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Paper Citation Record · LEDGER

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials

As of 23 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2506.15652.

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

pith.paper-citation-record.v1
2506.15652 v1

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:56:54.357673Z

measured 64 of 64 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

64 of 64 outbound references displayed

  • verified exact1
  • verified fuzzy44
  • unresolved19
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d6a8b6b9-d02e-4727-855d-c4b1be2c9cd7 · outbound

This paper cites J.; Jain, J.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials J.; Jain, J

Reference 1

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Source-reported events for the cited work

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Observation 03c210ae-218c-4ae8-94f8-b5b7d9883821 · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 2

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Source-reported events for the cited work

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Observation c0f5125a-d717-4d67-a22a-45ea9e713242 · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation d6d4ffab-7591-4555-90b8-259b8d2ae304 · outbound

This paper cites Phonon transport in disordered alloys: A Multiple-scattering approach.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Phonon transport in disordered alloys: A Multiple-scattering approach

Reference 4

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Source-reported events for the cited work

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Observation 7497ce0f-0991-40ba-9280-1d9ee8383e7f · outbound

This paper cites Dynamic disorder phonon scattering mediated by Cu atomic hopping and diffusion in Cu3SbSe3.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Dynamic disorder phonon scattering mediated by Cu atomic hopping and diffusion in Cu3SbSe3

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 1606e1f8-d5d7-4784-89a1-3a900843127c · outbound

This paper cites Thermal conductivity modeling on highly disordered crystalline Y _ 1-x Nb _x O _ 1.5+x : Beyond the phonon scenario.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Thermal conductivity modeling on highly disordered crystalline Y _ 1-x Nb _x O _ 1.5+x : Beyond the phonon scenario

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation ec2e4fa1-732f-4f3a-9426-358d2181a0c1 · outbound

This paper cites Atomic Disorder Enables Superior Catalytic Surface of Pt-Based Catalysts for Alkaline Hydrogen Evolution.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Atomic Disorder Enables Superior Catalytic Surface of Pt-Based Catalysts for Alkaline Hydrogen Evolution

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 982a8f5a-376e-4eff-9163-2d3ace8cea17 · outbound

This paper cites A.; Morgen, P.; Chamier, J.; Ravnsbæk, D.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials A.; Morgen, P.; Chamier, J.; Ravnsbæk, D

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 8b20a1b4-ea41-4281-909e-4c2d95cd61f9 · outbound

This paper cites J.; Pan, J.; Tamboli, A.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials J.; Pan, J.; Tamboli, A

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 11bb2abd-a884-479b-a4db-02041cf711e1 · outbound

This paper cites J.; Dove, M.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials J.; Dove, M

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation dd3d2db1-0733-41b7-8b5d-a6df0235f33e · outbound

This paper cites M.; Yim, S.-Y.; Agarwal, R.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials M.; Yim, S.-Y.; Agarwal, R

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0ea3d603-81f2-4088-8080-ee4fe1daaf3d · outbound

This paper cites Large scale hybrid Monte Carlo simulations for structure and property prediction.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Large scale hybrid Monte Carlo simulations for structure and property prediction

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.385925Z digest=sha256:f80244d5b1883280af389e3f22116fc1b5be05e2cba3a064acda3a39cd57fdb0

Observation 901c79db-09b8-429a-8e72-17150a37ec4a · outbound

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A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation ee49ee43-8015-4d4b-8d11-777a40f11d0a · outbound

This paper cites C.; Torbr\"ugge, S.; Landau, D.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials C.; Torbr\"ugge, S.; Landau, D

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation b47418a1-bafb-4721-aa71-aa351d53c664 · outbound

This paper cites Cluster expansion method for multicomponent systems based on optimal selection of structures for density-functional theory calculations.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Cluster expansion method for multicomponent systems based on optimal selection of structures for density-functional theory calculations

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.398073Z digest=sha256:47990eef4783dbaf0e14c6ad37a1b5085d277ed3ccd678d3fa94c1f78d1d2b70

Observation 9326ffad-ddd8-4893-9aae-d36e59414f4e · outbound

This paper cites Atomic cluster expansion for accurate and transferable interatomic potentials.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Atomic cluster expansion for accurate and transferable interatomic potentials

