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Paper Citation Record · LEDGER

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys

As of 16 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2608.07445.

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pith.paper-citation-record.v1
2608.07445 v1

Coverage vector

measured 64 of 64 reference resolution

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64 of 64 outbound references displayed

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Outbound references

Observation a8f0b05b-ef78-468c-a88e-803df84b530f · outbound

This paper cites Spectral quadrature for the first principles study of crystal defects: Application to magnesium.Journal of Computational Physics, 456:111035, 2022.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Spectral quadrature for the first principles study of crystal defects: Application to magnesium.Journal of Computational Physics, 456:111035, 2022

Reference 1

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Observation 8a1fb9f0-72d4-4cb3-92e9-94ac2549abb2 · outbound

This paper cites Hydrogen embrittlement of aluminum: the crucial role of vacancies.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Hydrogen embrittlement of aluminum: the crucial role of vacancies

Reference 2

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Observation ddc55f53-862b-4e24-8098-fb9bd3fa27bb · outbound

This paper cites Can vacancies lubricate dislocation motion in aluminum?Physical review letters, 89(10):105501, 2002.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Can vacancies lubricate dislocation motion in aluminum?Physical review letters, 89(10):105501, 2002

Reference 3

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Observation 06b2fa2c-2b7e-4acb-8688-90b91185d6f7 · outbound

This paper cites Vacancy clustering and prismatic dislocation loop formation in aluminum.Physical Review B—Condensed Matter and Materials Physics, 76(18):180101, 2007.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Vacancy clustering and prismatic dislocation loop formation in aluminum.Physical Review B—Condensed Matter and Materials Physics, 76(18):180101, 2007

Reference 4

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Observation fdf034ed-e033-4ae8-8c07-7c97f0d614e0 · outbound

This paper cites an unresolved cited work.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Unresolved cited work

Reference 5

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Observation 49399774-ebdf-43cd-b4d4-2d6824b7b27d · outbound

This paper cites Nanostructured high-entropy alloys with multiple principal elements: novel alloy design concepts and outcomes.Advanced engineering materials, 6(5):299–303, 2004.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Nanostructured high-entropy alloys with multiple principal elements: novel alloy design concepts and outcomes.Advanced engineering materials, 6(5):299–303, 2004

Reference 6

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Observation 7d63d596-2f4b-446b-a679-d7f2381051b0 · outbound

This paper cites Microstructural development in equiatomic multicomponent alloys.Materials Science and Engineering: A, 375:213–218, 2004.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Microstructural development in equiatomic multicomponent alloys.Materials Science and Engineering: A, 375:213–218, 2004

Reference 7

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Observation 8cd79d13-55ae-4437-a22e-704840b0a8f2 · outbound

This paper cites High-entropy alloys.Nature reviews materials, 4(8):515–534, 2019.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys High-entropy alloys.Nature reviews materials, 4(8):515–534, 2019

Reference 8

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Observation c8d7e0a7-f12a-4983-91cc-5654aa2871cc · outbound

This paper cites High entropy alloys: A focused review of mechanical properties and deformation mechanisms.Acta Materialia, 188:435–474, 2020.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys High entropy alloys: A focused review of mechanical properties and deformation mechanisms.Acta Materialia, 188:435–474, 2020

Reference 9

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Observation 3a5d7689-7fa7-46d1-8b8b-e1941c481b51 · outbound

This paper cites Solute strengthening in random alloys.Acta Materialia, 124:660–683, 2017.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Solute strengthening in random alloys.Acta Materialia, 124:660–683, 2017

Reference 10

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Observation 05f2935a-afc4-48a2-b9ff-a65cacf3ee4b · outbound

This paper cites Edge dislocation mediated anomalous charge transfer in face centered cubic high entropy alloys.Computational Materials Science, 273:114955, 2026.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Edge dislocation mediated anomalous charge transfer in face centered cubic high entropy alloys.Computational Materials Science, 273:114955, 2026

Reference 11

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Observation cfaafca6-2a76-4c64-8a8a-7637bf1510cd · outbound

