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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 21 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 2026-08-21T06:32:19.484+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
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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=sha256:838d8695b9079860024211d2c7d2530632d043236698811578de0f1d5ffde7be

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=sha256:1db9c4a4474f11c6220d0f16daad5644a395099f5a03056fea5795438721529a

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:29.777661Z digest=sha256:ffe6a27f08408b4761c5faef87909dc857434bcc1da54f7da585175b38e8af7f

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:e2b7292a946ee8f035df418897368e01b8f374842189acc653a797752031282c

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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unresolved
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=sha256:40f2af17407659556416c9d867cb3f7a3a628b253f75e5eebdda722ae2249a37

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
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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=sha256:00ac99ca4478f8edfa1297abe011871c2cca87303c9ba1ff996ed7c4b855ce32

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:e3f69a53d11b8d394acb1554fcc5c7e336813c5156e27b9c0934ddfdf295362f

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=sha256:0727a3db68f75ce84755ca050aa6941b5eae253d2396c7ba0b3b5dca89d59c93

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:30.605772Z digest=sha256:2cd7168c821a04a7a33dcb113be5e19f12b7fa4123913aa167203c61d92716c7

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:f280a55e66b77b5899f2f169fa505c157a97cd72d8bbfea4591d7a5ccd73fa25

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:b049a128d064c0258d0ff8dfb145dd9ce68bbd9771b8066cf6805bbd91268aef

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:b346b9db3bf91dca295e6b154ed2ff531eb363f5f63049b3731840c8c0576fa9

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

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:48:31.132367Z digest=sha256:6fb15e30d8b46d71ad04ee2cce1f17065874c0397b7a4d9e38ada5acae35f320

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
raw_fallback, observed 2026-08-05T13:48:56.559106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:31.207459Z digest=sha256:9f62f8feffc432b276ef2719b5551da061c729ad14c537c3e819ce7611a15b38

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:31.336282Z digest=sha256:45bd261557dfc427c08eb365d7bb5739eeddfc90ce505da51ea2427047ce573c

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:31.494025Z digest=sha256:d6db2860698eda49fe283c1a39499375566348738b327b244d5a54e4d7d0ccd7

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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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 2026-08-21T06:32:19.484+00:00.

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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

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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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:31.806509Z digest=sha256:d868dbe7d054c66e44b4a10d7523b9643276c12da5fc9e0c6a38dd489981f27f

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.103132Z digest=sha256:b3abc0bbceb588478d159c742ae5e69cce2e8b477a402e14caddf6fc9f98202b

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

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.300322Z digest=sha256:c17983cbe9e48338745f87ba32dde81576779ce030619a4c7b89f35a63f323a1

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.361852Z digest=sha256:2c4a7677d0036bcf93203a72a452fb486535d2c158fde1d6c3ba6649b4ed1c9a

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

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.492301Z digest=sha256:81530d6fde7deda185c31e9095a96df67103bdb45f2d74d11c569e142159c3cf

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

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.672103Z digest=sha256:5053b5a6a6f29e762586b7e481634bc831acb14300fa922d6b23dec1523494e7

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.837268Z digest=sha256:938701c054de260b5e3a7313bfc3db9fecb6dc2918a5ef4ce410d3eba89056ba

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:32.987753Z digest=sha256:3364f28522b6b1944076ec6065cdc58965d80a349e97347d1e3b3e7ff8e7739b

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.118538Z digest=sha256:87e7709b32602ec6087f785ea3346552e347559166670c161a9330f8619db6a2

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.231377Z digest=sha256:028fcc82fcda3b608bf81647814f1e603e252f086b995baa12c6d0f42325b78a

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

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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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.401890Z digest=sha256:b3604fcadad171e3f8572bf10265e950fcd68a1594b6fd0eb3cb2a5290353f34

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

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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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.505089Z digest=sha256:d93a1db6c62c550805fb8be0f68d5deb63f787208701a115c6a8b16faa091127

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

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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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.593364Z digest=sha256:355d0416e8aa50b67c5d64ed3edda8e8e8faf29d4ccba3b4ed4d305bf15103eb

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.714532Z digest=sha256:3f6f7f7651ae9636a0ff2eb1872042f874157a07739453086f4e9a3628bef46f

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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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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.801121Z digest=sha256:f0ff73b85ef2a413775bae173fb4021b89bf8f637d5bc6e51f46c9b56946d88c

