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The Science Behind Karax: Physics-Informed Polymer Aging Prediction 

At Karax, we bridge the gap between advanced material science and predictive computing. We develop the world's most accurate digital twin software for simulating polymer aging, rubber fatigue, and composite material degradation in high-stakes environments. 

Traditional physical testing of advanced materials takes months and costs millions. Karax replaces guesswork with certainty. By pairing physics-based models with decades of empirical degradation data, our K-Suite platform allows aerospace, defense, automotive, and energy pioneers to simulate years of environmental and mechanical aging in a matter of days. 

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Prof. Roozbeh Dargazany

"Our Founder"

Dr. Dargazany provides the core technical vision and structural framework of K-Suit. His research group's pioneering work on Reduced-PINN stiff-kinetics solvers and homogenized fiber-composite mechanics forms the algorithmic foundation for Karax's simulation tools. As Associate Professor of Civil and Environmental Engineering at Michigan State University, Dr. Dargazany leads the High-Performance Materials Group, whose published research on multi-stressor polymer aging under thermal, radiation, mechanical, and hygrothermal conditions is the scientific backbone of the K-Suite platform. 

Advisory Board

Prof. Hisaki Kudo

Polymer/Rubber Aging in Extreme Conditions 
 School of Engineering, The University of Tokyo

  • Bridges deep chemistry  and commercial FE-deployable engineering for life-time prediction of Elastomers

  • Work spans cable lifetime analysis, nuclear radiation  curing kinetics and inverse material characterization 

  • Co-author on nuclear cable insulation and elastomer aging publications 

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Dr. Kenneth T. Gillen

Rubber Aging & Lifetime Prediction

Sandia National Laboratories (Retired)

  • One of the world's foremost authorities on polymer degradation and service-life prediction 

  • Developed foundational methods for combined thermal, radiation, humidity, and mechanical stress 

  • Inventor of the modulus profiler — led to structural understanding of Diffusion-Limited Oxidation (DLO) 

  • Recipient of the ACS Rubber Division Melvin Mooney Distinguished Technology Award

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Dr. Omid Nabnejad 

Rubber Chemistry, Composites & Polymer Materials

  • Expert in polymer processing, composite mechanical characterization, thermal analysis, and materials durability  

  • 520+ citations across 17 publications 

  • Leads experimental characterization and composite benchmarking collaboration 

Why Technical Leaders Choose Karax?

Physics-Informed AI 

Unlike black-box ML models, our software enforces the strict laws of thermodynamics and chemistry. Predictions are physically admissible — not just statistically fitted.

Enterprise Integration 

Our algorithmic architecture exports directly into industrial workflows like ABAQUS, ANSYS, and FE solvers. No re-tooling of your existing pipeline.

Multi-Stressor Capabilities 

We map the simultaneous, complex interplay of thermal cycling, UV/radiation, chemical exposure, and mechanical load — the real conditions your materials face. 

Validated Accuracy

Every K-Suite module is anchored by peer-reviewed publications and laboratory data. 95% accuracy improvement validated in published CNPC industrial trials.

K-Suit: Polymer Aging & Rubber Durability Simulation Software, Validated by Real-World Data

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In prediction of long-term durability

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Experimental tests used for training/validation

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Replacing long-weathering tests with accelerated Tests

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in comparison to classic FE models of Durability

“In a recent study on oil-well sealings, K-Suite predicted 5-year rubber degradation in down-hole environment with 95% accuracy — replacing a 6-month/$180K physical test.” 
see our publications

Publication List 

Composites Science and Technology — 2026 — vol. 111687 

Physics-constrained data-driven model for elastomers under simultaneous thermal and radiation exposure 

Nasiri, P.; Fifield, L.S.; Nouri, H.; Kudo, H.; Dargazany, R. 

DOI: https://doi.org/10.1016/j.compscitech.2026.111687 

Macromolecular Theory and Simulations — 2026 — vol. 35(1), e00044 

Aging of FEPM Material in High-Pressure High-Temperature Hydrogen Sulfide Downhole Environment: Theory, Modeling, Experiments, and Material Lifetime Prediction 

Ghaderi, A.; Nouri, H.; Dargazany, R.; Meng, S.; Xing, P.; Ren, J.; Cheng, P. 

DOI: Pending 

Mechanics of Materials (Elsevier) — 2025 — pages 105548 

A physics-informed neural network model to predict thermo-oxidative/thermal aging of viscoelastic materials 

Naderi, H.; Dargazany, R. 

DOI: Pending 

International Journal of Solids and Structures (Elsevier) — 2022 — vol. 252, pages 111800 

Thermal aging coupled with cyclic fatigue in cross-linked polymers: Constitutive modeling & FE implementation 

Bahrololoumi, A.; Shaafaey, M.; Ayoub, G.; Dargazany, R. 

DOI: Pending 

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