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Paper Citation Record · LEDGER

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential

As of 19 August 2026, this Paper Citation Record lists 93 of 93 outbound references and 1 inbound Pith citation observation for arXiv:2509.00322.

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

pith.paper-citation-record.v1
2509.00322 v1

Coverage vector

measured 93 of 93 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:48:39.272461Z

measured 94 of 94 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T16:17:26.963678Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

93 of 93 outbound references displayed

  • verified exact2
  • verified fuzzy67
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation e96a9008-f547-4afa-95f8-883a1fd7e1e1 · outbound

This paper cites ACS Catal.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential ACS Catal

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:29.510259Z digest=sha256:71253e41e9000fecf18ee4e245a8abfdffdef82371abe1e09f6b653244d51662

Observation 1f690e10-21fa-486b-b56e-699d2e4b70da · outbound

This paper cites Catalytic conversion of ethanol and iso-propanol over ZnO -treated Co3O4 / Al2O3 solids.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Catalytic conversion of ethanol and iso-propanol over ZnO -treated Co3O4 / Al2O3 solids

Reference 2

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no resolver link, observed 2026-08-05T13:48:29.672273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:29.672273Z digest=sha256:9c4e35336cc7dd21c589bda4d27245223a7077f59d71176a65cbc251acde21a2

Observation 0e611f22-a835-4e12-bf64-ab74eab55a67 · outbound

This paper cites C.; others Selective electrooxidation of 2-propanol on Pt nanoparticles supported on Co3O4 : an in-situ study on atomically defined model systems.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential C.; others Selective electrooxidation of 2-propanol on Pt nanoparticles supported on Co3O4 : an in-situ study on atomically defined model systems

Reference 3

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no resolver link, observed 2026-08-05T13:48:29.777661Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-05T13:48:29.777661Z digest=sha256:b391915f58a11b63d186734b53ec5b513a01a37442b7ee81070ff8f40bf8db4f

Observation 83c5e1e3-fc3a-4d8e-a003-d13c0546f2ca · outbound

This paper cites H.; Bera, A.; Bullert, D.; Linke, M.; Salamon, S.; Webers, S.; Wende, H.; Hasselbrink, E.; Spohr, E.; Kenmoe, S.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential H.; Bera, A.; Bullert, D.; Linke, M.; Salamon, S.; Webers, S.; Wende, H.; Hasselbrink, E.; Spohr, E.; Kenmoe, S

Reference 4

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no resolver link, observed 2026-08-05T13:48:29.864355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:29.864355Z digest=sha256:7c9de241aba780737073e5310c6f5753ba9485a64171c32d6cce383380aa8ac0

Observation 3ccbe066-030c-40bb-9dcf-be772bd28e1b · outbound

This paper cites an unresolved cited work.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Unresolved cited work

Reference 5

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no resolver link, observed 2026-08-05T13:48:30.005904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:30.005904Z digest=sha256:1a33290c696d89b71968acd70e507ea997f0f3bce94da9baaafc04e76e63c2e7

Observation fac34eb3-114a-4e9f-9941-24551e63a311 · outbound

This paper cites H.; Nono, K.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential H.; Nono, K

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-05T13:48:30.132657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:30.132657Z digest=sha256:44d7273f52104ad5c145c2d811fa870aa8bbe1990b7dfccdc8a3c7d5aad7fcd9

Observation 626089c6-77d2-48bd-8ea9-49555f4f48b2 · outbound

This paper cites Influence of temperature, surface composition and electrochemical environment on 2-propanol decomposition at the Co3O4 (001)/ H2O interface.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Influence of temperature, surface composition and electrochemical environment on 2-propanol decomposition at the Co3O4 (001)/ H2O interface

Reference 7

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no resolver link, observed 2026-08-05T13:48:30.274795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:30.274795Z digest=sha256:c3acae17eb0dd9a0f26e13828a067bc283f556a69727435c6e230dfb4e0891f0

Observation d298b4c3-7dca-4b18-ba7c-b683e09b1226 · outbound

This paper cites H.; Raji, A.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential H.; Raji, A

Reference 8

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no resolver link, observed 2026-08-05T13:48:30.427232Z

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source=arxiv_source observed=2026-08-05T13:48:30.427232Z digest=sha256:8cb25b44fa34499627e5454e9d6d537e01216bc4c368837f4bb30506f0aa578e

Observation 33793d4c-552a-43c5-8bc6-0ef3003a1a1e · outbound

This paper cites H.; Kenmoe, S.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential H.; Kenmoe, S

Reference 9

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no resolver link, observed 2026-08-05T13:48:30.605772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:30.605772Z digest=sha256:0d0f1acd4101db59a3c2ee5124f2f8f3a82f77d985d7ee1f9bdb17d6b0cda999

