Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T19:24:31.664566Z
Paper Citation Record · LEDGER
Analysis of degradation in perovskite solar cells through physics-based machine learning
As of 18 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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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
Reference resolution
57 of 57 outbound references displayed
- verified exact1
- verified fuzzy46
- unresolved10
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation de7d10cb-7095-4508-b056-ac78d4e76ac6 · outbound
This paper cites De rerum natura: How do halide perovskites self-heal from damage?Advanced Materials, 38(21):e18808, 2026.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.504438Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1b985a79-fbc6-4a55-ad02-146fdbf9f049 · outbound
This paper cites Roadmap on established and emerging photovoltaics for sustainable energy conversion.J.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.489551Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 60c8549b-12bd-47d1-bb1b-35bb31367861 · outbound
This paper cites Eperon, Alessandro Virtuani, Quentin Jeangros, Dana B.
Analysis of degradation in perovskite solar cells through physics-based machine learning Eperon, Alessandro Virtuani, Quentin Jeangros, Dana B
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.475605Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 053a9c81-b989-4331-bf66-dd69479df7b8 · outbound
This paper cites Ion migration in perovskite solar cells.Nature Reviews Chemistry, pages 1–17, 2026.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.461163Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 623d12c8-32e0-444e-8637-7f010f3b2437 · outbound
This paper cites Nonradiative re- combination in perovskite solar cells: the role of interfaces.Advanced Materials, 31(52):1902762, 2019.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.447400Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 508b989d-2d97-4896-85f1-3d2ce044675a · outbound
This paper cites an unresolved cited work.
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 6
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T19:24:32.434218Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a32eb729-b511-44bc-9b00-2825eaeb22de · outbound
This paper cites The impact of interfacial quality and nanoscale performance disorder on the stability of alloyed perovskite solar cells.Nature Energy, 10(1):66–76, 2025.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.420427Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0c7f49a1-6bec-4ade-b50d-d8dc37e7e89c · outbound
This paper cites Challenges and opportunities for the characterization of electronic properties in halide perovskite solar cells.Chemical Science, 16(19):8153–8195, 2025.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.406490Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1cb4def9-d066-4c16-b83b-f6af17824081 · outbound
This paper cites How halide segregation governs the ion density evolution and ionic performance losses: From degradation to recovery.Advanced Energy Materials, page e03866, 2026.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.391749Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b82f6e50-1e6d-4f48-908d-d42299c763a1 · outbound
This paper cites an unresolved cited work.
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 10
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T19:24:32.378107Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation cabfccfe-9f00-4717-92fc-9f90581f48f4 · outbound
This paper cites O’Regan, and Piers R.F.
Analysis of degradation in perovskite solar cells through physics-based machine learning O’Regan, and Piers R.F
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.364829Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 66367a89-05c1-410e-bda3-99d799f8c3e8 · outbound
This paper cites Ion-induced field screening as a dominant factor in perovskite solar cell operational stability.Nature Energy, 9:1–13, 2024.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.351535Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation efae784e-83fd-40e8-8cdb-cc44982ca37b · outbound
This paper cites an unresolved cited work.
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 13
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T19:24:32.337110Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f3f2410f-0819-472f-92bf-44c916ca6651 · outbound
This paper cites Torre Cachafeiro and W Tress.
Analysis of degradation in perovskite solar cells through physics-based machine learning Torre Cachafeiro and W Tress
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.323525Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation cc702afe-af64-4e75-a5ae-49c089094e28 · outbound
This paper cites The curse(s) of dimensionality.Nat Methods, 15(15):399–400, 2018.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.309760Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6ea385ba-317b-4651-b702-7903ebdca84b · outbound
This paper cites Bayesian parameter estimation for characterising mobile ion vacancies in perovskite solar cells.Journal of Physics: Energy, 6:015005, 2023.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.296417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation cdc53913-c623-4295-b2e0-e546f6caae97 · outbound
This paper cites Taking control of ion transport in halide perovskite solar cells.ACS Energy Letters, 3(8):1983–1990, 2018.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.283039Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e254c620-ea64-4845-9185-cea53453e493 · outbound
This paper cites De Souza.
Analysis of degradation in perovskite solar cells through physics-based machine learning De Souza
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.269101Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6199108d-19f6-4ddb-bee2-dcedade9791f · outbound
This paper cites Mocanu, and M.
