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Record W3212332402 · doi:10.1039/d1cs00577d

Dynamics of photoconversion processes: the energetic cost of lifetime gain in photosynthetic and photovoltaic systems

2021· review· en· W3212332402 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemical Society Reviews · 2021
Typereview
Languageen
FieldEngineering
Topicsolar cell performance optimization
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of CanadaHorizon 2020 Framework Programme
KeywordsPhotovoltaic systemKinetic energyPhotosynthesisEnergy (signal processing)Solar energyDynamics (music)Simple (philosophy)PhysicsMaterials scienceChemical physicsChemistryEngineeringClassical mechanicsElectrical engineering

Abstract

fetched live from OpenAlex

The continued development of solar energy conversion technologies relies on an improved understanding of their limitations. In this review, we focus on a comparison of the charge carrier dynamics underlying the function of photovoltaic devices with those of both natural and artificial photosynthetic systems. The solar energy conversion efficiency is determined by the product of the rate of generation of high energy species (charges for solar cells, chemical fuels for photosynthesis) and the energy contained in these species. It is known that the underlying kinetics of the photophysical and charge transfer processes affect the production yield of high energy species. Comparatively little attention has been paid to how these kinetics are linked to the energy contained in the high energy species or the energy lost in driving the forward reactions. Here we review the operational parameters of both photovoltaic and photosynthetic systems to highlight the energy cost of extending the lifetime of charge carriers to levels that enable function. We show a strong correlation between the energy lost within the device and the necessary lifetime gain, even when considering natural photosynthesis alongside artificial systems. From consideration of experimental data across all these systems, the emprical energetic cost of each 10-fold increase in lifetime is 87 meV. This energetic cost of lifetime gain is approx. 50% greater than the 59 meV predicted from a simple kinetic model. Broadly speaking, photovoltaic devices show smaller energy losses compared to photosynthetic devices due to the smaller lifetime gains needed. This is because of faster charge extraction processes in photovoltaic devices compared to the complex multi-electron, multi-proton redox reactions that produce fuels in photosynthetic devices. The result is that in photosynthetic systems, larger energetic costs are paid to overcome unfavorable kinetic competition between the excited state lifetime and the rate of interfacial reactions. We apply this framework to leading examples of photovoltaic and photosynthetic devices to identify kinetic sources of energy loss and identify possible strategies to reduce this energy loss. The kinetic and energetic analyses undertaken are applicable to both photovoltaic and photosynthetic systems allowing for a holistic comparison of both types of solar energy conversion approaches.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.723
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.257
Teacher spread0.237 · 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