LabCompass

Marisol Koslowski

Materials Science · Purdue University West Lafayette

Established · publishing since 1999

Publications

131

Citations

2,160

Est. group size

~1

Recurring co-author estimate

Active years

28

Publishing since 1999

Research summary
AI-generated

Marisol Koslowski's research focuses on computational modeling of how materials behave under extreme conditions, particularly explosive (energetic) materials, metals, and solder joints subjected to shock, impact, or thermal stress. The work combines simulation techniques (such as crystal plasticity, phase field, and molecular dynamics models) with machine learning to predict how microscopic structural features—like grain boundaries, defects, and 'hot spots'—affect large-scale material failure, detonation, or fracture. This research is relevant to designing safer explosives, more reliable electronic solder joints, and impact-resistant materials.

Energetic materials and explosives modelingShock and impact-induced material failureMicrostructure-property relationships in metals and alloysMultiscale and machine-learning-based simulation methodsSolder joint reliability and electromigration

Publication output has fluctuated over the past decade, with a dip to zero in 2023 followed by a strong rebound in 2024 and continued output into 2026, suggesting a recently reactivated but variable publication pace.

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

Publication cadence
Publications per year over the last 10 years — averaging 4.0/year recently
2017: 8 publications172018: 6 publications182019: 5 publications192020: 8 publications202021: 7 publications212022: 3 publications22232024: 10 publications10242025: 1 publication252026: 6 publications26
Recent publications
Publishes in
  • Bulletin of the American Physical Society×11
  • Journal of Applied Physics×10
  • Modelling and Simulation in Materials Science and Engineering×5
  • Acta Materialia×3
  • Journal of the Mechanics and Physics of Solids×3
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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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