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Record W4366140787 · doi:10.1002/adma.202301129

Defect‐Rich MoSe<sub>2</sub> 2H/1T Hybrid Nanoparticles Prepared from Femtosecond Laser Ablation in Liquid and Their Enhanced Photothermal Conversion Efficiencies

2023· article· en· W4366140787 on OpenAlex
Fan Ye, Ahsan Ayub, Reza Karimi, Shawn Wettig, Joseph Sanderson, Kevin P. Musselman

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Materials · 2023
Typearticle
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsMaterials scienceNanoparticleNucleationNanoclustersLaserPhotothermal therapyLaser ablationFemtosecondLaser ablation synthesis in solutionCrystalliteOptoelectronicsLaser power scalingNanotechnologyOpticsOrganic chemistryX-ray laser

Abstract

fetched live from OpenAlex

Abstract MoSe 2 2H/1T hybrid nanoparticles are prepared by femtosecond laser ablation of MoSe 2 powder in isopropyl alcohol with different laser powers and ablation times, and their formation mechanisms and photothermal conversion efficiencies (PTCEs) are studied. Two types of spherical nanoparticles are observed. The first type is onion‐structured nanoparticles that are formed by nucleation on the surfaces of melted droplets followed by inward growth of {002} planes of MoSe 2 . The second type is polycrystalline nanoparticles, formed by coalescence of crystalline nanoclusters fragmented from the powder during the laser ablation. The nanoparticle size in all samples shows a bimodal distribution, corresponding to different fragmentation mechanisms. The 2H‐to‐1T phase transition in the nanoparticles is likely caused by electron doping from the laser‐induced plasma. The PTCEs of the nanoparticles increase with laser power and ablation time; the highest PTCE is around 38%. After examining the bandgaps and the Urbach energies of the nanoparticles, it is found that the high PTCEs are primarily attributed to defects and structural disorder in the laser‐synthesized nanoparticles, which allow absorption of photons with energies smaller than the bandgap energy and facilitate non‐radiative recombination of photoexcited carriers.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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