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Record W4314447505 · doi:10.1039/d2nr05565a

Biomolecules incorporated in halide perovskite nanocrystals: synthesis, optical properties, and applications

2023· review· en· W4314447505 on OpenAlexafffund
Masoud Aminzare, Jennifer Jiang, Gabrielle A. Mandl, Sara Mahshid, John A. Capobianco, Noémie‐Manuelle Dorval Courchesne

Bibliographic record

VenueNanoscale · 2023
Typereview
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsConcordia UniversityMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaConcordia UniversityCentre québécois sur les matériaux fonctionnelsCanada Research ChairsFaculty of Engineering, McGill UniversityMcGill University
KeywordsBiomoleculeNanotechnologyNanomaterialsMaterials sciencePerovskite (structure)NanocrystalNanoparticleChemistry

Abstract

fetched live from OpenAlex

.) that have shown promise for improving the performance of HPNCs and their potential applications. Specifically, we have reviewed the recent advances on incorporating biomolecules with HP nanomaterials on the formation, physicochemical properties, and stability of HP compounds. We have also shed light on the potential for using HPs in biological and environmental applications by compiling some recent of proof-of-concept demonstrations. Overall, this review aims to guide the field towards incorporating biomolecules into the next-generation of high-performance HPNCs for biological and environmental applications.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.059
GPT teacher head0.273
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations13
Published2023
Admission routes2
Has abstractyes

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