Pith. sign in

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

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2608.07445 v1

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T04:33:03.993670Z

measured 64 of 64 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

64 of 64 outbound references displayed

  • verified exact0
  • verified fuzzy52
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:05.087875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.653006Z digest=sha256:502701aa973aa7920a23281df0d0c974b2f456a04e3f77a4be3e66bd53d4bbd1

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:05.072189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.663010Z digest=sha256:91de4ff9fac729a002a899ee00b7e8f8ea7e2cc9114687817f562ec1db365b76

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:05.056155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.672510Z digest=sha256:e0035acc0349c653b9f846710c3988751b5f2918e897bcfc7afa8a92c8a0361f

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:05.040573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.678405Z digest=sha256:b0dece0154a69800721e49b0b26bbe0618e92cb456ca8bbf706ff0b25778e610

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

Resolution
unresolved
raw_fallback, observed 2026-08-10T04:33:05.024978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.683975Z digest=sha256:285b776cf40fceb070965e6b91aa617b106632b531ea09eb9319b760f04c06e7

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:05.009725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.693692Z digest=sha256:d452cec5d0a8032b5808b52bb66fe411994a943bbff9dd9cbd55ddc2fd169243

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.994064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.703395Z digest=sha256:eb00d88096b118b61457fc76c768d428c3d837603a06f358b6213ffd5864a1bd

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.979087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.708366Z digest=sha256:50ade023c218308820568d55fd96220dc1da546e48ad16bf5ce6a712d54bf5fa

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.964565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.713757Z digest=sha256:93a91fdff0d7235bd82c766026876edebdec6700555bd6de1dac19152beb10ae

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.949482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.720129Z digest=sha256:c8c49a7717f1b7a2e42a5effc831eba02ee31502563c1a00c6ecb4e1cea0e87e

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.932330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.727298Z digest=sha256:8f346fbfab483de631df6a365bbfe90760ec59c0f2f10a85643d51a12cdc344e

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.914644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.733491Z digest=sha256:8e7e600285ccac11d3ac9eb7288c628a5c2f15472ceff9013f5e7d4ffe4ad266

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.896362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.745577Z digest=sha256:e9458c9742aef93d740991ce50dfbc05ae8e7570806c3fce328daa6d04d2666e

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.877710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.758785Z digest=sha256:2f2fe18b4335469579fd941852eb068c0d5cd2dd1ff07712478513e745d089f8

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.852790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.765231Z digest=sha256:1325c927ae16f26cbdde1c5e3ef871f1664eb24017fb305329dc8c62ad4f0630

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.823193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.770275Z digest=sha256:04f1e6035721ebcc5348a0a29bed0c846853056407fe2b339e2a60efda7b495d

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.804111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.774965Z digest=sha256:dae8d927b205565d479446893e663f7f3b117ccc58673d01e5a05eea9624a2fd

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

Resolution
unresolved
no resolver link, observed 2026-08-10T04:33:03.779722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:33:03.779722Z digest=sha256:de6750e20e920141c84e412c840443ce6cbd531f80e22557e2d44f9b403a5e05

Observation 5483ecd8-4359-4144-830f-13b29545a6f8 · 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 19

Resolution
unresolved
raw_fallback, observed 2026-08-10T04:33:04.785318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.784697Z digest=sha256:07a2f5c4f47bf960b30a52857952559caafed51b8a4671f23f0571cf6ac8f67b

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.767221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.789183Z digest=sha256:953fd33fde4eb25db3eae4c6bd36f4561894f9f655f930b6eb9597e4bc9eaea7

Observation ca812579-bbf7-4caf-b2bc-96c1cb877b27 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.747964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.794199Z digest=sha256:dbb6b507ea597c6fd3274fe34f91fd9215001c05c9cceb0807a3699382abe125

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.729535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.798928Z digest=sha256:44332b954bdb218fbd98f0bb8c65f231fec39016bb91d8d80638eb60981cfaf7

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.712917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.803592Z digest=sha256:b00e001c1c073abf3db7d03a235a83f2fda8049a2f770c475d0720374f73f6dc

Observation 568940f5-2e27-4176-8794-9d7d4aec7af9 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.696228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.808229Z digest=sha256:83e86b567e6605ab6b776f547fceca7d5b515c196e760dc38e9dc912dcc33ab8

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.679654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.812677Z digest=sha256:ea38ed4f4ec6b3ca0f861571c0fc5afc04f8eb08f79e63a200b77b768a825e72

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.665258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.817115Z digest=sha256:a86fe523eca28c70ff36113b8d0f607907248015ea15c8567dd212b0c59f9b5a

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.650798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.821451Z digest=sha256:e7281de55f3baf7ea44f22c2541e3dbeb396ba3fa44d559ae1b3c87057e0d022

Observation 3c0e98ab-903a-4708-96ef-163e5337f280 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.634836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.826491Z digest=sha256:78a089fe797df75efd5be9afda73bb11fa382471ab6e8ab5ff9517edf865e607

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.616686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.831155Z digest=sha256:b3012a35f18bf611a2095ad3894bbadd989c3a6fb5de6ffa638a03a17ac50324

