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Record W4296715427 · doi:10.21203/rs.3.rs-1833016/v1

Switchable capillary and drainage containers for programmable three-dimensional liquid manipulation

2022· preprint· en· W4296715427 on OpenAlexaff
Yiyuan Zhang, Zhandong Huang, Zheren Cai, Feifei Qin, Xiaobing Cai, Junfeng Xiao, Jan Carmeliet, Yanlin Song, Jun Yang

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsWestern University
FundersCentro Svizzero di Calcolo ScientificoNational Supercomputing Centre SingaporeChina Scholarship Council
KeywordsCapillary actionDrainageComputer scienceMaterials scienceComposite materialBiology

Abstract

fetched live from OpenAlex

Abstract Capillarity-guided liquid manipulations are ubiquitous in nature. Multifarious bioinspired capillary microfluidic devices have been developed to control different liquid behaviors. However, current capillary systems still suffer substantial limitations in flexible three-dimensional (3D) liquid manipulation, especially in reversible liquid capture and release, programmable 3D liquid patterning, and large-scale multi-liquid manipulation. Here, we propose “switchable capillary and drainage containers” composed of connected frame units for versatile programmable 3D liquid manipulation. A small difference in the frame connections induces vastly distinct liquid behaviors, namely, liquid capture in capillary containers and liquid release in drainage containers. Liquid capture or release can be reversibly switched by establishing or breaking the liquid continuity between containers. Using predefined frame connections allows programmable 3D patterning of unary and binary liquids, enabling parallel multi-variable studies. The containers are proved to be powerful fluidic platforms with applications including reversible capillary sampling and release, high-flow evaporative humidifier, and efficient CO 2 capture. We envision that the containers will open broad applications in materials science, interfacial chemistry, and biomedical research. Main text

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.971

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.365
Teacher spread0.306 · 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 designTheoretical or conceptual
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

Citations0
Published2022
Admission routes1
Has abstractyes

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