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Temperature quenching in LAB based liquid scintillator

2018· article· en· W2782102644 on OpenAlexaff
A Sörensen, S. Hans, A. Junghans, B. von Krosigk, T. Kögler, V. Lozza, A. Wagner, M. Yeh, Κ. Zuber

Bibliographic record

VenueThe European Physical Journal C · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsUniversity of British Columbia
FundersNuclear PhysicsBrookhaven National LaboratoryOffice of ScienceU.S. Department of Energy
KeywordsScintillatorPhysicsElectronAtomic physicsQuenching (fluorescence)Analytical Chemistry (journal)Atmospheric temperature rangeMicrosecondMaterials scienceNuclear physicsOpticsDetectorChemistryFluorescenceThermodynamics

Abstract

fetched live from OpenAlex

The effect of temperature changes on the light output of LAB based liquid scintillator is investigated in a range from $$-5$$ to $$30\,^{\circ }$$ C with $$\alpha $$ -particles and electrons in a small scale setup. Two PMTs observe the scintillator liquid inside a cylindrically shaped aluminum cuvette that is heated or cooled and the temperature dependent PMT sensitivity is monitored and corrected. The $$\alpha $$ -emitting isotopes in dissolved radon gas and in natural Samarium (bound to a LAB solution) excite the liquid scintillator mixtures and changes in light output with temperature variation are observed by fitting light output spectra. Furthermore, also changes in light output by compton electrons, which are generated from external calibration $$\gamma $$ -ray sources, is analysed with varying temperature. Assuming a linear behaviour, a combined negative temperature coefficient of $${(-0.29 \pm 0.01)}{\,\%/^{\circ }}\hbox {C}$$ is found. Considering hints for a particle type dependency, electrons show $${(-0.17 \pm 0.02)}{\,\%/^{\circ }}\hbox {C}$$ , whereas the temperature dependency seems stronger for $$\alpha $$ -particles, with $${(-0.35 \pm 0.03)}{\,\%/^{\circ }}\hbox {C}$$ . Due to a high sampling rate, a pulse shape analysis can be performed and shows an enhanced slow decay component at lower temperatures, pointing to reduced non-radiative triplet state de-excitations.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.015
GPT teacher head0.292
Teacher spread0.276 · 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 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

Citations12
Published2018
Admission routes1
Has abstractyes

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