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Paper Citation Record · LEDGER

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells

As of 12 August 2026, this Paper Citation Record lists 100 of 112 outbound references and 1 inbound Pith citation observation for arXiv:2510.23514.

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

pith.paper-citation-record.v1
2510.23514 v3

Coverage vector

measured 100 of 112 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T07:56:11.175610Z

measured 101 of 101 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-09T23:29:55.933661Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T14:06:05.203521Z

Reference resolution

100 of 112 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved98
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e6498194-0d78-4dff-af29-772a5a391e7b · outbound

This paper cites Rojsatien, A.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Rojsatien, A

Reference 1

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no resolver link, observed 2026-08-04T07:55:58.723656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:55:58.723656Z digest=sha256:f5cd91683dc60aab8a1701da22f9b9d87e4e2a4921e2ca1e4b46c3347381704d

Observation 6917939c-acd6-4d98-a274-c11e5ecc48ef · outbound

This paper cites Rojsatien, A.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Rojsatien, A

Reference 2

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no resolver link, observed 2026-08-04T07:55:58.775176Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:55:58.775176Z digest=sha256:25895e77715f2bdbf14345d4eb632d323583a36edb4b748fb958cc5c69ac0e70

Observation 235331a3-1fdc-4588-9a4d-dc0fad97d26f · outbound

This paper cites Gloeckler, I.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Gloeckler, I

Reference 3

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no resolver link, observed 2026-08-04T07:55:58.859258Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:55:58.859258Z digest=sha256:dd2c227ce7f93fbb983a03b544ed3e901abd07e1da9f7293599e01711193511e

Observation 1da77622-8ec5-46ea-9ce3-44c6b43c26d5 · outbound

This paper cites Nideep, M.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Nideep, M

Reference 4

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no resolver link, observed 2026-08-04T07:55:58.916107Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:55:58.916107Z digest=sha256:d0424a25d26de50bd27b0a63e315f9fea89bfc40f510f2d9b3000e7684247e23

Observation 7ea3cbc3-d385-4df9-91ff-b7b3ff90f789 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 5

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no resolver link, observed 2026-08-04T07:55:58.970005Z

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source=arxiv_source observed=2026-08-04T07:55:58.970005Z digest=sha256:f55ba05f53e2adc08d18a282a41196c7ab1095235e7720015661c7c99f50ae9d

Observation 93ad7389-872c-401f-a77d-295ae3eddf6a · outbound

This paper cites Freysoldt, B.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Freysoldt, B

Reference 6

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no resolver link, observed 2026-08-04T07:55:59.031181Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:55:59.031181Z digest=sha256:c9101b2b3db5716f397ea4be240a9c98309f0ba0fe3686e7c86275338ca957ec

Observation b36dc7e0-5d9a-4053-b968-ada9878b6823 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 7

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no resolver link, observed 2026-08-04T07:55:59.093510Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:55:59.093510Z digest=sha256:3cc800104c8967f00747123b950c6458f6cea8b1775839d4759543903a550ba4

Observation 53dc1213-f485-472f-a4c5-c6854ee75446 · outbound

This paper cites Mannodi-Kanakkithodi, The devil is in the defects - Nature Physics, 2023, https://www.nature.com/articles/s41567-023-02049-9.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Mannodi-Kanakkithodi, The devil is in the defects - Nature Physics, 2023, https://www.nature.com/articles/s41567-023-02049-9

Reference 8

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no resolver link, observed 2026-08-04T07:55:59.096975Z

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source=arxiv_source observed=2026-08-04T07:55:59.096975Z digest=sha256:3d9f58c66700effceb727a779f75242469c70cba0af19a6f4f2cf2b7759c5094

Observation 7584a72c-9ac7-46e8-a58e-e974fbb3b1a4 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 9

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no resolver link, observed 2026-08-04T07:55:59.170556Z

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source=arxiv_source observed=2026-08-04T07:55:59.170556Z digest=sha256:afa5cef030d0b71dcb4c46ce36002947847aad760fde1218a10b6ce65aa60bc0

Observation 961682b6-b8b6-4dcb-9e8c-2edf7fc5f65e · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 10

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no resolver link, observed 2026-08-04T07:55:59.290769Z

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source=arxiv_source observed=2026-08-04T07:55:59.290769Z digest=sha256:2e753b8c7b0e57b5cc8ffd12300ca5385a954a382b68f200ac82a58a84c80cf7

Observation 236b8814-3290-4e7a-9074-ccb7605a2f60 · outbound

This paper cites Yang, W.-J.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Yang, W.-J

Reference 11

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no resolver link, observed 2026-08-04T07:55:59.391306Z

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source=arxiv_source observed=2026-08-04T07:55:59.391306Z digest=sha256:efe417b08cdf704e4ba6bbfdc08bbcdb131378afc6b643a5f7a9a1dfe8ffca77

