Detailed Inspection of γ-ray, Fast and Thermal Neutrons Shielding Competence of Calcium Oxide or Strontium Oxide Comprising Bismuth Borate Glasses
Bibliographic record
Abstract
For both the B2O3-Bi2O3-CaO and B2O3-Bi2O3-SrO glass systems, γ-ray and neutron attenuation qualities were evaluated. Utilizing the Phy-X/PSD program, within the 0.015–15 MeV energy range, linear attenuation coefficients (µ) and mass attenuation coefficients (μ/ρ) were calculated, and the attained μ/ρ quantities match well with respective simulation results computed by MCNPX, Geant4, and Penelope codes. Instead of B2O3/CaO or B2O3/SrO, the Bi2O3 addition causes improved γ-ray shielding competence, i.e., rise in effective atomic number (Zeff) and a fall in half-value layer (HVL), tenth-value layer (TVL), and mean free path (MFP). Exposure buildup factors (EBFs) and energy absorption buildup factors (EABFs) were derived using a geometric progression (G–P) fitting approach at 1–40 mfp penetration depths (PDs), within the 0.015–15 MeV range. Computed radiation protection efficiency (RPE) values confirm their excellent capacity for lower energy photons shielding. Comparably greater density (7.59 g/cm3), larger μ, μ/ρ, Zeff, equivalent atomic number (Zeq), and RPE, with the lowest HVL, TVL, MFP, EBFs, and EABFs derived for 30B2O3-60Bi2O3-10SrO (mol%) glass suggest it as an excellent γ-ray attenuator. Additionally, 30B2O3-60Bi2O3-10SrO (mol%) glass holds a commensurably bigger macroscopic removal cross-section for fast neutrons (ΣR) (=0.1199 cm−1), obtained by applying Phy-X/PSD for fast neutrons shielding, owing to the presence of larger wt% of ‘Bi’ (80.6813 wt%) and moderate ‘B’ (2.0869 wt%) elements in it. 70B2O3-5Bi2O3-25CaO (mol%) sample (B: 17.5887 wt%, Bi: 24.2855 wt%, Ca: 11.6436 wt%, and O: 46.4821 wt%) shows high potentiality for thermal or slow neutrons and intermediate energy neutrons capture or absorption due to comprised high wt% of ‘B’ element in it.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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 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".