Paper Citation Record · LEDGER

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001)

As of 15 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2607.23461.

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

pith.paper-citation-record.v1
2607.23461 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-30T21:41:28.395416Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

25 of 25 outbound references displayed

verified exact0
verified fuzzy0
unresolved25
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b7b25154-2ff0-4c65-b54f-bf7a1b2c238a · outbound

This paper cites an unresolved cited work.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:26.763771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c792732-e728-476b-84d7-4503641902a8 · outbound

This paper cites Amano, Y.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Amano, Y

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:26.824167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fe24cde-4d03-4b36-9b17-af13d533fc24 · outbound

This paper cites A new theoretical ap- proach to adsorption–desorption behavior of Ga on GaAs surfaces.Surf.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) A new theoretical ap- proach to adsorption–desorption behavior of Ga on GaAs surfaces.Surf

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:26.889505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fdcfc25-ae7d-4ae0-b190-14291ca9c750 · outbound

This paper cites Thermodynamic analy- sis of (0001) and (000¯1) GaN metalorganic vapor phase epitaxy.Jpn.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Thermodynamic analy- sis of (0001) and (000¯1) GaN metalorganic vapor phase epitaxy.Jpn

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:26.966894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22bc79a3-7b4d-4a11-a4d6-adcf85f474b6 · outbound

This paper cites Re- action pathway of surface-catalyzed ammonia decompo- sition and nitrogen incorporation in epitaxial growth of gallium nitride.J.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Re- action pathway of surface-catalyzed ammonia decompo- sition and nitrogen incorporation in epitaxial growth of gallium nitride.J

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.009579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a14885de-9e27-44fd-9991-e33282e2d055 · outbound

This paper cites First- principle study of ammonia decomposition and nitrogen incorporation on the GaN surface in metal organic vapor phase epitaxy.J.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) First- principle study of ammonia decomposition and nitrogen incorporation on the GaN surface in metal organic vapor phase epitaxy.J

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.071191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e17872da-513d-4d16-8e11-5ab8b7b3b862 · outbound

This paper cites Gallium–gallium weak bond that incorporates nitrogen at atomic steps during GaN epitaxial growth.Appl.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Gallium–gallium weak bond that incorporates nitrogen at atomic steps during GaN epitaxial growth.Appl

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.176916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33b505fe-d20e-45b6-9b44-03cb10c00dc8 · outbound

This paper cites Exploration of a large-scale re- constructed structure on GaN(0001) surface by Bayesian optimization.Appl.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Exploration of a large-scale re- constructed structure on GaN(0001) surface by Bayesian optimization.Appl

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.293225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00329398-a304-4ada-a2d2-8d3b176bc5f5 · outbound

This paper cites Bowler, and Akira Kusaba.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Bowler, and Akira Kusaba

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.352982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c58503e-7ae8-415c-99fb-1f18d7370cc6 · outbound

This paper cites Insight into the step flow growth of gallium nitride based on density functional theory.Appl.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Insight into the step flow growth of gallium nitride based on density functional theory.Appl

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.430024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e39e96a-7ff9-42c4-a7cd-7672be12f093 · outbound

This paper cites A two-dimensional liquid-like phase on Ga- rich GaN(0001) surfaces evidenced by first principles molecular dynamics.Jpn.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) A two-dimensional liquid-like phase on Ga- rich GaN(0001) surfaces evidenced by first principles molecular dynamics.Jpn

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.489001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd70b810-3577-4932-98ee-4ee49a802f20 · outbound

This paper cites An atomistic insight into reactions and free-energy pro- files of NH3 and Ga on GaN surfaces during the epitaxial growth.Appl.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) An atomistic insight into reactions and free-energy pro- files of NH3 and Ga on GaN surfaces during the epitaxial growth.Appl

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.554722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00e85553-d142-4273-9e63-8011c2f6937e · outbound

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

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Generalized neural- network representation of high-dimensional potential- energy surfaces.Phys

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.593849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6472b39f-bde3-486b-bb54-d53866c110e8 · outbound

This paper cites Deringer, Miguel A.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Deringer, Miguel A

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.631006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95a05957-c42d-4635-b725-52c46b9529fb · outbound

This paper cites Mailoa, Mordechai Kornbluth, Nicola Molinari, Tess E.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Mailoa, Mordechai Kornbluth, Nicola Molinari, Tess E

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.680628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 605a6650-1a0c-48ee-a17a-a3886b391cb2 · outbound

This paper cites A universal graph deep learning interatomic potential for the periodic table.Nat.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) A universal graph deep learning interatomic potential for the periodic table.Nat

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.752405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76dec28b-0048-46ea-a8f2-09ceb853f034 · outbound

This paper cites an unresolved cited work.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.855897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61ca3b6b-bbd2-438e-a551-db07ce0ca560 · outbound

This paper cites Wood, Misko Dzamba, Xiang Fu, Meng Gao, Muhammed Shuaibi, Luis Barroso-Luque, Kareem Abdelmaqsoud, Vahe Gharakhanyan, John R.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Wood, Misko Dzamba, Xiang Fu, Meng Gao, Muhammed Shuaibi, Luis Barroso-Luque, Kareem Abdelmaqsoud, Vahe Gharakhanyan, John R

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:27.960855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3985d7a9-b01f-4844-ad6f-5f9aa157ee5a · outbound

This paper cites Le, and Paulette Clancy.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Le, and Paulette Clancy

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:28.009290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8122a54-020d-44d5-bcfb-b14b9492350d · outbound

This paper cites Clark, Matthew D.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Clark, Matthew D

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:28.049478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aaf2e59d-e554-4480-9862-7a6ae82f3ac3 · outbound

This paper cites Perdew, Kieron Burke, and Matthias Ernzerhof.

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:28.143967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e90f37a-e3f6-43cd-8067-b2596bc62360 · outbound

This paper cites Thompson, H.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Thompson, H

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:28.190035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2f5e3dc-783c-4596-93ae-f8d394563f51 · outbound

This paper cites Structural relaxation made simple.Phys.

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:28.226949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4ccb89a-65c3-4080-8e4f-8e19170bb850 · outbound

This paper cites The atomic simulation environment—a Python library for working with atoms.J.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) The atomic simulation environment—a Python library for working with atoms.J

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:28.315841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0ac6f95-b8c1-4be4-9839-1ee499fca59b · outbound

This paper cites Visualization and analysis of atom- istic simulation data with OVITO–the Open Visualiza- tion Tool.Modelling Simul.

Molecular dynamics with a first-principles-validated universal machine-learning potential reveals dynamic elementary processes of growth-related adspecies on GaN(0001) Visualization and analysis of atom- istic simulation data with OVITO–the Open Visualiza- tion Tool.Modelling Simul

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-30T21:41:28.395416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.