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.600381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.835566Z digest=sha256:5ca292cc577fe48501df4e38701956757760abac56b350e78d616e2b458ceed4

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.840155Z digest=sha256:4780ea9a3b6ada5e612eb3d9f8af4161f0dc3e0782e152cb7092519759805808

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.844923Z digest=sha256:fd16fae441d85b273ba1928fc04d9e5cd6c9fded66f1429925fdde2f39110aa0

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.849467Z digest=sha256:6843fd82685eee25031981746f951c1562f8b8a0f47b990a911b20ce96c0d5c6

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

Resolution
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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.853995Z digest=sha256:6edb4f5be46a97794d722038160a5ab13f8c37b1430db1fcad17f696deb566ca

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.858947Z digest=sha256:3aaed0f0ca16be8286d2aeb15fd528f69a336571c100e7843f7da3622e43e690

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.863511Z digest=sha256:b651f08e632e44edbb25aa573e91ac1a5c3e75ae3ff55c6275de06f6cc971b56

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.868461Z digest=sha256:8262a9cb3e00e36cebc31cab1eaddfce82e72bfa55d81b9ac870699b5b0e7a1d

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.872957Z digest=sha256:9c5205afeda881d0e8145fd992a1d3fc813d047908b4bd9076ee789b31824dde

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.877515Z digest=sha256:17d24ae55ece86998e6b2995410f8e232399bab9aa29564ba33aaeb08564f255

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.882909Z digest=sha256:959d04237f7e4a79408d89930ab1852c26ff69e50ca1e5230542fc7aa0b286b7

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.887482Z digest=sha256:8b36b03670e819c1c9856d010416f417874db1f6f9aa79bf918f20ae9cc2d298

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.891997Z digest=sha256:f4cc14de9716151cdf3c4386e45be507fa8be19195e1d0f948eed909338428eb

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.896437Z digest=sha256:84337500ad0c5624833d8065b522a58980420dd2d40d93fd0f5c8de8b1b07c6a

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.900699Z digest=sha256:6a0f773f6b596c5e2b01ca10bf652f7e9794e40161bd7129a997d85c1376ad72

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:f7532e84f9bdf6d8f3cb3ee735b55fdb15eb8c0984d1160aed73ee03174f144b

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.909851Z digest=sha256:b52d3591ada5128d3b48d6eecf99c63edfa169dbba2d6b82c4ae28bfc00974a7

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=sha256:37a47f61762e9696a83e06cd9786ae8bed495029540047673405742a90051a80

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.918728Z digest=sha256:81d2f3dd4aa0c86339fc5dcf172f84b9a64f556fc5a7c9875422f2dade2576f9

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.923422Z digest=sha256:fac95c8958e5c965500446d4527b467a67d443e7963f6d2c0e97173efcc0c734

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.928803Z digest=sha256:17da0aff02d0ba82c6bb55022ea2c12ebc91f980175dc83d4b5a8025f99dbee4

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.933259Z digest=sha256:52bdd15c417db9be4ac01ba92692cdefd4d795f4ee3734c48688b28666d039f7

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.937959Z digest=sha256:922d2a6d6cfed049d104c10337cf25d4a2e0f82f4492a2ac83bcd0d58893c3ee

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.942810Z digest=sha256:2b96f0c96f0c8668f09d5442b9749ae04e050c087a71fd5ec4dc7d21e896c01a

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=sha256:841f6a176abeb8bad7cfdb98f7b67f80de18429e958630e1f32bfb9050465b19

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.952311Z digest=sha256:84f18bf5d928b5383c7ef7e839bb50185af0a1f88690749f8c88c2c6fcc3fe2c

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.956984Z digest=sha256:1bd90d2f21dfd226f9e9b6acf6b99efded1e7438a6f2f009cc52dc48c69e6ac3

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.961494Z digest=sha256:1b75e60e2a23edc19ad227bbc72d939d001243096b14eb9080b54725582774c8

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.966171Z digest=sha256:0c3f880422e344eae4d199151385852c8c7c05db0a0c5d879a4d9b5b79211522

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.970972Z digest=sha256:f807ff7fa791230da58f09cb5c669b8dc542599bcac9f7fc022a74e3974faba5

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.975219Z digest=sha256:717e8644127c61076c2aa69e2e46dc443c674cc1616429ddaf6e3bf49f050dee

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.980009Z digest=sha256:e3976299a9bd3abf577d92264dcfb949d72b645e76661977d75eab981b3579ab

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.984522Z digest=sha256:0a29e7db3c764de7a788cbeb94962e7624cb27855668868fee403a6892e7d363

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:33:03.988826Z digest=sha256:6ec36a0da6f5e9293e4af402f03e21905b2bfaaab5161f43e450d24f8fe4d1cf

Observation 84ab5ad5-03ac-49cf-b4cb-66f8c47cc252 · outbound

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

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:33:04.075343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T04:33:03.993670Z digest=sha256:b6b0755aa4c524380704cb76c2c186f5e76c8731c0590c2fb80ee927f68030ae

Pith citing papers

No inbound Pith citation observations are available.