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Record W2014461991 · doi:10.1038/srep07131

Impact of lattice distortion and electron doping on α-MoO3 electronic structure

2014· article· en· W2014461991 on OpenAlexaff
Pengru Huang, Yao He, Chao Cao, Zheng‐Hong Lu

Bibliographic record

VenueScientific Reports · 2014
Typearticle
Languageen
FieldMaterials Science
TopicTransition Metal Oxide Nanomaterials
Canadian institutionsUniversity of Toronto
FundersNational Key Research and Development Program of ChinaProgram for New Century Excellent Talents in UniversityApplied Basic Research Foundation of Yunnan ProvinceNational Natural Science Foundation of ChinaYunnan UniversityMinistry of Science and Technology of the People's Republic of China
KeywordsDopingBand gapMaterials scienceElectronic band structureCondensed matter physicsLattice (music)Distortion (music)ElectronOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

Band structure of transition metal oxides plays a critical role in many applications such as photo-catalysis, photovoltaics, and electroluminescent devices. In this work we report findings that the band structure of MoO3 can be significantly altered by a distortion in the octahedral coordination structure. We discovered that, in addition to epitaxial type of structural strain, chemical force such as hydrogen inclusion can also cause extended lattice distortion. The lattice distortion in hydrogenated MoO3 led to a significant reduction of the energy gap, overshadowing the Moss-Burstein effect of band filling. Charge doping simulations revealed that filling of conduction band drives the lattice distortion. This suggests that any charge transfer or n-type electron doping could lead to lattice distortion and consequentially a reduction in energy gap.

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)0.0010.000

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 head0.006
GPT teacher head0.262
Teacher spread0.255 · 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

Citations148
Published2014
Admission routes1
Has abstractyes

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Same venueScientific ReportsSame topicTransition Metal Oxide NanomaterialsFrench-language works237,207