Author

Seifallah Elfetni

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Aug 2026

Conservation-informed machine learning for physically admissible four-phase hydrothermal liquefaction surrogate modelling.

Hydrothermal liquefaction (HTL) distributes wet biomass and residues among bio-oil, char, aqueous product, and gas. Independent phase regressors can produce negative or non-closed allocations, and random validation obscures inter-study heterogeneity. We develop a conservation-informed constrained surrogate treating the...

Seifallah Elfetni, Sascha Thinius, Pooja Dwivedi et al. · Bioresource Technology · 0 citations

Preprint Aug 2026

PINN-Phase: A physics-informed neural network for curvature-driven multiphase-field evolution

PINN-Phase is introduced, a physics-informed neural time integrator that advances the full multiphase field from its initial condition and enforces phase bounds and unit sum at every step; on the reported explicit multiphase-field benchmarks, post-initial-condition reference states serve only for evaluation.

Seifallah Elfetni, P. Seeberger, Theodore Tyrikos-Ergas · 0 citations