This paper cites A comprehensive review of the computational approaches for structure– property prediction of high entropy materials.High Entropy Alloys & Materials, pages 1–46, 2026.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys A comprehensive review of the computational approaches for structure– property prediction of high entropy materials.High Entropy Alloys & Materials, pages 1–46, 2026

Reference 12

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Observation ad531fcc-0023-4290-9f1c-1d454183efdb · outbound

This paper cites Influence of chemical disorder on energy dissipation and defect evolution in concentrated solid solution alloys.Nature communications, 6(1):8736, 2015.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Influence of chemical disorder on energy dissipation and defect evolution in concentrated solid solution alloys.Nature communications, 6(1):8736, 2015

Reference 13

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Observation 1b714d4d-745d-4cfd-8da0-4fd6d666e539 · outbound

This paper cites Thermoelectric high-entropy alloys with low lattice thermal conductivity.Rsc Advances, 6(57):52164–52170, 2016.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Thermoelectric high-entropy alloys with low lattice thermal conductivity.Rsc Advances, 6(57):52164–52170, 2016

Reference 14

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Observation a0d28fc9-20dc-439a-baf4-8e59eabe5374 · outbound

This paper cites High-entropy alloys with high saturation magnetization, electrical resistivity and malleability.Scientific reports, 3(1):1455, 2013.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys High-entropy alloys with high saturation magnetization, electrical resistivity and malleability.Scientific reports, 3(1):1455, 2013

Reference 15

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Observation 7024aa2f-1c1b-413e-afaf-116bf1140dc5 · outbound

This paper cites Influence of thermomechanical loads on the energetics of precipitation in magnesium aluminum alloys.Acta Materialia, 193:28–39, 2020.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Influence of thermomechanical loads on the energetics of precipitation in magnesium aluminum alloys.Acta Materialia, 193:28–39, 2020

Reference 16

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Observation 611a4f4b-bf5c-4edb-94ff-4c0936360519 · outbound

This paper cites Precipitation during creep in magnesium–aluminum alloys.Continuum Mechanics and Thermodynamics, 33(6):2363–2374, 2021.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Precipitation during creep in magnesium–aluminum alloys.Continuum Mechanics and Thermodynamics, 33(6):2363–2374, 2021

Reference 17

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Observation b300ee9f-b6fb-408c-83e3-ddc0b7979d90 · outbound

This paper cites Effects of the local chemical environment on vacancy diffusion in multi-principal element alloys.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Effects of the local chemical environment on vacancy diffusion in multi-principal element alloys

Reference 18

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Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Unresolved cited work

Reference 19

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Observation c7667320-e258-4752-ac27-47986b8eb16b · outbound

This paper cites Thermodynamics of vacancies and clusters in high-entropy alloys.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Thermodynamics of vacancies and clusters in high-entropy alloys

Reference 20

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This paper cites Rapid precipitation behavior of crmnfeconi high-entropy alloy under electropulsing.Journal of Alloys and Com- pounds, page 189131, 2026.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Rapid precipitation behavior of crmnfeconi high-entropy alloy under electropulsing.Journal of Alloys and Com- pounds, page 189131, 2026

Reference 21

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Observation 1a7ea84a-11e7-408a-98d3-1e24303e164d · outbound

This paper cites Vacancy formation enthalpy in cocrfemnni high-entropy alloy.Scripta Materialia, 176:32–35, 2020.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Vacancy formation enthalpy in cocrfemnni high-entropy alloy.Scripta Materialia, 176:32–35, 2020

Reference 22

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Observation 45557d24-0f98-49ae-bb6a-2e4ac59689f5 · outbound

This paper cites Defect energetics for diffusion in crmnfeconi high- entropy alloy from first-principles calculations.Computational Materials Science, 170:109163, 2019.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Defect energetics for diffusion in crmnfeconi high- entropy alloy from first-principles calculations.Computational Materials Science, 170:109163, 2019

Reference 23

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This paper cites Nasrabadi.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Nasrabadi

Reference 24

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Observation fc4f5e11-4cd4-4401-842e-500a28c5064d · outbound