Observation bc971fc7-855d-426c-a525-293acea4126c · outbound

This paper cites u ker, J.; Weidenthaler, C.; Ortega, K. F.; Behrens, M.; T \.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential u ker, J.; Weidenthaler, C.; Ortega, K. F.; Behrens, M.; T \

Reference 10

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no resolver link, observed 2026-08-05T13:48:30.728455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:30.728455Z digest=sha256:96847f6459efb03e1ffe101b54b8e20df1bb5c483fd8f330e27223a4156179df

Observation 31501e40-3cfc-4ef5-a756-643a0219ede2 · outbound

This paper cites I.; Najafpour, M.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential I.; Najafpour, M

Reference 11

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unresolved
no resolver link, observed 2026-08-05T13:48:30.894529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:30.894529Z digest=sha256:0bcc3f0859166737bc970daa9d77fd7934a8552f4a82153572f3268b81d2f537

Observation f7e292d7-4e28-41be-bf79-91ceef1de8fd · outbound

This paper cites Nanostructured cobalt oxide clusters in mesoporous silica as efficient oxygen-evolving catalysts.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Nanostructured cobalt oxide clusters in mesoporous silica as efficient oxygen-evolving catalysts

Reference 12

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unresolved
no resolver link, observed 2026-08-05T13:48:30.978915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:30.978915Z digest=sha256:fc57e1a1cdd512e9073ac18a6d7d919426db1fa65273f1f5e37b81a452008689

Observation 43123b4b-4f37-449a-ae46-be371f144899 · outbound

This paper cites Selective synthesis of Co3O4 nanocrystal with different shape and crystal plane effect on catalytic property for methane combustion.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Selective synthesis of Co3O4 nanocrystal with different shape and crystal plane effect on catalytic property for methane combustion

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T13:48:31.132367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:31.132367Z digest=sha256:317aa5a80bc20235c9073c8ea4ac5af426bf4abba7f714095c66dc1aa13eb103

Observation 432afa6c-a59d-4957-af34-1340d32aab83 · outbound

This paper cites Low-temperature oxidation of CO catalysed by Co3O4 nanorods.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Low-temperature oxidation of CO catalysed by Co3O4 nanorods

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:31.207459Z digest=sha256:8fafc5538a9d883711d001d44c1774d0d9296c96cbcca00e2494b6fb3925cff8

Observation c192ba4d-f9cb-4ed8-baf9-083aed7245ac · outbound

This paper cites Co3O4 nanomaterials in lithium-ion batteries and gas sensors.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Co3O4 nanomaterials in lithium-ion batteries and gas sensors

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:31.336282Z digest=sha256:68dc2190ec6cca641b1437faaa97b006ea58244a592a28328b60150d7d5cdcf5

Observation 62283cc2-4e81-4e3a-89ce-3938bcc4e2e3 · outbound

This paper cites J.; Brummel, O.; Libuda, J.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential J.; Brummel, O.; Libuda, J

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:31.494025Z digest=sha256:6d3e5f9a8a93911a0d903bfd41fef4d86966439f8add5d74d4a532ff457a4610

Observation e92a6f4f-2943-4b75-8c98-ea6dabcbf565 · outbound

This paper cites K.; Hartwig, J.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential K.; Hartwig, J

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-05T13:48:55.965690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:31.645668Z digest=sha256:27251be08285ee60a9b6b96d232f2727188d4b7282edfe92226e72dec2358163

Observation b80acf84-d90b-43d8-ba12-328e62db7c32 · outbound

This paper cites J.; Busca, G.; Lorenzelli, V.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential J.; Busca, G.; Lorenzelli, V

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:55.810327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:31.806509Z digest=sha256:2e2c3568640ad7b19d406b2bba69006aa9d27084690c106e1826a40dcfeafdf1

Observation 48a65dee-89cf-4ef2-b7b1-8263e61f78d8 · outbound

This paper cites Structural origin: water deactivates metal oxides to CO oxidation and promotes low-temperature CO oxidation with metals.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Structural origin: water deactivates metal oxides to CO oxidation and promotes low-temperature CO oxidation with metals

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-05T13:48:55.607875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:31.929931Z digest=sha256:668925f22fd0fd40e1896477f845e851cebdbb7303aa54a08ca4741ba5e9d99a

Observation a92057e2-98ab-4bc3-90a3-9653e93ae81a · outbound

This paper cites J.; Sojka, Z.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential J.; Sojka, Z

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-05T13:48:55.452235Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.103132Z digest=sha256:facd889a973ca945269910429f8aec2d30e3ef08894642d72e1238bbde1a3f66

Observation 5d7b3f5c-65be-4757-af92-5f9c4b92f109 · outbound

This paper cites an unresolved cited work.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Unresolved cited work