Observation a96832ee-654a-4835-bc9d-ed5d1296357a · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 12

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no resolver link, observed 2026-08-04T07:55:59.462769Z

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source=arxiv_source observed=2026-08-04T07:55:59.462769Z digest=sha256:abb516b9301a76e369bec48a11bf781d9bb5426bb6967a13e9323f12bddc57f3

Observation cffbb597-ae4c-4819-9577-a895af5aa970 · outbound

This paper cites Krasikov, A.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Krasikov, A

Reference 13

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no resolver link, observed 2026-08-04T07:55:59.506491Z

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source=arxiv_source observed=2026-08-04T07:55:59.506491Z digest=sha256:decac9313990719c62d946e4a1b10b7c0aca7c28c08e587d31d73407f90e8830

Observation d14b00da-bb12-425f-b7ac-50a2dfbf28f6 · outbound

This paper cites Krasikov, D.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Krasikov, D

Reference 14

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unresolved
no resolver link, observed 2026-08-04T07:55:59.584221Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:55:59.584221Z digest=sha256:70959e329830cd388db83286d7b035cdc8b3503a263bf1113dd0821fd2d1360c

Observation 3263a276-2f15-42c7-a38f-d5dc607a5e4e · outbound

This paper cites Krasikov and I.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Krasikov and I

Reference 15

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unresolved
no resolver link, observed 2026-08-04T07:55:59.635733Z

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source=arxiv_source observed=2026-08-04T07:55:59.635733Z digest=sha256:7c9e1b8e1632766d7393c4113f29bcd56e9ff86404e143937bb964e5aad09b21

Observation bafac310-3cac-4c3e-8d37-3790c132bd3a · outbound

This paper cites Krasikov, Nat.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Krasikov, Nat

Reference 16

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no resolver link, observed 2026-08-04T07:55:59.723951Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:55:59.723951Z digest=sha256:20eb75a8cad03e4ac55e2abf34dc919cdef7854199de2080d2078ee903820769

Observation 0c093aac-b530-4b4a-88c7-e0aaa17d46cd · outbound

This paper cites Ablekim, S.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Ablekim, S

Reference 17

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no resolver link, observed 2026-08-04T07:55:59.852567Z

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source=arxiv_source observed=2026-08-04T07:55:59.852567Z digest=sha256:a80e2b9b3bb9d230f7b1102d0e35bf8065525e0de897eed01b13b94fc8f1fda8

Observation bde98476-413a-4696-bb48-b2f43100e18d · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 18

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no resolver link, observed 2026-08-04T07:56:00.061308Z

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source=arxiv_source observed=2026-08-04T07:56:00.061308Z digest=sha256:498bec1812a8e954350c68795753ea929cfb4fc2246190509de4f1002d32f40e

Observation f2ed5fe4-fd99-4fd9-ab0b-b2f60ce02ffb · outbound

This paper cites Gorai, D.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Gorai, D

Reference 19

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no resolver link, observed 2026-08-04T07:56:00.201702Z

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source=arxiv_source observed=2026-08-04T07:56:00.201702Z digest=sha256:be5f5ace4f80b387ffece00e3390b2abe0cb4b8aa801df2da73c72fdcc399b8b

Observation cb2edfbb-893d-48d1-a20b-be518786d0f5 · outbound

This paper cites De Souza and G.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells De Souza and G

Reference 20

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no resolver link, observed 2026-08-04T07:56:00.416644Z

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source=arxiv_source observed=2026-08-04T07:56:00.416644Z digest=sha256:5447d7e30c396f4475566d87f432cc399b8873399107135ea9ff3ea7a1c96d98

Observation e9679825-8e5d-4785-9d67-70997bf770ab · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 21

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no resolver link, observed 2026-08-04T07:56:00.630660Z

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source=arxiv_source observed=2026-08-04T07:56:00.630660Z digest=sha256:d3accfe62e580b6649d7b908c6aeab1f397c51ca678fda6ffc142ccb457e54e9

Observation 59f53a42-0872-44d7-978e-21ea458491e5 · outbound

This paper cites Wickramaratne, C.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Wickramaratne, C

Reference 22

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no resolver link, observed 2026-08-04T07:56:00.741705Z

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source=arxiv_source observed=2026-08-04T07:56:00.741705Z digest=sha256:1e5f4b40e526e2e462b8f54efaf82b8c5e5b6173131213219461810a371349b3

Observation 4fa268d0-db6e-43a7-b7c0-f4b5ac76ff75 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 23

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no resolver link, observed 2026-08-04T07:56:00.871257Z

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source=arxiv_source observed=2026-08-04T07:56:00.871257Z digest=sha256:1dbc4199e73c005fae0ff069db467a49e0aa1cff3bac1c17230c4b03d5af8926

Observation d45007a7-1976-4104-97c7-5e1f749a9c75 · outbound

This paper cites Broberg, K.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Broberg, K

