How SandboxAQ Is Helping Build America’s Semiconductor Supply Chain from the Materials Up
How can the U.S. build semiconductor capacity faster? In this video, SandboxAQ explains how physics-based AI and Large Quantitative Models (LQMs) can help speed advanced materials discovery and support stronger domestic manufacturing. With a new $500 million CHIPS Award, SandboxAQ's team of world-class scientists and engineers are developing new materials for the semiconductor industry, including U.S.-based alternatives for critical materials we don't currently control. By grounding AI in the laws of physics, chemistry, and mathematics, LQMs can predict how materials will behave before they are ever physically made — drastically cutting down a process that traditionally takes years. Discover how SandboxAQ is partnering with Fortune 500 companies, national labs, and manufacturing partners to revolutionize the hardware powering American defense, medical devices, and data centers. Learn more about SandboxAQ's materials science innovations here: https://www.sandboxaq.com/solutions/material-discovery TIMESTAMPS 00:00 - The Critical Material Dependency Problem 00:20 - Announcing the $500M CHIPS R&D Award 00:34 - Meet the SandboxAQ Materials Science Team 01:05 - Traditional Discovery vs. Physics-Based AI 01:38 - Validating New Materials for the U.S. Market 02:08 - The AQCat25 Model (As Seen in Nature) 02:30 - What is a Large Quantitative Model (LQM)? 02:51 - Strengthening American Advanced Manufacturing #Semiconductors #ArtificialIntelligence #materialsscience #SandboxAQ #CHIPSAct #TechInnovation #DeepTech #aqchemsim #lqms