Optimizing non‐Pb radiation shielding materials using bilayers
Bibliographic record
Abstract
PURPOSE: The objective of this study was to demonstrate that the weight of non-Pb radiation shielding materials can be minimized by structuring the material as a bilayer composed of different metal-powder-embedded elastomer layers. METHODS: Measurements and Monte Carlo (MC) calculations were performed to study the attenuation properties of several non-Pb metal bilayers over the x-ray energy range 30-150 keV. Metals for the layers were chosen on the basis of low cost, nontoxicity, and complementary photoelectric absorption characteristics. The EGSnrc user code cavity.cpp was used to calculate the resultant x-ray fluence spectra after attenuation by these metal layers. Air kerma attenuation was measured using commercially manufactured metal/elastomer test layers. These layers were irradiated using the primary standard calibration beams at the Institute for National Measurement Standards in Ottawa, Canada utilizing the six x-ray beam qualities recommended in the German Standard DIN 6857. Both the measurements and the calculations were designed to approximate surface irradiation as well as penetrating radiation at 10 mm depth in soft tissue. The MC modeling point and the position of the measurement detector for surface irradiation were both directly against the downstream face of the attenuating material, as recommended in DIN 6857. RESULTS: The low-Z upstream/high-Z downstream ordering of the metal bilayers provided substantially more attenuation than the reverse order. Optimal percentages of each metal in each bilayer were determined for each x-ray radiation beam quality. CONCLUSIONS: Depending on the x-ray quality, appropriate choices of two complementary metal-embedded elastomer layers can decrease the weight of radiation shielding garments by up to 25% compared to Pb-based elastomer garments while providing equivalent attenuation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".