Reference 21

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raw_fallback, observed 2026-08-05T13:48:55.271918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.300322Z digest=sha256:6fdc0ea795e0fba4c36b57a7c2494051a74bbf21960c94a1a0b10e1a120525ca

Observation fd8aef3e-8151-4947-a706-e07c55c94843 · outbound

This paper cites C.; Matolin, V.; others Structure-dependent dissociation of water on cobalt oxide.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential C.; Matolin, V.; others Structure-dependent dissociation of water on cobalt oxide

Reference 22

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raw_fallback, observed 2026-08-05T13:48:55.104281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.361852Z digest=sha256:52f2795064d433e67d7f4c97fe53dfcff9897345c8c674edf3108ec9074726a5

Observation 1c277c57-1f7d-4252-a107-8ab30f7e044b · outbound

This paper cites Impact of Highly Concentrated Alkaline Treatment on Mesostructured Cobalt Oxide for the Oxygen Evolution Reaction.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Impact of Highly Concentrated Alkaline Treatment on Mesostructured Cobalt Oxide for the Oxygen Evolution Reaction

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-05T13:48:54.934916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.492301Z digest=sha256:c5c01df5b833899c39d9e9ea560ff1625b53b992c499ee7a898f7be37309852e

Observation 1e8e4452-bb53-44db-abfd-734228ddc6a0 · outbound

This paper cites an unresolved cited work.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Unresolved cited work

Reference 24

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unresolved
raw_fallback, observed 2026-08-05T13:48:54.708143Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.672103Z digest=sha256:db70d8ab36ceb351f35edd883da862690781b786b47cf38033614d7f55d2ceb5

Observation 660cba36-5ebb-4dfc-8f3f-a2b47a21372f · outbound

This paper cites an unresolved cited work.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:48:54.514075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.837268Z digest=sha256:8d2f00cd4b778d13b2dca6e2bb2a9d4164092e59396af40712b389ededd68e0a

Observation 3daaa5fb-15c2-4fdf-8944-e977d60a7c91 · outbound

This paper cites ChemCatChem 2024, 16, e202400988.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential ChemCatChem 2024, 16, e202400988

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:54.352874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.987753Z digest=sha256:a7c26fbb95189b60a46d366635c152678d65e923f318426766f9e34127cece58

Observation d868994b-a5e7-46ab-b8c6-cf9edbf80dc7 · outbound

This paper cites ACS Catal.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential ACS Catal

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:54.129356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.118538Z digest=sha256:1fc499ad60e14c8c9cfaae37b42ad1b472b5322669d590b260a9e8b83d90910a

Observation 913797b7-69f0-40a9-9ff0-c91538de4ea6 · outbound

This paper cites an unresolved cited work.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Unresolved cited work

Reference 28

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unresolved
raw_fallback, observed 2026-08-05T13:48:53.911293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.231377Z digest=sha256:cf86f4d23573effb3c74187807584a2c42c3543de08ebc0a6d7b66cbe71202d8

Observation d756e365-bf88-49fa-9b24-7bdc25f94bc5 · outbound

This paper cites Hydroxylation of an ultrathin Co3O4 (111) film on Ir (100) studied by in situ ambient pressure XPS and DFT.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Hydroxylation of an ultrathin Co3O4 (111) film on Ir (100) studied by in situ ambient pressure XPS and DFT

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:53.704714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.401890Z digest=sha256:3065b92deb93e9e5acfb16a08e72fe694d3b5afd21be714724752ec02405f046

Observation 237dcfad-13ec-4f89-ad68-84ff7a5e0d51 · outbound

This paper cites V.; Ptasinska, S.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential V.; Ptasinska, S

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:53.550790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.505089Z digest=sha256:a915ba5ad942053c952694640d0e4e3d15a5a477e552bcc736178fe826bd9fb8

Observation 9ec62d07-3acc-4a1e-a877-ad786858a095 · outbound

This paper cites B.; Saddeler, S.; Schumacher, S.; Aiyappa, H.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential B.; Saddeler, S.; Schumacher, S.; Aiyappa, H

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:53.343352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.593364Z digest=sha256:611083d38ded743776a5569b358ddd3b2aebb33229158983b4aaf043928cefe9

Observation 21fa5529-d5a9-4c01-821f-45f1487f6058 · outbound

This paper cites Water adsorption and oxidation at the Co3O4 (110) surface.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Water adsorption and oxidation at the Co3O4 (110) surface

Reference 32

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raw_fallback, observed 2026-08-05T13:48:53.250619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.714532Z digest=sha256:724f9c2057bbbb489c571749311d6a99513a7a8fed0dfab553c5d091b2b7f879

