FAIR data enabling new horizons for materials research
The prosperity and lifestyle of our society are very much governed by achievements in
condensed matter physics, chemistry and materials science, because new products for …
condensed matter physics, chemistry and materials science, because new products for …
Extending machine learning beyond interatomic potentials for predicting molecular properties
Abstract Machine learning (ML) is becoming a method of choice for modelling complex
chemical processes and materials. ML provides a surrogate model trained on a reference …
chemical processes and materials. ML provides a surrogate model trained on a reference …
Artificial intelligence for science in quantum, atomistic, and continuum systems
X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y ** of quantum properties to structures for chemical space of small organic molecules
Computer-driven molecular design combines the principles of chemistry, physics, and
artificial intelligence to identify chemical compounds with tailored properties. While quantum …
artificial intelligence to identify chemical compounds with tailored properties. While quantum …
A perspective on sustainable computational chemistry software development and integration
The power of quantum chemistry to predict the ground and excited state properties of
complex chemical systems has driven the development of computational quantum chemistry …
complex chemical systems has driven the development of computational quantum chemistry …
SchNetPack 2.0: A neural network toolbox for atomistic machine learning
SchNetPack is a versatile neural network toolbox that addresses both the requirements of
method development and the application of atomistic machine learning. Version 2.0 comes …
method development and the application of atomistic machine learning. Version 2.0 comes …
[HTML][HTML] Improving machine-learning models in materials science through large datasets
The accuracy of a machine learning model is limited by the quality and quantity of the data
available for its training and validation. This problem is particularly challenging in materials …
available for its training and validation. This problem is particularly challenging in materials …
Operando modeling of zeolite-catalyzed reactions using first-principles molecular dynamics simulations
Within this Perspective, we critically reflect on the role of first-principles molecular dynamics
(MD) simulations in unraveling the catalytic function within zeolites under operating …
(MD) simulations in unraveling the catalytic function within zeolites under operating …