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Record W4396627499 · doi:10.11159/icnnfc24.106

Development of a Reduced Graphene Oxide-Based X-Ray Detector for Space Applications

2024· article· en· W4396627499 on OpenAlexvenueno aff
G Anshika, Govindaraju Shruthi, V. Koushal, S M Kruthika, V. Radhakrishna, G. Baishali

Bibliographic record

VenueProceedings of the World Congress on Recent Advances in Nanotechnology · 2024
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsnot available
FundersIndian Space Research OrganisationIndian Institute of Science
KeywordsGrapheneDetectorOxideSpace (punctuation)X-rayMaterials scienceX-ray detectorComputer scienceOptoelectronicsNanotechnologyPhysicsOpticsMetallurgyOperating system

Abstract

fetched live from OpenAlex

In this work, a light weight, reduced Graphene Oxide Field Effect Transistor based radiation detector is developed which detects X-rays at room temperature.Graphene Oxide is synthesized from Graphite flakes using modified Hummer's method which is then reduced by Hydroiodic acid fumes followed by low temperature treatment.Material characterization using X-ray diffraction technique and Raman spectra confirmed the reduction of Graphene oxide to reduced graphene oxide.Synthesized reduced graphene oxide is then put in back gate Field Effect Transistor architecture.The electrodes of the Field Effect transistor are made using thin film deposition technique.The detector is housed inside a simple packaging setup.The device showed promising response with Xrays of energy 20-40 KeV at room temperature at various incoming flus of X-ray photons.Response curve of device showed linear response with increasing X-ray energy and current.The device demonstrated a rise time of 0.25 s and fall time of 0.15s

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.299
Teacher spread0.284 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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