Reference 24

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source=arxiv_source observed=2026-08-04T07:56:00.936320Z digest=sha256:59c71ba24eb0466a9e68c376aa6945a02c71300511ca257dbcebbd7fa381a43c

Observation 03d500d3-bcf4-4dba-9f39-a901f7f8c6cc · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 25

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no resolver link, observed 2026-08-04T07:56:01.009201Z

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source=arxiv_source observed=2026-08-04T07:56:01.009201Z digest=sha256:5dcae693212703b41cef2d2109d157ce994951c00c63828203dc4a2d7e0df048

Observation 15a998f1-1bab-4c21-9906-539e2796724c · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 26

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no resolver link, observed 2026-08-04T07:56:01.078295Z

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source=arxiv_source observed=2026-08-04T07:56:01.078295Z digest=sha256:97dc54fef01ca6f88a2597ffb340cbe7ddbbca2b80cc01b4fdb0be45fb42aa44

Observation debf1a1c-a8b5-40c6-8cb1-83c1253b1d7d · outbound

This paper cites Grill and A.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Grill and A

Reference 27

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no resolver link, observed 2026-08-04T07:56:01.228225Z

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source=arxiv_source observed=2026-08-04T07:56:01.228225Z digest=sha256:ea8e9c5818a501cad8057019a4f49bad43f2093d1a0285351ddf4de72222ae85

Observation b2e2359a-8e13-495a-a686-8fc6b86c33b6 · outbound

This paper cites Buckeridge, Computer Physics Communications, 2019, 244, 329–342.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Buckeridge, Computer Physics Communications, 2019, 244, 329–342

Reference 28

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no resolver link, observed 2026-08-04T07:56:01.310139Z

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source=arxiv_source observed=2026-08-04T07:56:01.310139Z digest=sha256:7d0a27e36c2b78fe2ab3ed66fdb2866c785e4b3517d26db1f851fb6948919ea9

Observation d6b244a6-fbb3-4ac8-8514-608f654e3589 · outbound

This paper cites Mannodi-Kanakkithodi, X.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Mannodi-Kanakkithodi, X

Reference 29

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no resolver link, observed 2026-08-04T07:56:01.478375Z

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source=arxiv_source observed=2026-08-04T07:56:01.478375Z digest=sha256:013d1bdbe14b8b891477ef74edfd3c0f6f31cbb1a0a21a222b5ef13bceca6994

Observation 043047d0-83f7-4035-af9a-7a9514f784ff · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 30

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no resolver link, observed 2026-08-04T07:56:01.558140Z

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source=arxiv_source observed=2026-08-04T07:56:01.558140Z digest=sha256:4ad06e8879a591b051095d3a4f9f5d8d9e30363e549e87eaf4454183ffbb4216

Observation f29471b6-bd2f-464c-8c15-c8bf9508b159 · outbound

This paper cites Mannodi-Kanakkithodi, J.-S.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Mannodi-Kanakkithodi, J.-S

Reference 31

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no resolver link, observed 2026-08-04T07:56:01.660129Z

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source=arxiv_source observed=2026-08-04T07:56:01.660129Z digest=sha256:c6d72544c4152e70e7ee2fb4149b5bbc02d43ce916710e2ff20725c7e1edd69e

Observation 79aa4b0c-f988-4e96-983e-53d144d0eed5 · outbound

This paper cites Kim, J.-S.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Kim, J.-S

Reference 32

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no resolver link, observed 2026-08-04T07:56:01.803914Z

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source=arxiv_source observed=2026-08-04T07:56:01.803914Z digest=sha256:3a436352bb1909d19fc1ede997869a7336725ecf9f2d927a8dab88578639c221

Observation 84f5576d-f6fc-40f4-b373-edae6c6c4b9c · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 33

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no resolver link, observed 2026-08-04T07:56:01.931319Z

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source=arxiv_source observed=2026-08-04T07:56:01.931319Z digest=sha256:c50dc20390c73a5b54a4ac761dfd3264be4ce6a778e9f7cd0f00e6794da098b7

Observation 9c3f6067-d79f-459d-b23e-4be2bfe57fd5 · outbound

This paper cites Machín and F.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Machín and F

Reference 34

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no resolver link, observed 2026-08-04T07:56:02.074335Z

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source=arxiv_source observed=2026-08-04T07:56:02.074335Z digest=sha256:3dba24d7221fc1cd510c504cbd39d73b2f08ae5f5f986f92a7b6dde2a594e994

Observation 3f104fdc-6dfc-4c07-9f08-6790d9a77af8 · outbound

This paper cites Mosquera-Lois, J.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Mosquera-Lois, J

Reference 35

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no resolver link, observed 2026-08-04T07:56:02.227361Z

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source=arxiv_source observed=2026-08-04T07:56:02.227361Z digest=sha256:1661979fb21bd48a34a3cde785710d267b58cfad0a5d23c62c1b0e36fb8e66cf

