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Record W4400272648 · doi:10.1021/jacs.4c06187

Electrochemical Doping of Two-Dimensional Superatomic Materials

2024· article· en· W4400272648 on OpenAlexfundno aff
Shoushou He, Jessica Yu, William D. H. Stinson, Claire A. Looney, Saya Okuno, Andrew C. Crowther, Daniel V. Esposito, Michael L. Steigerwald, Xavier Roy, Colin Nuckolls

Bibliographic record

VenueJournal of the American Chemical Society · 2024
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsnot available
FundersAir Force Office of Scientific ResearchDivision of Materials ResearchNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryElectrochemistryDopingNanotechnologyPhysical chemistryCondensed matter physicsElectrode

Abstract

fetched live from OpenAlex

We report an electrochemical method for doping two-dimensional (2D) superatomic semiconductor Re 6 Se 8 Cl 2 that significantly improves the material’s electrical transport while retaining the in-plane and stacking structures. The electrochemical reduction induces the complete dissociation of chloride anions from the surface of each superatomic nanosheet. After the material is dehalogenated, we observe the electrical conductivity ( σ ) increases by two orders of magnitude while the 3D electron carrier density ( n 3D ) increases by three orders of magnitude. In addition, the thermal activation energy ( E a ) and electron mobility ( μ e ) decrease. We conclude that we have achieved effective electron-doping in 2D superatomic Re 6 Se 8 Cl 2, which significantly improves the electrical transport properties. Our work sets the foundation for electrochemically doping and tuning the transport properties of other 2D superatomic materials.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.310

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 head0.009
GPT teacher head0.272
Teacher spread0.263 · 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 teacher head, 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

Citations2
Published2024
Admission routes1
Has abstractyes

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