Black Phosphorus and its Biomedical Applications
Bibliographic record
Abstract
Black phosphorus (BP), also known as phosphorene, has attracted recent scientific attention since its first successful exfoliation in 2014 owing to its unique structure and properties. In particular, its exceptional attributes, such as the excellent optical and mechanical properties, electrical conductivity and electron-transfer capacity, contribute to its increasing demand as an alternative to graphene-based materials in biomedical applications. Although the outlook of this material seems promising, its practical applications are still highly challenging. In this review article, we discuss the unique properties of BP, which make it a potential platform for biomedical applications compared to other 2D materials, including graphene, molybdenum disulphide (MoS2), tungsten diselenide (WSe2) and hexagonal boron nitride (h-BN). We then introduce various synthesis methods of BP and review its latest progress in biomedical applications, such as biosensing, drug delivery, photoacoustic imaging and cancer therapies (i.e., photothermal and photodynamic therapies). Lastly, the existing challenges and future perspective of BP in biomedical applications are briefly discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".