Observation 0919f31e-dd6d-4d02-9335-6186c9022245 · outbound

This paper cites Mosquera-Lois, S.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Mosquera-Lois, S

Reference 36

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no resolver link, observed 2026-08-04T07:56:02.397519Z

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source=arxiv_source observed=2026-08-04T07:56:02.397519Z digest=sha256:13fd1c5d90af269ed2eb6b4f9472a52e130adb6f15218e4ad3383157b4fac581

Observation e879c16c-6de2-4d1e-9a93-587d9515b50f · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 37

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no resolver link, observed 2026-08-04T07:56:02.540297Z

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source=arxiv_source observed=2026-08-04T07:56:02.540297Z digest=sha256:97eef2047976f41a9649a16428722afd101b73c1842cf1b5f41b7afd224afe7f

Observation ce01ae0e-20a3-4088-bc7a-7c556744edd4 · outbound

This paper cites Mannodi-Kanakkithodi and M.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Mannodi-Kanakkithodi and M

Reference 38

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no resolver link, observed 2026-08-04T07:56:02.768578Z

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source=arxiv_source observed=2026-08-04T07:56:02.768578Z digest=sha256:91ca8b930df7212a738b56afba8252c4104b1ca2e5e7a2c20ca41cc69ddae880

Observation d14614cd-f9eb-4c46-af91-45d9220b2e4b · outbound

This paper cites Xie and J.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Xie and J

Reference 39

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no resolver link, observed 2026-08-04T07:56:02.963632Z

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source=arxiv_source observed=2026-08-04T07:56:02.963632Z digest=sha256:661b7f3f3050bb0274e5522a0a98769426a24958ab1a4c9155706c74f2675c2d

Observation 1f142167-39aa-4dcf-adaa-8d1f8653f1a4 · outbound

This paper cites Choudhary and B.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Choudhary and B

Reference 40

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no resolver link, observed 2026-08-04T07:56:03.141811Z

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source=arxiv_source observed=2026-08-04T07:56:03.141811Z digest=sha256:3213dad821b1560c64bf756a7e81f2a2ed2ef3b24b89ce09b903d1987ac8964d

Observation 87978213-6f93-4353-b45a-313e1980a935 · outbound

This paper cites Supervised Community Detection with Line Graph Neural Networks.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Supervised Community Detection with Line Graph Neural Networks

Reference 41

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no resolver link, observed 2026-08-04T07:56:03.276793Z

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source=arxiv_source observed=2026-08-04T07:56:03.276793Z digest=sha256:598daa11f9fd6d7714812dedeb903f686823fd3963a6727d522c815b95f1bf71

Observation b8da61d6-a836-4d1b-b3dd-666e5b07cffc · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Semi-Supervised Classification with Graph Convolutional Networks

Reference 42

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no resolver link, observed 2026-08-04T07:56:03.417156Z

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source=arxiv_source observed=2026-08-04T07:56:03.417156Z digest=sha256:2fbb1efa9cf2e9332c466f8141de364a63faad953ac165c5b01c70b1d5ee2265

Observation b1ead7c5-61f8-4773-95f9-5cdf28719003 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 43

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no resolver link, observed 2026-08-04T07:56:03.503004Z

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source=arxiv_source observed=2026-08-04T07:56:03.503004Z digest=sha256:d9c502c5c157a3904b71c3331eab2077bcea4880ad758598a258aa62348c5912

Observation 1239c01c-c2ba-4d30-b92b-6aa20969e1c4 · outbound

This paper cites Chen and S.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Chen and S

Reference 44

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no resolver link, observed 2026-08-04T07:56:03.625264Z

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source=arxiv_source observed=2026-08-04T07:56:03.625264Z digest=sha256:7fc70dd1fe3cb2ae6cc21b71df631efb5c884a2615823ae6cb4aa1eab63e13cf

Observation 8725826b-324f-41ab-9584-a160173b99dd · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 45

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no resolver link, observed 2026-08-04T07:56:03.812783Z

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source=arxiv_source observed=2026-08-04T07:56:03.812783Z digest=sha256:2365ed2e573897b820dfc8a0a6f06f4704f47dce43669c7544510c64ee64156f

Observation d1f85a5e-6278-4dd4-b38b-304ab62e0ca1 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 46

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no resolver link, observed 2026-08-04T07:56:03.943962Z

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source=arxiv_source observed=2026-08-04T07:56:03.943962Z digest=sha256:608177d103e91bcb758d09d08ad285e77dde569ec99f3c2e38b366853e072c93

Observation 6436b7b0-7e71-4f13-97d6-73475956e86a · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 47

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no resolver link, observed 2026-08-04T07:56:04.154019Z

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source=arxiv_source observed=2026-08-04T07:56:04.154019Z digest=sha256:e138a190bcc1e229db13e39da4893c6669bb6cbf43e29780aa3299d94c046fdf

