Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires | Paper Citation Record

Observation 1ab22581-a987-435a-bc64-cadc5f3ea07c · outbound

This paper cites This result is consistent with the strong representation of bulk crystalline environments in the pretraining data.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires This result is consistent with the strong representation of bulk crystalline environments in the pretraining data

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:32.350311Z

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Observation 970f0f58-898e-4462-8bd1-a175738135bc · outbound

This paper cites The zero-shot models pro- vide the closest overall agreement with the DFT disper- sion, with phonon eigenvalue RMSEs of 0.785 THz for MACE and 0.540 THz for ORB.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires The zero-shot models pro- vide the closest overall agreement with the DFT disper- sion, with phonon eigenvalue RMSEs of 0.785 THz for MACE and 0.540 THz for ORB

Reference 2

Resolution: malformed identifier; raw_fallback, observed 2026-08-10T22:59:32.335653Z

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Observation ad327c81-42d3-4b74-9a23-5ddd7b25bcfc · outbound

This paper cites For MACE, fine-tuning gives the lowest mean relative surface-energy error, ap- proximately 3.08%, compared with 3.33% for training from scratch and 16.14% for zero-shot inference.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires For MACE, fine-tuning gives the lowest mean relative surface-energy error, ap- proximately 3.08%, compared with 3.33% for training from scratch and 16.14% for zero-shot inference

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:32.319856Z

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Observation 9824c6f5-a88c-4b31-876e-445f69207f72 · outbound

This paper cites RMSD is used to identify structural drift relative to the initial configuration after removing rigid translation and rotation.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires RMSD is used to identify structural drift relative to the initial configuration after removing rigid translation and rotation

Reference 4

Resolution: verified exact; doi, observed 2026-08-10T22:59:32.303132Z

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Observation bccc37b9-9d3c-4f87-8d1e-b900c2bbf708 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:32.285207Z

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Observation da3a786f-7098-42b6-8b15-da997c580178 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:32.268878Z

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Observation 8da83faf-ad55-4982-be8f-9629e93e84ba · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:30.849481Z

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Observation 1911f13a-6f2f-463d-9feb-be90a95f62cc · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:32.253632Z

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Observation ff976d93-e229-4ff8-9e1b-13985eac39da · outbound

This paper cites Mishin, Machine-learning interatomic potentials for materials science, Acta Materialia 214, 116980 (2021).

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Mishin, Machine-learning interatomic potentials for materials science, Acta Materialia 214, 116980 (2021)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:32.237835Z

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Observation 14a0382b-4d83-4ae3-b0ec-fd1430fe02e6 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:32.221012Z

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Observation f193275f-e9ce-4a30-b3b2-4eba26520b2d · outbound

This paper cites Batzner, A.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Batzner, A

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:30.871765Z

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Observation e9cab222-bc4e-4ecf-8970-fa1b1bc1d3a7 · outbound

This paper cites Batatia, D.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Batatia, D

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:32.203708Z

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Observation 7ce98d15-daa1-44c9-945e-e2eb64210452 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:30.881499Z

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Observation a2cf5e00-4afa-41ff-a136-a59c78ff4c3e · outbound

This paper cites Chen and S.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Chen and S

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:30.886365Z

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Observation 7678cee0-99ac-410f-bb84-c28d1fb78542 · outbound

This paper cites Musaelian, S.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Musaelian, S

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:30.891650Z

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Observation 1e4fe7d9-ecb9-4626-9226-da0c33c45f99 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:32.167369Z

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Observation 29373873-4a2d-44b2-83f1-eeaededb2522 · outbound

This paper cites Creed, T.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Creed, T

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:32.150728Z

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Observation e55e6072-d3f1-48f6-b6a0-3ba73e42a01a · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:32.134258Z

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Observation ea3bb9b9-1385-4b65-9cfb-44f1c3cc277d · outbound

This paper cites Schmidt, T.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Schmidt, T

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:32.118266Z

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Observation c5116394-f48d-4e77-b270-025c19681a72 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:32.102117Z

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Observation 62891514-00d5-4d28-a6ae-977aead0f3c9 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:32.086066Z

