MétaCan
Menu
Back to cohort
Record W4392152133 · doi:10.1002/adfm.202315648

Self‐Powered Underwater Pressing and Position Sensing and Autonomous Object Grasping with a Porous Thermoplastic Polyurethane Film Sensor

2024· article· en· W4392152133 on OpenAlexaff
Quanyu Wang, Yongxin Song, Pu Liu, Deyu Li, Jiahui Wang, Xianping Fu, Dongqing Li

Bibliographic record

VenueAdvanced Functional Materials · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of Waterloo
FundersNational Natural Science Foundation of China
KeywordsMaterials scienceSIGNAL (programming language)UnderwaterHydrostatic pressureThermoplastic polyurethanePressingPressure sensorAcousticsPorosityComposite materialOptoelectronicsComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Most flexible ionic tactile sensors can hardly be used in deep sea due to their poor antiswelling and anticompression properties under high hydrostatic pressure. To achieve pressure and position sensing under high hydrostatic pressure, a self‐powered underwater tactile sensor made of a porous thermoplastic polyurethane (TPU) film is presented in this paper. The sensor works by generating an electric current due to the different moving velocities of ions in the porous film under pressing. Experimental results show that the magnitude of the generated current signal increases with the applied pressure, the contacting area, and ion concentration of the solution. The direction and magnitude of the current signal depend on the pressing position of the film. The signal magnitude decreased with the closer to the center of the film. The maximum pressure sensitivity and positioning resolution are 0.62 kPa −1 and 1.31 mm respectively. Response time (0.19 s), 0.67 s recovery time, and 50–600 kPa pressure detection range are achieved. In addition, the signal magnitude is decreased only by 15.53% when the sensor is placed underwater at a simulated depth of 100 m. Proof of concept demonstration of underwater autonomously grasping objects of different weights with this sensor is successfully achieved.

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 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 score0.024
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 communication0.0000.000
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 head0.007
GPT teacher head0.195
Teacher spread0.188 · 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.

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

Citations27
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueAdvanced Functional MaterialsSame topicAdvanced Sensor and Energy Harvesting MaterialsFrench-language works237,207