Observation 09163633-5cfb-4daa-bdbe-12799571583b · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 48

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no resolver link, observed 2026-08-04T07:56:04.240409Z

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source=arxiv_source observed=2026-08-04T07:56:04.240409Z digest=sha256:325a266cdd343baae363b854fe63a66eddf94a59b9145c2b9de91e866cfe3e34

Observation 05d4eafe-3a84-4e01-9c88-4afddfa50b65 · outbound

This paper cites Borlido, J.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Borlido, J

Reference 49

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no resolver link, observed 2026-08-04T07:56:04.367898Z

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source=arxiv_source observed=2026-08-04T07:56:04.367898Z digest=sha256:48a07194e583a8bcafbab7e23cf19d80d2268a89d2397b51e9c38121e5bf1872

Observation 945f687e-7938-41a6-b8d3-df2551cbed47 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 50

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no resolver link, observed 2026-08-04T07:56:04.459684Z

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source=arxiv_source observed=2026-08-04T07:56:04.459684Z digest=sha256:013e4c2ddc7149357a02c1c0b6480ba0420a037fcd954c96c8e889d172e16069

Observation 2fc66d46-c36d-437d-b29b-1860853a5d5b · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 51

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no resolver link, observed 2026-08-04T07:56:04.563302Z

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source=arxiv_source observed=2026-08-04T07:56:04.563302Z digest=sha256:7022278cd6a7ce0b2a0e61a937a8fe7792f6186d69945503ea70da9dfc533393

Observation 6a9ee433-04a9-4615-a36f-412ff8ee9e78 · outbound

This paper cites Menéndez‐Proupin, M.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Menéndez‐Proupin, M

Reference 52

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no resolver link, observed 2026-08-04T07:56:04.665935Z

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source=arxiv_source observed=2026-08-04T07:56:04.665935Z digest=sha256:9ab3395fcea0f93cde943947b8c03a598ea2205838240b8dda279506d79e9274

Observation 6933bc88-779a-4c47-9fa5-ca3113fedb87 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 53

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no resolver link, observed 2026-08-04T07:56:04.834454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:56:04.834454Z digest=sha256:899548dc5fb9db7c5ac41c5ee8b66a48a385e9f4f6ec485884fffd6b6597b6a9

Observation 83f28045-6cf8-4276-b7b3-22d4b0ed4ddb · outbound

This paper cites de Melo, M.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells de Melo, M

Reference 54

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no resolver link, observed 2026-08-04T07:56:04.980926Z

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source=arxiv_source observed=2026-08-04T07:56:04.980926Z digest=sha256:c645e18f5e5714ee8483d01fbcc46d3156e481b98a0020f8112f56acdee617bd

Observation 16831941-25f7-49fa-a869-279f86ecdc66 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 55

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no resolver link, observed 2026-08-04T07:56:05.084063Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-04T07:56:05.084063Z digest=sha256:36e0f314cb59267460e5e2d9ed39b7131260aaf18789ccbe3cc397c2732e96f1

Observation 90ccf0fb-a93a-478c-a9a9-18164fdf63f6 · outbound

This paper cites Chen, C.-Y.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Chen, C.-Y

Reference 56

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no resolver link, observed 2026-08-04T07:56:05.275591Z

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source=arxiv_source observed=2026-08-04T07:56:05.275591Z digest=sha256:c70670cd0dbaff596a445bd5ec9953d2d7bf369328c4154b90404aee15d120f3

Observation 3ff275e5-b25b-496f-a6cc-e1581b071152 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 57

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no resolver link, observed 2026-08-04T07:56:05.465010Z

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source=arxiv_source observed=2026-08-04T07:56:05.465010Z digest=sha256:13c530741e43258b2768f4d4b995d36242437bcca66a2de0d9803e482587a122

Observation 87d2c10c-410b-4347-8f53-388499b1efb6 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 58

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unresolved
no resolver link, observed 2026-08-04T07:56:05.637528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:56:05.637528Z digest=sha256:094703ddba70a0995e7a0563217e77f355be2d782716e78b5518ab1916cb452e

Observation 29c51965-c57e-4d04-8b54-222eacc42a23 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 59

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no resolver link, observed 2026-08-04T07:56:05.798291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:56:05.798291Z digest=sha256:52c251ed14713ab932276ca4fa5806f79c6031694bc830a635b2d00debcedf42

Observation 34ca4869-e48a-47a4-926b-cbb57589bc82 · outbound

This paper cites Zheng, E.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Zheng, E

Reference 60

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no resolver link, observed 2026-08-04T07:56:05.982620Z

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source=arxiv_source observed=2026-08-04T07:56:05.982620Z digest=sha256:e00179dfa506307096e5b8ed6a68d796c48d084335df292c4d28ce6561b05c03

