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Record W3163858257 · doi:10.2533/chimia.2021.398

Nanocrystal Quantum Dot Devices: How the Lead Sulfide (PbS) System Teaches Us the Importance of Surfaces

2021· article· en· W3163858257 on OpenAlexafffund
Weyde M. M. Lin, Maksym Yarema, Mengxia Liu, Edward H. Sargent, Vanessa Wood

Bibliographic record

VenueCHIMIA International Journal for Chemistry · 2021
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
FundersTianjin UniversityH2020 Marie Skłodowska-Curie ActionsUniversity of TorontoQueen's UniversityEuropean CommissionEidgenössische Technische Hochschule ZürichNational Science FoundationUniversity of CambridgeSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsNanocrystalLead sulfideMaterials scienceNanotechnologyQuantum dotFabricationNanometreThin filmSemiconductorOptoelectronics

Abstract

fetched live from OpenAlex

Semiconducting thin films made from nanocrystals hold potential as composite hybrid materials with new functionalities. With nanocrystal syntheses, composition can be controlled at the sub-nanometer level, and, by tuning size, shape, and surface termination of the nanocrystals as well as their packing, it is possible to select the electronic, phononic, and photonic properties of the resulting thin films. While the ability to tune the properties of a semiconductor from the atomistic- to macro-scale using solution-based techniques presents unique opportunities, it also introduces challenges for process control and reproducibility. In this review, we use the example of well-studied lead sulfide (PbS) nanocrystals and describe the key advances in nanocrystal synthesis and thin-film fabrication that have enabled improvement in performance of photovoltaic devices. While research moves forward with novel nanocrystal materials, it is important to consider what decades of work on PbS nanocrystals has taught us and how we can apply these learnings to realize the full potential of nanocrystal solids as highly flexible materials systems for functional semiconductor thin-film devices. One key lesson is the importance of controlling and manipulating surfaces.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.032
GPT teacher head0.261
Teacher spread0.229 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations24
Published2021
Admission routes2
Has abstractyes

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