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p-Type vdW Semiconductor CrSCl Featuring Multipolarity Coexistence

2025· article· en· W4406708238 on OpenAlexaff
Yong Wang, Dingyi Yang, Shaopeng Wang, Wei Xu, Yu Zhang, Tarnjit Kaur Johal, Yongjie Xu, Yihan Zhang, Yin Zhang, Wubin Bai, Yizhang Wu, Yue Hao

Bibliographic record

VenueACS Materials Letters · 2025
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Science Basic Research Program of Shaanxi ProvinceNational Postdoctoral Program for Innovative TalentsXidian UniversityChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsSemiconductorType (biology)Condensed matter physicsMaterials sciencePhysicsOptoelectronicsGeologyPaleontology

Abstract

fetched live from OpenAlex

Multipolar materials represent a paradigm shift in energy conversion, nonvolatile memory, and multifunctional sensing, enabling innovative, compact, and energy-efficient devices. However, achieving multipolarity in a single material is challenging due to often conflicting structural and electronic requirements. Herein, for the first time, we synthesized a p-type vdW semiconductor CrSCl featuring the coexistence of piezoelectricity and ferromagnetism. The carrier mobility of CrSCl at room temperature was found to be approximately 473.7 cm 2 v –1 s –1 . Few-layer CrSCl crystals exhibit stable intrinsic magnetic order and effective piezoelectric coefficients. Theoretical calculations confirm that the magnetic properties of the CrSCl stem from its (a 1 ) ↑ 1 (1e) ↑ 2 electron configuration and verify the stability of the ferromagnetic ground-state. The novel material CrSCl, a 2D ferromagnetic semiconductor with piezoelectric properties, enriches the class of transition-metal-based sulfide halides and provides a robust foundation for developing scalable 2D magnetic spintronics devices.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 integrity0.0000.000
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 head0.018
GPT teacher head0.270
Teacher spread0.252 · 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

Citations12
Published2025
Admission routes1
Has abstractyes

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