US 12,124,452 B1
Materials information database including machine learning models
Chi Chen, Renton, WA (US); Hongbin Liu, Redmond, WA (US); Andrea Cepellotti, Arlington, MA (US); Mark A Woodlief, Duvall, WA (US); Nihit Pokhrel, Seattle, WA (US); Adrian Dumitrascu, Redmond, WA (US); Matthias Troyer, Clyde Hill, WA (US); and Nathan Andrew Baker, Seattle, WA (US)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on May 22, 2023, as Appl. No. 18/321,415.
Int. Cl. G06F 16/24 (2019.01); G06F 16/2453 (2019.01); G06F 16/2455 (2019.01); G06F 16/248 (2019.01)
CPC G06F 16/2455 (2019.01) [G06F 16/24542 (2019.01); G06F 16/248 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method enacted on a computing system, the method comprising:
receiving a query comprising one or more of element information and material property information;
based on the query, retrieving material data from a materials information database, the material data comprising,
structural information for each material within a set of materials matching the query, the set comprising one or more materials, and
for one or more materials in the set of materials, one or more predicted material properties determined using one or more trained machine learning models; and
outputting the material data.