Advancements in hydrogen energy research with the assistance of computational chemistry

Alexander V. Vorontsov, Panagiotis G. Smirniotis

Research output: Contribution to journalReview articlepeer-review

5 Scopus citations

Abstract

Hydrogen and electricity are the leading energy sources for most applications in the near future. With the rapid development of computers and computational chemistry methods, the research in hydrogen production, infrastructure materials, storage, and utilization more than ever benefits from close interactions with computational chemistry. The present review aims at presenting the modern state of hydrogen energy chemical research in all processes of hydrogen economy. Directions of further research efforts are given in the context of chemometrics and computational chemistry advancements. Problems of computational chemistry that hinder rapid progress are given and their possible solutions are outlined. It is expected that new artificial neural network (ANN) algorithms will play a decisive role in the creation of dependable computational chemistry methods and their application for hydrogen infrastructure, production, storage, and consumption.

Original languageEnglish
Pages (from-to)14978-14999
Number of pages22
JournalInternational Journal of Hydrogen Energy
Volume48
Issue number40
DOIs
StatePublished - 8 May 2023

Keywords

  • Chemometrics
  • DFT
  • Data science
  • Machine learning
  • Review

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