MétaCan
Menu
Back to cohort
Record W4389475241 · doi:10.1021/acs.inorgchem.3c02841

Synthesis, Characterization, and Single-Crystal X-ray Structures of Refractory Metal Compounds as Precursors for the Single-Source Chemical Vapor Deposition of Metal Nitrides

2023· article· en· W4389475241 on OpenAlexafffund
Kieran G. Lawford, Michael A. Land, Eden Goodwin, Katherine N. Robertson, Seán T. Barry

Bibliographic record

VenueInorganic Chemistry · 2023
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsSaint Mary's UniversityCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Ontario
KeywordsChemistryChemical vapor depositionThermogravimetric analysisMolybdenumVanadiumNitrideTungstenSingle crystalInorganic chemistryMetalNiobiumOrganic chemistryCrystallography

Abstract

fetched live from OpenAlex

The chemical vapor deposition of refractory metal nitrides requires volatile precursors and has previously been achieved by using metal complexes containing a variety of imide ligands. Recently, the 1,4-di- tert -butyl-1,3-diazabutadiene (DAD) adduct of bis( tert -butylimide)dichloridemolybdenum(VI) was shown to be an excellent precursor for the single-source CVD of Mo 2 N thin films. Leveraging the success of this work, we prepared chromium and tungsten compounds with the same framework. Additionally, the framework has been modified slightly to allow the isolation of mono( tert -butylimide)trichloride complexes of vanadium, niobium, tantalum, and molybdenum(V) to extend the search for new vapor-phase precursors. These compounds were all fully characterized using the standard methods of multinuclear magnetic resonance spectroscopy, combustion analysis, and single-crystal X-ray diffraction. Their thermal properties were determined by using thermogravimetric analysis and differential scanning colorimetry to assess their utility as vapor-phase precursors. Finally, preliminary deposition studies were carried out to investigate their potential as single-source CVD precursors.

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 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 score0.620

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.013
GPT teacher head0.206
Teacher spread0.193 · 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

Citations5
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueInorganic ChemistrySame topicSemiconductor materials and devicesFrench-language works237,207