Harvard researchers bring the accuracy, sample efficiency, and robustness of deep equivariant neural networks to the simulate 44 million atoms. This is achieved through a combination of innovative ...

Northwestern Engineering researchers have developed a new framework using machine learning that improves the accuracy of interatomic potentials — the guiding rules describing how atoms interact — in ...

The global market for 2D materials — already estimated at several billion dollars annually — is growing at a 4 percent rate. This is explained by the importance of these newly synthesized materials, ...

Figure 1. Various methodologies are utilized in the simulation of materials and materials, such as quantum mechanical calculations at the nanometer (nm) level, classical mechanical force fields at the ...