A pioneering study presents a multiscale differential-algebraic neural network (MDANN) that advances the field of dynamical system learning. This innovative method adeptly forecasts system behaviors ...

Complex multiscale dynamics are inherent to materials, where the interconnection across molecular, microscopic, and macroscopic levels is key to understanding their fundamental mechanisms. A prime ...

Lawrence Livermore National Laboratory researchers and a multi-institutional team of scientists have developed a highly detailed, machine learning-backed multiscale model revealing the importance of ...

Electro- and photocatalytic materials are central to enabling sustainable energy conversion processes such as water splitting, CO2 reduction, oxygen ...