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Record W2807932825 · doi:10.1039/c8cp02470g

Two-dimensional pentagonal CrX (X = S, Se or Te) monolayers: antiferromagnetic semiconductors for spintronics and photocatalysts

2018· article· en· W2807932825 on OpenAlexaff
Wenzhou Chen, Yoshiyuki Kawazoe, Xingqiang Shi, Hui Pan

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2018
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsHatch (Canada)
FundersJapan Society for the Promotion of ScienceOffice of Naval Research GlobalUniversidade de MacauNational Natural Science Foundation of China
KeywordsSpintronicsMonolayerMagnetismAntiferromagnetismMaterials scienceSemiconductorIonic bondingBand gapPhotocatalysisNanotechnologyCondensed matter physicsOptoelectronicsChemistryFerromagnetismPhysicsCatalysis

Abstract

fetched live from OpenAlex

Two dimensional (2D) materials with hexagonal building blocks have received tremendous interest in recent years and show promise as nanoscale devices for versatile applications. Herein, we propose a new family of 2D pentagonal CrX (X = S, Se or Te) monolayers (penta-CrX) for applications in electronics, spintronics and photocatalysis. We find that the 2D penta-CrX monolayers are thermally, structurally and mechanically stable. The penta-CrX monolayers are antiferromagnetic and semiconducting. We show that the magnetism is attributed to the super-exchange induced by the ionic interactions between the Cr and X atoms and can be enhanced upon applying tension. We further show that the penta-CrS and penta-CrSe monolayers show good redox potentials versus a normal hydrogen electrode, and their band gaps are comparable to the energy of a photon in the visible light region, indicating their capability of maximal utilization of solar energy for water splitting. With intrinsic semiconducting and controllable magnetic properties, the proposed penta-CrX monolayers may hold promise as flexible spintronics and photocatalysts.

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 categoriesMeta-epidemiology (narrow)
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 score0.012
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 studies0.0000.001
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 head0.027
GPT teacher head0.301
Teacher spread0.274 · 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

Citations33
Published2018
Admission routes1
Has abstractyes

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