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.401721Z digest=sha256:5f3080b5d26875c1002e68cf2ae0100b362fe869a9e295fdb223b9a1a0af8ba9

Observation e89c0923-d5f5-46b8-b644-df51132a8f40 · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.405594Z digest=sha256:244c10c9f5e5a3560813f7ae97a67b6b5ebf6cc6452aee3e702b69826c835cf6

Observation b5ac7aa1-c6e6-41c2-86c9-44b53bffcb0d · outbound

This paper cites Constructing and Evaluating Machine-Learned Interatomic Potentials for Li-Based Disordered Rocksalts.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Constructing and Evaluating Machine-Learned Interatomic Potentials for Li-Based Disordered Rocksalts

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 393c4039-306e-466b-857e-155167b805b3 · outbound

This paper cites M.; Isayev, O.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials M.; Isayev, O

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 718bb0a1-72a2-4c73-aed6-df6dc9dbc94a · outbound

This paper cites S.; Armiento, R.; Alling, B.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials S.; Armiento, R.; Alling, B

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation cec68eb2-d21d-4d4f-ad2f-c491751cd6bd · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 21

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 508bf5e5-e06a-4185-a2e1-40f6757aa640 · outbound

This paper cites Graph Attention Networks.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Graph Attention Networks

Reference 22

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation ddcc6158-2824-4aef-a35c-badd3b0765c1 · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.467200Z digest=sha256:b612a8d30fcb6510a2cdb5cb2b38539b480e26fef1efcd0bb196589c17ff5811

Observation 26473fce-673d-489d-988b-f59066384dd2 · outbound

This paper cites Graph neural networks for materials science and chemistry.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Graph neural networks for materials science and chemistry

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.474667Z digest=sha256:f80cc97a7ce578ddfbdb96dcceda79197c2ee7ab42e1227bb2d375eb29e6ed55

Observation 643c5999-a9b5-44c5-84ea-9e3374e9b181 · outbound

This paper cites Leveraging Persistent Homology Features for Accurate Defect Formation Energy Predictions via Graph Neural Networks.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Leveraging Persistent Homology Features for Accurate Defect Formation Energy Predictions via Graph Neural Networks

Reference 25

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verified fuzzy
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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.485065Z digest=sha256:2c2910eed11da5bba3df037581340ebd684a38ceee0a67e549a3a16ff277c02c

Observation 71a87ec1-4dc6-445c-aed6-aa66278e2946 · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 26

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raw_fallback, observed 2026-08-06T23:57:01.146064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.495580Z digest=sha256:5e911131c9fde74b82b6fd1aac75ac2a48c5e699981108ab7cd87cc2d2227590

Observation d8010bbb-c159-47ef-b111-0bd00767e685 · outbound

This paper cites T.; Alatas, A.; Kong, J.; Li, M.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials T.; Alatas, A.; Kong, J.; Li, M

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.506623Z digest=sha256:ddb4ad9deeeae7334895984f8329d9a137ecdacb3a063d3b7a941ee289e5abee

Observation 0d339139-6d77-41d0-ba19-24f659f747bd · outbound

This paper cites T.; Okabe, R.; Chotrattanapituk, A.; Li, M.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials T.; Okabe, R.; Chotrattanapituk, A.; Li, M

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.519652Z digest=sha256:ca8f6324d349faeddc2261bd3c556bb309a0ee2efcd1158946acfefa0a6738d0

Observation 5ad4c416-a2df-485e-aac2-0fca1b094795 · outbound

This paper cites M.; Charpagne, M.-A.; Latypov, M.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials M.; Charpagne, M.-A.; Latypov, M

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.528812Z digest=sha256:55c5dd461e7ddfd6d9b0d0ec480f32f27fa358b042ef57d92dd1e9ff64993b69

Observation 721a21e9-a8cb-4ac0-909d-aca56c00e290 · outbound

This paper cites Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation

Reference 30

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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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.539400Z digest=sha256:235cf7923f432ea47e6ee7520baa0075fd9f658d54182bf35d777af7109f4432

