Vacancy formation and migration energy for fcc Cu

Junhao Li

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VacancyFormationMigration_fcc_Cu__TE_038488899376_001

Title A single sentence description.	Vacancy formation and migration energy for fcc Cu
Description	Computes relaxed monovacancy formation and migration energy for fcc Cu at zero temperature and zero pressure
Species The supported atomic species.	Cu
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	None

Contributor	Junhao Li
Maintainer	Daniel S. Karls
Developer	Junhao Li
Published on KIM	2023
How to Cite	This Test originally published in [1] is archived in OpenKIM [2-5]. [1] Jónsson H, Mills G, Jacobsen KW. Nudged elastic band method for finding minimum energy paths of transitions. In: Classical and quantum dynamics in condensed phase simulations. 1998. p. 385–404. doi:10.1142/9789812839664_0016 [2] Li J. Vacancy formation and migration energy for fcc Cu [Internet]. OpenKIM; 2023. Available from: https://openkim.org/cite/TE_038488899376_001 [3] Li J, Fuemmeler E. Vacancy formation and migration energies for cubic and hcp monoatomic crystals v001. OpenKIM; 2023. doi:10.25950/c27ba3cd [4] Tadmor EB, Elliott RS, Sethna JP, Miller RE, Becker CA. The potential of atomistic simulations and the Knowledgebase of Interatomic Models. JOM. 2011;63(7):17. doi:10.1007/s11837-011-0102-6 [5] Elliott RS, Tadmor EB. Knowledgebase of Interatomic Models (KIM) Application Programming Interface (API). OpenKIM; 2011. doi:10.25950/ff8f563a
Funding	Not available

Short KIM ID The unique KIM identifier code.	TE_038488899376_001
Extended KIM ID The long form of the KIM ID including a human readable prefix (100 characters max), two underscores, and the Short KIM ID. Extended KIM IDs can only contain alpha-numeric characters (letters and digits) and underscores and must begin with a letter.	VacancyFormationMigration_fcc_Cu__TE_038488899376_001
Citable Link	https://openkim.org/cite/TE_038488899376_001
KIM Item Type	Test
Driver	VacancyFormationMigration__TD_554849987965_001
Properties Properties as defined in kimspec.edn. These properties are inhereted from the Test Driver.	tag:staff@noreply.openkim.org,2015-07-28:property/monovacancy-neutral-relaxed-formation-potential-energy-crystal-npt tag:staff@noreply.openkim.org,2015-09-16:property/monovacancy-neutral-migration-energy-crystal-npt
KIM API Version	2.3.0
Simulator Name The name of the simulator as defined in kimspec.edn. This Simulator Name is inhereted from the Test Driver.	ase
Programming Language(s) The programming languages used in the code and the percentage of the code written in each one.	100.00% Python

