Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...

As the world grapples with the energy crisis and environmental concerns, the focus on renewable energy sources has intensified. Lithium-ion batteries, with their high energy density and low pollution, ...

Researchers have used machine learning to create a model that simulates reactive processes in organic materials and conditions. Researchers from Carnegie Mellon University and Los Alamos National ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

The product development process can be improved with single-physics simulation, multiphysics simulation and simulation apps. This article looks at three real-world examples that show how integrating ...

How in-house-developed and third-party general-purpose simulation tools are limited to a few expert users and aren’t easily shareable. How multiphysics simulation of subsystems can result in an ...

DETROIT ARSENAL—The Center for Army Analysis has given two of its prestigious Modeling & Simulation awards to the U.S. Army DEVCOM Ground Vehicle Systems Center. Both awards, in the team category—one ...