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Record W3194002813 · doi:10.22452/mnij.vol1no1.6

Microwave-Assisted Synthesized Gadolinium Doped Barium Strontium Titanate Nanostructures: Structural and Optical Properties for DSSC Applications

2021· article· en· W3194002813 on OpenAlexaff
V. Kavitha, V. Ragavendran, N. Sethupathi, Suresh Sagadevan, V. Sasirekha, Joshua M. Pearce, Jeyanthinath Mayandi

Bibliographic record

VenueMalaysian NANO-An International Journal · 2021
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsWestern University
FundersDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsDye-sensitized solar cellMaterials scienceDopingDopantGadoliniumBarium titanateBariumStrontium titanateCrystalliteBand gapStrontiumMicrowaveNanotechnologyOptoelectronicsCeramicThin filmPhysical chemistryChemistryComposite materialMetallurgy

Abstract

fetched live from OpenAlex

Gadolinium (Gd) doped barium strontium titanate (BST) was prepared using the microwave-assisted solid-state reaction method for dye sensitized solar cell (DSSC) applications. The optical properties and the structural analysis of the prepared samples reveal the optical band gap and the morphology. The XRD pattern of the annealed samples confirms the polycrystalline nature with the cubic crystal structure. When the dopant is added, the bandgap increases slightly from 3.11 to 3.27 eV. The J-V characteristics of DSSCs prepared with pure and doped BST were investigated. The efficiency of the DSSCs remained constant and there is a slight increase in the Jsc for highly doped samples under 1-sun illumination. Gadolinium doped barium strontium titanate shows variation in the J-V characteristics and could be a potential candidate for the solar photovoltaic applications.

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 score0.002

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 head0.017
GPT teacher head0.260
Teacher spread0.243 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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