A three-dimensional periodic space sampling method that decomposes large nanoporous structures into local geometrical sites for combined property prediction and site-wise contribution quantification and enables the interpretation of the prediction and allows for accurate identification of significant local sites for targeted properties.
Metal-organic frameworks (MOFs) and MOF-like porous materials exhibit vast structural diversity and support critical applications in gas storage, separations, and catalysis. Predictive modeling remains difficult because their structure-property relationships are multiscale and cage-like, governed by both local chemical...
This perspective examines three interconnected issues, namely, glass formation procedures, interatomic potential development, and machine learning applications, which emerged from the 5th International Workshop on Challenges of Atomistic Simulations of Glasses and Amorphous Materials.
N. A. Anoop Krishnan, A. Pedone, Xiao-Nan Lu et al.· Journal of The American Cera...· 0 citations
The structure and dynamical behavior of water confined at or within nanostructures is a topic central to many fields, from biology to emerging electronics such as carbon nanostructures. Nanoporous graphene (NPG) containing periodic nanoscale pores with specific topologies has emerged as a promising material in carbon-b...
Sneha Mittal, Alan E. Anaya Morales, V. Rosendal et al.· 0 citations
A generalizable, similarity-driven sampling approach, powered by a novel stage-wise optimization strategy, to recover atom types, atomic positions, and unit cell shapes directly from a descriptor without any prior structural knowledge is proposed.
LUMOS combines neural networks with a fast time-dependent density functional theory calculation workflow to build a suite of complementary predictors spanning different trade-offs in speed, accuracy, and generalizability, enabling reliable property prediction across diverse scenarios.
Yan-Heng Li, Zhi-Chen Pu, Li-Jiang Yang et al.· JACS Au· 0 citations
Polymers are fundamental to modern materials science because their backbone chemistry, monomer composition, and chain architecture can be systematically tuned to achieve a virtually unlimited range of mechanical, thermal, electronic, and optical properties. To accelerate the discovery and design of polymeric material...
Amberbir Alemayoh, Zhi-Xin Pan, Ning Wang· Polymer Science & Techno...· 0 citations
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