Analysis of degradation in perovskite solar cells through physics-based machine learning Mocanu, and M
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.255607Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4040c4a5-500b-4911-8845-1b8544e9a7aa · outbound
This paper cites American Chemical Society, 2022.
Analysis of degradation in perovskite solar cells through physics-based machine learning American Chemical Society, 2022
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.242171Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 679f8d3b-335c-49ff-970c-72f3be1f4723 · outbound
This paper cites Rombach, David P.
Analysis of degradation in perovskite solar cells through physics-based machine learning Rombach, David P
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.228452Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 020e08a2-1c0f-4d56-9303-c0d1f9bc3b9d · outbound
This paper cites Rapid parameter prediction in perovskite solar cells via ai-assisted performance analysis.ACS Energy Letters, 2026.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.213977Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0732681a-1767-4030-98f8-db163ef96ef2 · outbound
This paper cites Inversion of the impedance response towards physical parameter extraction using interpretable machine learning.Advanced Energy Materials, page e06352, 2026.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.199739Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e6b89563-11f3-41e7-a34e-c4db00e60087 · outbound
This paper cites Bayesian optimization approach to quantify the effect of input parameter uncertainty on predictions of numerical physics simulations.APL Machine Learning, 1(4), 2023.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.184946Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation bd7e418b-504d-46ff-8647-4ba872bd6ac8 · outbound
This paper cites Rayflare: flexible optical modelling of solar cells.Journal of Open Source Software, 6(65):3460, 2021.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.170994Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 3d6ba263-5828-44da-911c-c7706c008802 · outbound
This paper cites an unresolved cited work.
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 26
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T19:24:32.156900Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c6d57633-bf46-4a77-bf64-bef2e8553ca0 · outbound
This paper cites an unresolved cited work.
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 27
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T19:24:32.143435Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 664d7e6b-8696-4d8f-a5d6-8bec33c6555e · outbound
This paper cites Inverted hysteresis as a diagnostic tool for perovskite solar cells: Insights from the drift-diffusion model.Journal of Applied Physics, 133(9), 2023.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.129921Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b80c760e-628b-44cd-a8bd-a875ef8ea8e7 · outbound
This paper cites an unresolved cited work.
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 29
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T19:24:32.114870Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e7462fe2-fc51-4fe3-a2e8-89d446b5fc19 · outbound
This paper cites Understanding the full zoo of perovskite so- lar cell impedance spectra with the standard drift-diffusion model.Advanced Energy Materials, page 2400955, 2024.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.101385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b003bc83-3344-4db7-a27b-0e96ec09e841 · outbound
This paper cites an unresolved cited work.
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 31
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T19:24:32.087214Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 64ec226b-9ebc-4bb3-9f4f-bccd9018fb8a · outbound
This paper cites CreateSpace, United States, 3rd ed edition, 2013.
Analysis of degradation in perovskite solar cells through physics-based machine learning CreateSpace, United States, 3rd ed edition, 2013
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.073311Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 16cb8766-69f4-447a-acb0-77d5dfc4176d · outbound
This paper cites Multifunctional dual-interface layer enables efficient and stable inverted perovskite solar cells.Physical Chemistry Chemical Physics, 26(10):8299–8307, 2024.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.058861Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 105d6e82-ff86-4366-b123-2a1757532752 · outbound
This paper cites 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.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.043777Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d0db3985-49c8-41ea-a4a3-ab5a60c839db · outbound
This paper cites Kauf- mann, and Aldo Di Carlo.
Analysis of degradation in perovskite solar cells through physics-based machine learning Kauf- mann, and Aldo Di Carlo
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.028843Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9e5c7a0e-8702-4152-bb47-7c2a814a887c · outbound
This paper cites Hill, Matthew V.
Analysis of degradation in perovskite solar cells through physics-based machine learning Hill, Matthew V
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:32.013959Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation bae19d30-3058-4ef2-aeb8-c9cda296750c · outbound
This paper cites an unresolved cited work.
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 37
- Resolution
- verified exact
- doi, observed 2026-08-12T19:24:31.702947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4a41d316-8785-4cae-9e15-6d347d54cd7c · outbound
This paper cites an unresolved cited work.
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 38
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T19:24:31.998450Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 20866f2e-8b52-4a0a-9a09-40ef45e5e1af · outbound
This paper cites Cave, Nicola E.