This paper cites Disentangling diffusion heterogeneity in high-entropy alloys.Acta Materialia, 224:117527, 2022.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Disentangling diffusion heterogeneity in high-entropy alloys.Acta Materialia, 224:117527, 2022

Reference 25

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Observation 836544d0-a0cb-450f-864a-788f19b9495a · outbound

This paper cites Defect energetics in an high-entropy alloy fcc cocrfemnni.Materials Advances, 5(10):4231–4241, 2024.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Defect energetics in an high-entropy alloy fcc cocrfemnni.Materials Advances, 5(10):4231–4241, 2024

Reference 26

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Observation 8717d475-0d10-463c-88cd-6a1276881da2 · outbound

This paper cites Irradiation resistance mechanism of the cocrfemnni equiatomic high-entropy alloy.Scientific reports, 11(1):608, 2021.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Irradiation resistance mechanism of the cocrfemnni equiatomic high-entropy alloy.Scientific reports, 11(1):608, 2021

Reference 27

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This paper cites Ab initio investigation of energetics and stability of vacancy clusters in the fcc high-entropy alloy fecrconi.Journal of Nuclear Materials, 609:155744, 2025.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Ab initio investigation of energetics and stability of vacancy clusters in the fcc high-entropy alloy fecrconi.Journal of Nuclear Materials, 609:155744, 2025

Reference 28

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Observation d2e779c7-ced5-41f9-8286-9daeffb62be8 · outbound

This paper cites Machine learning assisted design of feconicrmn high-entropy alloys with ultra-low hydrogen diffusion coefficients.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Machine learning assisted design of feconicrmn high-entropy alloys with ultra-low hydrogen diffusion coefficients

Reference 29

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Observation b8ac626a-a633-49fa-baa9-44a3eac99d25 · outbound

This paper cites Revealing the crucial role of rough energy landscape on self-diffusion in high-entropy alloys based on machine learning and kinetic monte carlo.Acta Materialia, 234:118051, 2022.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Revealing the crucial role of rough energy landscape on self-diffusion in high-entropy alloys based on machine learning and kinetic monte carlo.Acta Materialia, 234:118051, 2022

Reference 30

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.835566Z digest=sha256:514fa292ba8b8610f6d549a9c530a684119b397bb99d35d461080895df49edc2

Observation 739b6dd4-8261-4518-baa9-2b5a591c1f2d · outbound

This paper cites Framework to completely bypass expensive dft calculations via graph neural networks for vacancy formation energy predictions in fcc high entropy alloys.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Framework to completely bypass expensive dft calculations via graph neural networks for vacancy formation energy predictions in fcc high entropy alloys

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.585692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.840155Z digest=sha256:9c79d677588e1daa7d3b8ac1a99663d41768af0fc64f8f384481533686c8feb9

Observation cd5c48f3-1dd6-45f8-a48e-0d53d4a633a3 · outbound

This paper cites an unresolved cited work.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-10T04:33:04.570177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.844923Z digest=sha256:2458245f902226445cda465bfe8c8f70815fd8f1a837c29631e2d291657983e4

Observation edef843b-a66c-4c11-9f1b-a7a869ff7564 · outbound

This paper cites Electronic structure study regarding the influence of macro- scopic deformations on the vacancy formation energy in aluminum.Mechanics Research Communications, 99:58–63, 2019.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Electronic structure study regarding the influence of macro- scopic deformations on the vacancy formation energy in aluminum.Mechanics Research Communications, 99:58–63, 2019

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.554642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.849467Z digest=sha256:8ab3e853e7494bca413d548218a54af9291752a0cf3f6200c295b291870055a2

Observation 50d1203e-4f3d-4653-a221-c9678d61f45e · outbound

This paper cites John wiley & sons, 1994.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys John wiley & sons, 1994

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.539248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.853995Z digest=sha256:22bad8c3a27fd57c7ec1de77b2ab126097e4a25cd8f188ae10b3366f110d02b3