Observation 0425c0a6-98f1-4d52-8e0b-b41cc7163f3b · outbound

This paper cites A.; Kotomin, E.; Akilbekov, A.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential A.; Kotomin, E.; Akilbekov, A

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-05T13:48:53.001846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.801121Z digest=sha256:6d8d3393b4700a12a5e78d6d3016eea16cb6775e4cecfa71f45cb9d7444319ec

Observation a9bfa9e6-c844-4409-8e68-acac88df348d · outbound

This paper cites Surface structure of Co3O4 (111) under reactive gas-phase environments.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Surface structure of Co3O4 (111) under reactive gas-phase environments

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:52.675156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.876861Z digest=sha256:eeb237e025e8dd61eea0673f9230445e5d30e88d2c01cc473a195f89fa3932d6

Observation de110d4f-c868-46c8-b8be-d9cdde2a8f83 · outbound

This paper cites Water on oxide surfaces: a triaqua surface coordination complex on Co3O4 (111).

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Water on oxide surfaces: a triaqua surface coordination complex on Co3O4 (111)

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:52.436607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.935839Z digest=sha256:3fe378386dbc7e55b7d2a5f8a3fc669f1be6eee3ce87189914b1238d7e01c237

Observation 43a74327-e06b-41d8-b716-b9f3218b611a · outbound

This paper cites A DFT investigation on surface and defect modulation of the Co3O4 catalyst for efficient oxygen evolution reaction.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential A DFT investigation on surface and defect modulation of the Co3O4 catalyst for efficient oxygen evolution reaction

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:52.153643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.027931Z digest=sha256:8954f9f3052cb340519be811fb5fc7ae3484eb7f8d61e2c400592f01f331b03b

Observation 440304e8-47f0-4804-9345-1965e525b4af · outbound

This paper cites Influence of Fe and Ni doping on the OER performance at the Co3O4 (001) surface: insights from DFT+U calculations.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Influence of Fe and Ni doping on the OER performance at the Co3O4 (001) surface: insights from DFT+U calculations

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:51.892868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.115676Z digest=sha256:17d4982fec7d26cb87b19101cb8e8efd1866cc0b23e89005281c09713ab87807

Observation c2056eb0-2c13-483b-aa8a-ab6aab2ff69a · outbound

This paper cites Impact of solvation on the structure and reactivity of the Co _3 O _4 (001)/H _2 O interface: Insights from molecular dynamics simulations.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Impact of solvation on the structure and reactivity of the Co _3 O _4 (001)/H _2 O interface: Insights from molecular dynamics simulations

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:51.634278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.173708Z digest=sha256:f080ebc34404bfaa86b22440e3bd20dbd13058ce9791d43393d1e5b0ef4cab67

Observation 708fe189-d8c1-494f-b390-1dab0701c875 · outbound

This paper cites R.; Pezzotti, S.; Gaigeot, M.-P.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential R.; Pezzotti, S.; Gaigeot, M.-P

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:51.325342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.239149Z digest=sha256:0fdd58c915cecf46816817a0d96a80e656059d783ded2200016cfc81fe031a2f

Observation 834e0b9e-cb1e-4b0e-90e4-bee57ec4460c · outbound

This paper cites Co _3 O _4 (111) surfaces in contact with water: molecular dynamics study of the surface chemistry and structure at room temperature.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Co _3 O _4 (111) surfaces in contact with water: molecular dynamics study of the surface chemistry and structure at room temperature

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:51.056706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.287063Z digest=sha256:7c7817e3eb2dc88e932958d1f128a6d1d5a54ed39b1c99ae7ad111144c00d717

Observation 2308bf28-60af-4117-af81-c715458dda1c · outbound

This paper cites Perspective: Machine Learning Potentials for Atomistic Simulations.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Perspective: Machine Learning Potentials for Atomistic Simulations

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:50.743527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.338095Z digest=sha256:124afa2327e6419cced19b0ef622e1dd79ed128776e2aaadc13ef82edad8386a

Observation ea9ce1ab-6806-4b13-be98-85b5650e4e18 · outbound

This paper cites L.; Caro, M.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential L.; Caro, M

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:50.563408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.402875Z digest=sha256:8b73ac8ae00ebe136d2dc01890088a5ce72b0a34dda8983a9bb73c0bab02d6aa

Observation 3ce1fd3c-1497-4295-bd2a-9a89b9fe0c13 · outbound

This paper cites u tt, K. T.; Tkatchenko, A.; M \.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential u tt, K. T.; Tkatchenko, A.; M \

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:50.384355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.461966Z digest=sha256:c34b20b2c5e85ba5d58d85ff86b57d78e70e0d0656eda3c97719bf91352db566

