[On-Demand Webinar] Matlantis: Universal Atomistic Simulation for AI-Driven Materials Discovery

Are you looking for a way to cut your simulation time from months to hours and bring your next-generation materials to market faster?

This is the on-demand version of the highly-acclaimed webinar, “Matlantis: Universal Atomistic Simulation for AI-Driven Materials Discovery,” originally held on December 9th, 2025. Whether you're joining for the first time, missed the live session, or want to watch it again—everyone is welcome.

In this session, we explore how to break your computational bottlenecks using AI-powered simulation.

• The live event was exceptionally vibrant, attended by more than 100 experts from chemical, electronics, semiconductor and automotive industries, as well as prominent research universities.
• This webinar also features a deep-dive Q&A session with over 20 insightful questions from these R&D leaders, offering practical insights for your own materials discovery.

Webinar Overview

Traditional atomic simulations are powerful, but too slow and limited in scale for today's R&D challenges. Matlantis changes that.

Join our free webinar to see how researchers across industries are accelerating materials discovery using a next-generation machine learning simulation platform that delivers DFT-level accuracy up to 20 million times faster.

This session is for R&D professionals who want to break through computational bottlenecks and bring new materials to market faster.

You will:

• Understand how the PFP works, a single, universal machine learning interatomic potential (uMLIP) that combines accuracy, speed, and scalability.
• Discover what’s new in PFP v8, now using the r²SCAN functional for even higher predictive accuracy.
• See real-world case studies showing how Matlantis enables simulations that were previously impossible: large-scale dynamic analysis, reaction discovery, and beyond.

You’ll leave with a clear view of how Matlantis can integrate into your workflow to cut simulation time from months to hours and turn ideas into results faster. 

Speakers

Joshua Young

Senior Application Scientist,
Matlantis Inc.

Joshua received his Ph.D. in Materials Science and Engineering from Drexel University, followed by appointments at the Naval Research Laboratory, Binghamton University, and the New Jersey Institute of Technology. Over the course of his career, he has used a wide variety of computational techniques, including density functional theory, molecular dynamics, and materials informatics/machine learning, to study and design materials for electronics, batteries, catalysis, and more.

Qing-Jie Li

Senior Application Scientist,
Matlantis Inc.

After receiving his Ph.D.in Materials Science and Engineering from Johns Hopkins University, he was a Postdoctoral Associate at MIT, where his research focused on developing and applying machine learning interatomic potentials (MLIP) for energy materials. He then worked as a Senior Engineer at Samsung Semiconductor US, contributing to computational materials discovery for battery applications before joining Matlantis, Inc. He is currently focused on sustainable materials solutions through the application of computational materials science and artificial intelligence (AI).

On-demand Webinar Details

Registration Form