Bringing Quantum Mechanics to Coarse-Grained Soft Materials Modeling

被引:9
作者
Wang, Chun-, I [1 ]
Jackson, Nicholas E. [1 ]
机构
[1] Univ Illinois, Dept Chem, Urbana, IL 61801 USA
基金
美国国家科学基金会;
关键词
DEPENDENT CHARGE-TRANSPORT; MACHINE LEARNING APPROACH; CONJUGATED POLYMERS; ORGANIC SEMICONDUCTORS; ELECTRONIC-STRUCTURE; RECENT PROGRESS; ENERGY-TRANSFER; CHEMISTRY; DISORDER; DYNAMICS;
D O I
10.1021/acs.chemmater.2c03712
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Fundamental knowledge gaps are endemic in our understanding of how emergent properties of soft materials are linked to the quantum mechanical (QM) world. The limitations of current QM modeling paradigms inhibit the understanding and design of classes of soft materials for which QM phenomenology is critical. At its root, these limitations derive from the seemingly innocuous premise of requiring all atomic positions to solve the molecular Schrodinger equation, which necessitates supercomputing resources to incorporate even simple QM phenomenology into small (similar to nm) systems of soft materials. Here, we review emerging efforts to overcome these challenges through the development of electronic prediction models that operate at the coarse-grained resolution. We motivate the origins of this new computational paradigm, denoted electronic coarse-graining (ECG), discuss its relationship to existing molecular modeling frameworks, and describe recent successes of ECG and related models for soft materials. Importantly, we highlight the classes of soft materials where ECG models can be potentially transformative.
引用
收藏
页码:1470 / 1486
页数:17
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