Observation a9f21f7c-7b54-4f94-88c0-0e6f935ac442 · outbound

This paper cites Towards accurate prediction of configurational disorder properties in materials using graph neural networks.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Towards accurate prediction of configurational disorder properties in materials using graph neural networks

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.550025Z digest=sha256:51c0ccc1508d022b1d8cee14fc5252c0dc292cfc6bc33eadbf9b0d9f9fd7176b

Observation dbe9d56d-1950-4bed-808e-c39a89b004bf · outbound

This paper cites A.; Pereyra, C.; Soroush, M.; Rappe, A.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials A.; Pereyra, C.; Soroush, M.; Rappe, A

Reference 32

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raw_fallback, observed 2026-08-06T23:57:00.153053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.566066Z digest=sha256:1ad360685f3852566467643878085425cf121bd08a45ce63db9291e889f62500

Observation 659f9f6e-7a7c-4d61-b2af-f78dd5a699ad · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 33

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unresolved
raw_fallback, observed 2026-08-06T23:56:59.964970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.577817Z digest=sha256:ba53dbd573e06bbdf739066f0fa64d4df477218758926329c25e8a519f2ba7ab

Observation 2f53833f-53e0-4baf-98d4-60a1c3593c7d · outbound

This paper cites The world of two-dimensional carbides and nitrides (MXenes).

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials The world of two-dimensional carbides and nitrides (MXenes)

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-06T23:56:59.702594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.639337Z digest=sha256:ea67ec6031d7a7575a5a2052e4e8d17ef15e470984dd90d52941356adb1c4c44

Observation 958cafbf-b9a9-4f43-9862-5627f298a5ed · outbound

This paper cites Chemical Origin of Termination-Functionalized MXenes: Ti3C2 T 2 as a Case Study.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Chemical Origin of Termination-Functionalized MXenes: Ti3C2 T 2 as a Case Study

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:59.468643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.704295Z digest=sha256:c87bd1b3fd7f21ef031330b38908f18e9ca25e9032016709cce400a76b429966

Observation b8489f31-1941-499e-92a9-4e573cdc7fa3 · outbound

This paper cites Database of Tensorial Optical and Transport Properties of Materials From the Wannier Function Method.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Database of Tensorial Optical and Transport Properties of Materials From the Wannier Function Method

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:56:54.616366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.783811Z digest=sha256:63a21cdd2f3108fe76a8ab1ed4dd69f23e192cd9ee2c40b4d6682c91dbd38a91

Observation 2f463c48-88c7-49ac-a58d-90b163212649 · outbound

This paper cites A.; Yates, J.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials A.; Yates, J

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:59.254408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.895255Z digest=sha256:d2b234dc103647a2263a828497d339d88e0ef28acbd5c264cd5c05da0b91131d

Observation d2027533-f82d-4b42-818c-9eb6c3610c10 · outbound

This paper cites High-Throughput Screening and Automated Processing toward Novel Topological Insulators.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials High-Throughput Screening and Automated Processing toward Novel Topological Insulators

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:59.094083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:51.973842Z digest=sha256:908f3a4290351d6802dca9f0dfa86889cbdf2fa2c5f1421e0ed0b4fe8c36444a

Observation f03ca5eb-a635-4eb8-a703-988aba94b0d3 · outbound

This paper cites How Attentive are Graph Attention Networks? International Conference on Learning Representations.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials How Attentive are Graph Attention Networks? International Conference on Learning Representations

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:58.883307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:52.042539Z digest=sha256:15ad44a5699084f915a35d16c1f1a70d76d9c8ee02075e60b7e260e1d0c6b378

Observation bfcbf0e3-3dcb-4c94-83dc-03e633ccd3a0 · outbound

This paper cites Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:58.718489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:52.094754Z digest=sha256:337dec6b6711e1e1b3dedf06f74a05c0d721d71f16b160cb409c73d2e9c3b080

Observation 3332ec75-aa0a-482a-8a7c-3f26e2d1435c · outbound

This paper cites P.; Kornbluth, M.; Molinari, N.; Smidt, T.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials P.; Kornbluth, M.; Molinari, N.; Smidt, T