Analysis of degradation in perovskite solar cells through physics-based machine learning Cave, Nicola E
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.983777Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1ac3147b-2571-4994-acc3-973094afb5a7 · outbound
This paper cites Understanding performance limiting interfacial recombination in pin perovskite solar cells.Advanced Energy Materials, 13:230313, 2023.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.969466Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a90ed578-30ab-4a8f-8cb1-ee3cd3a7ce5f · outbound
This paper cites Rombach, Akash Dasgupta, Manuel Kober-Czerny, et al.
Analysis of degradation in perovskite solar cells through physics-based machine learning Rombach, Akash Dasgupta, Manuel Kober-Czerny, et al
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.954870Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 5319c06a-60cd-4f74-84e0-f414537e90b3 · outbound
This paper cites Preventing phase segregation in mixed-halide per- ovskites: a perspective.Energy & Environmental Science, 13(7):2024–2046, 2020.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.940610Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 67d4093e-dcba-4331-ae34-cb3fca059ffc · outbound
This paper cites De Souza and Denis Barboni.
Analysis of degradation in perovskite solar cells through physics-based machine learning De Souza and Denis Barboni
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.926264Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6965d9e8-601b-421e-b045-9ddc8f70145e · outbound
This paper cites Defect chemistry of mixed ionic–electronic conductors under light: halide perovskites as a master example.Mater.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.912160Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 02bd5db4-3848-4907-87e7-eaae5d18ccd4 · outbound
This paper cites an unresolved cited work.
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 45
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T19:24:31.898594Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a196d0bc-20f9-4fa7-9c9d-3ec75e802c72 · outbound
This paper cites Electrical conductivity of halide perovskites follows expectations from classical defect chemistry.European Journal of Inorganic Chemistry, 2021(28):2882–2889, 2021.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.884819Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation dfb00fd9-5df3-41e1-9884-8cb77dc3211d · outbound
This paper cites Toolsets for assessing ionic migration in halide per- ovskites.Joule, 8(5):1239–1273, 2024.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.871233Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation eadf57a2-ee34-4a53-bbbe-38ce3a704bd8 · outbound
This paper cites Effect of thermal stress on the ion density and mobility distribution in perovskite solar cells.The Journal of Physical Chemistry Letters, 2026.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.857326Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation eaeb2ba9-d654-4fc9-b1a5-a103b6fbe631 · outbound
This paper cites Ionic-defect distribution revealed by improved evaluation of deep-level transient spectroscopy on perovskite solar cells.Physical Review Applied, 13(3):034018, 2020.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.842653Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 5d59e420-e6de-4d87-9b31-bc5ab49c693e · outbound
This paper cites How to tell the difference between a model and a digital twin.Advanced Modeling and Simulation in Engineering Sciences, 7:7–13, 2020.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.828219Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 696f61d5-3bee-4980-b18b-8e2eb58ec5c3 · outbound
This paper cites A fast and robust numerical scheme for solving models of charge carrier transport and ion vacancy motion in perovskite solar cells.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.813392Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6325e9bc-804d-4d04-b76f-6b93bdf8bd45 · outbound
This paper cites Substitution of lead with tin suppresses ionic transport in halide perovskite optoelectronics.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.798538Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 3a6e818a-40a9-4bf4-852c-3b3c1c89aa5f · outbound
This paper cites Avoid pitfalls in identi- fying perovskite grain size.The journal of physical chemistry letters, 13(31):7236–7242, 2022.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.783116Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation fa503479-2ed6-401b-95d8-c469f8373ce7 · outbound
This paper cites Light management in perovskite photovoltaic solar cells: A perspective.
Analysis of degradation in perovskite solar cells through physics-based machine learning Light management in perovskite photovoltaic solar cells: A perspective
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.767196Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 54851721-2033-4440-a38a-3e55a1482cf5 · outbound
This paper cites an unresolved cited work.
Analysis of degradation in perovskite solar cells through physics-based machine learning Unresolved cited work
Reference 55
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T19:24:31.751420Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1f856b38-8832-470f-89f1-488f554ae865 · outbound
This paper cites Functionalized substrates for reduced nonradiative recombination in metal-halide per- ovskites.The Journal of Physical Chemistry Letters, 16(1):372–377, 2025.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.735065Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 97665eea-c58c-4b25-b206-f47063058915 · outbound
This paper cites 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.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:24:31.719357Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Pith citing papers
No inbound Pith citation observations are available.