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Observation cbe71f71-2fa4-4a5f-9491-75aff8ba657c · outbound

This paper cites Benedini, A.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Benedini, A

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:32.069810Z

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Observation c357090d-838d-4819-a661-b3f7ff206ece · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:30.934098Z

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Observation d86d4fda-7de4-46f5-9b1a-da94fec26722 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:32.052927Z

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Observation e583d7ca-bc6a-415e-967f-43ab4a8e7827 · outbound

This paper cites Pa¸ sca, H.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Pa¸ sca, H

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:32.037356Z

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Observation dafbae1c-3d42-48d7-b9eb-711f0bafe6fe · outbound

This paper cites Verdi, F.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Verdi, F

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:32.019797Z

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Observation cd3c9277-a91e-48e7-b784-6ae2f74bf512 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:32.003538Z

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Observation 0890349c-2821-4c86-909e-77030290dd99 · outbound

This paper cites Zhang, G.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Zhang, G

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.987243Z

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Observation 8729b15c-9732-45a5-9449-e28e1273362f · outbound

This paper cites Focassio, T.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Focassio, T

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.968825Z

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Observation 8ff40de7-0a8a-4ce3-a248-8c71bea0dc1e · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:31.952359Z

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Observation 5e06acf5-44b6-4a05-8f2e-d191f063ad0d · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:31.934466Z

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Observation 912fe7f7-b122-43f0-b078-83d0ba657620 · outbound

This paper cites Rumiantsev, M.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Rumiantsev, M

Reference 33

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Observation 2b4f97b1-1d80-49ad-b239-e1c111e84d76 · outbound

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Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:31.917931Z

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Observation 1c50dcfc-ed04-4ec2-92e7-24557ee885d2 · outbound

This paper cites Kim and B.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Kim and B

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.902823Z

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Observation 03e3f915-1554-4ae4-ab1e-feddaa53bf7d · outbound

This paper cites Cheng, Latent ewald summation for machine learning of long-range interactions, npj Computational Materials 11, 10.1038/s41524-025-01577-7 (2025).

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Cheng, Latent ewald summation for machine learning of long-range interactions, npj Computational Materials 11, 10.1038/s41524-025-01577-7 (2025)

Reference 36

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Observation 45094081-ff5e-4eb9-aa37-aaec40a07259 · outbound

This paper cites Kabylda, J.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Kabylda, J

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.887486Z

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Observation 2c60d399-b78a-4535-8a69-546ebbd799d5 · outbound

This paper cites Batatia, W.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Batatia, W

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.871627Z

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Observation e3233d9d-6683-4623-a3d1-ef394a00b0e7 · outbound

This paper cites Riebesell, R.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Riebesell, R

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:31.007122Z

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Observation 7f922c8c-7ddf-477b-b14a-6f90fd8d87a9 · outbound

This paper cites Maxson, A.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Maxson, A

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.847083Z

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Observation 65e104ba-2f57-4c34-9876-6ae83c819f3f · outbound

This paper cites Jacobs, D.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Jacobs, D

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.832885Z

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Observation 85cff09c-a078-4d63-9b10-79dc823d5b8c · outbound

This paper cites Focassio, L.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Focassio, L

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.818635Z

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Observation d69df198-b59c-4140-af37-f6954e099b11 · outbound

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Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 43

Resolution: verified exact; doi, observed 2026-08-10T22:59:31.303932Z

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Observation a72d6d41-d665-4940-914c-094f47c19105 · outbound

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Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 44

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:31.802958Z

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Observation 11418b62-8e3e-4ecc-9a4e-ba005bc8d447 · outbound

This paper cites Huang, B.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Huang, B

Reference 45

Resolution: malformed identifier; doi_truncated, observed 2026-08-10T22:59:31.289176Z

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Observation d3575652-1c75-46bf-89ab-0452f3e7213e · outbound

This paper cites Alampara, M.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Alampara, M

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.787229Z

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Observation a5f2e2a7-f124-4e19-88f0-a6ac68994cd3 · outbound

This paper cites Iftimie, P.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Iftimie, P

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.770811Z

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Observation 7e2abdc2-a691-4d8f-bab4-9b5cae638c3d · outbound

This paper cites Zanineli, S.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Zanineli, S

