Lightweight and flexible bismuth oxide composite with enhanced <scp>x‐ray</scp> shielding efficiency
Bibliographic record
Abstract
Abstract Lead‐based shielding materials are commonly used to protect clinical personnel and patients from high energy x‐ray radiations. However, the toxicity and heavy weight of lead can result in serious health concerns and limit its applications. Alternatively, polymer composites are known as one of the potential candidates to shield high energy photons. Herein, polydimethylsiloxane (PDMS) nanocomposites are fabricated using different weight percentages (wt.%) of bismuth oxide (Bi 2 O 3 ) and multi walled carbon nanotube (MWCNT) nanoparticles. The mechanical strength of nanocomposites is evaluated by Instron 5548 Micro Tester. Also, x‐ray shielding properties are characterized using continuous x‐ray energies from 60 to 90 keV. To study the effect of the nanocomposite structure on mechanical and shielding properties, multilayer nanocomposites in 2 to 5 layers are also fabricated with alternately PDMS/Bi 2 O 3 and PDMS/MWCNT layers and are characterized by the same methods. The 5‐layer nanocomposite improves the mechanical strength from 1.7 MPa in neat PDMS to 4.68 MPa. It is also capable of attenuating 89% of the scattered x‐rays generated at a tube potential of 60 keV, with a weight advantageous in comparison with pure lead.
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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 | 0.000 | 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 | 0.000 |
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".