guest ::
| Home > Publications database > Breakdown of Archard law due to transition of wear mechanism from plasticity to fracture > print |
| Home > Publications database > Breakdown of Archard law due to transition of wear mechanism from plasticity to fracture > print |
| 001 | 908591 | ||
| 005 | 20230228121600.0 | ||
| 024 | 7 | _ | |a 10.1016/j.triboint.2022.107660 |2 doi |
| 024 | 7 | _ | |a 0301-679X |2 ISSN |
| 024 | 7 | _ | |a 1879-2464 |2 ISSN |
| 024 | 7 | _ | |a 2128/33789 |2 Handle |
| 024 | 7 | _ | |a WOS:000808336700004 |2 WOS |
| 037 | _ | _ | |a FZJ-2022-02707 |
| 082 | _ | _ | |a 660 |
| 100 | 1 | _ | |a Hu, Jianqiao |0 P:(DE-HGF)0 |b 0 |
| 245 | _ | _ | |a Breakdown of Archard law due to transition of wear mechanism from plasticity to fracture |
| 260 | _ | _ | |a Amsterdam [u.a.] |c 2022 |b Elsevier Science |
| 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 1674743887_19833 |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 Widely used to quantify material wear, the Archard wear law was derived from the asperity flattening model. However, the flattening model is so idealized that it cannot properly represent the real situation with general interlocked asperities, where asperity plowing dominates the wear instead of shearing flattened asperity. Using molecular dynamics simulations, we discussed if Archard law can hold during plowing wear of interlocked interface. Our results indicated Archard law breaks down when fracture dominates the wear. Furthermore, increasing interfacial adhesion or decreasing material ductility changes the dominant wear factor from plasticity to fracture. Finally, we proposed a criterion to determine when Archard wear law will break down and discussed the proposed criterion for real materials. |
| 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 Song, Hengxu |0 P:(DE-Juel1)186711 |b 1 |e Corresponding author |
| 700 | 1 | _ | |a Sandfeld, Stefan |0 P:(DE-Juel1)186075 |b 2 |
| 700 | 1 | _ | |a Liu, Xiaoming |0 P:(DE-HGF)0 |b 3 |e Corresponding author |
| 700 | 1 | _ | |a Wei, Yueguang |0 P:(DE-HGF)0 |b 4 |
| 773 | _ | _ | |a 10.1016/j.triboint.2022.107660 |g Vol. 173, p. 107660 - |0 PERI:(DE-600)1501092-2 |p 107660 - |t Tribology international |v 173 |y 2022 |x 0301-679X |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/908591/files/13_PDFsam_TRIBINT-D-22-00641_R1.pdf |y Published on 2022-05-26. Available in OpenAccess from 2024-05-26. |
| 909 | C | O | |o oai:juser.fz-juelich.de:908591 |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)186711 |
| 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 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2021-02-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2021-02-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1160 |2 StatID |b Current Contents - Engineering, Computing and Technology |d 2021-02-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2021-02-02 |
| 915 | _ | _ | |a Creative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0 |0 LIC:(DE-HGF)CCBYNCND4 |2 HGFVOC |
| 915 | _ | _ | |a Embargoed OpenAccess |0 StatID:(DE-HGF)0530 |2 StatID |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b TRIBOL INT : 2019 |d 2021-02-02 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2021-02-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2021-02-02 |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |d 2021-02-02 |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2021-02-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2021-02-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2021-02-02 |
| 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 | 1 | _ | |a FullTexts |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|