Documentation for MLatom Python API is out!
The new MLatom 3 release comes with the versatile Python API. We are happy to announce the release of its documentation which is available at http://mlatom.com/docs.
SMLQC 2023: The 2nd International Symposium on Machine Learning in Quantum Chemistry
The 2nd edition of the International Symposium on Machine Learning in Quantum Chemistry, SMLQC 2023, is approaching and will be held from November 29 to December 1 in Uppsala, Sweden. See the symposium’s website https://www.smlqc2023.com/ for more information. The deadline …
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MLatom 3: 10-year anniversary edition is released!
We are happy to announce that on the occasion of its ten-year anniversary, we have released on September 12 a brand new MLatom 3 with tons of new features including more simulation options, Python API for user-customized workflows, and its …
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Energy-conserving molecular dynamics is not energy conserving!
Molecular dynamics simulations are widely used to study molecules and materials and lots of effort is put into making these simulations obey the physical laws. Energy conservation law is obviously one of the most important laws that MD should respect. …
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Beyond 3D-Machine Learning Interatomic Potentials: Meet 4D-Spacetime Atomistic Artificial Intelligence Models
We have introduced a concept of 4D-spacetime atomistic AI models that learn how the molecule changes in time. We demonstrate that this concept is feasible by developing the 4D-spacetime GICnet models that directly predict the atomic coordinates of a molecule …
Chapter “Machine Learning Methods in Photochemistry and Photophysics”
Surging efforts and fast progress in AI methods for photochemistry and photophysics make it difficult to track the current state of the art. We cover the recent developments in this field in the chapter on Machine learning methods in photochemistry …
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QD3SET-1: A Database with Quantum Dissipative Dynamics Data Sets
In a recent article published in Frontiers in Physics, we introduce QD3SET-1, a database consisting of 8 data sets that provide the time-evolved population and coherence dynamics for two widely studied systems: the so-called spin-boson model and FMO complex. The …
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Submissions to Special Issue ‘Artificial Intelligence in Computational Chemistry’ is extended to September 30!
We have got many interesting submissions to the Special Issue ‘Artificial Intelligence in Computational Chemistry’ and some papers are already online. Many authors requested more time for submission, so we are pleased to extend it to two more months. There …
The themed collection and the editorial on Insightful machine learning for physical chemistry in finalized and published in PCCP
Check out the themed collection and our editorial on Insightful machine learning for physical chemistry in PCCP – it was a pleasure for me to guest edit it with Aurora Clark, Olexandr Isayev, and Isaac Tamblyn. Happy reading!
Methane Conversion via Photo-Driven Nitration
Activation of methane and its conversion to added-value products is an important topic which requires chemical solutions with high yields and selectivity. In our recent collaborative study, we present the oxidation of methane to methanol using nitrogen dioxide as a …