Previous Version	VacancyFormationMigration_fcc_Cu__TE_038488899376_000

Models

EAM_Dynamo__MD_120291908751_006

Model	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
EAM_Dynamo_AcklandTichyVitek_1987_Cu__MO_179025990738_006	view	1720548
EAM_Dynamo_AcklandTichyVitek_1987v2_Cu__MO_762798677854_001	view	1580426
EAM_Dynamo_AcklandVitek_1990_Cu__MO_642748370624_001	view	757981
EAM_Dynamo_AdamsFoilesWolfer_1989Universal6_Cu__MO_145873824897_001	view	644580
EAM_Dynamo_BonnyPasianotCastin_2009_FeCuNi__MO_469343973171_006	view	569078
EAM_Dynamo_BonnyTerentyevBakaev_2013_FeCuNiMn__MO_398449950394_000	view	610516
EAM_Dynamo_BorovikovMendelevKing_2016_CuZr__MO_097471813275_001	view	1493602
EAM_Dynamo_CaiYe_1996_AlCu__MO_942551040047_006	view	579043
EAM_Dynamo_ClementAuger_2022_CuZn__MO_875501152989_000	view	435892
EAM_Dynamo_DeluigiPasianotValencia_2021_FeNiCrCoCu__MO_657255834688_001	view	1172708
EAM_Dynamo_FarkasCaro_2018_FeNiCrCoCu__MO_803527979660_001	view	1279121
EAM_Dynamo_FischerSchmitzEich_2019_CuNi__MO_266134052596_001	view	762180
EAM_Dynamo_Foiles_1985_Cu__MO_831121933939_001	view	604805
EAM_Dynamo_FoilesBaskesDaw_1986Universal3_Cu__MO_666348409573_005	view	402596
EAM_Dynamo_GolaPastewka_2018_CuAu__MO_426403318662_001	view	794280
EAM_Dynamo_HoytGarvinWebb_2003_PbCu__MO_119135752160_006	view	993244
EAM_Dynamo_LiuLiuBorucki_1999_AlCu__MO_020851069572_001	view	425442
EAM_Dynamo_MendelevKing_2013_Cu__MO_748636486270_006	view	1060610
EAM_Dynamo_MendelevKramerBecker_2008_Cu__MO_945691923444_006 This Model has a disclaimer The potential was designed to simulate solidification in Cu. For simulation of solid properties, the version published in [M.I. Mendelev and A.H. King, Phil. Mag. 93, 1268-1278 (2013), KIM item https://doi.org/10.25950/34748b8d ] is better for this purpose. Other versions of this potentials with different SFE and USFE were published in: [M.I. Mendelev and A.H. King, Phil. Mag. 93, 1268-1278 (2013), KIM item https://doi.org/10.25950/34748b8d ], [V. Borovikov, M.I. Mendelev, A.H. King and R. LeSar, MSMSE 23, 055003 (2015)] and [V. Borovikov, M.I. Mendelev and A.H. King, MSMSE 24, 085017 (2016) KIM item https://doi.org/10.25950/e49bf93d ].	view	1013609
EAM_Dynamo_MendelevKramerOtt_2009_CuZr__MO_600021860456_006 This Model has a disclaimer The potential was developed to simulate vitrification in the Cu64.5Zr35.5 alloy. Another model developed with improved fidelity to this vitrification process is [M.I. Mendelev, Y. Sun, F. Zhang C.Z. Wang and K.M. Ho, J. Chem. Phys. 151, 214502 (2019)], see https://openkim.org/id/MO_609260676108_000.	view	1351971
EAM_Dynamo_MendelevSordeletKramer_2007_CuZr__MO_120596890176_006	view	895260
EAM_Dynamo_MendelevSunZhang_2019_CuZr__MO_609260676108_001	view	1088941
EAM_Dynamo_MishinMehlPapaconstantopoulos_2001_Cu__MO_346334655118_006	view	394454
EAM_Dynamo_OnatDurukanoglu_2014_CuNi__MO_592013496703_006	view	1050041
EAM_Dynamo_VoterChen_1993_Cu__MO_808763161866_001	view	2248485
EAM_Dynamo_WilliamsMishinHamilton_2006_CuAg__MO_128703483589_006	view	634800
EAM_Dynamo_WuTrinkle_2009_CuAg__MO_270337113239_006	view	599276
EAM_Dynamo_ZhouJohnsonWadley_2004_Cu__MO_127245782811_006	view	732401
EAM_Dynamo_ZhouJohnsonWadley_2004_CuAgAuNiPdPtAlPbFeMoTaWMgCoTiZr__MO_870117231765_001	view	1551871
EAM_Dynamo_ZhouJohnsonWadley_2004_CuTa__MO_547744193826_001	view	698497
EAM_Dynamo_ZhouJohnsonWadley_2004NISTretabulation_Cu__MO_759493141826_001	view	408915
EAM_Dynamo_ZhouJohnsonWadley_2004NISTretabulation_CuAgAu__MO_318213562153_001	view	1033706
EAM_Dynamo_ZhouJohnsonWadley_2004NISTretabulation_CuTa__MO_950828638160_001	view	1422767
EAM_Dynamo_ZhouWadleyJohnson_2001_Cu__MO_380822813353_001	view	505888

EMT_Asap__MD_128315414717_004

Model	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
EMT_Asap_MetalGlass_BaileySchiotzJacobsen_2004_CuMg__MO_228059236215_001	view	1919581
EMT_Asap_MetalGlass_PaduraruKenoufiBailey_2007_CuZr__MO_987541074959_001	view	1662940
EMT_Asap_Standard_JacobsenStoltzeNorskov_1996_AlAgAuCuNiPdPt__MO_115316750986_001	view	1986060
EMT_Asap_Standard_JacobsenStoltzeNorskov_1996_Cu__MO_396616545191_001	view	2036343