Observation 5d1392ef-286b-4bf2-9091-d514c935728a · outbound

This paper cites Machine-learned potentials for next-generation matter simulations.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Machine-learned potentials for next-generation matter simulations

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:50.115520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.534569Z digest=sha256:ccf962cc8e50b4d2641ffe65056dad760db1038ddc1fbc1ccfcda51c6a225589

Observation aac2cf36-b830-4c0e-81ef-99cc3bea1c14 · outbound

This paper cites W.; Behler, J.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential W.; Behler, J

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:49.799271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.599804Z digest=sha256:00b9357bb32749a9a7c898386386e2af15dc592e439dd408675fb0f7283cc703

Observation fbec4a3a-3de3-412f-be2d-7767d59f2ab4 · outbound

This paper cites Improving Molecular-Dynamics Simulations for Solid--Liquid Interfaces with Machine-Learning Interatomic Potentials.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Improving Molecular-Dynamics Simulations for Solid--Liquid Interfaces with Machine-Learning Interatomic Potentials

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:49.551992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.664582Z digest=sha256:26d6b2e91934151f5b4d6909d846fc75789b7b35b2bf5a73ec622cc5302221c2

Observation 95346f86-8b7b-4db8-a383-fe87d197f6b3 · outbound

This paper cites L.; Rowe, P.; M \"u ller, E.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential L.; Rowe, P.; M \"u ller, E

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:49.254371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.725143Z digest=sha256:7cc9790f6e0760abf71aff7345057ed6a27e6115b98879b4bba0590a3207467c

Observation e166df04-8d63-40e2-8aa6-1c15b51c1201 · outbound

This paper cites Perspective: Atomistic simulations of water and aqueous systems with machine learning potentials.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Perspective: Atomistic simulations of water and aqueous systems with machine learning potentials

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:49.012720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.800702Z digest=sha256:7a55634b48060c1411cbb35d7bee044611fa8a3dbfee8e70e7900695e6a64cec

Observation 30d94761-b7ff-4992-b33f-d46293456a97 · outbound

This paper cites N.; Behler, J.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential N.; Behler, J

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:48.830769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.887447Z digest=sha256:371e110d274c79bf1aadb94ac2f2a7ef956e3291670cdeea2fc7d6cc566928aa

Observation cc8b0d53-3c94-448d-9da2-a36d2dcdd6d9 · outbound

This paper cites o newald, F.; Risch, M.; Volkert, C. A.; Bl \.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential o newald, F.; Risch, M.; Volkert, C. A.; Bl \

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:48.625707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.977314Z digest=sha256:4c40f892e12520899f4072f4aaa353ade320e088b19e24120a53d6a6fdb490a9

Observation 78fc2a62-8099-4ed8-ad0c-af08d07dbf5b · outbound

This paper cites N.; Bl \"o chl, P.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential N.; Bl \"o chl, P

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:48.424627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.059306Z digest=sha256:cc71fdcca4f192814d48ae2546cffee6fcb5611c9d1dbf6b5ecae49a363ec45e

Observation 03a1a76b-9535-4187-99ec-7f1c8d5e9148 · outbound

This paper cites Insights into lithium manganese oxide-water interfaces using machine learning potentials.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Insights into lithium manganese oxide-water interfaces using machine learning potentials

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:48.124114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.134752Z digest=sha256:79a56f37a8ce597790427934b0cb25af30cf325f6a63c359897a107273dbb1cd

Observation 744bdf1c-dee2-4ca2-bfd4-372adedfb64d · outbound

This paper cites Nanosecond solvation dynamics of the hematite/liquid water interface at hybrid DFT accuracy using committee neural network potentials.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Nanosecond solvation dynamics of the hematite/liquid water interface at hybrid DFT accuracy using committee neural network potentials

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:47.923812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.204741Z digest=sha256:6cb3040dc86bc3f977a21fbc52cf8544feb5b35283e9cda2cbf4c921dfc3ff5f

Observation 70666c33-4274-4c1b-b271-122f7548adbc · outbound

This paper cites Structure and dynamics of the magnetite (001)/water interface from molecular dynamics simulations based on a neural network potential.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Structure and dynamics of the magnetite (001)/water interface from molecular dynamics simulations based on a neural network potential

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:47.662422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.286136Z digest=sha256:2faf3a078cabd9300705fca4d6b4e3d4d1956730b0c2ffb6b4f7c03b2e5f4ea1

Observation fc54b5b4-2e59-43a8-a597-4773c82a294d · outbound

This paper cites Structure of the water/magnetite interface from sum frequency generation experiments and neural network based molecular dynamics simulations.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Structure of the water/magnetite interface from sum frequency generation experiments and neural network based molecular dynamics simulations

