Characterizing the detector response and testing the performance of a new well counter for neutron coincidence measurements of plutonium in residues.
Bibliographic record
Abstract
A thermal neutron detector has been developed that integrates the neutron capture medium ({sup 6}LiF) and scintillator (ZnS) into a thin screen, which is coupled to wavelength shifting fiber-optic ribbon. The {sup 6}LiF and ZnS powders are incorporated in a hydrogenous binder. The detector is constructed of alternating layers of the capture/scintillator screen and the fiber-optic ribbon. The scintillation light produced in the ZnS is absorbed and reemitted in the fibers and is transported to photomultiplier tubes (PMTs). The detector is sensitive to gamrna radiation, but the difference in the pulse decay times of gamma-ray and neutron events allows for discrimination using pulse shape analysis (PSA). To determine the feasibility of using PSA with this detector, a number of intrinsic characteristics of the detector have been measured; specifically, the number of photoelectrons produced at the photocathode of the PMT from the average neutron capture event in the screen and the temperature stability of the detector with respect to pulse shape. The number of photons that reach the PMTs was measured with two different PMTs. One was a typical PMT with single-photoelectron resolution, and the other was a Hybrid PMT comprised of a photocathode coupled to a PIN diode with few-photoelectron resolution. The number of photons that reach the PMTs is between 1600 and 2200, which is sufficient for PSA. The sensitivity of pulse shape to temperature has also been evaluated. Although the pulse decay time changes with varying temperature between -25 to +50 C, the normalized detector pulses have approximately the same amplitude around 400 ns. This results in a stable zero-crossing time of the 400-ns delay-line shaped pulse, and thus the PSA is independent of temperature. A four-sided prototype well counter has been built, It has a short neutron die-away time ({tau} < 5 {micro}s), which increases its sensitivity to measurements of {sup 240}Pu by neutron coincidence counting. Because of the high {alpha},n-neutron yields in pyrochemical residues, greater sensitivity is required to measure these materials. Counters with relatively long {tau} (for example, those that use {sup 3}He detectors) will suffer from high accidental coincidence rate. Results with the prototype counter from high-rate measurements, equivalent to those expected from residues, are presented.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".