Velar Scientific offers a GPU‑accelerated simulation engine that computes electronic structure and transport from first principles, eliminating the need for empirical corrections or material‑specific parameters. By solving a single governing equation, the platform predicts material properties—such as critical current density in high‑temperature superconductors or plasma‑facing behavior for fusion materials—in regimes where traditional DFT tools fail, enabling targeted material design before any physical synthesis.
Funding
Funding not disclosed
Founders
Product
Problem
Researchers studying strongly correlated electron materials lack computational tools that can predict electronic structure and transport properties from first principles without relying on empirical corrections or material‑specific parameters. Existing methods such as standard DFT cannot accurately model high‑temperature superconductors, fusion‑grade plasma‑facing materials, or quantum substrates, leading to costly trial‑and‑error synthesis cycles.
Solution
Velar Scientific offers a GPU‑accelerated simulation platform that solves a single governing equation to compute electronic structure and transport directly from quantum mechanical principles. The engine leverages three decades of geometric physics research to deliver predictions in regimes where conventional tools fail. By running fully first‑principles calculations, the platform provides quantitative material property forecasts for strongly correlated systems before any physical sample is made. Users define target properties, the platform performs the simulations, and the results guide focused synthesis and testing, reducing development time and expense. The service supports applications in high‑temperature superconductivity, fusion material design, and quantum substrate engineering, enabling targeted material discovery across these domains.
Target Audience
Primary customers are materials scientists and engineers in academia, national labs, and industry who develop high‑temperature superconductors, fusion reactor components, or quantum electronic materials, as well as R&D teams seeking predictive computational tools for strongly correlated systems.
Features
- GPU‑accelerated computation of electronic structure and transport from a single governing equation
- Fully first‑principles modeling without empirical corrections or material‑specific parameters
- Capability to handle strongly correlated electron systems that are beyond the reach of standard DFT
- End‑to‑end workflow: target definition, high‑performance simulation, and validated property predictions
- Predictions of critical properties such as critical current density, plasma‑facing durability, and topological band structures
- Cloud‑based delivery of results for integration into material design and experimental planning