Paper on Machine Learning of Quantum Chemical Reaction Prediction was selected as BCSJ Selected Paper.

“Quantum chemical reaction prediction method based on machine learning”
Mikito Fujinami, Junji Seino, and Hiromi Nakai, Bull. Chem. Soc. Jpn., 93, 685-693 (2020). (Selected Paper)

Twitter by CSJ

“DCDFTBMD” and “RAQET” (Software News and Updates) papers has been recognized as 2018-2019 top download papers.

“DCDFTBMD: Divide‐and‐Conquer Density Functional Tight‐Binding Program for Huge‐System Quantum Mechanical Molecular Dynamics Simulations”

“RAQET: Large‐Scale Two‐Component Relativistic Quantum Chemistry Program Package”

——

Congratulations — your work was one of the top downloaded in recent publication history!

Dear Author,

We are excited to share that your research, published in Journal of Computational Chemistry, is among the top 10% most downloaded papers!

Dcdftbmd: Divide‐and‐Conquer Density Functional Tight‐Binding Program for Huge‐System Quantum Mechanical Molecular Dynamics Simulations

RAQET: Large‐scale two‐component relativistic quantum chemistry program package

What this means for you:
Among work published between January 2018 and December 2019, yours received some of the most downloads in the 12 months following online publication.
Your research generated immediate impact and helped to raise the visibility of Journal of Computational Chemistry.

Thank you for helping to grow our profile so that work like yours is more discoverable.

Best wishes,
Journal of Computational Chemistry