LabCompass

Jingfan Yang

Engineering · Purdue University West Lafayette

OpenAlex ORCID
Mid career · publishing since 2008Rising activity
Additive Manufacturing Materials and ProcessesNuclear Materials and PropertiesFusion materials and technologiesAdditive Manufacturing and 3D Printing TechnologiesHigh Entropy Alloys Studies

Publications

26

Citations

487

Est. group size

~1

Recurring co-author estimate

Active years

19

Publishing since 2008

Research summary
AI-generated

Jingfan Yang studies how metal alloys, especially stainless steels made through additive manufacturing (3D printing with metal powders), behave under extreme conditions found in nuclear reactors, such as radiation exposure and corrosive high-temperature water. This work combines materials characterization, alloy design, and irradiation testing to understand and improve materials' resistance to cracking, swelling, and other forms of degradation. The research aims to make 3D-printed metal components more reliable for use in demanding environments like nuclear power plants.

Additive manufacturing of metals (3D printing)Nuclear materials and irradiation damageStress corrosion cracking and stainless steel performanceAlloy design (including high-entropy and oxide-dispersion-strengthened alloys)Microstructure characterization and composite reinforcement

Publication output has grown from little to no activity in the late 2010s to a more active and steady pace of several papers per year since 2021, with a peak in 2023.

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

Publication cadence
Publications per year over the last 10 years — averaging 3.6/year recently
172018: 1 publication18192020: 1 publication202021: 5 publications212022: 2 publications222023: 8 publications8232024: 2 publications242025: 4 publications252026: 2 publications26
Recent publications
Publishes in
  • Journal of Nuclear Materials×7
  • Materials Science and Engineering A×3
  • Acta Materialia×2
  • Corrosion Science×2
  • JOM×2
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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 20, 2026.

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