Keyword search (4,163 papers available)

"force" Keyword-tagged Publications:

Title Authors PubMed ID
1 Structural Behavior and Fatigue of FRP-Reinforced Concrete Beams Exposed to Different Weathering Conditions Rahmatian A; Saleem H; Hejazi F; Nokken M; Bagchi A; 41828174
ENCS
2 Robust and Compact Electrostatic Comb Drive Arrays for High-Performance Monolithic Silicon Photonics Fasihanifard M; Packirisamy M; 41156349
ENCS
3 Disentangling prediction error and value in a formal test of dopamine s role in reinforcement learning Usypchuk AA; Maes EJP; Lozzi M; Avramidis DK; Schoenbaum G; Esber GR; Gardner MPH; Iordanova MD; 40738112
CSBN
4 Comprehensive review of reinforcement learning for medical ultrasound imaging Elmekki H; Islam S; Alagha A; Sami H; Spilkin A; Zakeri E; Zanuttini AM; Bentahar J; Kadem L; Xie WF; Pibarot P; Mizouni R; Otrok H; Singh S; Mourad A; 40567264
ENCS
5 Activating Group II Metabotropic Glutamate Receptors in the Basolateral Amygdala Inhibits Increases in Reward Seeking Triggered by Discriminative Stimuli in Rats LeCocq MR; Mainville-Berthiaume A; Laplante I; Samaha AN; 40341317
CSBN
6 Machine learning innovations in CPR: a comprehensive survey on enhanced resuscitation techniques Islam S; Rjoub G; Elmekki H; Bentahar J; Pedrycz W; Cohen R; 40336660
ENCS
7 Computational neuroscience across the lifespan: Promises and pitfalls van den Bos W; Bruckner R; Nassar MR; Mata R; Eppinger B; 29066078
PSYCHOLOGY
8 Relapse after intermittent access to cocaine: Discriminative cues more effectively trigger drug seeking than do conditioned cues Ndiaye NA; Shamleh SA; Casale D; Castaneda-Ouellet S; Laplante I; Robinson MJF; Samaha AN; 38767684
PSYCHOLOGY
9 Impaired performance of rapid grip in people with Parkinson's disease and motor segmentation Rebecca J Daniels 38507858
PSYCHOLOGY
10 Post-reinforcement pauses during slot machine gambling are moderated by immersion W Spencer Murch 38429228
PSYCHOLOGY
11 Does phasic dopamine release cause policy updates? Carter F; Cossette MP; Trujillo-Pisanty I; Pallikaras V; Breton YA; Conover K; Caplan J; Solis P; Voisard J; Yaksich A; Shizgal P; 38039083
PSYCHOLOGY
12 Nonlinear dynamic modeling and model-based AI-driven control of a magnetoactive soft continuum robot in a fluidic environment Moezi SA; Sedaghati R; Rakheja S; 37932207
ENCS
13 Sub-hourly measurement datasets from 6 real buildings: Energy use and indoor climate Sartori I; Walnum HT; Skeie KS; Georges L; Knudsen MD; Bacher P; Candanedo J; Sigounis AM; Prakash AK; Pritoni M; Granderson J; Yang S; Wan MP; 37153123
ENCS
14 Deep learning approach to security enforcement in cloud workflow orchestration El-Kassabi HT; Serhani MA; Masud MM; Shuaib K; Khalil K; 36691661
ENCS
15 Reinforcement learning for automatic quadrilateral mesh generation: A soft actor-critic approach Pan J; Huang J; Cheng G; Zeng Y; 36375347
ENCS
16 Trust-Augmented Deep Reinforcement Learning for Federated Learning Client Selection Rjoub G; Wahab OA; Bentahar J; Cohen R; Bataineh AS; 35875592
ENCS
17 Gold Nano-Bio-Interaction to Modulate Mechanobiological Responses for Cancer Therapy Applications Sohrabi Kashani A; Larocque K; Piekny A; Packirisamy M; 35839330
BIOLOGY
18 Measures of motor segmentation from rapid isometric force pulses are reliable and differentiate Parkinson's disease from age-related slowing Howard SL; Grenet D; Bellumori M; Knight CA; 35768733
PSYCHOLOGY
19 Neural evidence for age-related deficits in the representation of state spaces Ruel A; Bolenz F; Li SC; Fischer A; Eppinger B; 35510942
PERFORM
20 Optical Fiber Array Sensor for Force Estimation and Localization in TAVI Procedure: Design, Modeling, Analysis and Validation Bandari N; Dargahi J; Packirisamy M; 34450813
ENCS
21 Corrigendum: Deep Learning-Based Haptic Guidance for Surgical Skills Transfer Fekri P; Dargahi J; Zadeh M; 34026860
ENCS
22 Deep Learning-Based Haptic Guidance for Surgical Skills Transfer. Fekri P, Dargahi J, Zadeh M 33553246
ENCS
23 Designing a hybrid reinforcement learning based algorithm with application in prediction of the COVID-19 pandemic in Quebec. Khalilpourazari S, Hashemi Doulabi H 33424076
ENCS
24 Cue-Evoked Dopamine Neuron Activity Helps Maintain but Does Not Encode Expected Value. Mendoza JA, Lafferty CK, Yang AK, Britt JP 31693885
CSBN
25 Drude polarizable force field for cation-π interactions of alkali and quaternary ammonium ions with aromatic amino acid side chains Orabi EA; Davis RL; Lamoureux G; 31652004
CERMM
26 Metacontrol of decision-making strategies in human aging. Bolenz F, Kool W, Reiter AM, Eppinger B 31397670
PERFORM
27 Effects of contingent and noncontingent nicotine on lever pressing for liquids and consumption in water-deprived rats. Frenk H, Martin J, Vitouchanskaia C, Dar R, Shalev U 27889434
CSBN
28 Odorous gaseous emissions as influence by process condition for the forced aeration composting of pig slaughterhouse sludge. Blazy V, de Guardia A, Benoist JC, Daumoin M, Lemasle M, Wolbert D, Barrington S 24768513
MASSSPEC
29 Developmental Changes in Learning: Computational Mechanisms and Social Influences. Bolenz F, Reiter AMF, Eppinger B 29250006
PERFORM

