Making advanced catalyst materials in milliseconds
A flame aerosol process rapidly forms high-entropy alloy nanoparticles, opening new ways to explore catalyst compositions for energy applications.
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Deep learning for new alloys
High-throughput quantum calculations and Deep Sets learning connect alloy composition with stability and elastic properties, helping guide the search for new materials.
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An open database of crystal elastic properties
First-principles calculations deliver complete elastic tensors for more than 1,000 inorganic compounds, helping researchers screen materials for mechanical performance.
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Last updated September 29, 2026
8 research stories · 13 coverage links
Complex materials
Making advanced catalyst materials in milliseconds
A flame aerosol process rapidly forms high-entropy alloy nanoparticles, opening new ways to explore catalyst compositions for energy applications.
Collaborative work with Mark Swihart, Chaochao Dun, and a multi-institution team. UB identifies Haolan Sun and Wei Chen among the Materials Design and Innovation contributors.
Also covered by (1)
- Non-Equilibrium Flame Aerosol Synthesis for Scalable High Entropy Alloy NanoparticlesBerkeley Lab · Molecular Foundry · May 28, 2026 · Research highlight
Energy & resources
An ion sponge for selective lithium and magnesium recovery
A reusable polyoxoniobate material captures magnesium from brine while leaving lithium in solution, connecting selective separation with recovery of both resources.
Coauthored research with Linfeng Chen, Chenyang Li, Chaochao Dun, Jeffrey Urban, and collaborators. The study combines structural, spectroscopic, and computational analysis.
Research highlightUltraselective sequestration of Li+ and Mg2+ from brines via a reusable polyoxoniobate-based ion sponge
Related paper DOI: 10.1126/sciadv.adz7696Energy & resources
Tuning particle size for selective lithium extraction
Iron phosphate particle size helps determine how selectively electrodes capture lithium rather than sodium, informing materials design for extraction from dilute solutions.
Research led by Chong Liu and Gangbin Yan, with Jialiang Wei and Wei Chen among the coauthors from Illinois Tech, alongside UChicago and Argonne collaborators.
Syndicated institutional newsNew method optimizes lithium extraction from seawater and groundwater
Related paper DOI: 10.1038/s41467-024-49191-3AI & materials data
Deep learning for new alloys
High-throughput quantum calculations and Deep Sets learning connect alloy composition with stability and elastic properties, helping guide the search for new materials.
TACC interviews Wei Chen as the study’s senior author. The work brings together Jie Zhang and George Kim at Illinois Tech with Chen Cai and Yusu Wang at UC San Diego.
Institutional feature & podcastDeep Learning for New Alloys
Also covered by (1)
- Deep learning for new alloysPhys.org · University of Texas at Austin · Jul 21, 2022 · Syndicated institutional news
Energy & resources
Copper catalysts for solar-driven conversion of carbon dioxide
Oxygen-functionalized copper nanoparticles improve methane selectivity in a solar-powered carbon dioxide conversion system.
Coverage of Mohammad Asadi’s research team. The paper credits Wei Chen and Jialiang Wei with the density functional theory calculations that help explain catalyst activity and selectivity.
Institutional newsAssistant Professor Publishes Research on High Efficiency Renewable Production of Hydrocarbons from Carbon Dioxide
Related paper DOI: 10.1021/acsnano.9b08792Energy & resources
Combining theory and experiment to discover solar-fuel materials
A joint computational and experimental screening approach identifies promising metal-vanadate photoanodes for converting sunlight into chemical fuels.
Wei Chen coauthored the associated PNAS paper with the Caltech and Berkeley Lab team. The news feature focuses on work led by John Gregoire, Jeffrey Neaton, Kristin Persson, and Qimin Yan.
Institutional newsNew Materials Could Turn Water into the Fuel of the Future
Related paper DOI: 10.1073/pnas.1619940114AI & materials data
Computing a textbook of crystal physics
Automated calculations map piezoelectric properties across nearly 1,000 inorganic compounds, creating an open resource for discovering useful crystal responses.
Coauthored with Maarten de Jong, Henry Geerlings, Mark Asta, and Kristin Persson. Berkeley Lab and Illinois Tech identify Wei Chen as a member of the research team.
Institutional newsComputing A Textbook of Crystal Physics
Also covered by (3)
- Computing a textbook of crystal physicsPhys.org · Berkeley Lab · Sep 30, 2015 · Syndicated institutional news
- Computing A Textbook of Crystal PhysicsIllinois Tech · Oct 7, 2015 · Institutional republication
- MMAE Assistant Professor Wei Chen Member of Team That Published Largest Database of Piezoelectric PropertiesIllinois Tech · Oct 12, 2015 · Institutional news
AI & materials data
An open database of crystal elastic properties
First-principles calculations deliver complete elastic tensors for more than 1,000 inorganic compounds, helping researchers screen materials for mechanical performance.
Berkeley Lab identifies Maarten de Jong and Wei Chen as the two lead authors, working with Mark Asta, Kristin Persson, and a broader international team.
Institutional newsAccelerating Materials Discovery With World’s Largest Database of Elastic Properties
Related paper DOI: 10.1038/sdata.2015.9This archive brings together verified research coverage found to date. Reports about the same study are grouped together; institutional republications are identified alongside their sources. Featured figures are reproduced in full, with only display size and file format optimized.