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:58.481407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:52.200867Z digest=sha256:27dbf04024d56890dc283b3f8baf6b5c2ce884042bbca0c46ecc50878e9685c0

Observation 9d4c1004-978a-4fc3-a19b-f5b80c8075eb · outbound

This paper cites B.; Anasori, B.; Hong, S.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials B.; Anasori, B.; Hong, S

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:58.276999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:52.257974Z digest=sha256:b0500663aeef2ef5d70c5d51b81d7e4517a842358717f7f7e56c9197cf1e9dae

Observation 12160905-2730-4f4e-adca-11eb87f70bbc · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:56:58.052149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:52.333710Z digest=sha256:58acdcf24087d9207d9cfbf9298024bd582fe1a65068568d7e9d9e424c46b7f8

Observation f6001cca-8a30-4c39-8c99-cb1d2be04ebe · outbound

This paper cites Advanced materials (Weinheim) 2011, 23, 4248--4253.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Advanced materials (Weinheim) 2011, 23, 4248--4253

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:57.851366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:52.437961Z digest=sha256:f3e1583176712393a82de6f1035573500db703202e663f174153b50ba26ad906

Observation 7d99dedf-3472-4995-8030-1fa7b910e534 · outbound

This paper cites The Rise of MXenes.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials The Rise of MXenes

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:57.633661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:52.493315Z digest=sha256:fdadcc94668beeb809af66cfa5711a211c27a23f8436a61b5e2db6b40e38cfad

Observation ec296ca5-10a9-493b-b6c3-7ac3eac1ec10 · outbound

This paper cites Li-intercalation boosted oxygen vacancies enable efficient electrochemical nitrogen reduction on ultrathin TiO2 nanosheets.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Li-intercalation boosted oxygen vacancies enable efficient electrochemical nitrogen reduction on ultrathin TiO2 nanosheets

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:57.388825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:52.529862Z digest=sha256:2dda457aae464388b81b0f1e28e7670027c1255c8042b98915da9f83026540c9

Observation 9a212681-f621-4408-a2fc-916d5ac51678 · outbound

This paper cites Cation-induced Ti3C2Tx MXene hydrogel for capacitive energy storage.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Cation-induced Ti3C2Tx MXene hydrogel for capacitive energy storage

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:57.204965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:52.623386Z digest=sha256:b18c926bc3444bba03d17bd4d1cd9c3f8da415e7ab810b22585b687af5b6a8a3

Observation b6f0fb73-064b-46d2-8a1b-d29978f70bfb · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:56:57.014083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:52.696595Z digest=sha256:aa39a1c992422a5dc12810dc12e48a61da5ced62a1d963b459c37fe46abde1fc

Observation 6f78cfd5-ae6a-4a2d-8026-31677c4a3343 · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:56:56.786271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:52.751173Z digest=sha256:9c289ad82a0425cd65b87fc6b45ad923682379c33c54c0f034ca7b7bb4c83544

Observation 645a8f2c-221a-4e0d-9425-96120a96285b · outbound

This paper cites Chalcogen and halogen surface termination coverage in MXenes—structure, stability, and properties.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Chalcogen and halogen surface termination coverage in MXenes—structure, stability, and properties

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:56.514005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:52.831961Z digest=sha256:292fa0b4213db48912105fb798adecb28446f3283ced1bf89429307c2dfa5b79

Observation d69aef51-84f8-401c-9cc5-267c6823b5b2 · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:56:56.326269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:52.896588Z digest=sha256:ad597b47c78e09d22090e88464e99b036f5097883ccbce23ca0665ab28e4521c

Observation d5e40be3-9c75-499e-9bc9-d4571e18483b · outbound

This paper cites Ab initio molecular dynamics for liquid metals.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Ab initio molecular dynamics for liquid metals

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T23:56:53.003899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:56:53.003899Z digest=sha256:3296a6cc88b56ba1c7e1acb0ce212fdab833050511d934b542ab8b49c42123dd

Observation 89a035e2-9dbe-4925-9bc5-4c320f521ff5 · outbound

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

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:56.147545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:53.081626Z digest=sha256:8e42058b7b91ca453c9c525717f15b7fe0582292b674ca0adbfe69fc225bf002

