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Record W2804911248 · doi:10.1149/ma2018-01/10/883

(Invited) Quasi-Two-Dimensional Thermoelectricity in Snse

2018· article· en· W2804911248 on OpenAlexaff
Thomas Szkopek, G. Gervais, Alexander Grueneis

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Thermoelectric Materials and Devices
Canadian institutionsMcGill University
Fundersnot available
KeywordsSeebeck coefficientThermoelectric effectCondensed matter physicsDopingSemiconductorMaterials scienceThermoelectric materialsSelenideSpectroscopyOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

Stannous selenide is a layered semiconductor with a puckered honeycomb lattice that constitutes a polar analogue of black phosphorus, and of great interest as a thermoelectric material [1-3]. Hole doped SnSe supports a large Seebeck coefficient at high conductivity. We combine experimental techniques in the form of angle resolved photo-emission spectroscopy, optical reflection spectroscopy and magnetotransport measurements to map out a multiple-valley valence band structure and a quasi two-dimensional dispersion. The quasi two-dimensional dispersion realizes the low-dimensional Hicks-Dresselhaus thermoelectric, which contributes to the high Seebeck coefficient reported at high carrier density [1-2]. We further demonstrate that the hole accumulation layer in exfoliated SnSe transistors exhibits a field effect mobility of up to 250 cm 2 /Vs at T=1.3 K. Unintentional hole doping and persistent photoconductivity has been observed, suggesting material quality can be further improved. SnSe is thus found to be a high quality, quasi two-dimensional semiconductor. References: [1] L.-D. Zhao et al., Nature 508 , 373 (2014). [2] L.-D. Zhao et al., Science 351 , 141 (2016). [3] C. W. Li et al., Nature Phys. 11 , 1063 (2015).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.019
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.001

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 head0.015
GPT teacher head0.266
Teacher spread0.251 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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