Observation 016040b9-4a57-4dbc-923d-9ebf7c3d46a7 · outbound

This paper cites Deformation and failure of the crconi medium-entropy alloy subjected to extreme shock loading.Science advances, 9(18):eadf8602, 2023.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Deformation and failure of the crconi medium-entropy alloy subjected to extreme shock loading.Science advances, 9(18):eadf8602, 2023

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.524080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.858947Z digest=sha256:4a333f19d021073dbf7456d634c401dc27c8b32c0ae62799a36520c1cebd308f

Observation 26d67cd4-f2a4-426c-9f3e-9e0cfb23ee03 · outbound

This paper cites Vacancy dependent shock response of high-entropy alloy fenicrcocu.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Vacancy dependent shock response of high-entropy alloy fenicrcocu

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.508653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.863511Z digest=sha256:77e5feeab9f00e5b1dd879d1244f4b32aaf088ae6c667eb2be0753b5c15beba5

Observation 32ab8427-89a5-4e74-891d-9168fa2b78d9 · outbound

This paper cites Role of lattice resistance in the shock dynamics of fcc-structured high entropy alloy.Materials Today Communications, 33:104884, 2022.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Role of lattice resistance in the shock dynamics of fcc-structured high entropy alloy.Materials Today Communications, 33:104884, 2022

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.492817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.868461Z digest=sha256:af79c2bbe07dddabbd4678a8498bf96b1c92050fd1eb825c1fd14bdffed369b8

Observation 5f91a4f7-0c8c-4570-83b9-3f0897b81e8d · outbound

This paper cites Dynamic shock response of high-entropy alloy with elemental anomaly distribution.International Journal of Mechanical Sciences, 253:108408, 2023.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Dynamic shock response of high-entropy alloy with elemental anomaly distribution.International Journal of Mechanical Sciences, 253:108408, 2023

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.477918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.872957Z digest=sha256:91a0ef214e42beac375229ade94ec31aa7aed58e727eef770519ee67a11ac877

Observation d1d8463c-1450-4d28-96eb-163621490344 · outbound

This paper cites Shock compression response of high entropy alloys.Materials Research Letters, 4(4):226–232, 2016.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Shock compression response of high entropy alloys.Materials Research Letters, 4(4):226–232, 2016

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.462296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.877515Z digest=sha256:5ef7a38b1de1af74b48014b0b09144064c058d0a51b190d82b481fd043fe862c

Observation aaacc40b-441f-4f2e-b32f-083ab3615a71 · outbound

This paper cites Estreicher.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Estreicher

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.445331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.882909Z digest=sha256:d712f64bd01274170b6faf355ffaa711a48f3e6b3dea906520fc634983d04dc5

Observation 44f90de9-d821-441a-a6c9-be2d8e550de0 · outbound

This paper cites an unresolved cited work.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-10T04:33:04.429377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.887482Z digest=sha256:f1353fe029973b45b9c026ec4904ec628db83bef0ffcade3aafec2a6833dfad8

Observation 19da8217-c113-4deb-ad90-e1ae8e6b6e78 · outbound

This paper cites an unresolved cited work.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-10T04:33:04.413486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.891997Z digest=sha256:eb12b939572ae85e150ace4b7ed4d8e5395d73d59d426cfc95bd277deda9c270

Observation bdd7a806-bfe3-4b4a-abfc-d832aa8df356 · outbound

This paper cites Defect properties in a vtacrw equiatomic high entropy alloy (hea) with the body centered cubic (bcc) structure.Journal of Materials Science & Technology, 44:133–139, 2020.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Defect properties in a vtacrw equiatomic high entropy alloy (hea) with the body centered cubic (bcc) structure.Journal of Materials Science & Technology, 44:133–139, 2020

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.397266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.896437Z digest=sha256:378b90a7046aa2e43438be1d4f5dcb842e715175703616c6ae5f19fcf460ab86

Observation 2507f21c-cbe7-4ec1-87bc-50740d76a3d1 · outbound

This paper cites Vacancy energetics and diffusivities in the equiatomic multiele- ment nb-mo-ta-w alloy.Materials, 15(15):5468, 2022.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Vacancy energetics and diffusivities in the equiatomic multiele- ment nb-mo-ta-w alloy.Materials, 15(15):5468, 2022

