University Events

Description: Mechanical Engineering (MNE) SEMINAR

DATE:
Friday, October 20, 2023

TIME:
2:00 p.m. - 3:00 p.m.

Zoom: https://umassd.zoom.us/j/91640406955?pwd=eklBZWVDOXVDa2VwUFMra1kwNWhjdz09
(Contact hling1@umassd.edu or scunha@umassd.edu for Passcode)

SPEAKER:
Dr. Vahid Attari, Postdoctoral Researcher
Materials Science and Engineering, Texas A&M University

TOPIC:
Materials by Design: Harnessing AI for Accelerated Exploration of Chemistry-Microstructure-Property Networks

ABSTRACT:
Envision the ability to meticulously design materials with tailored properties at the mesoscopic level, such as optimizing thermal conductivity for thermoelectric generators or improving the electrochemical response of resistive-switching materials for brain-like computing. The expedition to introducing a novel material, from its initial discovery to practical application, is a lengthy journey that can span up to two decades. Recognizing inefficiencies within the current materials discovery cycle, from initial prediction calculations to fabrication and analysis stages, we have integrated Artificial Intelligence (AI) to drive a rapid material screening process inspired by extensive chemical assays and contemporary materials informatics innovations. In this seminar, we delve into the realm of Integrated Computational Materials Engineering (ICME), a field that blends diverse methods to understand material behavior. Within this exploration, I present a comprehensive framework featuring a microstructure evolution model rooted in phase-field theory for computing properties, an uncertainty propagation framework leveraging the Radon-Nikodym theorem, and several machine learning models for seamlessly connecting materials' chemistry/process, microstructure, and property. To prove utility, the model is evaluated on dual-phase alloy microstructures and the tedious task of analyzing massive amounts of data via the generative AI model reveals the model looks for the same material characteristics as a materials engineer would.

BIO:
Dr. Vahid Attari, a postdoctoral researcher at Texas A&M University (TAMU), specializes in computational materials science and engineering, particularly AI-driven materials design. He works within TAMU's Department of Energy Frontier Research Center (DOE EFRC) and TAMU's newly established BIRDSHOT center on high-throughput materials discovery for electrochemical devices and under extreme conditions. He develops a fusion of inverse and forward materials design methods to uncover new materials, mechanisms, and interfaces. He received a postdoctoral award from the Texas A&M Institute of Data Science for his work on accelerated microstructure design tools. His focus on accelerating materials discovery involves devising uncertainty-aware high-throughput phase-field models for understanding the role of heat, charge, and defect dynamics in microstructural phenomena. Additionally, he implements computer vision AI solutions through deep generative machine learning models that emphasize the seamless interconnection between material properties, microstructures, and process conditions.

For more information please contact Dr. Hangjian Ling, MNE Seminar Coordinator (hling1@umassd.edu).

All are welcome.

Students taking MNE-500 are REQUIRED to attend!

All other MNE MS and BS students are encouraged to attend. EAS students are also encouraged to attend.