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Record W3012678162 · doi:10.1021/acsenergylett.0c00068

A Taxonomy for Three-Terminal Tandem Solar Cells

2020· article· en· W3012678162 on OpenAlexfundno aff
Emily L. Warren, William E. McMahon, Michael Rienäcker, Kaitlyn T. VanSant, Riley C. Whitehead, Robby Peibst, Adele C. Tamboli

Bibliographic record

VenueACS Energy Letters · 2020
Typearticle
Languageen
FieldEngineering
Topicsolar cell performance optimization
Canadian institutionsnot available
FundersInstitute of Gender and HealthOffice of Energy EfficiencyU.S. Department of EnergySolar Energy Technologies ProgramOffice of Energy Efficiency and Renewable EnergyBundesministerium für Wirtschaft und Energie
KeywordsTandemTerminal (telecommunication)Computer scienceSolar cellOptoelectronicsEngineeringMaterials scienceComputer networkAerospace engineering

Abstract

fetched live from OpenAlex

Tandem and multijunction solar cells offer the only demonstrated path to terrestrial 1-sun solar cell efficiency over 30%. Three-terminal tandem (3TT) solar cells can overcome some of the limitations of two-terminal and four-terminal tandem solar cell designs. However, the coupled nature of the cells adds a degree of complexity to the devices themselves and the ways that their performance can be measured and reported. While many different configurations of 3TT devices have been proposed, there is no standard taxonomy to discuss the device structure or loading topology. This Perspective proposes a taxonomy for 3TT solar cells to enable a common nomenclature for discussing these devices and their performance. It also provides a brief history of three-terminal devices in the literature and demonstrates that many different 3TT devices can work at efficiencies above 30% if properly designed.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0020.002
Scholarly communication0.0040.005
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.004

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 head0.017
GPT teacher head0.174
Teacher spread0.157 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations79
Published2020
Admission routes1
Has abstractyes

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