Physics-Informed Machine Learning for Microscale Drying of Plant-Based Foods: A Systematic Review of Computational Models and Experimental Insights
CP Batuwatta-Gamage, H Jeong… - arXiv preprint arXiv …, 2025 - arxiv.org
This review examines the current state of research on microscale cellular changes during
the drying of plant-based food materials (PBFM), with particular emphasis on computational …
the drying of plant-based food materials (PBFM), with particular emphasis on computational …
A physics-informed neural network framework to investigate nonlinear and heterogenous shrinkage of drying plant cells
CP Batuwatta-Gamage, CM Rathnayaka… - International Journal of …, 2024 - Elsevier
This paper introduces a novel Physics-Informed Neural Network-based (PINN-based) multi-
domain computational framework to analyse nonlinear and heterogeneous morphological …
domain computational framework to analyse nonlinear and heterogeneous morphological …
A novel machine learning-based computational framework for predicting microscale morphological changes of plant cells during drying
CP Batuwatta Gamage - 2024 - eprints.qut.edu.au
This thesis proposes a novel and effective physics-informed machine learning framework to
explore microscale variations in plant-based foods during drying. By initiating fundamental …
explore microscale variations in plant-based foods during drying. By initiating fundamental …