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Record W2768968349 · doi:10.1002/mp.12693

Toward Scintillator High‐Gain Avalanche Rushing Photoconductor Active Matrix Flat Panel Imager (<scp>SHARP</scp>‐<scp>AMFPI</scp>): Initial fabrication and characterization

2017· article· en· W2768968349 on OpenAlexaff
James R. Scheuermann, Adrian Howansky, Marc Hansroul, Sébastien Léveillé, Kenkichi Tanioka, Wei Zhao

Bibliographic record

VenueMedical Physics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsAnalogic (Canada)
FundersBasic Energy SciencesNational Cancer InstituteNational Institutes of HealthNational Institute of Biomedical Imaging and BioengineeringU.S. Department of Energy
KeywordsAvalanche photodiodeActive matrixMaterials scienceOptoelectronicsOpticsAvalanche diodeScintillatorDetective quantum efficiencyNoise (video)DetectorBreakdown voltagePhysicsVoltageThin-film transistorLayer (electronics)Image qualityNanotechnology

Abstract

fetched live from OpenAlex

Purpose We present the first prototype Scintillator High‐Gain Avalanche Rushing Photoconductor Active Matrix Flat Panel Imager ( SHARP ‐ AMFPI ). This detector includes a layer of avalanche amorphous Selenium (a‐Se) ( HARP ) as the photoconductor in an indirect detector to amplify the signal and reduce the effects of electronic noise to obtain quantum noise‐limited images for low‐dose applications. It is the first time avalanche a‐Se has been used in a solid‐state imaging device and poses as a possible solution to eliminate the effects of electronic noise, which is crucial for low‐dose imaging performance of AMFPI . Methods We successfully deposited a solid‐state HARP structure onto a 24 × 30 cm 2 array of thin‐film transistors ( TFT array) with a pixel pitch of 85 μm. The HARP layer consists of 16 μm of a‐Se with a hole‐blocking and electron‐blocking layer to prevent charge injection from the high‐voltage bias and pixel electrodes, respectively. An electric field ( E S e ) up to 105 V μm −1 was applied across the a‐Se layer without breakdown. A 150 μm thick‐structured CsI:Tl scintillator was used to form SHARP ‐ AMFPI . The x‐ray imaging performance is characterized using a 30 kV p Mo/Mo beam. We evaluate the spatial resolution, noise power, and detective quantum efficiency at zero frequency of the system with and without avalanche gain. The results are analyzed using cascaded linear system model ( CLSM ). Results An avalanche gain of 76 ± 5 was measured at E S e = 105 V μm −1 . We demonstrate that avalanche gain can amplify the signal to overcome electronic noise. As avalanche gain is increased, image quality improves for a constant (0.76 mR ) exposure until electronic noise is overcome. Our system is currently limited by poor optical transparency of our high‐voltage electrode and long integrating time which results in dark current noise. These two effects cause high‐spatial frequency noise to dominate imaging performance. Conclusions We demonstrate the feasibility of a solid‐state HARP x‐ray imager and have fabricated the largest active area HARP sensor to date. Procedures to reduce secondary quantum and dark noise are outlined. Future work will improve optical coupling and charge transport which will allow for frequency DQE and temporal metrics to be obtained.

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.031
GPT teacher head0.286
Teacher spread0.255 · 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

Citations28
Published2017
Admission routes1
Has abstractyes

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