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Record W4391874964 · doi:10.1002/9781119600862.ch7

Utilizing the Band Diagram Framework to Interpret the Operation of Photoelectrochemical Cells

2024· other· en· W4391874964 on OpenAlexaff
Kirk H. Bevan, Botong Miao, Asif Iqbal

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicGas Sensing Nanomaterials and Sensors
Canadian institutionsMcGill University
Fundersnot available
KeywordsBand diagramDiagramComputer scienceOptoelectronicsMaterials scienceBand gapDatabase

Abstract

fetched live from OpenAlex

In this chapter, the authors explore the fundamental semiconductor concepts, which underpin the operation of photoelectrochemical (PEC) devices. They aim to demonstrate how the current–voltage characteristics of PEC devices can be understood by utilizing the “band diagram” methodology commonly applied in the semiconductor device community. The authors also overview the underlying assumptions present in the band diagram framework. A short summary of reference electrodes is also provided. This discussion is then extended to illuminated PEC devices through an exploration of two analytical models. The authors explore how the operation of PEC devices can be further understood through the use of semiclassical device modeling. Concepts pertaining to the photovoltage and current–voltage characteristics are explained with the aid of numerically calculated band diagrams. To illustrate all of these concepts clearly, an emphasis is placed on analyzing photoanodes.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.005
GPT teacher head0.213
Teacher spread0.208 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations2
Published2024
Admission routes1
Has abstractyes

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