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Dynamic Modelling of a Metal Hydride Reactor During Discharge Through Artificial Neural Network Regression

Abstract

With hydrogen as a clean but hazardous energy carrier, solid-state hydrogen storage in the form of a metal hydride has come forth as a safe and low-pressure storage solution with competitive volumetric energy density.

Research topics

  • Hydrogen Storage and Materials
  • Machine Learning in Materials Science
  • Hybrid Renewable Energy Systems

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DOI: 10.3390/engproc2025117070

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