MEAM_LAMMPS__MD_249792265679_002

Model	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
MEAM_LAMMPS_AgrawalMirzaeifar_2021_CuC__MO_028979335952_002	view	2420568
MEAM_LAMMPS_AsadiZaeemNouranian_2015_Cu__MO_390178379548_002	view	4247682
MEAM_LAMMPS_EtesamiAsadi_2018_Cu__MO_227887284491_002	view	2261327
MEAM_LAMMPS_JelinekGrohHorstemeyer_2012_AlSiMgCuFe__MO_262519520678_002	view	6252442
MEAM_LAMMPS_JeongParkDo_2018_PdCu__MO_353393547686_002	view	2114970
MEAM_LAMMPS_KangSaLee_2009_ZrAgCu__MO_813575892799_002	view	1866059
MEAM_LAMMPS_KimLee_2008_CuZr__MO_407917731909_001	view	1879163
MEAM_LAMMPS_KimSeolJi_2017_PtCu__MO_070797404269_002	view	4444838
MEAM_LAMMPS_LeeShim_2004_NiCu__MO_409065472403_002	view	1595430
MEAM_LAMMPS_LeeShimBaskes_2003_Cu__MO_087820130586_001	view	1521588
MEAM_LAMMPS_LeeWirthShim_2005_FeCu__MO_063626065437_002	view	1746867
MEAM_LAMMPS_MirazDhariwalMeng_2020_CuNTi__MO_122936827583_002	view	2206186
MEAM_LAMMPS_SharifiWick_2025_FeMnNiTiCuCrCoAl__MO_675947402254_000 This Model has a disclaimer This potential is designed for the structural properties of High Entropy Alloys (HEA)s and Complex Concentrated Alloys (CCAs). The fitting procedure involved developing all included unary, binary and ternary systems so it can be used for any alloy subset. This potential focuses on the structural analysis of alloys including shear strength and elastic constants, dislocation dynamics and their impact on alloy strength, and the analysis of defect effects, such as voids, on material properties. However, the potential was not optimized for temperature-dependent properties and was not fit to density, thermal expansion coefficients, or thermal conductivity data.	view	9025593
MEAM_LAMMPS_Wagner_2007_Cu__MO_313717476091_002	view	3607036
MEAM_LAMMPS_WangOhLee_2020_CuCo__MO_694335101831_002	view	1889985
MEAM_LAMMPS_WangOhLee_2020_CuCo__MO_849011491644_002	view	4181497
MEAM_LAMMPS_WangOhLee_2020_CuMo__MO_380272712420_002	view	1959336
MEAM_LAMMPS_WangOhLee_2020_CuMo__MO_486450342170_002	view	1607062

Morse_Shifted__MD_552566534109_004

Model	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Morse_Shifted_GirifalcoWeizer_1959HighCutoff_Cu__MO_151002396060_004	view	4712375
Morse_Shifted_GirifalcoWeizer_1959LowCutoff_Cu__MO_673777079812_004	view	3042588
Morse_Shifted_GirifalcoWeizer_1959MedCutoff_Cu__MO_173787283511_004	view	2778290

PolyMLP__MD_367995833009_000

Model	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
PolyMLP_Seko_2022p2_AlCu__MO_933443908371_000 This Model has a disclaimer Several models from the PolyMLP repository are available for AlCu, all laying on a pareto front of computational speed vs. RMS accuracy. They are labeled p1, p2, p3, p4, p5 in their KIM IDs. Higher numbers mean slower models. The author-recommended model for this system is p2 (this model).		view	7936107

SNAP__MD_536750310735_000

Model	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
SNAP_LiHuChen_2018_Cu__MO_529419924683_000 This Model has a disclaimer This potential is designed for Cu fcc systems. It is not appropriate for other elements. The potential was trained using LAMMPS version 17Nov2016. Newer LAMMPS may see energy differences, but the relative values should remain to be the same.	view	3469513
SNAP_ZuoChenLi_2019_Cu__MO_931672895580_000 This Model has a disclaimer This potential is designed for Cu fcc systems. It is not appropriate for other elements. The potential was trained using LAMMPS version 12Dec2018. Newer LAMMPS may see energy differences, but the relative values should remain to be the same.	view	8180563
SNAP_ZuoChenLi_2019quadratic_Cu__MO_265210066873_000 This Model has a disclaimer This potential is designed for Cu fcc systems. It is not appropriate for other elements. The potential was trained using LAMMPS version 12Dec2018. Newer LAMMPS may see energy differences, but the relative values should remain to be the same.	view	5336676

No Driver

Model	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
EAM_Mendelev_2019_CuZr__MO_945018740343_000	view	3184087
EAM_NN_Johnson_1988_Cu__MO_887933271505_003	view	1952710
Sim_LAMMPS_ADP_ApostolMishin_2011_AlCu__SM_667696763561_000	view	14174228
Sim_LAMMPS_ADP_PunDarlingKecskes_2015_CuTa__SM_399364650444_000	view	11924312
Sim_LAMMPS_BOP_ZhouWardFoster_2015_CCu__SM_784926969362_000	view	54906979
Sim_LAMMPS_BOP_ZhouWardFoster_2015_CuH__SM_404135993060_000	view	19612943
Sim_LAMMPS_MEAM_AsadiZaeemNouranian_2015_Cu__SM_239791545509_000	view	3001544
Sim_LAMMPS_MEAM_JelinekGrohHorstemeyer_2012_AlSiMgCuFe__SM_656517352485_000	view	15705245
Sim_LAMMPS_MEAM_Wagner_2007_Cu__SM_521856783904_000	view	2217180
Sim_LAMMPS_Polymorphic_Zhou_2004_CuTa__SM_453737875254_000	view	7361461

Errors

LJ__MD_414112407348_003

Model	Error Categories	Link to Error page
LJ_ElliottAkerson_2015_Universal__MO_959249795837_003	other	view

Files

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