PMMA/MWCNT nanocomposite for proton radiation shielding applications
Bibliographic record
Abstract
Radiation shielding in space missions is critical in order to protect astronauts, spacecraft and payloads from radiation damage. Low atomic-number materials are efficient in shielding particle-radiation, but they have relatively weak material properties compared to alloys that are widely used in space applications as structural materials. However, the issues related to weight and the secondary radiation generation make alloys not suitable for space radiation shielding. Polymers, on the other hand, can be filled with different filler materials for reinforcement of material properties, while at the same time provide sufficient radiation shielding function with lower weight and less secondary radiation generation. In this study, poly(methyl-methacrylate)/multi-walled carbon nanotube (PMMA/MWCNT) nanocomposite was fabricated. The role of MWCNTs embedded in PMMA matrix, in terms of radiation shielding effectiveness, was experimentally evaluated by comparing the proton transmission properties and secondary neutron generation of the PMMA/MWCNT nanocomposite with pure PMMA and aluminum. The results showed that the addition of MWCNTs in PMMA matrix can further reduce the secondary neutron generation of the pure polymer, while no obvious change was found in the proton transmission property. On the other hand, both the pure PMMA and the nanocomposite were 18%-19% lighter in weight than aluminum for stopping the protons with the same energy and generated up to 5% fewer secondary neutrons. Furthermore, the use of MWCNTs showed enhanced thermal stability over the pure polymer, and thus the overall reinforcement effects make MWCNT an effective filler material for applications in the space industry.
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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".