• Predictive materials design (DFT, ML-accelerated DFT, MD)
• Nano-structured materials for photonics, batteries, catalysis
• Polymer physics for industrial chemistry
• Material degradation & lifetime modelling (corrosion/oxidation physics)
• Electronic structure modelling for catalytic surfaces. Models & equations:
• Schrödinger-based DFT approximations
• MD force-field dynamics   F = −∇V
• Mesoscale models (phase-field methods)
• Fickian diffusion, reaction–diffusion PDEs

Scientific Value: build a bridge between materials physics and industrial applications (energy, chemical, pharma, mobility).

• Reaction kinetics (micro to macro scale)
• Catalysis under high-pressure/temperature regimes
• Multiphase systems (gas–liquid–solid)
• Reactor engineering & optimization pipelines
• CFD for chemical plants (mixing, turbulence, heat transfer) Equations & frameworks:

• Navier–Stokes momentum equations
• Arrhenius kinetics
• Species transport equations
• Energy balance PDEs for industrial reactors

Scientific Value: advanced chemical engineering with rigorous physical modeling.