Challenges and Strategies for Optimizing Corrosion and Biodegradation Stability of Biomedical Micro‐ and Nanoswimmers: A Review
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 The last two decades have witnessed the emergence of micro‐ and nanoswimmers (MNSs). Researchers have invested significant efforts in engineering motile micro‐ and nanodevices to address current limitations in minimally invasive medicine. MNSs can move through complex fluid media by using chemical fuels or external energy sources such as magnetic fields, ultrasound, or light. Despite significant advancements in their locomotion and functionalities, the gradual deterioration of MNSs in human physiological media is often overlooked. Corrosion and biodegradation caused by chemical reactions with surrounding medium and the activity of biological agents can significantly affect their chemical stability and functional properties during their lifetime performance. It is therefore essential to understand the degradation mechanisms and factors that influence them to design ideal biomedical MNSs that are affordable, highly efficient, and sufficiently resistant to degradation (at least during their service time). This review summarizes recent studies that delve into the physicochemical characteristics and complex environmental factors affecting the corrosion and biodegradation of MNSs, with a focus on metal‐based devices. Additionally, different strategies are discussed to enhance and/or optimize their stability. Conversely, controlled degradation of non‐toxic MNSs can be highly advantageous for numerous biomedical applications, allowing for less invasive, safer, and more efficient treatments.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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