AstralQ Raises Seed Funding to Accelerate AI-Driven End-to-End Materials Discovery Platform

AstralQ, a U.S.-incorporated startup building an AI-powered end-to-end materials development cloud lab, has closed a seed funding round. The round was backed by Korea Investment Accelerator, Bluepoint Partners, Schmidt, and Smilegate Investment.

The company has developed what it claims to be the world’s first Machine-learned Hamiltonian (MLH) model capable of computing electronic structures at large scale, enabling energy calculations grounded in electronic structure across a wide range of materials. Alongside the MLH model, AstralQ has built a Machine-learned Force Field (MLFF) model trained on proprietary Density Functional Theory (DFT) datasets, and has established an automated inorganic synthesis lab that rapidly validates AI-generated predictions through real-world synthesis — completing the loop from computation to physical experiment.

Proceeds from the round will fund further development of its AI models for advanced materials, including the MLH and MLFF frameworks, as well as pilot evaluations of the end-to-end cloud lab platform.

AstralQ’s founding team brings deep domain expertise across materials science and computational chemistry. CEO Jeongju Cho is a 30-year veteran of materials development with experience at Samsung Research (US), Samsung SDI, A123 Systems, and LG Chem, and formerly led the Advanced Materials Lab at Samsung Research US, publishing dozens of papers in journals including Science, Nature Synthesis, and Nature Communications. Chief Product Officer Maenguen Lee holds a doctorate from the Max-Planck Institute in Germany, Chief Science Officer Wenhao Sun earned his PhD in materials science from MIT, and Chief Technology Officer Lincoln Miara holds a doctorate in materials science from Boston University.

“AstralQ possesses groundbreaking technology that can compress a materials development process that traditionally takes decades into a matter of years,” said Sanghoon Byun, team lead at Korea Investment Accelerator. “Beyond AI model development, the company holds irreplaceable competitive advantages — the ability to execute the full materials development lifecycle end-to-end, from prediction all the way through final synthesis.”

“With computation, experimentation, and validation now fully integrated into a single system, we’re at an inflection point where materials development can be 10 to 20 times faster and costs can fall to one-twentieth of today’s levels,” said CEO Jeongju Cho. “AstralQ’s cloud lab platform lets researchers develop new materials without needing a laboratory or specialized computational staff — and we intend to make it the new global standard for materials scientists everywhere.”