Protein-Mediated Aqueous Synthesis of Stable Methylammonium Lead Bromide Perovskite Nanocrystals: Implications for Biological and Environmental Applications
Bibliographic record
Abstract
Lead halide perovskites (HPs) hold great potential for the next generation of optoelectronic devices. However, their promise for real-world applications has not been realized because of their poor phase stability and decomposition when subjected to heat, moisture, and light. Here, we report a facile strategy for synthesizing highly stable, compositionally rich, and size-controlled methylammonium lead HP [CH3NH3PbX3 (X = Cl, Br, and I)] nanocrystals (HPNCs) in an aqueous environment, assisted by diverse proteins as capping agents. Freeing HPNC production of the complications of organic solvents provides much needed flexibility for the further cost-effective and efficient development of these structures. Stabilized by a delicate ionic balance during synthesis and via interactions with proteins, the synthesized protein-HPNCs exhibit high aqueous and colloidal stability over months. Protein capping also yields promising optical characteristics, including narrow emission wavelength and a photoluminescence quantum yield of up to ∼50%. Furthermore, we demonstrate that this approach can be extended to the synthesis of protein-mediated HPNCs with different chemistries and protein compositions. We anticipate that this method can serve as a general platform that can be used for the fabrication of a wide range of metal HPs for many biological and environmental applications including cell imaging and sensing.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".