Paper Citation Record · LEDGER

Thermodynamic assessment of machine learning models for solid-state synthesis prediction

As of 19 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 1 inbound Pith citation observation for arXiv:2602.04075.

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

pith.paper-citation-record.v1
2602.04075 v2

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T04:50:53.041939Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

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

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T16:54:05.019578Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-06-29T17:13:45.057998Z

Reference resolution

21 of 21 outbound references displayed

verified exact7
verified fuzzy0
unresolved14
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a3f0a7c6-4015-4f96-bbd5-529c37a25a66 · outbound

This paper cites an unresolved cited work.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:52.310099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f52286dc-7114-4eff-b05d-4ed887080587 · outbound

This paper cites #$+0.56 𝐶%+0.28 𝐶& (2) 18 For novel materials with unknown synthesis recipes, we generated reactions at 600, 900, 1200, 1500, and 1800 K and chose the “optimum.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction #$+0.56 𝐶%+0.28 𝐶& (2) 18 For novel materials with unknown synthesis recipes, we generated reactions at 600, 900, 1200, 1500, and 1800 K and chose the “optimum

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:52.369835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81efc184-db78-415b-ae73-d8b5992a8e6d · outbound

This paper cites (13) Neumann, M.; Gin, J.; Rhodes, B.; Bennett, S.; Li, Z.; Choubisa, H.; Hussey, A.; Godwin, J.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (13) Neumann, M.; Gin, J.; Rhodes, B.; Bennett, S.; Li, Z.; Choubisa, H.; Hussey, A.; Godwin, J

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:52.670565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df2d7106-04a4-4148-9286-dea9e3ea014e · outbound

This paper cites MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:52.837609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e96fd84-4865-458d-bdd4-250d19e7bf71 · outbound

This paper cites (47) Ong, S.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (47) Ong, S

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:53.035845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 594bf888-315c-4cc7-810d-a11185ade3f0 · outbound

This paper cites (11) Deng, B.; Zhong, P.; Jun, K.; Riebesell, J.; Han, K.; Bartel, C.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (11) Deng, B.; Zhong, P.; Jun, K.; Riebesell, J.; Han, K.; Bartel, C

Reference 97

Resolution: verified exact; doi, observed 2026-08-03T04:53:54.983711Z

Source-reported events for the cited work

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

Observation a9eeb2f5-088b-480f-8f37-3c871356638a · outbound

This paper cites (4) Horton, M.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (4) Horton, M

Reference 121

Resolution: verified exact; doi, observed 2026-08-03T04:53:55.130432Z

Source-reported events for the cited work

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

Observation 3d303b75-26b1-4b7d-99a7-842f37f4e6cd · outbound

This paper cites (31) Amariamir, S.; George, J.; Benner, P.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (31) Amariamir, S.; George, J.; Benner, P

Reference 155

Resolution: verified exact; doi, observed 2026-08-03T04:53:53.993389Z

Source-reported events for the cited work

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

Observation 1003df04-d7fd-487f-95f3-f4bdb4c9b66f · outbound

This paper cites (52) Schütt, K.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (52) Schütt, K

Reference 185

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:53.041939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07cd9a15-63d5-40e7-ba4e-5e482a70ba2f · outbound

This paper cites (27) Chung, V .; Walsh, A.; J.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (27) Chung, V .; Walsh, A.; J

Reference 203

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:53.017130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f25f58b0-7f3e-4f6d-904e-d5f127cc12f4 · outbound

This paper cites (39) Wang, Z.; Sun, Y .; Cruse, K.; Zeng, Y .; Fei, Y .; Liu, Z.; Shangguan, J.; Byeon, Y .-W.; Jun, K.; He, T.; Sun, W.; Ceder, G.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (39) Wang, Z.; Sun, Y .; Cruse, K.; Zeng, Y .; Fei, Y .; Liu, Z.; Shangguan, J.; Byeon, Y .-W.; Jun, K.; He, T.; Sun, W.; Ceder, G

Reference 231

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:53.026750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06c0d190-1802-46e3-bc82-802bebcd7fa5 · outbound

This paper cites E.; Haberland, M.; Reddy, T.; Cournapeau, D.; Burovski, E.; Peterson, P.; Weckesser, W.; Bright, J.; van der Walt, S.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction E.; Haberland, M.; Reddy, T.; Cournapeau, D.; Burovski, E.; Peterson, P.; Weckesser, W.; Bright, J.; van der Walt, S

Reference 1998

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:53.032898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26680948-5d1e-41cf-a4a6-62226dcdf2a2 · outbound

This paper cites (22) Szymanski, N.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (22) Szymanski, N

Reference 2018

Resolution: verified exact; doi, observed 2026-08-03T04:53:54.740072Z

Source-reported events for the cited work

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

Observation 3eb547f7-93d0-4e9d-b511-e65c1312003d · outbound

This paper cites Orb: A Fast, Scalable Neural Network Potential.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction Orb: A Fast, Scalable Neural Network Potential

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:52.752485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57556fbc-04f2-45aa-9488-8c682c04b272 · outbound

This paper cites (5) Park, H.; Li, Z.; Walsh, A.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (5) Park, H.; Li, Z.; Walsh, A

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:52.473280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55cc8f41-d550-47d6-9f1a-cb5a8db3ed3e · outbound

This paper cites (25) McDermott, M.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (25) McDermott, M

Reference 3097

Resolution: verified exact; doi, observed 2026-08-03T04:53:54.359239Z

Source-reported events for the cited work

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

Observation c019105e-ff45-491c-9f07-96569235776c · outbound

This paper cites (43) Chase, M.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (43) Chase, M

Reference 4168

Resolution: verified exact; doi, observed 2026-08-03T04:53:53.806495Z

Source-reported events for the cited work

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

Observation b810c6de-4a3e-4798-a069-aef0aef2fea8 · outbound

This paper cites (34) Szymanski, N.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (34) Szymanski, N

Reference 4379

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:53.023586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e71361c-9a8a-49a1-8757-3abf3f437d0f · outbound

This paper cites (9) Calderon, C.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (9) Calderon, C

Reference 5388

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:52.530550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4e4820d-49f5-497a-afbc-4d89df9423b5 · outbound

This paper cites (49) Zhou, Q.; Tang, P.; Liu, S.; Pan, J.; Yan, Q.; Zhang, S.-C.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (49) Zhou, Q.; Tang, P.; Liu, S.; Pan, J.; Yan, Q.; Zhang, S.-C

Reference 6280

Resolution: unresolved; no resolver link, observed 2026-08-03T04:50:53.038894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28410147-4ad7-428b-9110-1d82894323a2 · outbound

This paper cites (23) Szymanski, N.

Thermodynamic assessment of machine learning models for solid-state synthesis prediction (23) Szymanski, N

Reference 6956

Resolution: verified exact; doi, observed 2026-08-03T04:53:54.566783Z

Source-reported events for the cited work

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

Pith citing papers

Observation 928ce344-e652-42f8-aa06-827d67354154 · inbound

Rapid estimation of synthesizability windows of inorganic materials from first principles cites this paper.

Rapid estimation of synthesizability windows of inorganic materials from first principles Thermodynamic assessment of machine learning models for solid-state synthesis prediction

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-06-29T17:13:45.059711Z

Source-reported events for the cited work

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