Observation ed10211f-79b6-4a82-9dc5-5d5152674a29 · outbound

This paper cites Wardak, W.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Wardak, W

Reference 61

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no resolver link, observed 2026-08-04T07:56:06.258560Z

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source=arxiv_source observed=2026-08-04T07:56:06.258560Z digest=sha256:3d29e91a51cde7ec88b0a869d73075f145a4c81cd59d845b141f18e4eb179e21

Observation 70b886c0-83ce-4e1f-9e56-d8c011bc022f · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 62

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no resolver link, observed 2026-08-04T07:56:06.390061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:56:06.390061Z digest=sha256:d92ac2d9c5d441c6b6b358ca4ae761a99fb83105750a2050ec05442af68680b3

Observation a6ced590-90b7-4572-9e7c-13e7e03ddac8 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 63

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no resolver link, observed 2026-08-04T07:56:06.472171Z

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source=arxiv_source observed=2026-08-04T07:56:06.472171Z digest=sha256:8876e9c4f5a26dbbe37f4acb6c5e26e4cf845e99ed2f7d4f25ad418598d8aed1

Observation b2df4b5d-8d77-4a67-a9d7-bccebdbd18dc · outbound

This paper cites Huang, S.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Huang, S

Reference 64

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no resolver link, observed 2026-08-04T07:56:06.562722Z

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source=arxiv_source observed=2026-08-04T07:56:06.562722Z digest=sha256:de8b465bcf4014d6db2ac9362588bc225a124ea4cb9e4e70ca2c4bf40d59ca0b

Observation 1fdaf37d-e3aa-43e8-9fe1-af120b326fa0 · outbound

This paper cites Bidaud, J.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Bidaud, J

Reference 65

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verified exact
doi, observed 2026-08-04T07:58:31.448630Z

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=arxiv_source observed=2026-08-04T07:56:06.631528Z digest=sha256:6747d3aab360c33dba114b5262ebc79d1f81c7424afcc8da1512c09dbfb5ff9b

Observation 2304fa8d-1507-4179-b80c-150a87bc7324 · outbound

This paper cites Shi and M.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Shi and M

Reference 66

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no resolver link, observed 2026-08-04T07:56:06.821862Z

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source=arxiv_source observed=2026-08-04T07:56:06.821862Z digest=sha256:34a3eeacae6ebf3671306e34421c7b74a5fbbe658be12b338031020393164a74

Observation b5905f16-b775-4454-9231-a14cce1df955 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 67

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no resolver link, observed 2026-08-04T07:56:06.973174Z

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source=arxiv_source observed=2026-08-04T07:56:06.973174Z digest=sha256:ff4460ba1b26aea6db23558d9627643c3ef54053309c2f6d5508243c61184591

Observation 539214ef-e807-45a6-aa51-f987d325db8e · outbound

This paper cites Manna, H.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Manna, H

Reference 68

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no resolver link, observed 2026-08-04T07:56:07.095225Z

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source=arxiv_source observed=2026-08-04T07:56:07.095225Z digest=sha256:9aa27d7a749b4c6f249aa711f90dbe72dd161d75f145de32ed91e1448ffc3a87

Observation 4fda2db1-934c-4e41-8fa4-b14b7b1009fc · outbound

This paper cites Cheng, C.-L.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Cheng, C.-L

Reference 69

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no resolver link, observed 2026-08-04T07:56:07.256582Z

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source=arxiv_source observed=2026-08-04T07:56:07.256582Z digest=sha256:ff9f010b3b04b18a534c4443841098568481518d185aee383a49e2f2b1fc0ffc

Observation f8ecb4bd-08e0-4c23-93af-7be00e7f012b · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 70

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no resolver link, observed 2026-08-04T07:56:07.434593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:56:07.434593Z digest=sha256:afcc233e4e60ff28f683508621e68816399030c709a60baed0e4b8ca6356c902

Observation b055460c-1319-4370-bd28-90459fa83823 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 71

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no resolver link, observed 2026-08-04T07:56:07.647801Z

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source=arxiv_source observed=2026-08-04T07:56:07.647801Z digest=sha256:2dc5dd9f8733004e8673ca379e89ade3312d38e0e08d77d087686fdb2ccee494

Observation 1f204c8d-7710-4a14-b097-13f53c79228c · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 72

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no resolver link, observed 2026-08-04T07:56:07.878849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:56:07.878849Z digest=sha256:0de6b2afd244413f2f06168f3ada889f9b87a8c8eca5535c1fea812415e5b5fe

Observation e7b09cf8-daa8-4e33-8700-0eaf59173c08 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 73

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no resolver link, observed 2026-08-04T07:56:07.972765Z

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source=arxiv_source observed=2026-08-04T07:56:07.972765Z digest=sha256:1dec3a011f86b0466335fda5861b34b0fe0f15dfe20f39fcef5705b5f72fd3c7

