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Record W3215692850 · doi:10.1002/adfm.202108495

Conversion of 2D MXene to Multi‐Low‐Dimensional GerMXene Superlattice Heterostructure

2021· article· en· W3215692850 on OpenAlexafffund
Alireza Rafieerad, Ahmad Amiri, Weiang Yan, Hossein Eshghi, Sanjiv Dhingra

Bibliographic record

VenueAdvanced Functional Materials · 2021
Typearticle
Languageen
FieldMaterials Science
TopicMXene and MAX Phase Materials
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
FundersCanadian Institutes of Health ResearchUniversity of Manitoba
KeywordsHeterojunctionMaterials scienceSuperlatticeNanotechnologyQuantum dotTitanium carbideTitaniumOptoelectronicsMetallurgy

Abstract

fetched live from OpenAlex

Abstract Integration of 2D structures into other low‐dimensional materials results in the development of distinct van der Waals heterostructures (vdWHSs) with enhanced properties. However, obtaining 2D–1D–0D vdWHSs of technologically useful next generation materials, transition‐metal carbide MXene and monoelemental Xene nanosheets in a single superlattice heterostructure is still challenging. Here, the fabrication of a new multidimensional superlattice heterostructure “GerMXene” from exfoliated M 3 X 2 T x MXene and hydrogenated germanane (GeH) crystals, is reported. Direct experimental evidence for conversion of hydrothermally activated titanium carbide MXene (A‐MXene) to GerMXene heterostructure through the rapid and spontaneous formation of titanium germanide (TiGe 2 and Ti 6 Ge 5 ) bonds, is provided. The obtained GerMXene heterostructure possesses enhanced surface properties, aqueous dispersibility, and Dirac signature of embedded GeH nanosheets as well as quantum dots. GerMXene exhibits functional bioactivity, electrical conductivity, and negative surface charge, paving ways for its applications in biomedical field, electronics, and energy storage.

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), Insufficient 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 score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0190.001

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 head0.016
GPT teacher head0.252
Teacher spread0.236 · 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

Citations22
Published2021
Admission routes2
Has abstractyes

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