Vikas Tomar
Materials Science · Purdue University West Lafayette
Publications
243
Citations
3,401
Est. group size
~7
Recurring co-author estimate
Active years
37
Publishing since 1990
Vikas Tomar's research examines how materials behave under extreme conditions such as high-speed impact, shock loading, and stress, using techniques like Raman spectroscopy and terahertz spectroscopy to study fracture, phase changes, and strain in materials ranging from crystals and ceramics to polymers and battery components. Recent work also applies machine learning to problems like predicting lithium-ion battery degradation and health, and detecting flaws in materials nondestructively. The lab combines experimental characterization with computational modeling and data-driven methods.
Publication output has declined from a peak of around 16-21 papers per year in 2017-2018 to roughly 5-7 papers per year in recent years, indicating a slowing pace of publication.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Subsurface Fracture Mapping in Adhesive Interfaces Using Terahertz Spectroscopy
Materials · 2026
- Measurement of elastic–plastic shock propagation and phase transition using multi-point time-gated Raman spectroscopy
Journal of Applied Physics · 2025
- DegradAI: A scalable framework for early battery health diagnosis from limited data
npj Clean Energy · 2025
- Federated Learning for Detecting Anomaly in IoT Networks
2025
- Anisotropy of the fracture toughness in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si244.svg" display="inline" id="d1e2158"><mml:mi>β</mml:mi></mml:math>-HMX crystals: A computational study
Mechanics of Materials · 2025
- Low Data Machine Learning Framework for Accelerated Lithium-Ion Battery Degradation Prediction
ECS Meeting Abstracts · 2025
- Real-Time Classification of Mixed Plastics Using Machine Learning Based on Terahertz and Raman Spectroscopy Data
SSRN Electronic Journal · 2025
- A comparative analysis of the influence of data-processing on battery health prediction by two machine learning algorithms
Journal of Energy Storage · 2024
- In Operando Health Monitoring for Lithium-Ion Batteries in Electric Propulsion Using Deep Learning
Batteries · 2024
- An Analytical Model to Evaluate the Volumetric Strain in a Polymeric Material Using Terahertz Time-Domain Spectroscopy
Journal of Nondestructive Evaluation · 2024
- IMPACT OF INTEGRATED NUTRIENT MANAGEMENT ON QUALITY PARAMETERS OF NON-SCENTED RICE (ORYZA SATIVA L.) UNDER DSR
PLANT ARCHIVES · 2024
- Data science assisted cohesive finite element modelling of impact behaviour of AP‐HTPB crystal binder composite
Strain · 2023
- Visualizing Shock Induced Thermo-Mechanical Change at Bi-Crystal Interface Using Laser Array Based Nano-Second Raman Spectral Imaging
Journal of Dynamic Behavior of Materials · 2023
- Growth, yield and economics of direct seeded non-scented rice (Oryza sativa L.) influenced by integrated nutrient management
The Pharma Innovation · 2023
- Enhancing Temperature-Dependent Li-Ion Battery Behavior Predictions with Transfer Learning
ECS Meeting Abstracts · 2023
- JOM×9
- Conference proceedings of the Society for Experimental Mechanics×6
- International Journal of Fracture×4
- ECS Meeting Abstracts×4
- International Journal of Plasticity×3
- Cody Kirk
Materials Science · Purdue University West Lafayette
- Amos Gilat
Materials Science · The Ohio State University
- Zherui Guo
Materials Science · Purdue University West Lafayette
- Weinong W. Chen
Materials Science · Purdue University West Lafayette
- Weinong Chen
Materials Science · Purdue University West Lafayette
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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