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Record W3106088216 · doi:10.1039/d0na00705f

The formation principle of micro-droplets induced by using optical tweezers

2020· article· en· W3106088216 on OpenAlexaff
Cong Zhai, Chunguang Hu, Shuai Li, Yanhua Ma, Yajing Zhang, Tong Guo, Hongbin Li

Bibliographic record

VenueNanoscale Advances · 2020
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsUniversity of British Columbia
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsOptical tweezersMicrofluidicsNanotechnologyOpticsMaterials sciencePhysics

Abstract

fetched live from OpenAlex

solution. Considering that the generated droplet size is at the μm level, we have adopted a variety of methods in experiments to reduce external interference. Second, using a confocal microscopic video camera, the growth process of the droplet is completely recorded in a common glass-based chamber. The finite element simulations help us to further understand that the droplet generation process using optical tweezers can be divided into two stages: "capture" caused by optical force field and "aggregation" induced by a photothermal phenomenon and thermal acceleration. Through these studies, the nature of the optical tweezer-generated droplets is revealed. As a general principle for the droplet generation, this method will provide inspiration and prospects in the fields of microfluidics and biophysics-chemistry.

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 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 score0.325
Threshold uncertainty score0.324

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 communication0.0000.000
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 head0.018
GPT teacher head0.264
Teacher spread0.246 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

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