Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Yao-Kun Lei"'
Publikováno v:
Chinese Journal of Chemical Physics. 35:927-934
Deriving reaction coordinates for the characterization of chemical reactions has long been a demanding task. In our previous work [ACS Cent. Sci. 3, 407 (2017)], the reaction coordinate of a (retro-) Claisen rearrangement in aqueous solution optimize
Publikováno v:
Journal of chemical theory and computation. 18(10)
Understanding the reaction mechanism is required for better control of chemical reactions and is usually achieved by locating transition states (TSs) along a proper one-dimensional coordinate called reaction coordinate (RC). The identification of RC
Autor:
Maodong Li, Jun Zhang, Haiyang Niu, Yao-Kun Lei, Xu Han, Lijiang Yang, Zhiqiang Ye, Yi Isaac Yang, Yi Qin Gao
Publikováno v:
The journal of physical chemistry letters. 13(36)
Water is one of the most abundant molecules on Earth. However, this common and "simple" material has more than 18 different phases, which poses a great challenge to theoretically study the nature of water and ice. We designed two reaction coordinates
Autor:
Zhen Zhang, Yi Isaac Yang, Maodong Li, Jun Zhang, Lijiang Yang, Yi Qin Gao, Xu Han, Yao-Kun Lei
Publikováno v:
Physical Chemistry Chemical Physics. 23:6888-6895
Combining reinforcement learning (RL) and molecular dynamics (MD) simulations, we propose a machine-learning approach (RL$^\ddag$) to automatically unravel chemical reaction mechanisms. In RL$^\ddag$, locating the transition state of a chemical react
Publikováno v:
SCIENTIA SINICA Chimica. 50:1407-1421
Energy transfer and spatial diffusion are two significant sub-processes in chemical reaction. Traditional rate theory is based on two assumptions: (1) energy transfer is faster than chemical reaction so that specific energy transfer channel is not im
Publikováno v:
The Journal of Physical Chemistry Letters. 10:5571-5576
In this Letter, we analyzed the inductive bias underlying complex free-energy landscapes (FELs) and exploited it to train deep neural networks that yield reduced and clustered representation for the FEL. Our parametric method, called information dist
Autor:
Xu Han, Zhen Zhang, Yi Isaac Yang, Maodong Li, Lijiang Yang, Jun Zhang, Yi Qin Gao, Yao-Kun Lei, Junhan Chang
Deep learning is transforming many areas in science, and it has great potential in modeling molecular systems. However, unlike the mature deployment of deep learning in computer vision and natural language processing, its development in molecular mod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b5656269839d1e442a4d39f192b32af
http://arxiv.org/abs/2004.13011
http://arxiv.org/abs/2004.13011
Publikováno v:
The journal of physical chemistry letters. 10(11)
Chemical reactions can be strongly influenced by an external electric field (EEF), but because the EEF is often time-dependent and in case it does not adapt quickly enough to the reaction progress, especially during fast barrier crossing processes, d
Publikováno v:
The Journal of Chemical Physics. 153:174115
Molecular simulations are widely applied in the study of chemical and bio-physical problems. However, the accessible timescales of atomistic simulations are limited, and extracting equilibrium properties of systems containing rare events remains chal
Publikováno v:
Journal of Solid State Chemistry. 218:202-212
The new semirigid exo-bidentate ligand incorporating furfurysalicylamide terminal groups, namely, 1,4-bis{[(2′-furfurylaminoformyl)phenoxyl]methyl}-2,5-bismethylbenzene (L) was synthesized and used as building blocks for constructing lanthanide coo