Observation 67c72505-1df2-4ee5-b3e5-be0ae632bd69 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 74

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:56:08.031677Z digest=sha256:b5093d1c1c6e1d67d56945694ef76158fc273e0802a1ae55b01b31ee55019c52

Observation 8a3ea9b5-aa61-49a9-a063-77ca2641efe6 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 75

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no resolver link, observed 2026-08-04T07:56:08.150929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:56:08.150929Z digest=sha256:fcb50460835ed7ed52fd873acd581b0954dbde849e65a9f4ae91aecdc328afc3

Observation dc1cc667-f0c0-4214-b686-d951f04f7ffa · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 76

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verified exact
doi, observed 2026-08-04T07:58:31.273305Z

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=arxiv_source observed=2026-08-04T07:56:08.309852Z digest=sha256:82765986014dbc6a964b20f4377ff58b4b6bfd9931eae70085c243fc5016b44a

Observation 9834ed13-847f-4a5b-bc76-7aac2941f2f1 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 77

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no resolver link, observed 2026-08-04T07:56:08.388254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:56:08.388254Z digest=sha256:4b7ccd656b8bc3368a4f7ec2983b02ba344f03ee2d4a813efcb24f56219fc5c0

Observation 1f566a06-cd2d-4387-b24b-602875a4c6c4 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 78

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no resolver link, observed 2026-08-04T07:56:08.493458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:56:08.493458Z digest=sha256:e9e770244bae51983f3fe6f9fcc90c27e477bde400571674b5e0b212f753760a

Observation 0d4895c9-88a3-4e87-8f12-c49619ac5be3 · outbound

This paper cites Bapst, T.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Bapst, T

Reference 79

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unresolved
no resolver link, observed 2026-08-04T07:56:08.635546Z

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source=arxiv_source observed=2026-08-04T07:56:08.635546Z digest=sha256:0b3cc23016560aa77813dccac406c021efd6b875b52a4319cc531e772dc3794a

Observation 0dec3c14-9c7f-4132-bda9-44ed1f724073 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 80

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source=arxiv_source observed=2026-08-04T07:56:08.740994Z digest=sha256:36919085149258f32bb291e4905b9dc99ff533bdb3e4a5aca4727b396450ae8b

Observation d66ab43f-13bc-49c4-9536-e87d1a3cff29 · outbound

This paper cites Battaglia, A.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Battaglia, A

Reference 81

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source=arxiv_source observed=2026-08-04T07:56:08.810648Z digest=sha256:a7c835ad94bb396eb0213a8e9dcce4907fdf37e9c9f7a8f667579be87b63b2fd

Observation 1befa377-c522-4245-a37d-7c5374423586 · outbound

This paper cites Mannodi-Kanakkithodi, Modelling and Simulation in Materials Science and Engineering, 2022, 30, 044001.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Mannodi-Kanakkithodi, Modelling and Simulation in Materials Science and Engineering, 2022, 30, 044001

Reference 82

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source=arxiv_source observed=2026-08-04T07:56:08.904908Z digest=sha256:2123f4b8ee69c66aba732db180dab0596173a64516183cb3b30f36c3a5766bcb

Observation 9aed2452-d7ef-4904-b935-f98acfc57978 · outbound

This paper cites Mannodi-Kanakkithodi, M.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Mannodi-Kanakkithodi, M

Reference 83

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source=arxiv_source observed=2026-08-04T07:56:09.054752Z digest=sha256:39b92f8959d7a69fc36cdbfa297e202d4b5438130813949d684f4af7147cd728

Observation b397d466-0408-4669-8bb5-1f011975a1a7 · outbound

This paper cites Zunger, S.-h.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Zunger, S.-h

Reference 84

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source=arxiv_source observed=2026-08-04T07:56:09.213989Z digest=sha256:9426e989cbc6eb662f0ed159af6484c4fdc962ba9a2696dd5ba336329362df2c

Observation 48aaf5f5-8ee1-4c31-bbde-b803dc29ae0a · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 85

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source=arxiv_source observed=2026-08-04T07:56:09.277464Z digest=sha256:de82cf02e764a9f83668adda11e245e03418097a39f4cf7ef5a94b9800293d09

Observation 4e265115-f1d3-435e-ac68-13e59c930e18 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 86

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source=arxiv_source observed=2026-08-04T07:56:09.456028Z digest=sha256:09e3b15ed41938b65feeaa8b44c8795f758ce677e3d7bfeb65b6f8d006b3b9c4

Observation 6b408153-6c04-4f01-8ae9-b43329f5c701 · outbound

This paper cites Choudhary and B.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Choudhary and B

Reference 87

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source=arxiv_source observed=2026-08-04T07:56:09.568273Z digest=sha256:c522459ef5fee58a24ebea0ad42ba4660101fb6e5b105c3ee9ff0ad13157e125