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.380401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.900699Z digest=sha256:a85741829b5b6c239fe445cdc3136a09e551fd6c5e01d75c768102378caf904b

Observation 81feb061-7631-420a-b00b-de125a570e2b · outbound

This paper cites Deep sets.Advances in neural information processing systems, 30, 2017.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Deep sets.Advances in neural information processing systems, 30, 2017

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T04:33:03.905272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:33:03.905272Z digest=sha256:f4891497629719e709a041f9ed62a658694e3c54caac02a65e96707c653634ee

Observation 2f7baad7-0236-4279-ae62-a51335c50786 · outbound

This paper cites Sch¨ utt, Pieter-Jan Kindermans, Huziel E.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Sch¨ utt, Pieter-Jan Kindermans, Huziel E

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.352953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.909851Z digest=sha256:31980e603e0d09751338ab2b3404b2d9cf1d11fe292356b6f28e495c454c5444

Observation 4524d39a-b93f-4623-8d64-fe4f409fa802 · outbound

This paper cites Courier Corporation, 1997.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Courier Corporation, 1997

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T04:33:03.914207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:33:03.914207Z digest=sha256:abe39262dea0aed2e8ecd82a476f732d9eeab0c68b0fa9bdd1be7e9170b8edbf

Observation 584ecbe0-dd7b-4c4b-901e-cb01d983b12a · outbound

This paper cites an unresolved cited work.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-10T04:33:04.325209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.918728Z digest=sha256:8e425cb6da02702804c9468266670deaf9d66a236b57bf08452ca43b204a181b

Observation 344b4769-6ec3-424d-a428-f3a31c87da28 · outbound

This paper cites Manzoor, G.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Manzoor, G

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.308128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.923422Z digest=sha256:0ecdeb9faa7b293d9ef0c0d011b9f76c0ccd1df35c251c3cffb6822e0e45e9df

Observation 96a603ad-dfed-43fb-a5de-5b7e9f3f0cee · outbound

This paper cites an unresolved cited work.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-10T04:33:04.292260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.928803Z digest=sha256:4e533bbe33ecf91c23707080e25ca2bbaf880d72685a5074ea7f971669fea02a

Observation 5e6a1be2-e6d4-40f9-a5b7-50c3dff26756 · outbound

This paper cites Data-inspired atomic environment-dependence of vacancy formation energy in high-entropy alloys.International Journal of Plasticity, 175:104545, 2025.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Data-inspired atomic environment-dependence of vacancy formation energy in high-entropy alloys.International Journal of Plasticity, 175:104545, 2025

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.275961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.933259Z digest=sha256:2fb192850656a52ceb13d222118ae7c7851e6634d677f02b67f58d1e7107a36f

Observation 4900b446-d01a-463f-9b45-8a07f015a076 · outbound

This paper cites Oxford University Press, 2020.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Oxford University Press, 2020

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.260207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.937959Z digest=sha256:2a0eada9db4c87efee3a499ac416f754beff5c19cc170529facfde12e3d9ce1d

Observation 49b16591-4518-4dd2-b67b-1f3272577784 · outbound

This paper cites Order parameter engineering for random sys- tems.High Entropy Alloys & Materials, pages 1–14, 2023.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Order parameter engineering for random sys- tems.High Entropy Alloys & Materials, pages 1–14, 2023

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.243544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.942810Z digest=sha256:9ab321f90258fe173e2f14c7adffe0a923cf6866a486d575d12c97880976f845

Observation 013d28f8-b2db-4185-a4a0-e2ffa9b5d142 · outbound

This paper cites Lammps-a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales.Computer physics communications, 271:108171, 2022.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Lammps-a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales.Computer physics communications, 271:108171, 2022

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-10T04:33:03.947611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:33:03.947611Z digest=sha256:7ae1f585d8bf4fb8adfa6ffd173a28ec09750f82c29034821083a9147b400d12

Observation e9b7ea71-62f8-46d0-a1ba-9022ea8421be · outbound

This paper cites Model interatomic potentials and lattice strain in a high-entropy alloy.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Model interatomic potentials and lattice strain in a high-entropy alloy

