Additive manufacturing of smart <scp>3D</scp> ‐printed radiation shielding materials—An innovation in recent times
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Advancements in 3D‐printed radiation shielding materials have ushered in a new era of radiation protection, characterized by enhanced efficiency, accuracy, and personalization. The use of additive manufacturing technology in creating shielding materials against electromagnetic interference (EMI), gamma rays, neutrons, and X‐rays is well covered in this article. An overview of additive manufacturing and the basic ideas of radiation and shielding are covered first. This article also highlights the various types of 3D printing materials and technologies used to create radiation shielding components, including metal composites, polymers, and hybrid materials. The benefits of 3D printing are highlighted, including the ability to create intricate designs that enhance shielding effectiveness while using less weight and material. This paper also highlights the development of intelligent, multipurpose shielding structures tailored for specific applications, summarizing significant scientific advancements in the field. The conclusion highlights the potential of additive manufacturing to transform radiation shielding in the electronic, nuclear, aerospace, and medical sectors while outlining present issues and anticipated future developments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 it