Polymer nanocomposite‐based shielding against diagnostic X‐rays
Bibliographic record
Abstract
Abstract Lead is commonly used in medical radiology departments as a shielding material. Lead‐based protective materials are also used by clinical personnel during X‐ray image‐guided interventional radiology (IVR) procedures. However, lead is extremely toxic and prolonged exposure to it can result in serious health concerns. Polymer composites, on the other hand, can be designed to be lead‐free in addition to being lightweight, conformable, cost effective, and potentially capable of significantly attenuating X‐rays. Nanomaterials have unique material properties that can be exploited to develop novel lead‐free radiation‐protection materials. In this study, polydimethylsiloxane (PDMS) nanocomposites were fabricated using different weight percentages (wt %) of bismuth oxide (BO) nanopowder. The attenuation properties of the nanocomposites were characterized using diagnostic X‐ray energies from 40 to 150 kV tube potential and were compared to the attenuation characteristics of 0.25‐mm‐thick pure lead sheet. The PDMS/BO nanocomposite (44.44 wt% of BO and 3.73‐mm thick) was capable of attenuating all the scattered X‐rays generated at a tube potential of 60 kV, which is the beam energy commonly employed in IVR. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2013
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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".