2容量超过2 m mol/g，优于假设数据集中96.9%的结构。
First-principles and semi-empirical van der Waals study of thymine on Cu(110) surface
本文采用密度泛函理论计算方法研究了胸腺嘧啶（C $_5$ H $_6$ N $_2$ O $_2$）分子在Cu（110）表面的吸附几何构型和成键机理.在最稳定的能量配置中，分子平面沿着$[1\bar{1}0]$方向垂直于衬底取向。对于这种吸附几何形状，胸腺嘧啶分子通过一个去质子化的氮原子和两个氧原子与表面相互作用，使得键合机制涉及最高占据分子轨道（HOMO）和基底的d-态之间的强杂交。在平行吸附几何形状的情况下，长程范德华相互作用对分子表面几何形状和吸附能都起着重要作用。通过半实证和无缝对接的方法分析了它们的具体作用。特别是，对于一个平面的配置，包括分散效果显着改变的字符的吸附过程从物理吸附到化学吸附。最后，我们通过模拟扫描隧道显微镜（STM）图像预测了分子-表面界面的真实空间形貌。从这些模拟，我们预计，只有某些吸附几何形状可以在STM实验中成像。
Given the strong dependence of material structure and properties on the length and strength of constituent bonds and the fact that surface adsorption and chemical reactions are initiated by the formation of bonds between two systems, bonding parameters are of key importance for material design and industrial processes. In this study, a machine learning (ML)-based model is used to accurately predict bonding properties from information pertaining to isolated systems before bonding. This model employs the density of states (DOS) before bond formation as the ML descriptor and accurately predicts b…
Strong Adsorption between Uranium Dicarbide and Graphene Surface Induced by f Electrons
Institute of Atomic and Molecular Physics, Jilin University（吉林大学原子与分子物理研究所）；Shanghai Institute of Applied Physics, Chinese Academy of Sciences（中国科学院上海应用物理研究所）；Beijing Computational Science Research Center（北京计算科学研究中心）；Department of Physics and Materials Science and Centre for Functional Photonics (CFP), City University of Hong Kong（香港城市大学物理及材料科学系和功能光子学中心）
