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Record W2973476051 · doi:10.1002/adem.201900977

A Bioinspired Photothermal Pneumatic Device Enabling Optical Manipulation of Microfluid toward Precise Control of Microreactions

2019· article· en· W2973476051 on OpenAlex

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.

Bibliographic record

VenueAdvanced Engineering Materials · 2019
Typearticle
Languageen
FieldEngineering
TopicElectrowetting and Microfluidic Technologies
Canadian institutionsMinistry of Education and Child Care
FundersMinistry of Science and Technology of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsPhotothermal therapyMicrofluidicsMaterials sciencePhotothermal effectTube (container)NanotechnologyProcess (computing)ThermalComposite materialComputer science

Abstract

fetched live from OpenAlex

Various driving methods are developed in microfluidic technology to manipulate small amounts of liquid. Among them, the photocontrol method is highlighted for its advantages in contactless and accuracy control. However, the illumination method may induce risks of radiation damage, thermal damage, or chemical environment changes. To avoid these risks, a photothermal pneumatic microfluidic device (PPMD) containing a photothermal composite, an air chamber, and a tube is designed, bioinspired by the feeding process of female mosquitos. One way to drive liquid columns at a constant velocity higher than 1.0 cm s −1 in microtubes without interface modification is successfully obtained, and a method to separate out water–oil two‐phase liquid mixtures is proposed. The integration of several single PPMDs enables complex logical operations (AND and OR) toward precise control of microreactions. This work is promising in fields of microfluidic chips, pneumatic devices, liquid transfer, microreactions, and water–oil phase separation.

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 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 score0.028
Threshold uncertainty score0.909

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 head0.006
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