Aditya W. Sakti, Yoshifumi Nishimura, Hiromi Nakai
Published Online: Dec 05 2019
DOI: 10.1002/wcms.1459
The cover image is based on the Advance Review Recent advances in quantum‐mechanical molecular dynamics simulations of proton transfer mechanism in various water‐based environments by Aditya Wibawa Sakti, Yoshifumi Nishimura and Hiromi Nakai. https://doi.org/10.1002/wcms.1419
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Attila G. Császár, Csaba Fábri, János Sarka
Published Online: Jul 24 2019
DOI: 10.1002/wcms.1432
Pictorial representation of the quantum graph applied to the quantum‐dynamical description of the low‐energy vibrations of CH5+. The 120 internal rotation and 60 flip edges connecting the 120 equivalent vertices (versions) are indicated by blue and red lines, respectively
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Sergey I. Bokarev, Oliver Kühn
Published Online: Jul 24 2019
DOI: 10.1002/wcms.1433
Calculations of various types of X‐ray spectroscopic observables are challenging and require modification of the existing quantum‐chemistry methods.
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Alicia Palacios, Fernando Martín
Published Online: Jul 18 2019
DOI: 10.1002/wcms.1430
Attosecond XUV pulses ionize molecules and generate electronic wave packets that rapidly evolve in time ultimately dictating their chemistry.
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Chao Shen, Junjie Ding, Zhe Wang, Dongsheng Cao, Xiaoqin Ding, Tingjun Hou
Published Online: Jun 27 2019
DOI: 10.1002/wcms.1429
This overview summarizes the progress of traditional ML‐based SFs in the last few years and provides insights into recently developed DL‐based SFs
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Hongshuai Wang, Yujin Ji, Youyong Li
Published Online: Jun 13 2019
DOI: 10.1002/wcms.1421
Application of machine learning in accelerating the energy materials exploration.
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Aditya W. Sakti, Yoshifumi Nishimura, Hiromi Nakai
Published Online: May 31 2019
DOI: 10.1002/wcms.1419
We review the current quantum‐mechanical molecular dynamics studies of proton transfer in various water‐based environments, namely liquid water, ice phases, and confined water environment, as well as in carbon capture and storage technology.
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Siyao Qiu, Qinye Li, Yongjun Xu, Shaohua Shen, Chenghua Sun
Published Online: May 28 2019
DOI: 10.1002/wcms.1422
Computer‐aided learning and understanding of [NiFe] hydrogenases and their catalysis role for hydrogen oxidation reaction advance the development of bio‐inspired molecular catalysts.
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