Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T19:24:31.664566Z
Paper Citation Record · LEDGER
As of 16 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2608.10691.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T19:24:31.664566Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
57 of 57 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation de7d10cb-7095-4508-b056-ac78d4e76ac6 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning De rerum natura: How do halide perovskites self-heal from damage?Advanced Materials, 38(21):e18808, 2026
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1b985a79-fbc6-4a55-ad02-146fdbf9f049 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Roadmap on established and emerging photovoltaics for sustainable energy conversion.J
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 60c8549b-12bd-47d1-bb1b-35bb31367861 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Eperon, Alessandro Virtuani, Quentin Jeangros, Dana B
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 053a9c81-b989-4331-bf66-dd69479df7b8 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Ion migration in perovskite solar cells.Nature Reviews Chemistry, pages 1–17, 2026
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 623d12c8-32e0-444e-8637-7f010f3b2437 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Nonradiative re- combination in perovskite solar cells: the role of interfaces.Advanced Materials, 31(52):1902762, 2019
Reference 5
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 508b989d-2d97-4896-85f1-3d2ce044675a · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a32eb729-b511-44bc-9b00-2825eaeb22de · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning The impact of interfacial quality and nanoscale performance disorder on the stability of alloyed perovskite solar cells.Nature Energy, 10(1):66–76, 2025
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 0c7f49a1-6bec-4ade-b50d-d8dc37e7e89c · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Challenges and opportunities for the characterization of electronic properties in halide perovskite solar cells.Chemical Science, 16(19):8153–8195, 2025
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1cb4def9-d066-4c16-b83b-f6af17824081 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning How halide segregation governs the ion density evolution and ionic performance losses: From degradation to recovery.Advanced Energy Materials, page e03866, 2026
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b82f6e50-1e6d-4f48-908d-d42299c763a1 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 10
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation cabfccfe-9f00-4717-92fc-9f90581f48f4 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning O’Regan, and Piers R.F
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 66367a89-05c1-410e-bda3-99d799f8c3e8 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Ion-induced field screening as a dominant factor in perovskite solar cell operational stability.Nature Energy, 9:1–13, 2024
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation efae784e-83fd-40e8-8cdb-cc44982ca37b · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation f3f2410f-0819-472f-92bf-44c916ca6651 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Torre Cachafeiro and W Tress
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation cc702afe-af64-4e75-a5ae-49c089094e28 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning The curse(s) of dimensionality.Nat Methods, 15(15):399–400, 2018
Reference 15
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6ea385ba-317b-4651-b702-7903ebdca84b · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Bayesian parameter estimation for characterising mobile ion vacancies in perovskite solar cells.Journal of Physics: Energy, 6:015005, 2023
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation cdc53913-c623-4295-b2e0-e546f6caae97 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Taking control of ion transport in halide perovskite solar cells.ACS Energy Letters, 3(8):1983–1990, 2018
Reference 17
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e254c620-ea64-4845-9185-cea53453e493 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning De Souza
Reference 18
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6199108d-19f6-4ddb-bee2-dcedade9791f · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Mocanu, and M
Reference 19
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 4040c4a5-500b-4911-8845-1b8544e9a7aa · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning American Chemical Society, 2022
Reference 20
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 679f8d3b-335c-49ff-970c-72f3be1f4723 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Rombach, David P
Reference 21
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 020e08a2-1c0f-4d56-9303-c0d1f9bc3b9d · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Rapid parameter prediction in perovskite solar cells via ai-assisted performance analysis.ACS Energy Letters, 2026
Reference 22
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 0732681a-1767-4030-98f8-db163ef96ef2 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Inversion of the impedance response towards physical parameter extraction using interpretable machine learning.Advanced Energy Materials, page e06352, 2026
Reference 23
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e6b89563-11f3-41e7-a34e-c4db00e60087 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Bayesian optimization approach to quantify the effect of input parameter uncertainty on predictions of numerical physics simulations.APL Machine Learning, 1(4), 2023
Reference 24
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation bd7e418b-504d-46ff-8647-4ba872bd6ac8 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Rayflare: flexible optical modelling of solar cells.Journal of Open Source Software, 6(65):3460, 2021
Reference 25
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3d6ba263-5828-44da-911c-c7706c008802 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 26
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c6d57633-bf46-4a77-bf64-bef2e8553ca0 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 27
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 664d7e6b-8696-4d8f-a5d6-8bec33c6555e · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Inverted hysteresis as a diagnostic tool for perovskite solar cells: Insights from the drift-diffusion model.Journal of Applied Physics, 133(9), 2023
Reference 28
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b80c760e-628b-44cd-a8bd-a875ef8ea8e7 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e7462fe2-fc51-4fe3-a2e8-89d446b5fc19 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Understanding the full zoo of perovskite so- lar cell impedance spectra with the standard drift-diffusion model.Advanced Energy Materials, page 2400955, 2024