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.876861Z digest=sha256:c8b2ffd89889bb7910e3b9406c7ba9ca9c1db616b1e358ac6e482a8938c7fbd4

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:33.935839Z digest=sha256:e31a3ae2dcdbe5018dfbbc6242bfcd0a45acf8b02d3af33f153b1f6eb8ef2571

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.027931Z digest=sha256:b2747c5cf5a9815154c4a04000dd105eaecdd4fb87873b88d91fd5da12d14151

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.115676Z digest=sha256:393268bc0661318a80d1e8c83815f475b204405c794e6cbf438bca5378b300f9

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.173708Z digest=sha256:7510ce0a5031b0385502a242bb2b88cc6e7bedd989764c485c31ef5f16940c6a

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.239149Z digest=sha256:e40a3144e7dbf1dd208429f5ba1cf5bbd074f407eb7557dfcbe40f6a1f0898b6

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.287063Z digest=sha256:45ea012784d6f14822993e7d2a9a036e26693af8ffedefc63ee08f3d69547d40

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.338095Z digest=sha256:d960a39e773fd2038501aa59190dee098e9a0c6b5396090aceced492486fc67a

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.402875Z digest=sha256:276a7de20efb0ca6fd82530ca036e0d65418e8ccb732270198dac5acdbd291bc

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.461966Z digest=sha256:0b38d6e083007d72ea29413834adc7d687b861cae02db0aa712571b035c91f78

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.534569Z digest=sha256:dcc6341fd96a9369b4c2fe15e0e419c7ebdfdcc2537a01974f1ecd660c48b4e8

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.599804Z digest=sha256:effe1d524b8d2f44394267e2708315e8230a93bdcee9d50c8a65e54ed5cfd745

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.664582Z digest=sha256:d77fc312451683aababd16d10256c7bee85ba882a92da95bc889ac461e7d79ee

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.725143Z digest=sha256:04f9e23d5002bf9872fcf4705d36554296d8120427f70f17397624b98bcc919b

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.800702Z digest=sha256:accb3a4158830df60750f7053681169e425c533fe658a6e2a5b61d896c4414c4

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.887447Z digest=sha256:c1a8f804eef41269ddaf1eb2d5457c6b0bb947920f999899111a531a8e1dec41

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:34.977314Z digest=sha256:cff5d9cf5e6cac17746011167845451c43bb9ab448232c959d735284afa3b291

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.059306Z digest=sha256:fcbf15bf530b9f22dadea0b7780c224a1fa3cd66eddb894ceb23adf6e190817c

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.134752Z digest=sha256:062a977efb0a6f61703e8566944f0fe1b1af85b8a056b426ff6eaa4f0c9b694c

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.204741Z digest=sha256:61e4eaadacd44f4df39e62aeaed93496b411d58dac8fbf939f32e2f41bf33064

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.286136Z digest=sha256:b337b90c407aaef1c07ddd7cb4050b74a547fd2b2238a33eb1c85f14de719fe5

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.418379Z digest=sha256:a151b974f60f950e91b92c3b2b8d0b724f621a4123b4b7d5544eb6d1356dd500

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.548906Z digest=sha256:b475c9525af75822e31e6b1e28e60589be2bec44f8e22e6e21c2712631707d00

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.644340Z digest=sha256:e3e70816bd3cbf43a342b375d2d663d00d8f2c89ed7220480cb5e8d710df9388

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.739154Z digest=sha256:3ef669cc7f6fcffbaffe1fbb2421a8bcecc56261c23c29b4beb00d545afbf6d3

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.858278Z digest=sha256:1812b13df96ead3f9088d1002e0a444c38210ed745a66d8f82ba958f67580239

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:35.932088Z digest=sha256:604915b9acc9ff35e06b06cf11d46c2f3a54c1bc911a9634b73ea8545f3ec003

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.121648Z digest=sha256:6ebb3b3b9646368776e2cd0a3e5a253601326c79fd0f76804ab899ce6d8eca55

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.208892Z digest=sha256:5beb29ed37323d05213be8feee0bebcfed8ef93643575d5984262710bbd9c322

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.330571Z digest=sha256:815a07eebad19929977bd1a1c694639bef7ba154296ed0e1cb2cdfbc29a976ce

