Apurva Mehta
Researcher / author (OpenAlex)
Facts
2 properties- Affiliation
- SLAC National Accelerator Laboratory, Linac Coherent Light Sourceas of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
🔖 Identifiers · 2
- ORCID iD
- 0000-0003-0870-6932
- OpenAlex ID
- A5028798684as of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
📚 Sources · 1
📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 12
Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments,
Autonomous experimentation systems for materials development: A community perspective,
Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery,
Consistency and Completeness,
Detecting rare, abnormally large grains by x-ray diffraction,
Finding a Needle in the Haystack: Identification of Functionally Important Minority Phases in an Operating Battery,
Machine learned synthesizability predictions aided by density functional theory,
Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics
+4 more
← Authored by 12
Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments,
Autonomous experimentation systems for materials development: A community perspective,
Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery,
Consistency and Completeness,
Detecting rare, abnormally large grains by x-ray diffraction,
Finding a Needle in the Haystack: Identification of Functionally Important Minority Phases in an Operating Battery,
Machine learned synthesizability predictions aided by density functional theory,
Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics
+4 more
Affiliated with 2
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Summary
Apurva Mehta is a human[1].