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-08-05T13:48:39.750385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.418379Z digest=sha256:0142122188ffaf090e94db6866506e15d06d7b9086bf077aea2da47cb4f56c7a

Observation ac25b84a-5492-49ac-9307-ead3f9fb4455 · outbound

This paper cites Generalized neural-network representation of high-dimensional potential-energy surfaces.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Generalized neural-network representation of high-dimensional potential-energy surfaces

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:47.454683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.548906Z digest=sha256:47b88495d3dee9f2847b5ddf9e664be9f7a4ff360378b6afae38b1878d5be812

Observation a9b94f22-42c1-4f93-913e-28d34bbee73f · outbound

This paper cites Four generations of high-dimensional neural network potentials.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Four generations of high-dimensional neural network potentials

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:47.195645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.644340Z digest=sha256:7c8c4a5a1ab7b771be49f4a3b0e557ff7dc092e732b87aae683fd5d4eeacce8e

Observation 92dcee41-7763-4cd2-bb01-07d45e96754e · outbound

This paper cites Method for locating low-energy solutions within DFT+U.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Method for locating low-energy solutions within DFT+U

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:46.967070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.739154Z digest=sha256:d2ca8991bfbee76535d08e4c1b81e8c77e25d919fd1351cc58e2e95954008629

Observation 5b1f0226-05af-4b1e-882e-46162da732b3 · outbound

This paper cites P.; Payne, M.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential P.; Payne, M

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:46.770739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.858278Z digest=sha256:5da416eceabd262ffbdb6f47a89a82e0ec97404e9fb2c9a846d798a3433f6a76

Observation 5313684e-a35f-4f99-8a52-677f1315b288 · outbound

This paper cites Atom-centered symmetry functions for constructing high-dimensional neural network potentials.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Atom-centered symmetry functions for constructing high-dimensional neural network potentials

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:46.529596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.932088Z digest=sha256:a15ae4e0607ea124323742d0e93044a60315417dc2b3a6db3ce758553d2cf732

Observation e1e3c1ef-591c-44c5-b423-667b217e29c7 · outbound

This paper cites an unresolved cited work.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:48:46.312946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.121648Z digest=sha256:dccb12f7882c7577eb1532abe335a74b59f82a8cc839c0972d0a9aa1ae23cbb9

Observation b984f039-0694-467f-9b9a-7b82ac84b619 · outbound

This paper cites B.; Brown, S.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential B.; Brown, S

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:46.057497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.208892Z digest=sha256:b311ecd0d4f5a5275924828a847889807883c6dbbe4ae1132a41bd40c01d73da

Observation b282a5db-7fd1-49ca-984a-c71b7b504bc3 · outbound

This paper cites First principles neural network potentials for reactive simulations of large molecular and condensed systems.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential First principles neural network potentials for reactive simulations of large molecular and condensed systems

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:45.870051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.330571Z digest=sha256:8fcb087b3dbad3a974722ecc681555b704b501dea888cc44c7c6f277b9df3711

Observation 177794e3-486b-4fa7-8b51-ed472ceec2c5 · outbound

This paper cites Representing potential energy surfaces by high-dimensional neural network potentials.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Representing potential energy surfaces by high-dimensional neural network potentials

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:45.621935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.414281Z digest=sha256:9395360ee4c06c62e7855921ab22d9ca2e84f05012a9678b65cd86efe2f5d9a0

Observation e9ac53db-5c04-4274-a090-aa8bb7cead71 · outbound

This paper cites Constructing high-dimensional neural network potentials: a tutorial review.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Constructing high-dimensional neural network potentials: a tutorial review

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:45.445162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.484886Z digest=sha256:ce4a78fa7af88be9aa1f06384f5d74efe48061cc2a536f9eb08c400841977ebb

Observation 6551e67f-ebed-4e4f-87ab-dca9117c610b · outbound

This paper cites M.; Behler, J.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential M.; Behler, J

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:45.155751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.586130Z digest=sha256:dda71fb0eb3e3fdafff2d2e791bad44a9ef4eb8855236a0daeaa21e096d4a157

Observation 7f2cfcd4-1df9-4711-bf70-f4b0510853e6 · outbound

This paper cites Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:44.919292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.658567Z digest=sha256:6f5522182119b5ff22cb2a74442c024155776d8b80639d1da4faee64afce7816

Observation ba476733-e0bc-457f-95ec-b3dcabd2a041 · outbound

This paper cites Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:44.644917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.750507Z digest=sha256:c6307f7cc4975442754b12ca45e231715aada1ca410cf134ab85bd23807801af

Observation b8ee2a90-3b8a-4217-9e62-e08ac30751e3 · outbound

This paper cites P.; Burke, K.; Ernzerhof, M.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential P.; Burke, K.; Ernzerhof, M

