Author

Theodore Tyrikos-Ergas

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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, Sascha Thinius, P. Seeberger et al. · 0 citations

Open access Aug 2026

Site-specific processing of phosphoethanolamine cellulose by the BcsZ cellulase reveals stochastic biofilm cellulose modification

Surprisingly, the periplasmic cellulase BcsZ, encoded in the cellulose biosynthesis operon, is necessary for efficient bacterial cellulose production and functions independently of the biosynthetic complex to clear mislocalized pEtN cellulose from the periplasm.

J. Rum, Jhih-Yi Huang, E. Kitova et al. · bioRxiv · 0 citations