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Record W2341379262 · doi:10.3762/bjnano.7.44

Bacteriorhodopsin–ZnO hybrid as a potential sensing element for low-temperature detection of ethanol vapour

2016· article· en· W2341379262 on OpenAlexaff
Saurav Kumar, Sudeshna Bagchi, Senthil Prasad, Anupma Sharma, Ritesh Kumar, Rishemjit Kaur, Jagvir Singh, Amol P. Bhondekar

Bibliographic record

VenueBeilstein Journal of Nanotechnology · 2016
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsUniversity of Alberta
FundersCSIR-Central Scientific Instruments Organisation
KeywordsBacteriorhodopsinMaterials scienceEthanolNanotechnologyOptoelectronicsChemistryMembraneOrganic chemistry

Abstract

fetched live from OpenAlex

Zinc oxide (ZnO) and bacteriorhodopsin (bR) hybrid nanostructures were fabricated by immobilizing bR on ZnO thin films and ZnO nanorods. The morphological and spectroscopic analysis of the hybrid structures confirmed the ZnO thin film/nanorod growth and functional properties of bR. The photoactivity results of the bR protein further corroborated the sustainability of its charge transport property and biological activity. When exposed to ethanol vapour (reducing gas) at low temperature (70 °C), the fabricated sensing elements showed a significant increase in resistivity, as opposed to the conventional n-type behaviour of bare ZnO nanostructures. This work opens up avenues towards the fabrication of low temperature, photoactivated, nanomaterial-biomolecule hybrid gas sensors.

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 score0.001

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)0.0000.000

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 head0.017
GPT teacher head0.284
Teacher spread0.266 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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