Gast ::
| Hauptseite > Publikationsdatenbank > Sintering of alumina nanoparticles: comparison of interatomic potentials, molecular dynamics simulations, and data analysis > print |
| Hauptseite > Publikationsdatenbank > Sintering of alumina nanoparticles: comparison of interatomic potentials, molecular dynamics simulations, and data analysis > print |
| 001 | 910213 | ||
| 005 | 20230224084237.0 | ||
| 024 | 7 | _ | |a 10.1088/1361-651X/ac8172 |2 doi |
| 024 | 7 | _ | |a 0965-0393 |2 ISSN |
| 024 | 7 | _ | |a 1361-651X |2 ISSN |
| 024 | 7 | _ | |a 2128/33719 |2 Handle |
| 024 | 7 | _ | |a WOS:000840970100001 |2 WOS |
| 037 | _ | _ | |a FZJ-2022-03690 |
| 082 | _ | _ | |a 530 |
| 100 | 1 | _ | |a Roy, Shyamal |0 P:(DE-Juel1)187252 |b 0 |u fzj |
| 245 | _ | _ | |a Sintering of alumina nanoparticles: comparison of interatomic potentials, molecular dynamics simulations, and data analysis |
| 260 | _ | _ | |a Bristol |c 2022 |b IOP Publ. |
| 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 1674199962_31589 |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 |
| 520 | _ | _ | |a Sintering of alumina nanoparticles is of interest both from the view of fundamental research as well as for industrial applications. Atomistic simulations are tailor-made for understanding and predicting the time- and temperature-dependent sintering behaviour. However, the quality and predictability of such analysis is strongly dependent on the performance of the underlying interatomic potentials. In this work, we investigate and benchmark four empirical interatomic potentials and discuss the resulting properties and drawbacks based on experimental and density functional theory data from the literature. The potentials, which have different origins and formulations, are then used in molecular dynamics (MD) simulations to perform a systematic study of the sintering process. To analyse the results, we develop a number of tailored data analysis approaches that are able to characterise and quantify the sintering process. Subsequently, the disparities in the sintering behaviour predicted by the potentials are critically discussed. Finally, we conclude by providing explanations for the differences in performance of the potentials, together with recommendations for MD sintering simulations of alumina. |
| 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 Prakash, A. |0 0000-0003-0795-5777 |b 1 |
| 700 | 1 | _ | |a Sandfeld, S. |0 P:(DE-Juel1)186075 |b 2 |e Corresponding author |
| 773 | _ | _ | |a 10.1088/1361-651X/ac8172 |g Vol. 30, no. 6, p. 065009 - |0 PERI:(DE-600)2001737-6 |n 6 |p 065009 - |t Modelling and simulation in materials science and engineering |v 30 |y 2022 |x 0965-0393 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/910213/files/Roy_2022_Modelling_Simul._Mater._Sci._Eng._30_065009.pdf |y OpenAccess |
| 909 | C | O | |o oai:juser.fz-juelich.de:910213 |p openaire |p open_access |p driver |p VDB |p openCost |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)187252 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)186075 |
| 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 |
| 914 | 1 | _ | |y 2022 |
| 915 | p | c | |a Local Funding |0 PC:(DE-HGF)0001 |2 APC |
| 915 | p | c | |a DFG OA Publikationskosten |0 PC:(DE-HGF)0002 |2 APC |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2021-01-28 |
| 915 | _ | _ | |a Creative Commons Attribution CC BY 4.0 |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2021-01-28 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 915 | _ | _ | |a National-Konsortium |0 StatID:(DE-HGF)0430 |2 StatID |d 2022-11-12 |w ger |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2022-11-12 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2022-11-12 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2022-11-12 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1160 |2 StatID |b Current Contents - Engineering, Computing and Technology |d 2022-11-12 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2022-11-12 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1150 |2 StatID |b Current Contents - Physical, Chemical and Earth Sciences |d 2022-11-12 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b MODEL SIMUL MATER SC : 2021 |d 2022-11-12 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2022-11-12 |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2022-11-12 |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |d 2022-11-12 |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)IAS-9-20201008 |k IAS-9 |l Materials Data Science and Informatics |x 0 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)IAS-9-20201008 |
| 980 | _ | _ | |a APC |
| 980 | 1 | _ | |a APC |
| 980 | 1 | _ | |a FullTexts |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|