Observation bbf02945-98a5-4951-8452-3a6a994def3a · outbound

This paper cites Mosquera-Lois, S.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Mosquera-Lois, S

Reference 88

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source=arxiv_source observed=2026-08-04T07:56:09.717033Z digest=sha256:51db490434817e67a5def7af15ed88e9d812d396bc9b79cf43cd61118e912884

Observation 657b1905-8c55-466e-91d2-2bef10e1a50d · outbound

This paper cites Choudhary, B.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Choudhary, B

Reference 89

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source=arxiv_source observed=2026-08-04T07:56:09.827071Z digest=sha256:a61119686531e5077ab3355f8065b553e4aa47a532e68d1b627a4f5f6358be30

Observation 8339e3d9-19f3-4f41-b980-47259a85fcfe · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 90

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source=arxiv_source observed=2026-08-04T07:56:09.970524Z digest=sha256:0af89d53a0c12e4b4b33fd4110a959d040213a554c2692d719823e77c5a5d546

Observation dd4e8405-a526-47a4-8a0a-cb7b679b8275 · outbound

This paper cites Cheng, C.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Cheng, C

Reference 91

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source=arxiv_source observed=2026-08-04T07:56:10.055862Z digest=sha256:cc57e4dfe537d410444f861dbc9c1ea3d9ecd31ca1435a02b4200a1c49c71c8a

Observation f5519dba-d1f4-4c76-8c4a-2cc37079a7c7 · outbound

This paper cites Lee and R.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Lee and R

Reference 92

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source=arxiv_source observed=2026-08-04T07:56:10.156168Z digest=sha256:5ce22421fbeec43e40592121f607fe64612c866cea104eba6e8f206bed4809d6

Observation 6bade3ec-9eb8-4e72-93fb-4faa001b34c4 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 93

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source=arxiv_source observed=2026-08-04T07:56:10.223000Z digest=sha256:ba931fbd9ddd314180e2c68639a067f64f4631bf74866ada4c6365e11e4901aa

Observation 27d425e8-c115-427f-b198-03470b1f7503 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 94

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source=arxiv_source observed=2026-08-04T07:56:10.314350Z digest=sha256:b27a609a75bd86e4047bd2e783fdc3cb7f813886e0e66b1ff2ca29ebfad329a8

Observation 60aab817-edbe-4731-83c6-8656b33e5416 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 95

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source=arxiv_source observed=2026-08-04T07:56:10.451718Z digest=sha256:bbc1420a6117cf87bd8ac1023ff1e1ba002babcb18e55c96ed4097835cb9dcfc

Observation 602ed70a-3557-4544-ae91-469a6642c3e0 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 96

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source=arxiv_source observed=2026-08-04T07:56:10.660650Z digest=sha256:1e0d322470885808a39521fa9dc5118a36c0b0fe60235730f86a88a880681819

Observation b76f122e-354d-4831-affb-6e672a86039f · outbound

This paper cites Ščajev, M.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Ščajev, M

Reference 97

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source=arxiv_source observed=2026-08-04T07:56:10.739358Z digest=sha256:aef6e4b452960e925d2b800a2d1ab5de58f5f7500af5b3cee81ed19b88643010

Observation 74e7535b-42ee-4e55-985a-744658307638 · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 98

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source=arxiv_source observed=2026-08-04T07:56:10.897161Z digest=sha256:4578211a8c835191f0af9aeb35332ef8ca850cb3d9e07cb124aeba96d370f92f

Observation b6402bd7-3fff-4fe6-bee4-9584811977eb · outbound

This paper cites Mahoney, C.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Mahoney, C

Reference 99

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no resolver link, observed 2026-08-04T07:56:11.034757Z

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source=arxiv_source observed=2026-08-04T07:56:11.034757Z digest=sha256:845652c8b4e6a42713800d36a2cc5bf0bda3ee9a8e75e56fb65525e940acb1db

Observation 003bb17d-2cbb-42df-be4a-e12bbe347e1a · outbound

This paper cites an unresolved cited work.

DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells Unresolved cited work

Reference 100

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source=arxiv_source observed=2026-08-04T07:56:11.175610Z digest=sha256:3b0b600cd7dbdc9c1f04aac54876dd8d3026cbe8f4c7fde373bbfa36d7dc5ec5

Pith citing papers

Observation 30c6b661-3aa6-4254-a28f-dcf9fe20b59b · inbound

Accelerating point defect simulations using data-driven and machine learning approaches cites this paper.

Accelerating point defect simulations using data-driven and machine learning approaches DeFecT-FF: a machine learning force field framework for high throughput defect modeling in CdTe-based solar cells

Reference 97

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verified exact
arxiv_id, observed 2026-05-26T02:03:04.649519Z

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=2026-05-09T23:29:55.933661Z digest=sha256:5c5d49ff1b4764e5f4807c7afa13927d284b5da32aa01bc925fa6716f1b40b9c