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-05T13:48:36.828681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:36.828681Z digest=sha256:0ba255a9222c168cac15548a92134702bacdab72b7353ed9fa0e87702c57e5a9

Observation 8962cc0a-2ff5-43ef-941d-32086790fa91 · outbound

This paper cites R.; Michaelides, A.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential R.; Michaelides, A

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:44.388428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.899799Z digest=sha256:e76caac47279944d4e70d70ed9b850b86fdafbd20048a3ea840f9b710af714ae

Observation 6a440210-e864-4edd-8b52-194f430ec44e · outbound

This paper cites R.; Michaelides, A.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential R.; Michaelides, A

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:44.127069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.004937Z digest=sha256:1a9277112aacb7936033cb61d64356a127fd93fc4d0453ed20b01cca9d713796

Observation f86ec819-29ee-4000-952f-6a3eb1531c0e · outbound

This paper cites L.; Botton, G.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential L.; Botton, G

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:43.829694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.071351Z digest=sha256:75bdbbb8bf23ae124b8a438484a2a36c028d7522371a8536de33adc385ef4694

Observation 63345eb5-468d-479c-ab21-2053f974fd07 · outbound

This paper cites an unresolved cited work.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Unresolved cited work

Reference 73

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:48:43.617552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.192042Z digest=sha256:15ec011902ef4a9b44e5e2c1218e18bd75a5639118a19bcd605e530a9e2b04a8

Observation fb42c403-3cfe-49b2-83eb-55d40a13096c · outbound

This paper cites From ultrasoft pseudopotentials to the projector augmented-wave method.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential From ultrasoft pseudopotentials to the projector augmented-wave method

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:43.392229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.312189Z digest=sha256:d9d26ab6062f81739642c6083c9221a67a39af9118dd3b3b743efcc74f504ffd

Observation 24b131e4-b74c-4458-b1b2-972ea7fd9390 · outbound

This paper cites Committee neural network potentials control generalization errors and enable active learning.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Committee neural network potentials control generalization errors and enable active learning

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:43.168152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.364329Z digest=sha256:8425c75f317a3f3c1dadb5418cb884ea998f5dfeb45296d5bdbb5925997dbc46

Observation 6ad3ba59-7a65-4cbe-96e7-53a1224ca28b · outbound

This paper cites A high-dimensional neural network potential for Co _3 O _4.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential A high-dimensional neural network potential for Co _3 O _4

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:42.988365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.451172Z digest=sha256:7d68a6cde6de334a8c2a9b57754f38490a190a417fbd4981dd6b4265e23e770a

Observation f79e9e9e-38e5-44b9-8d86-8151b1c3bc09 · outbound

This paper cites an unresolved cited work.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Unresolved cited work

Reference 77

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:48:42.750943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.590579Z digest=sha256:da00308b67ea79ef871ba337e04ef568e4116cf7b2e086164f9667068e932e9a

Observation 3f56a298-ba7f-4134-bbfb-97bda2659e14 · outbound

This paper cites High-dimensional neural network potentials for magnetic systems using spin-dependent atom-centered symmetry functions.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential High-dimensional neural network potentials for magnetic systems using spin-dependent atom-centered symmetry functions

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:42.558126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.707962Z digest=sha256:6fb36d58fc062e40548406fe0d2514c32f26fbee3f148e43a74ff4b2afcbd868

Observation 2496f945-fc8a-4630-95ea-c278800a07ef · outbound

This paper cites From molecular fragments to the bulk: development of a neural network potential for MOF-5.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential From molecular fragments to the bulk: development of a neural network potential for MOF-5

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:42.335139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.759586Z digest=sha256:cf7981db6625c52e42bf8f9f564f7228721cbf15c018f6a66f172f6601318ef3

Observation 9329c01c-a65e-4665-9f74-188d8864280a · outbound

This paper cites Fast parallel algorithms for short-range molecular dynamics.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Fast parallel algorithms for short-range molecular dynamics

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:42.150601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.845602Z digest=sha256:e632c5dd73872259411fe6b10b483f6001f60db0792e5fa7fde32feab9b06eb0

Observation b4fc2239-48f4-4a4a-a406-4e562fae0b9e · outbound

This paper cites Parallel multistream training of high-dimensional neural network potentials.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Parallel multistream training of high-dimensional neural network potentials

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:41.964742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.958321Z digest=sha256:096d0c09871d84ebb21a6062e83b39b2b1e8254680efcd479bc54597d9f90921

Observation 41872ddc-c302-44eb-a0c7-2a66f3d06f72 · outbound

This paper cites C.; Andersen, H.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential C.; Andersen, H

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:41.805363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.086750Z digest=sha256:519a6f0278fe8f34284b5f4322014d482d95f8dda322c447e959eb6e951b7d5b