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.757207Z

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Observation 9a0d0fd9-ed7b-43d6-8e41-3838536f9ef0 · outbound

This paper cites Hjorth Larsen, J.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Hjorth Larsen, J

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.743215Z

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Observation d1deaf0e-48d5-42a3-aa60-2bb5cfb1e398 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 50

Resolution: malformed identifier; doi_truncated, observed 2026-08-10T22:59:31.273630Z

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Observation d97ee20e-6511-4906-babf-29525208bef7 · outbound

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Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:31.711242Z

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Observation 4f35c36f-f267-40a8-aea2-dc58460b36ad · outbound

This paper cites Pokluda, M.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Pokluda, M

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.695828Z

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Observation c1fad4ce-bcb3-4c60-b440-879b6d64ee97 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:31.680819Z

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Observation 14a5bafb-319c-4375-8c05-5858c5de501d · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:31.664687Z

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Observation bd975911-1011-4b60-84a1-5d3621b9dd7f · outbound

This paper cites Zhang, A.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Zhang, A

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:31.094414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b547f269-847a-4940-aab0-bd2f30e22cda · outbound

This paper cites Bochkarev, Y.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Bochkarev, Y

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:31.099114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 008bd161-a00e-4708-b44e-1eee21e624ed · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:31.648503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2708a574-e352-45c3-84cc-7e8f24c88746 · outbound

This paper cites Batatia, P.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Batatia, P

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:31.109322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4752444-1808-4e22-b1af-7b06298359e4 · outbound

This paper cites Rhodes, S.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Rhodes, S

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.611074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d30e3667-0854-4be9-9802-a8f5f6c3d9d1 · outbound

This paper cites Gubaev, V.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Gubaev, V

Reference 62

Resolution: verified exact; doi, observed 2026-08-10T22:59:31.238644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dd5618f9-601a-4b68-ad37-eb8f69ce6bf4 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:31.595330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 11ee05b1-ba49-4027-82f9-f9c6e44fe285 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:31.134663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 984c17a6-881e-4936-a702-f9ceca22d0e1 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:31.579280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2116cb50-d401-4df9-bb2e-f4f81a19acb8 · outbound

This paper cites Kloppenburg, L.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Kloppenburg, L

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.562083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fd74790d-f96c-49a9-8138-3ffeda9d3f3c · outbound

This paper cites Cross-Geometry Transferability Assessment of Foundation Machine Learning Interatomic Potentials: From bulk materials to atomic nanowires.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Cross-Geometry Transferability Assessment of Foundation Machine Learning Interatomic Potentials: From bulk materials to atomic nanowires

Reference 67

Resolution: malformed identifier; raw_fallback, observed 2026-08-10T22:59:31.546534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2aa2b39a-5a98-4cec-bd52-068c35649cdb · outbound

This paper cites Batatia, P.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Batatia, P

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:31.154553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1669cb96-de79-4522-b525-e35ecf3e5c48 · outbound

This paper cites Neumann, J.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Neumann, J

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:31.159312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44c822dd-e961-47dc-a66f-b2cfe8341d9b · outbound

This paper cites Rhodes, S.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Rhodes, S

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.520129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d5139a70-92f0-4711-8ca2-d09ebe052276 · outbound

This paper cites Gardner, graph-pes: train and use graph-based ml models of potential energy surfaces (2024).

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Gardner, graph-pes: train and use graph-based ml models of potential energy surfaces (2024)

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.727147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 44fd775e-fbf8-4569-9ecd-3111b70e96f1 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 72

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:59:31.503742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ab84c892-3a87-4eb2-83f9-9abb3d8232c5 · outbound

This paper cites an unresolved cited work.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Unresolved cited work

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:31.178496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4153c873-c234-437e-bdfd-bd3549a84aae · outbound

This paper cites Hjorth Larsen, J.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Hjorth Larsen, J

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.486962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5f0e77ad-b446-4528-a3a2-263a3353b29c · outbound

This paper cites Focassio, T.

Cross-Geometry Transferability Assessment of Universal Machine Learning Interatomic Potentials: From Bulk Materials to Atomic Nanowires Focassio, T

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:31.471194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers