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An automatic-recovery inertial switch based on a gallium-indium metal droplet

2016· article· en· W2532806140 on OpenAlex
Teng Shen, Dongxing Zhang, Liu Huang, Jiong Wang

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

VenueJournal of Micromechanics and Microengineering · 2016
Typearticle
Languageen
FieldEngineering
TopicElectrowetting and Microfluidic Technologies
Canadian institutionsWestern University
FundersGovernment of Jiangsu Province
KeywordsIndiumGalliumMetalMaterials scienceInertial frame of referenceNuclear engineeringOptoelectronicsEngineeringMechanical engineeringNanotechnologyMetallurgyPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

In this paper, an automatic-recovery inertial switch is presented which for the first time adopts gallium–indium (EGaIn) as the switching metal droplet. The device consists of a glass substrate with patterned sensing electrodes, a PDMS microfluidic chip with microchannels and microvalves and a metal droplet. Here, we used EGaIn as the conductive element of the switch because it has several advantages compared with other conductive materials such as water or mercury. Specifically, the proposed device has the ability to automatically recover and can be used repeatedly. In the initial off-state, the droplet is stored in the reservoir. During the working state, the metal droplet passes through the channel and connects the sensing electrodes when the acceleration exceeds the designed threshold level. After that, the EGaIn will return to its original position by a subtle use of its structural characteristics.

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 score0.099
Threshold uncertainty score0.827

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 head0.003
GPT teacher head0.175
Teacher spread0.172 · 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