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.414281Z digest=sha256:b804d1c74e75009a66cebbda0a3768d948f6b9a1bfbfd7a0f2f3b204e7f38c4c

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.484886Z digest=sha256:435f958bdf8b8578dae08b77243278e0cee3d39726cbf03b651fb4af09848ecc

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.586130Z digest=sha256:a7c2184d00355f58037b8ca6d1c41e4226f9a2902e740e8b71f523c29ed76a60

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.658567Z digest=sha256:51ea6552f6e3f7d004c618cfaa4c3e46584a203880d22af0e29680a70954fadb

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.750507Z digest=sha256:0c112b517c07f680da6933b1207705039f9413d4368563a6b27ede093f2a0830

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=sha256:96e3f13cff8586d536bd3b6716144ebfe3d2281c9b52c0e56ab7beb27530771d

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:36.899799Z digest=sha256:78004a034b62085b4789dd08beeb66df45993a44a18cc39b6316e999daaa7828

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.004937Z digest=sha256:999db4364305f9f787c43caee2aef94816a49077418695139173b0aaa3f6dc5f

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.071351Z digest=sha256:c800b28041cd9c9487a67190e13d40b931ac425e9f9e003990df7806f991dca0

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.192042Z digest=sha256:5b485b299221eb806cc250e4882dbcb7b5227afafe06b3fc4c66e10fd6671cce

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.312189Z digest=sha256:d6319dbb05843b6c06050a28105b2f75f6f4d6e1a3f03503063a31c9badc092b

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.364329Z digest=sha256:3805e134df03da5b9598eba3a49a8d975b7a947da7f37f156346721709c191ee

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.451172Z digest=sha256:2b81ca93f7a3de8f7880d1e14488e33f1e8f0c4b336604b67c4c677717f74d10

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.590579Z digest=sha256:4ff3f2b494d90ebbbc2a9252ded62b04eba575e7ecb7d898a068701d3d65c6cc

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.707962Z digest=sha256:97289576c9f8c9b600c3f2320955dd0644d899ed9ea33a4823e0e51be79fa557

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.759586Z digest=sha256:24dd0ab06db8f5430a9b9b95ec91d7db38289075f95289f7347165c9fb65e6d1

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.845602Z digest=sha256:9e110a3915755023305209470f3916473ec363669bc1fcf6966afa7a678a197d

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:37.958321Z digest=sha256:71ef762edd86b398ff6144ad9d10788cce34cb71ccf20a9dd261e6b74547ceac

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.086750Z digest=sha256:ac541f5bd70edee7c8eb5b30d14c22c01d58843a836d844b6fd387f0d44a9785

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.206247Z digest=sha256:2e6ade250e2b2419f4d356410331e1153b7e4ab20d5aba68238ffe81f5bba392

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.364575Z digest=sha256:d98591796e80fd46b718d3733a9fc45a6c3e980e5b49741306dd992422d2a165

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.473318Z digest=sha256:17a89a22f48cd50454d6aee7f4e2be01d46303230ae504cf82080fa21e2ccc58

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.620223Z digest=sha256:afd5ed8b50fb4d41405ea087768283b06c48482658beafcea74ec69b343f8486

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.714898Z digest=sha256:fef6301f80487b5f1b3aefac28ab18034abecf32b4f02babc39d6c661d43b684

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.823367Z digest=sha256:2c667b9b46894bf9bc928fa1a844bc6c68b56c2c20861f3decc2be2c4525bce0

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:38.961960Z digest=sha256:294e09cd8dbd6031822991e57d054ce54eb463027d0e9ec1af8a3575d98367a2

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:39.042492Z digest=sha256:e586f87fa72188a1c6d11b50066412f8c98d71f7ce3ed81795d112588e740644

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:39.144172Z digest=sha256:a0aa90b591e525d5b8c02ec7951e5fd7721e5ffc036f8483e9cbb3517cd17646

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:39.226186Z digest=sha256:4c80df403aaa3ca4bee1f2913724b00100d4feec7ce1432918a956aa3e1b1b1a

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-05T13:48:39.272461Z digest=sha256:d43e7bfd596c1a07a0c9f1c8e18515ce85cc452cdbed85de70fd06f46bd1c000

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-07-11T16:17:26.963678Z digest=sha256:d18a9df918ca2ac4032fa694a6e40cf9f6ef45b85d8dc0f6d4239bce55bb6ebd