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Record W2785626989 · doi:10.1039/c8ta00173a

High-throughput theoretical optimization of the hydrogen evolution reaction on MXenes by transition metal modification

2018· article· en· W2785626989 on OpenAlexaff
Pengkun Li, Jinguo Zhu, Albertus D. Handoko, Ruifeng Zhang, Haotian Wang, Dominik Legut, Xiaodong Wen, Zhongheng Fu, Zhi Wei Seh, Qianfan Zhang

Bibliographic record

VenueJournal of Materials Chemistry A · 2018
Typearticle
Languageen
FieldMaterials Science
TopicMXene and MAX Phase Materials
Canadian institutionsFPInnovations
FundersEuropean Regional Development FundProgram for New Century Excellent Talents in UniversityChinese Academy of SciencesRowland Institute at HarvardMinistry of Human Resources and Social SecurityNational Natural Science Foundation of ChinaNational Research Foundation Singapore
KeywordsMXenesElectrocatalystRaw materialHydrogenThroughputBiochemical engineeringClean energyNanotechnologyMaterials scienceChemistryEnvironmental scienceComputer scienceEngineeringPhysical chemistryEnvironmental protectionTelecommunicationsOrganic chemistry

Abstract

fetched live from OpenAlex

Electrocatalysis has the potential to become a more sustainable approach to generate hydrogen as a clean energy source and chemical feedstock.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.245
Teacher spread0.233 · 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 designSimulation or modeling
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

Citations240
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Materials Chemistry ASame topicMXene and MAX Phase MaterialsFrench-language works237,207