Superior X-ray Radiation Shielding Effectiveness of Biocompatible Polyaniline Reinforced with Hybrid Graphene Oxide-Iron Tungsten Nitride Flakes
Bibliographic record
Abstract
X-ray radiation is a harmful carcinogenic electromagnetic source that can adversely affect the health of living species and deteriorate the DNA of cells, thus it’s vital to protect vulnerable sources from them. To address this flaw, the conductive polymeric structure of polyaniline (PANi) was reinforced with diverse filler loadings (i.e., 25 wt % and 50 wt %) of hybrid graphene oxide-iron tungsten nitride (ITN) flakes toward attenuation of X-ray beams and inhabitation of microorganisms’ growth. Primary characterizations confirmed the successful decoration of graphene oxide (GO) with interconnected and highly dense structure of iron tungsten nitride with a density of about 24.21 g·cm−3 and reinforcement of PANi with GO-ITN. Additionally, the outcome of evaluations showed the superior performance of developed shields, where a shield with 1.2 mm thickness containing 50 wt % GO-ITN showed 131.73% increase in the electrical conductivity (compared with neat PANi) along with 78.07%, 57.12%, and 44.99% decrease in the amplitude of the total irradiated X-ray waves at 30, 40, and 60 kVp tube voltages, respectively, compared with control X-ray dosage. More importantly, the developed shields not only showed non-toxic nature and improved the viability of cells, but also completely removed the selected microorganisms at a concentration of 1000 µg·mL−1.
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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".