Here we summarize recent progress in machine learning for the chemical sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future i
Reviewhttps://doi.org/10.1038/s41586-018-0337-2Machine learning for molecular and materials science Keith T. Butler 1 , Daniel w. Davies 2 , Hugh Cartwright 3 , Olexandr isayev 4 * & Aron walsh 5,6 *Here we summarize recent progress in machine learning for the chemical sciences. We...
We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future in which the design, synthesis, characterization and application of molecules and materials is accelerated by artificial ...
Here we summarize recent progress in machine learning for the chemical sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future i
Isayev, Aon Walsh, Machine learning for molecular and materials science. Nature 559(7715), 547–555 (2018). https://doi.org/10.1038/s41586-018-0337-2 Article CAS Google Scholar L. Bornmann, R. Mutz, Growth rates of modern science: a bibliometric analysis based on the number of ...
Wiltschko (Google), highlighting the key areas where machine learning has made, and will continue to make, a positive impact on molecular and materials research. Specifically, the focus of this issue will be on the many ways that machine learning informs, bridges, and aids aspects of the ...
As the big data generated by the development of modern experiments and computing technology becomes more and more accessible, the material design method based on machine learning (ML) has opened a new paradigm for materials science research. With its ability to automatically solve complex tasks, mac...
We review recent studies dealing with the generation of machine learning models of molecular and solid properties. The models are trained and validated using standard quantum chemistry results obtained for organic molecules and materials selected from chemical space at random....
The development of materials is one of the driving forces to accelerate modern scientific progress and technological innovation. Machine learning (ML) technology is rapidly developed in many fields and opening blueprints for the discovery and rational design of materials. In this review, we retrospect...
Quantum chemistry in the age of machine learning. J. Phys. Chem. Lett. 11, 2336–2347 (2020). CAS PubMed Google Scholar Butler, K. T., Davies, D. W., Cartwright, H., Isayev, O. & Walsh, A. Machine learning for molecular and materials science. Nature 559, 547–555 (2018). ...