001     1050181
005     20260113204522.0
024 7 _ |a 10.3390/molecules30214270
|2 doi
024 7 _ |a 1420-3049
|2 ISSN
024 7 _ |a 1431-5157
|2 ISSN
024 7 _ |a 10.34734/FZJ-2025-05877
|2 datacite_doi
037 _ _ |a FZJ-2025-05877
082 _ _ |a 540
100 1 _ |a Chihaia, Viorel
|0 P:(DE-Juel1)144509
|b 0
|e Corresponding author
245 _ _ |a Molecular Simulations of Energy Materials
260 _ _ |a Basel
|c 2025
|b MDPI
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1768291564_9545
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
500 _ _ |a ISSN 1420-3049 not unique: **2 hits**.
520 _ _ |a The accelerating demand for energy, coupled with the ongoing depletion of conventional energy resources and environmental problems, poses a critical challenge to the scientific community. Addressing this challenge requires the development of innovative materials capable of generating, converting, storing, and utilizing energy in ways that are both sustainable and environmentally benign. Understanding these complex systems—spanning diverse phenomena and interacting across multiple spatial (from atomic to macroscopic) and temporal (from femtoseconds to years) scales—demands an integrated scientific approach. While experimental research remains essential in uncovering the behavior of energy materials, especially under harsh environmental conditions, many microscopic-scale mechanisms remain poorly understood. This is where molecular-level computational simulations can play an important role. Advances in computer molecular sciences now offer powerful methods for probing the structure, dynamics, and reactivity of materials at the atomic and molecular levels, complementing experimental findings and offering predictive insights. In particular, molecular simulations—encompassing static modeling, molecular dynamics, and Monte Carlo methods—enable the exploration of energy materials under various conditions. These approaches can operate across quantum, classical, and coarse-grained frameworks, each providing valuable perspectives on intra- and intermolecular forces. Quantum mechanical methods reveal critical details of electronic structure, which underpin macroscopic properties and device performance, while atomistic and coarse-grained simulations offer scalable insights into larger systems and longer-time-scale processes. To fully capture the multiscale nature of energy materials, there is a growing need to integrate particle-based methods with continuum models through multiresolution and multiscale approaches. Such hybrid strategies promise to deepen our understanding of the fundamental phenomena governing the behavior of materials in real-world energy and environmental applications.This Special Issue aims to highlight recent advances in atomic-scale simulation methods and their application to energy materials science. Contributions demonstrate how computational tools provide crucial insights into the design, characterization, and optimization of materials for a sustainable energy future.
536 _ _ |a 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)
|0 G:(DE-HGF)POF4-5111
|c POF4-511
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Sutmann, Godehard
|0 P:(DE-Juel1)132274
|b 1
|e Corresponding author
|u fzj
773 _ _ |a 10.3390/molecules30214270
|g Vol. 30, no. 21, p. 4270 -
|0 PERI:(DE-600)2008644-1
|n 21
|p 4270
|t Molecules
|v 30
|y 2025
|x 1420-3049
856 4 _ |u https://juser.fz-juelich.de/record/1050181/files/molecules-30-04270-v2.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:1050181
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)132274
913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
|1 G:(DE-HGF)POF4-510
|0 G:(DE-HGF)POF4-511
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Enabling Computational- & Data-Intensive Science and Engineering
|9 G:(DE-HGF)POF4-5111
|x 0
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2024-12-16
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2024-12-16
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2024-12-16
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b MOLECULES : 2022
|d 2024-12-16
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2024-04-10T15:26:48Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2024-04-10T15:26:48Z
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2024-12-16
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2024-12-16
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2024-12-16
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2024-12-16
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2024-12-16
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2024-12-16
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1150
|2 StatID
|b Current Contents - Physical, Chemical and Earth Sciences
|d 2024-12-16
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2024-12-16
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2024-12-16
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21