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Record W4406133302 · doi:10.1002/mp.17608

Design optimization of a 1‐D array of stemless plastic scintillation detectors

2025· article· en· W4406133302 on OpenAlexafffund
Samaneh Aynehband, Ian G. Hill, Alasdair Syme

Bibliographic record

VenueMedical Physics · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsNova Scotia Health AuthorityDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsScintillationDetectorOpticsPhysicsMedical physicsComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: A stemless plastic scintillation detector (SPSD) is composed of an organic plastic scintillator coupled to an organic photodiode. Previous research has shown that SPSDs are ideally suited to challenging dosimetry measurements such as output factors and profiles in small fields. Lacking from the current literature is a systematic effort to optimize the performance of the photodiode component of the detector. An optimized detector could permit a reduction in detector element size, thus improving spatial resolution without degradation of the signal to noise ratio values seen previously. PURPOSE: SPSDs use an organic photodiode coupled to a plastic scintillator to measure ionizing radiation fields. The design retains the benefits of plastic scintillation detectors (energy and dose rate independence, no perturbation factors, etc.) but avoids the challenges of optical fiber-based systems (Cerenkov radiation). In this work, the design of a 1-dimensional array of SPSDs is optimized to maximize the measured signal. METHODS: ITO-covered PET was etched using hydrochloric acid, and the substrate was cleaned. PEDOT: PSS and P3HT: PCBM (different weight ratios) were then applied to the substrate using spin-coating. Finally, aluminum top electrodes were added using vacuum thermal evaporation to complete the fabrication process. The variables studied for the optimization included: spin coater's speed (i.e., film thickness), P3HT: PCBM ratio, solution concentration, and scintillator coating. RESULTS: Increasing the film thickness from ∼80 nm to ∼138 nm increased the measured signal by a factor of approximately 7.7. Changing the ratio of P3HT to PCBM from (1:1) to (4:1) resulted in approximately 3.5 times higher signal. Additionally, increasing the total concentration of the solution from 2% to 4% by weight ratio increased the signal by roughly a factor of 2.5 for a P3HT: PCBM ratio of 2:1. However, for a P3HT: PCBM ratio of 4:1, increased solution concentration reduced measured signals to approximately 1.7 times lower than normal concentration. Covering the air gaps of the etched scintillator with white paint resulted in a signal increase of about 2.2 times higher compared to black paint. CONCLUSION: An optimization process was conducted to improve the signal output of the radiation detector, which consisted of a 1-dimensional photodiode array combined with a scintillator. This approach has resulted in a sensitivity increase of about 24 times compared to the original sample prior to optimizing the fabrication parameters and scintillator's properties (∼0.02 nC/cGy vs. ∼0.5 nC/cGy). The most efficient device was found to have a weight ratio of (2:1) P3HT: PCBM and a total solution concentration of 4%. Additionally, using a scintillator painted white was found to produce superior outcomes compared to black paint.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score0.302

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 head0.248
Teacher spread0.235 · 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 designSimulation or modeling
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
Published2025
Admission routes2
Has abstractyes

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