TY - JOUR
T1 - Advancements in hydrogen energy research with the assistance of computational chemistry
AU - Vorontsov, Alexander V.
AU - Smirniotis, Panagiotis G.
N1 - Publisher Copyright:
© 2023 Hydrogen Energy Publications LLC
PY - 2023/5/8
Y1 - 2023/5/8
N2 - 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.
AB - 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.
KW - Chemometrics
KW - DFT
KW - Data science
KW - Machine learning
KW - Review
UR - http://www.scopus.com/inward/record.url?scp=85146581243&partnerID=8YFLogxK
U2 - 10.1016/j.ijhydene.2022.12.356
DO - 10.1016/j.ijhydene.2022.12.356
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.systematicreview???
AN - SCOPUS:85146581243
SN - 0360-3199
VL - 48
SP - 14978
EP - 14999
JO - International Journal of Hydrogen Energy
JF - International Journal of Hydrogen Energy
IS - 40
ER -