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Record W4392658396 · doi:10.1021/acs.langmuir.3c03411

Recent Progress of Solid–Liquid Interface-Mediated Contact-Electro-Catalysis

2024· article· en· W4392658396 on OpenAlexaff
Zhixiang Chen, Yi Lu, Ruolan Hong, Zijun Liang, Leyan Wen, Xinyi Liu, Qingxia Liu

Bibliographic record

VenueLangmuir · 2024
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
FundersNational Natural Science Foundation of ChinaShenzhen Technology University
KeywordsInterface (matter)CatalysisSolid surfaceNanotechnologyMaterials scienceChemistryContact angleChemical engineeringChemical physicsOrganic chemistryEngineeringComposite materialSessile drop technique

Abstract

fetched live from OpenAlex

Contact electrification (CE) is a common physical process by which triboelectric charges are generated through the mutual contact between two objects. Despite the ongoing debates on CE’s mechanism, recent advancements in technology have elucidated the primary role of electron transfer in most CE processes. This discovery leads to the spawning of an emerging field, known as contact-electro-catalysis (CEC), which utilizes the electron transfer phenomenon during CE to initiate CEC. In this work, we provide the first comprehensive review of the recent progress of the solid–liquid interface-mediated CEC process, including its working principles, relationship with surface science, recent breakthroughs in applications, and future challenges. We aim to provide fundamental guidance for researchers to understand the reaction mechanism of the CEC process and to propose potential pathways to enhance CEC efficiency from a surface and interfacial science perspective. Later, recent application scenarios using the novel CEC techniques are summarized, including wastewater treatment, efficient generation of hydrogen peroxide (H 2 O 2 ), lithium-ion battery recycling, and CO 2 reduction. In general, CEC technology has opened a new avenue for catalysis, effectively expanding the range of catalyst options and holding promise as a solution to a variety of complex catalytic challenges in the future.

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 categoriesInsufficient payload (model declined to judge)
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 score0.191
Threshold uncertainty score1.000

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)0.0010.000

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 head0.281
Teacher spread0.272 · 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.

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

Citations24
Published2024
Admission routes1
Has abstractyes

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