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Record W4285399173 · doi:10.1149/ma2022-0112853mtgabs

(Invited) Van Der Waals Growth and in Situ Studies of Two-Dimensional Pnictogens

2022· article· en· W4285399173 on OpenAlexaff
Oussama Moutanabbir, Matthieu Fortin‐Deschênes

Bibliographic record

VenueECS Meeting Abstracts · 2022
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsPolytechnique Montréal
Fundersnot available
Keywordsvan der Waals forceAntimonyPhase (matter)Materials sciencePhysicsNanotechnologyCrystallographyChemistryQuantum mechanicsMolecule

Abstract

fetched live from OpenAlex

With their ns2 np3 electron configuration and sp3 hybridization, pnictogens (N, P, As, Sb, Bi) form a unique class of elemental van der Waals (vdW) and two-dimensional (2D) materials. The layered allotropes and the wide range of atomic masses span by pnictogens endows them with a broad spectrum of electronic, optical, and topological properties. For instance, few-layer black phosphorus and arsenic have thickness-dependent direct bands spanning the visible and near infrared, as well anisotropic transport properties. On the other hand, 2D-Sb and 2D-Bi are predicted to exhibit several topological phase transitions near atomic thicknesses, as well as a high-mobility single layer semiconducting phase. Despite the important technological potential of 2D pnictogens, stability and synthesis challenges impede their integration in emerging technologies. This talk presents theoretical and real-time electron microscopy studies of the vdW growth and stability of 2D pnictogens [1-6]. The insights obtained from these studies lay the groundwork for the integration of this new class of 2D materials in emerging electronic, optoelectronic, and quantum technologies. References Fortin-Deschênes, H. Zschiesche, T. O. Menteş, A. Locatelli, R. Jacobberger, F. Genuzio, M. J. Lagos, D. Biswas, C. Jozwiak, J. A. Miwa, S. Ulstrup, A. Bostwick, E. Rotenberg, M. S. Arnold, G. A. Botton, O. Moutanabbir. Pnictogens Allotropy and Phase Transformation during van der Waals Growth. Nano Letters. 2020; 20 (11), 8258-8266. Fortin-Deschênes, O. Waller, Q. An, M. J. Lagos, G. Botton, H. Guo, O. Moutanabbir. 2D Antimony-Arsenic Alloys. Small. 2020; 16, 1906540. Fortin-Deschênes, R. M. Jacobberger, C. A. Deslauriers, O. Waller, É. Bouthillier, M. S. Arnold, O. Moutanabbir. Dynamics of Antimonene–Graphene Van Der Waals Growth. Advanced Materials. 2019; 1900569. Fortin-Deschênes, O. Moutanabbir. Recovering the Semiconductor Properties of the Epitaxial Group V 2D Materials Antimonene and Arsenene. The Journal of Physical Chemistry C. 2018; 122(16), 9162–9168. Fortin-Deschênes, O. Waller, T. O. Mentes, A. Locatelli, S. Mukherjee, F. Genuzio, P. Levesque, A. Hebert, R. Martel, O. Moutanabbir. Synthesis of Antimonene on Germanium. Nano Letters. 2017; 17(8), 4970–4975. Fortin-Deschênes, P. Levesque, R. Martel, O. Moutanabbir. Dynamics and mechanisms of exfoliated black phosphorus sublimation. The Journal of Physical Chemistry Letters. 2016; 7(9), 1667-1674.

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 score0.004
Threshold uncertainty score0.013

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)0.0040.001

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 head0.032
GPT teacher head0.291
Teacher spread0.259 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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