Longsheng Feng

Longsheng Feng's research focuses on computational and materials modeling of microstructures in metals, ceramics, and polymers, with applications spanning batteries, superalloys, shape-memory alloys, and 3D-printed porous materials. Work combines machine learning, phase-field simulations, and atomistic modeling to understand how microstructure controls mechanical, transport, and electrochemical properties. Much of the recent output centers on energy storage materials (solid electrolytes, battery electrodes) and structural alloys used in high-temperature or shape-changing applications.

Publication output has grown substantially over the last decade, rising from near zero in 2017-2019 to a peak of 12 publications in 2024 and continuing at a high level into 2026, indicating an increasingly active and productive research program.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026