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Record W4391743724 · doi:10.1002/wene.508

Bio‐based materials for solar cells

2024· article· en· W4391743724 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWiley Interdisciplinary Reviews Energy and Environment · 2024
Typearticle
Languageen
FieldEngineering
Topicsolar cell performance optimization
Canadian institutionsUniversity of British Columbia
FundersH2020 European Research CouncilHorizon 2020 Framework ProgrammeNordForskSuomen KulttuurirahastoLuonnontieteiden ja Tekniikan Tutkimuksen ToimikuntaAalto-Yliopisto
KeywordsPhotovoltaic systemSustainabilityPhotovoltaicsSolar energyRenewable energyEnergy harvestingProcess engineeringBiochemical engineeringSystems engineeringComputer scienceNanotechnologyEnvironmental scienceEngineeringEnergy (signal processing)Materials scienceElectrical engineeringPhysicsEcology

Abstract

fetched live from OpenAlex

Abstract Plant‐based materials are emerging as an alternative to conventional components in advanced energy applications. Among these, energy harvesting from sunlight is highly attractive and, in fact, represents the fastest growing energy technology. This review addresses the broad field of solar cell science since plant‐based components can be utilized in almost all solar technologies, and in certain photovoltaic technologies, they can fulfill most of the roles in photovoltaic devices. There is strengthened recent interest in developing sustainable materials options as well as new functionalities being developed for bio‐based materials. This contribution describes the different options for plant‐derived materials in photovoltaics and discusses their deployment feasibility. We focus on performance, lifetime, and embedded energy, all of which are critical to achieve—economically and sustainably–competitive photovoltaic devices. We address the tendency in the current literature for greenwashing, given that not all plant‐based solutions are environmentally‐sound at the device level. On the other hand, plant‐based materials can offer functionalities that cannot be reached with currently used materials. This article is categorized under: Sustainable Energy > Solar Energy Emerging Technologies > Materials Sustainable Energy > Bioenergy

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.803
Threshold uncertainty score0.697

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.225
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it