Calls for Papers

In addition these ongoing topical areas, JMR also publishes Focus Issues several times a year on a single topic within materials research. Upcoming Focus Issues for 2022-2023 are:

Focus Issue: Machine-learned Potentials in Materials Research: From Basic Theory to Engineering Applications
Submission Deadline: January 31, 2023

Materials research has benefited greatly from the powerful synergy of highly accurate ab initio computational methods and a new generation of DFT-based interatomic potentials enabling quantum-accurate material performance simulations at larger length and time scales and realistic engineering temperatures. Whereas classical forcefields suffer shortcomings with respect to accuracy, transferability and flexibility especially for inorganic materials, the emergence of machine-learned potentials (MLPs) in the past decade has profoundly changed this situation. While MLPs inherit the high accuracy of their ab initio training sets, they enable mesoscale simulations of the dynamics of plastic deformation, mass transport and phase transformations. With the foundations having been laid, and an increasing body of evidence demonstrating the validity and advantages of MLPs, it is an appropriate time to review the current state of the art in this dynamic field. This JMR Focus Issue will include topics about machine-learned potentials in materials research ranging from basic concepts and methodological developments to successful applications of this new technology to simulations at length and time scales inaccessible to DFT calculations and beyond the validity of classical forcefields. Contributions may address, e.g., microstructures, extended defects, mass and heat transport, and phase transformations.

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