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.213381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.952311Z digest=sha256:1f550a67c199b79304772b3fef5e3d333079d6de6a4efe4e854b94119c1e9727

Observation 14c91334-986f-4744-ba0f-b830b8eb965b · outbound

This paper cites Violation of the cauchy–born rule in multi-principal element alloys.Applied Physics Letters, 124(17), 2024.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Violation of the cauchy–born rule in multi-principal element alloys.Applied Physics Letters, 124(17), 2024

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.197757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.956984Z digest=sha256:4115e054e8839cf686e178bc9b4de7e716ffcb0b778bc3d42edad7bc9e8a7912

Observation fb749ce1-9306-4fbf-b1ef-6ce118c9fc8d · outbound

This paper cites Element effects on high-entropy alloy vacancy and heterogeneous lattice distortion subjected to quasi-equilibrium heating.Scientific reports, 9(1):14788, 2019.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Element effects on high-entropy alloy vacancy and heterogeneous lattice distortion subjected to quasi-equilibrium heating.Scientific reports, 9(1):14788, 2019

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.182459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.961494Z digest=sha256:ba0e9237f4d7a143c65563e481cb03fc61bbd9ddacc8b8660108a9f72e4072a9

Observation 484d1104-9996-497c-b7c1-713fab07bf0d · outbound

This paper cites Nitol, Artur Tamm, Subah Mubassira, Shuozhi Xu, and Saryu J.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Nitol, Artur Tamm, Subah Mubassira, Shuozhi Xu, and Saryu J

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.165642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.966171Z digest=sha256:26f1ef26ffb024caf8f3daa98ccbbb35a74e5b110fd165c2c7ccaa05368ef845

Observation 712bd10b-6f7d-4675-a728-e041358d068b · outbound

This paper cites Understanding the phys- ical metallurgy of the cocrfemnni high-entropy alloy: an atomistic simulation study.npj Computational Materials, 4(1):1, 2018.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Understanding the phys- ical metallurgy of the cocrfemnni high-entropy alloy: an atomistic simulation study.npj Computational Materials, 4(1):1, 2018

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.144510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.970972Z digest=sha256:1f686f6e2ec017db1ae4f36af4c169382da8cde2ef0779bfe622686a26d2b8bb

Observation 247ef590-371e-4ca8-8d1c-1194aedad1f9 · outbound

This paper cites Effect of alloying on the thermal-elastic properties of 3d high-entropy alloys.Materials Chemistry and Physics, 210:320–326, 2018.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Effect of alloying on the thermal-elastic properties of 3d high-entropy alloys.Materials Chemistry and Physics, 210:320–326, 2018

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.124443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.975219Z digest=sha256:34a51fb8ad02a1ea4cfe487e640d22ed661f4c552f927479bb7b9107c1c1ac3c

Observation 6298754f-2381-4f84-bd10-ded6650e6aea · outbound

This paper cites Lu, Dianzhong Li, Yiyi Li, C.T.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Lu, Dianzhong Li, Yiyi Li, C.T

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.107671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.980009Z digest=sha256:aca7cbd82f44218870c24e096effa4a3c02d54da6cb60423c0a77a8f75e877c4

Observation 28ecc759-001e-4357-80c4-95c6adf62318 · outbound

This paper cites Frontier: The first exascale supercomputer, 2022.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Frontier: The first exascale supercomputer, 2022

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.092022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T04:33:03.984522Z digest=sha256:ec28d35dc55dcb44e3d2078253eaf57cd6817192d769abcc67f23d1f75a72af3

Observation 90b345e9-2e0b-481f-8b78-b3447e1f7794 · outbound

This paper cites Decoupled Weight Decay Regularization.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Decoupled Weight Decay Regularization

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-10T04:33:03.988826Z

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This paper cites Rectified linear units improve restricted boltzmann machines.

Permutation invariant neural network prediction of vacancy formation under deformation and varying chemical environment in FCC high entropy alloys Rectified linear units improve restricted boltzmann machines

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