Organic–inorganic hybrid perovskite scintillators for mixed field radiation detection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Sensitive and fast detection of neutrons and gamma rays is vital for homeland security, high‐energy physics, and proton therapy. Fast‐neutron detectors rely on light organic scintillators, and γ‐ray detectors use heavy inorganic scintillators and semiconductors. Efficient mixed‐field detection using a single material is highly challenging due to their contradictory requirements. Here we report hybrid perovskites (C 8 H 12 N) 2 Pb(Br 1− x Cl x ) 4 that combine light organic cations and heavy inorganic skeletons at a molecular level to achieve unprecedented performance for mixed‐field radiation detection. High neutron absorption due to a high density of hydrogen, strong radiative recombination within the highly confined [PbX 6 ] 4− layer, and sub‐nanometer distance between absorption sites and radiative centers, enable a light yield of 41 000 photons/MeV, detection pulse width of 2.97 ns and extraordinary linearity response toward both fast neutrons and γ‐rays, outperforming commonly used fast‐neutron scintillators. Neutron energy spectrum, time‐of‐flight based fast‐neutron/γ‐ray discrimination and neutron yield monitoring were all successfully achieved using (C 8 H 12 N) 2 Pb(Br 0.95 Cl 0.05 ) 4 detectors. We further demonstrate the monitoring of reaction kinetics and total power of a nuclear fusion reaction. We envision that molecular hybridized scintillators open a new avenue for mixed‐field radiation detection and imaging. image
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it