Observation 7be5f6df-3ee8-4a98-85f2-75789a426511 · outbound

This paper cites A molecular dynamics method for simulations in the canonical ensemble.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential A molecular dynamics method for simulations in the canonical ensemble

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:41.679637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.206247Z digest=sha256:a0bfb97cf2db8bb5be2beeefd82b02978728f03b160bf987c14fbe7d6ec7fd81

Observation 003ae59e-c409-4ad1-8255-8ac006ee9d63 · outbound

This paper cites an unresolved cited work.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Unresolved cited work

Reference 84

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:48:41.541748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.364575Z digest=sha256:b25e4ebd70180c7b4ab19d9158851293c6bf7da18fbb10b79b91af9b45582bfc

Observation f813f7b4-a745-4f3b-a38c-9974dd11e8c3 · outbound

This paper cites Proton-transfer mechanisms at the water--ZnO interface: The role of presolvation.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Proton-transfer mechanisms at the water--ZnO interface: The role of presolvation

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:41.359110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.473318Z digest=sha256:37483360cb4011b5e8263bd83ef024941eac890a5c9be0fa895673356abeeed4

Observation 0614142c-82f5-46f9-b5f7-eea63eb35066 · outbound

This paper cites an unresolved cited work.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Unresolved cited work

Reference 86

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:48:41.157413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.620223Z digest=sha256:423af046b9529a3b37145bc494c09c150e68bdbd231a4c557f7a821baba4ab17

Observation f88fa5be-181c-403c-b464-2aaa0d9a6d97 · outbound

This paper cites H.; Hodgson, A.; Liu, L.-M.; Limmer, D.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential H.; Hodgson, A.; Liu, L.-M.; Limmer, D

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:41.008584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.714898Z digest=sha256:566836ccccafa0bea73cb726fe8fc32098c3998c92c1466f4def8aeba18c8348

Observation eeb21854-ede9-4ad6-9a9d-b43275d125d5 · outbound

This paper cites an unresolved cited work.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Unresolved cited work

Reference 88

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:48:40.791868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.823367Z digest=sha256:6928f69e5d85471d5080982f33fe3da7a173a9b806d916ccede693a20bab4072

Observation 988f5045-5f48-43cb-a56d-c003c73b9e7a · outbound

This paper cites Heterogeneous catalysis in water.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Heterogeneous catalysis in water

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:40.590267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.961960Z digest=sha256:4b702dc2c97be644b532628b3d317c6b8c9636acf2868e21c77a8854bd1bf8c1

Observation 81f83ed0-fdb9-49da-8040-fb41f1e19dd5 · outbound

This paper cites Theory of coupled electron and proton transfer reactions.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Theory of coupled electron and proton transfer reactions

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:40.408203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:39.042492Z digest=sha256:92808df0b462aec1b9cfbfe1e684cb2bf3524b668c33499fe6514743d6d7f453

Observation 6703af8e-65d6-43c8-9cdd-755d9e6137bb · outbound

This paper cites J.; Campen, R.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential J.; Campen, R

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:40.143772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:39.144172Z digest=sha256:0b26027b10b8ea6801417feaba360eb0e5940f6d2dd44743f27c79d2b85e9066

Observation fe21a415-082e-4d9d-8c37-2ac12f5206af · outbound

This paper cites Solvation-induced changes in the mechanism of alcohol oxidation at gold/titania nanocatalysts in the aqueous phase versus gas phase.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential Solvation-induced changes in the mechanism of alcohol oxidation at gold/titania nanocatalysts in the aqueous phase versus gas phase

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:48:39.942420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:39.226186Z digest=sha256:84f085dc08811aae51760e15e926905feb3a989508c0606f423cea856f09926c

Observation d0033e87-f44f-44bb-a064-63b15be70c43 · outbound

This paper cites ur Theoretische Chemie II, Ruhr-Universit\.

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential ur Theoretische Chemie II, Ruhr-Universit\

Reference 93

Resolution
verified exact
raw_fallback, observed 2026-08-05T13:48:39.579700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-05T13:48:39.272461Z digest=sha256:f4a255508f8472ffbdbd971640fedcbf3d4f566d5f456590888867ffe4714370

Pith citing papers

Observation c635d2f3-3555-4f52-a4ed-758c6c6ca244 · inbound

VASP Plugins: Linking the Vienna ab-initio Simulation Package with Python cites this paper.

VASP Plugins: Linking the Vienna ab-initio Simulation Package with Python Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential

Reference 226

Resolution
verified exact
local_arxiv, observed 2026-07-11T16:18:07.772857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-07-11T16:17:26.963678Z digest=sha256:151dec89b52375584732daa9c538294c8e3814580910207f1bf7bf282f69513d