 

Title:Robust and Compact Electrostatic Comb Drive Arrays for High-Performance Monolithic Silicon Photonics
Authors:Fasihanifard MPackirisamy M
Link:https://pubmed.ncbi.nlm.nih.gov/41156349/
DOI:10.3390/mi16101102
Publication:Micromachines
Keywords:MEMS actuatorselectrostatic comb driveforce intensity optimizationsilicon photonicsslab waveguide actuation
PMID:41156349 Category: Date Added:2025-10-29
Dept Affiliation: ENCS
1 Optical-Bio Microsystems Laboratory, Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, 1515 St. Catherine W., Montreal, QC H3G 2W1, Canada.

Description:

Actuating monolithic photonic components (particularly slab waveguides) requires higher force due to their inherent stiffness. However, two primary constraints must be addressed: actuator footprint and fabrication limits. Increasing the number of fingers to provide the required force is not a viable solution due to space constraints, and we must also adhere to the process design kits of standard fabrications and respect their design limits. Therefore, it is crucial to increase the actuator force output without significantly enlarging the actuator footprint while maintaining the necessary travel range. In order to achieve this, we utilize arrays of electrostatic comb drives, with each repeating cell geometry optimized to produce the highest force per actuator footprint. Our optimization strategy focuses on finger geometry, the arrangement of fingers and arms design in the comb structure, including the number of fingers per arm and arm length, ensuring that each repeating cell delivers maximum force per unit area or force intensity. Co-optimizing a repeatable, footprint-optimized comb-array unit cell (arm length, arm width, finger pitch, finger count) and validating it against an asymmetric slab waveguide load, we reach a maximum pre-pull-in force intensity of about 342 N m-2 at 70 V with about 6 µm travel, confirmed by analytical modeling, numerical simulation, and measurement. Despite fabrication challenges such as over-etching and variations in electrode dimensions, detailed SEM analyses and correction functions ensure that the theoretical models closely match the experimental data, confirming the robustness and accuracy of the design. These optimized actuators, capable of achieving substantial force output without sacrificing travel range or mechanical stability, are particularly effective for applications in optical beam steering for in-plane silicon-photonics and related optical microsystems applications.





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