MétaCan
Menu
Back to cohort
Record W2178331097 · doi:10.1002/celc.201500463

Low‐Temperature Synthesis and Electrochemical Properties of Mesoporous Titanium Oxysulfides

2015· article· en· W2178331097 on OpenAlexaff
Luke A. C. Smith, Michel L. Trudeau, Manon Provencher, Mark E. B. Smith, David M. Antonelli

Bibliographic record

VenueChemElectroChem · 2015
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsHydro-Québec
FundersEngineering and Physical Sciences Research CouncilUniversity of South Wales
KeywordsMaterials scienceMesoporous materialElectrochemistryTitaniumPorosityConductivityThermal conductivityDopingChemical engineeringOxideSpecific surface areaThermal stabilityComposite materialMetallurgyElectrodeChemistryCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract This paper describes the synthesis and electrochemical properties of mesoporous titanium oxysulfides prepared through the chemical treatment of pristine mesoporous titanium oxide under various synthesis conditions. The materials were doped with sulfur by using hexamethyldisilathiane (HMDST), a strategy that was developed to improve the conductivity of the material, whilst also retaining the porosity and thermal stability. Varying amounts of HMDST and different synthesis temperatures were tested to optimize the surface area and electrochemical performance. Lower temperatures generally yielded materials with superior properties and, even though the conductivity was improved by using higher loading levels of HMDST, it also led to a drop in initial capacity at the highest synthesis temperature of 200 °C (137–41 mAh g −1 ). The best performing material was, thus, synthesized by using the highest level of HMDST (3.5 mL) at lower heating temperatures (100–150 °C). This set of conditions maximizes the combination of surface area, initial capacity, conductivity, and capacity retention, the latter of which was notably superior to that of the pristine material (81 vs. 35 %), emphasizing the overall success of this doping strategy in improving the electrochemical properties of these otherwise insulating materials.

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 score0.602

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 head0.016
GPT teacher head0.209
Teacher spread0.192 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueChemElectroChemSame topicSupercapacitor Materials and FabricationFrench-language works237,207