Reference 30
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b003bc83-3344-4db7-a27b-0e96ec09e841 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 31
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 64ec226b-9ebc-4bb3-9f4f-bccd9018fb8a · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning CreateSpace, United States, 3rd ed edition, 2013
Reference 32
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 16cb8766-69f4-447a-acb0-77d5dfc4176d · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Multifunctional dual-interface layer enables efficient and stable inverted perovskite solar cells.Physical Chemistry Chemical Physics, 26(10):8299–8307, 2024
Reference 33
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 105d6e82-ff86-4366-b123-2a1757532752 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Solution-processed metal-oxide nanoparticles to prevent the sputtering damage in perovskite/silicon tandem solar cells.ACS Applied Materials & Interfaces, 17(11):17599–17610, 2025
Reference 34
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d0db3985-49c8-41ea-a4a3-ab5a60c839db · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Kauf- mann, and Aldo Di Carlo
Reference 35
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 9e5c7a0e-8702-4152-bb47-7c2a814a887c · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Hill, Matthew V
Reference 36
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation bae19d30-3058-4ef2-aeb8-c9cda296750c · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 37
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 4a41d316-8785-4cae-9e15-6d347d54cd7c · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 38
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 20866f2e-8b52-4a0a-9a09-40ef45e5e1af · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Cave, Nicola E
Reference 39
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1ac3147b-2571-4994-acc3-973094afb5a7 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Understanding performance limiting interfacial recombination in pin perovskite solar cells.Advanced Energy Materials, 13:230313, 2023
Reference 40
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a90ed578-30ab-4a8f-8cb1-ee3cd3a7ce5f · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Rombach, Akash Dasgupta, Manuel Kober-Czerny, et al
Reference 41
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5319c06a-60cd-4f74-84e0-f414537e90b3 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Preventing phase segregation in mixed-halide per- ovskites: a perspective.Energy & Environmental Science, 13(7):2024–2046, 2020
Reference 42
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 67d4093e-dcba-4331-ae34-cb3fca059ffc · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning De Souza and Denis Barboni
Reference 43
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6965d9e8-601b-421e-b045-9ddc8f70145e · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Defect chemistry of mixed ionic–electronic conductors under light: halide perovskites as a master example.Mater
Reference 44
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 02bd5db4-3848-4907-87e7-eaae5d18ccd4 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 45
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a196d0bc-20f9-4fa7-9c9d-3ec75e802c72 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Electrical conductivity of halide perovskites follows expectations from classical defect chemistry.European Journal of Inorganic Chemistry, 2021(28):2882–2889, 2021
Reference 46
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation dfb00fd9-5df3-41e1-9884-8cb77dc3211d · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Toolsets for assessing ionic migration in halide per- ovskites.Joule, 8(5):1239–1273, 2024
Reference 47
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation eadf57a2-ee34-4a53-bbbe-38ce3a704bd8 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Effect of thermal stress on the ion density and mobility distribution in perovskite solar cells.The Journal of Physical Chemistry Letters, 2026
Reference 48
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation eaeb2ba9-d654-4fc9-b1a5-a103b6fbe631 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Ionic-defect distribution revealed by improved evaluation of deep-level transient spectroscopy on perovskite solar cells.Physical Review Applied, 13(3):034018, 2020
Reference 49
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5d59e420-e6de-4d87-9b31-bc5ab49c693e · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning How to tell the difference between a model and a digital twin.Advanced Modeling and Simulation in Engineering Sciences, 7:7–13, 2020
Reference 50
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 696f61d5-3bee-4980-b18b-8e2eb58ec5c3 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning A fast and robust numerical scheme for solving models of charge carrier transport and ion vacancy motion in perovskite solar cells
Reference 51
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6325e9bc-804d-4d04-b76f-6b93bdf8bd45 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Substitution of lead with tin suppresses ionic transport in halide perovskite optoelectronics
Reference 52
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3a6e818a-40a9-4bf4-852c-3b3c1c89aa5f · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Avoid pitfalls in identi- fying perovskite grain size.The journal of physical chemistry letters, 13(31):7236–7242, 2022
Reference 53
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation fa503479-2ed6-401b-95d8-c469f8373ce7 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Light management in perovskite photovoltaic solar cells: A perspective
Reference 54
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 54851721-2033-4440-a38a-3e55a1482cf5 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 55
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1f856b38-8832-470f-89f1-488f554ae865 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning Functionalized substrates for reduced nonradiative recombination in metal-halide per- ovskites.The Journal of Physical Chemistry Letters, 16(1):372–377, 2025
Reference 56
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 97665eea-c58c-4b25-b206-f47063058915 · outbound
Analysis of degradation in perovskite solar cells through physics-based machine learning 30 (a) (b) (c) Figure A.6: QFLS,qV oc and their difference, in eV, from open-circuit IonMonger runs for combina- tions of interface recombination velocity values
Reference 57
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
No inbound Pith citation observations are available.