MétaCan
Menu
Back to cohort
Record W3087620914 · doi:10.1038/s41699-020-00175-z

Synthesis of epitaxial monolayer Janus SPtSe

2020· article· en· W3087620914 on OpenAlexfundno aff

Bibliographic record

Venuenpj 2D Materials and Applications · 2020
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsnot available
FundersEquipexEuropean Synchrotron Radiation FacilityAgence Nationale de la RechercheOttawa Hospital Research Institute
KeywordsChalcogenJanusMonolayerIsostructuralRecrystallization (geology)Transition metalEpitaxyvan der Waals force

Abstract

fetched live from OpenAlex

Abstract Janus single-layer transition metal dichalcogenides, in which the two chalcogen layers have a different chemical nature, push chemical composition control beyond what is usually achievable with van der Waals heterostructures. Here, we report such a Janus compound, SPtSe, which is predicted to exhibit strong Rashba spin–orbit coupling. We synthetized it by conversion of a single-layer of PtSe2 on Pt(111) via sulfurization under H2S atmosphere. Our in situ and operando structural analysis with grazing incidence synchrotron X-ray diffraction reveals the process by which the Janus alloy forms. The crystalline long-range order of the as-grown PtSe2 monolayer is first lost due to thermal annealing. A subsequent recrystallization in presence of a source of sulfur yields a highly ordered SPtSe alloy, which is isostructural to the pristine PtSe2. The chemical composition is resolved, layer-by-layer, using angle-resolved X-ray photoelectron spectroscopy, demonstrating that Se-by-S substitution occurs selectively in the topmost chalcogen layer.

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 score0.004

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)0.0010.001

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 head0.019
GPT teacher head0.243
Teacher spread0.224 · 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

Citations133
Published2020
Admission routes1
Has abstractyes

Explore more

Same venuenpj 2D Materials and ApplicationsSame topic2D Materials and ApplicationsFrench-language works237,207