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Record W3024117197 · doi:10.1021/acsenergylett.0c00714

Decoupling Kinetics and Thermodynamics of Interfacial Catalysis at a Chemically Modified Black Silicon Semiconductor Photoelectrode

2020· article· en· W3024117197 on OpenAlexfundno aff
Caitlin M. Hanna, Ryan T. Pekarek, Elisa M. Miller, Jenny Y. Yang, Nathan R. Neale

Bibliographic record

VenueACS Energy Letters · 2020
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsnot available
FundersCanadian Institute for Advanced ResearchCamille and Henry Dreyfus FoundationAlfred P. Sloan FoundationU.S. Department of Energy
KeywordsSemiconductorSiliconCatalysisKineticsNanoporousElectrodeMaterials scienceDecoupling (probability)CobaltChemistryChemical physicsThermodynamicsChemical engineeringNanotechnologyPhysical chemistryInorganic chemistryOrganic chemistryOptoelectronics

Abstract

fetched live from OpenAlex

Understanding the interplay between the kinetics of interfacial catalytic reactions and the thermodynamics of an underlying semiconductor electrode is imperative for rational construction of efficient photoelectrocatalytic systems. Current understanding of the thermodynamic effects of molecular catalyst attachment to semiconductor electrodes is limited. We report the immobilization of a molecular cobalt bis(benzenedithiolate) proton reduction catalyst onto nanoporous black silicon (b-Si) electrodes through π–π interactions with a series of aromatic molecules covalently attached to the surface. Intensity-modulated high-frequency resistivity and linear sweep voltammetry measurements are used to show that the kinetics of proton reduction are decoupled from the thermodynamic properties of the underlying b-Si photoelectrode.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.201
Teacher spread0.192 · 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 designBench or experimental
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

Citations14
Published2020
Admission routes1
Has abstractyes

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