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Prediction of hydrogen adsorption in nanoporous materials from the energy distribution of adsorption sites

机译:从吸附位点的能量分布中预测纳米多孔材料中的氢吸附

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We present a fast and accurate, semi-analytical method for predicting hydrogen adsorption in nanoporous materials. For any temperature and pressure, the adsorbed amount is calculated as an integral over the energy density of adsorption sites (guest-host interactions) plus an average guest-guest term. The guest-host interaction energy is calculated using a classical force field with hydrogen modelled as a single-site probe. The guest-guest interaction energy is approximated using an average coordination number, which is regressed using Gaussian Process Regression (GPR). Local adsorption at each site is then modelled using a Langmuir isotherm, which when weighted with its probability density gives an accurate description of hydrogen adsorption. The method is tested on 933 metal-organic frameworks (MOFs) from the Computation-Ready Experimental (CoRE) MOF database at 77 K from to 100 bar, and the results are compared against GCMC predictions. To demonstrate the utility of the method, we calculated hydrogen adsorption isotherms for 12,914 existing MOF structures, at two different temperatures at a speed about 100 times that of GCMC simulations and analyzed the results. We found 13 MOFs with predicted deliverable capacities exceeding the DOE target of 50 g/L for adsorption at 100 bar, 77 K and desorption at 5 bar, 160 K.
机译:我们介绍了一种快速准确的半分析方法,用于预测纳米多孔材料中的氢吸附。对于任何温度和压力,吸附量计算为吸附位点的能量密度(访客交互)加上普通嘉宾术语。客人 - 主机交互能量是使用具有氢模型作为单站点探头的经典力场来计算的。使用平均协调数量近似,使用平均协调数字来近似,这些能器近似使用高斯进程回归(GPR)。然后使用Langmuir等温线进行建模在每个部位的局部吸附,其当加权时,其概率密度可以准确地描述氢吸附。该方法在从10巴的77 k处从计算就绪实验(核心)MOF数据库的933金属 - 有机框架(MOF)测试,并将结果与​​GCMC预测进行比较。为了证明该方法的效用,我们计算了12,914个现有的MOF结构的氢吸附等温,在两个不同的温度下,以GCMC仿真的约100倍并分析结果。我们发现了13个MOF,其具有预测的可交付能力超过50g / L的DOE靶,用于在100巴,77 k和5巴的解吸中吸附,160 k。

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