Observation 813652ba-ba48-49fe-b9e7-5ec045d6626f · outbound

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

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials From ultrasoft pseudopotentials to the projector augmented-wave method

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-06T23:56:53.224390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:56:53.224390Z digest=sha256:0621a57848844a9c62c6b24c753456f24639d1d6e0030f5664f66bba3eb0797e

Observation a439f5ea-9bf9-46d8-8f0b-282f7677b0db · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:56:55.987009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:53.352315Z digest=sha256:e7fc645632d47d0a983c029a3f41654972831fd219c3adb121c37629dcdba6ca

Observation 81a162fa-d672-4ba7-8808-4dd5f5fabd9d · outbound

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

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials P.; Burke, K.; Ernzerhof, M

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T23:56:53.462329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:56:53.462329Z digest=sha256:19455be1ffb43d8fe86fc6fc5e1fa8afa8b7ba97ae6389fc93714f9261f2b39a

Observation 01076b67-a82c-41c0-b620-4bd5ebc5c359 · outbound

This paper cites I.; Zaanen, J.; Andersen, O.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials I.; Zaanen, J.; Andersen, O

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:55.797700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:53.571491Z digest=sha256:7aea37058d615c5d9c32bf954c202af1e2ba67d82d796b7649c65677a19467a3

Observation 9c25f4ce-f6b4-43a7-862f-ecd0532e6483 · outbound

This paper cites G., Stephan Ehrlich Effect of the Damping Function in Dispersion CorrectedDensity Functional Theory.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials G., Stephan Ehrlich Effect of the Damping Function in Dispersion CorrectedDensity Functional Theory

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:55.601428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:53.643164Z digest=sha256:199ff3895fb6725ada3b44632e7f2d51a25d5d77d8edc6a3eb6f995800ec9f49

Observation 973497eb-412c-4f74-8833-558a5f9e0569 · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:56:55.460870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:53.756254Z digest=sha256:4c45da2511dec123efddb1b538f5453770fef209c083a3b365bdb9bc942f577b

Observation 2bf50043-5f68-41f3-8343-b921eb841328 · outbound

This paper cites BoltzWann: A code for the evaluation of thermoelectric and electronic transport properties with a maximally-localized Wannier functions basis.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials BoltzWann: A code for the evaluation of thermoelectric and electronic transport properties with a maximally-localized Wannier functions basis

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:55.255346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:53.833295Z digest=sha256:65ca8848c1df2e4a1c08928855552f2c2738232a3b1c6c9f0e1f63dc302052cb

Observation 4e518099-7a56-4f27-b5cc-8b4bad71b3b5 · outbound

This paper cites High-throughput prediction of the carrier relaxation time via data-driven descriptor.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials High-throughput prediction of the carrier relaxation time via data-driven descriptor

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:55.123541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:53.934669Z digest=sha256:2e47fc12ffc9f2718ea5a5193dea6a650f22a0c7d255671abbaa350f5e22deda

Observation 86403460-92ee-4eea-ba9c-f3398c07d4b1 · outbound

This paper cites an unresolved cited work.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Unresolved cited work

Reference 62

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:56:54.966227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:54.072302Z digest=sha256:f148786c0dcc8e7133fb072871fd8b6990643e15a041a22e4313cadfc763d3f1

Observation e65ac8f5-fcda-4215-ba56-297bdfad09f3 · outbound

This paper cites Optuna: A Next-Generation Hyperparameter Optimization Framework.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Optuna: A Next-Generation Hyperparameter Optimization Framework

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:54.841444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:54.192818Z digest=sha256:9c2f4289e499adae634af2ec099fa606e6193cb2646c98c47d82df467af50ad5

Observation ae0eb557-9c52-4bc9-9096-4510cdfe0960 · outbound

This paper cites Algorithms for Hyper-Parameter Optimization.

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials Algorithms for Hyper-Parameter Optimization

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:56:54.758346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-06T23:56:54.357673Z digest=sha256:e3f7c900214133a86ed3e5b362c1c663a85489f4031266eedd6753e398a314a8

Pith citing papers

No inbound Pith citation observations are available.