金属有机骨架
纳米技术
电催化剂
表征(材料科学)
密度泛函理论
化学
多样性(控制论)
吸附
量子
生化工程
材料科学
计算机科学
计算化学
物理
物理化学
电化学
量子力学
工程类
人工智能
电极
作者
Indrani Choudhuri,Jingyun Ye,Donald G. Truhlar
出处
期刊:Chemical physics reviews
[American Institute of Physics]
日期:2023-08-07
卷期号:4 (3)
被引量:6
摘要
Metal–organic frameworks (MOFs) have premium exceptional properties for a variety of functions, such as gas separation and storage and catalysis. The large variety of possible inorganometallic nodes and organic linkers provide an almost unlimited number of combinations for assembling MOFs, which makes the experimental characterization and examination of all potentially useful combinations practically impossible. Furthermore, experimental studies of MOFs typically fall short in uncovering crucial details regarding their mechanisms of action or the molecular details responsible for their functional properties, such as the nature of adsorbate binding or the structures of transition states. Computational modeling has, therefore, become an efficient and important tool for strategizing the functionalization of MOFs and explicating the mechanisms of their functions. Here, we review the computational methodologies used for computational studies of MOFs, especially Kohn–Sham density functional theory and combined quantum mechanical and molecular mechanical methods for calculating their structural, electronic, and magnetic properties, as well as for understanding the mechanisms of MOFs' applications to magetic devices, thermal conduction, gas adsorption, separation, storage, and sensing, thermal catalysis, photocatalysis, and electrocatalysis.
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