Tag Archives: computational models

New Materials For New Processors

Computers used to take up entire rooms. Today, a two-pound laptop can slide effortlessly into a backpack. But that wouldn’t have been possible without the creation of new, smaller processors — which are only possible with the innovation of new materials. But how do materials scientists actually invent new materials? Through experimentation, explains Sanket Deshmukh, an assistant professor in the chemical engineering department of Virginia Tech whose team’s recently published computational research might vastly improve the efficiency and costs savings of the material design process.

Deshmukh’s lab, the Computational Design of Hybrid Materials lab, is devoted to understanding and simulating the ways molecules move and interact — crucial to creating a new material. In recent years, materials scientists have employed machine learning, a powerful subset of artificial intelligence, to accelerate the discovery of new materials through computer simulations. Deshmukh and his team have recently published research in the Journal of Physical Chemistry Letters demonstrating a novel machine learning framework that trainson the fly,” meaning it instantaneously processes data and learns from it to accelerate the development of computational models. Traditionally the development of computational models are “carried out manually via trial-and-error approach, which is very expensive and inefficient, and is a labor-intensive task,” Deshmukh explained.

This novel framework not only uses the machine learning in a unique fashion for the first time,” Deshmukh said, “but it also dramatically accelerates the development of accurate computational models of materials.” “We train the machine learning model in a ‘reverse’ fashion by using the properties of a model obtained from molecular dynamics simulations as an input for the machine learning model, and using the input parameters used in molecular dynamics simulations as an output for the machine learning model,” said Karteek Bejagam, a post-doctoral researcher in Deshmukh’s lab and one of the lead authors of the study.

This new framework allows researchers to perform optimization of computational models, at unusually faster speed, until they reach the desired properties of a new material.

Source: https://vtnews.vt.edu/