Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Electroactive polymer gels as probabilistic reservoir automata for computation

ABSTRACT: Summary Electroactive Polymer (EAP) hydrogels are an active matter material used as actuators in soft robotics. Hydrogels exhibit active matter behavior through a form of memory and can be used to embody memory systems such as automata. This study exploited EAP responses, finding that EAP memory functions could be utilized for automaton and reservoir computing frameworks. Under sequential electrical stimulation, the mechanical responses of EAPs were represented in a probabilistic Moore automaton framework and expanded through shaping the reservoir’s energy landscape. The EAP automaton reservoir’s computational ability was compared with digital computation to assess EAPs as computational resources. We found that the computation in the EAP’s reaction to stimuli can be presented through automaton structures, revealing a potential bridge between EAP’s use as an integrated actuator and controller, i.e., our automaton framework could potentially lead to control systems wherein the computation was embedded into the media dynamical responses. Graphical abstract Highlights • EAP gel memory mechanics were demonstrated via voltage potential measurements• Probabilistic Moore automata were constructed from EAP gel responses to stimulation• Through tuning response encoding a computational reservoir was created• The reservoir was shown as more memory efficient than general digital alternatives Theoretical physics; Materials science; Polymers

SUBMITTER: Strong V

PROVIDER: S-EPMC9708913 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Synaptic computation underlying probabilistic inference.

Project description:We propose that synapses may be the workhorse of the neuronal computations that underlie probabilistic reasoning. We built a neural circuit model for probabilistic inference in which information provided by different sensory cues must be integrated and the predictive powers of individual cues about an outcome are deduced through experience. We found that bounded synapses naturally compute, through reward-dependent plasticity, the posterior probability that a choice alternative is correct given that a cue is presented. Furthermore, a decision circuit endowed with such synapses makes choices on the basis of the summed log posterior odds and performs near-optimal cue combination. The model was validated by reproducing salient observations of, and provides insights into, a monkey experiment using a categorization task. Our model thus suggests a biophysical instantiation of the Bayesian decision rule, while predicting important deviations from it similar to the 'base-rate neglect' observed in human studies when alternatives have unequal prior probabilities.

| S-EPMC2921378 | biostudies-literature

Good-for-MDPs Automata for Probabilistic Analysis and Reinforcement Learning

Project description:We characterize the class of nondeterministic

| S-EPMC7439745 | biostudies-literature

Ionic electroactive polymer artificial muscles in space applications.

Project description:A large-scale effort was carried out to test the performance of seven types of ionic electroactive polymer (IEAP) actuators in space-hazardous environmental factors in laboratory conditions. The results substantiate that the IEAP materials are tolerant to long-term freezing and vacuum environments as well as ionizing Gamma-, X-ray, and UV radiation at the levels corresponding to low Earth orbit (LEO) conditions. The main aim of this material behaviour investigation is to understand and predict device service time for prolonged exposure to space environment.

| S-EPMC5381380 | biostudies-literature

Counting primary loops in polymer gels.

Project description:Much of our fundamental knowledge related to polymer networks is built on an assumption of ideal end-linked network structure. Real networks invariably possess topological imperfections that negatively affect mechanical properties; modifications of classical network theories have been developed to account for these defects. Despite decades of effort, there are no known experimental protocols for precise quantification of even the simplest topological network imperfections: primary loops. Here we present a simple conceptual framework that enables primary loop quantification in polymeric materials. We apply this framework to measure the fraction of primary loop junctions in trifunctional PEG-based hydrogels. We anticipate that the concepts described here will open new avenues of theoretical and experimental research related to polymer network structure.

| S-EPMC3511143 | biostudies-literature

Soft Tunable Lenses Based on Zipping Electroactive Polymer Actuators.

Project description:Compact and entirely soft optics with tunable and adaptive properties drive the development of life-like soft robotic systems. Yet, existing approaches are either slow, require rigid components, or use high operating voltages of several kilovolts. Here, soft focus-tunable lenses are introduced, which operate at practical voltages, cover a high range of adjustable focal lengths, and feature response times in the milliseconds range. The nature-inspired design comprises a liquid-filled elastomeric lens membrane, which is inflated by zipping electroactive polymers to tune the focal length. An analytic description of the tunable lens supports optimized designs and accurate prediction of the lens characteristics. Focal length changes between 22 and 550 mm (numerical aperture 0.14-0.005) within 260 ms, equal in performance to human eyes, are demonstrated for a lens with 3 mm aperture radius, while applying voltages below 500 V. The presented model, design rules, and fabrication methods address central challenges of soft electrostatic actuators and optical systems, and pave the way toward autonomous bio-inspired robots and machines.

| S-EPMC7856880 | biostudies-literature

Probabilistic computation in human perception under variability in encoding precision.

Project description:A key function of the brain is to interpret noisy sensory information. To do so optimally, observers must, in many tasks, take into account knowledge of the precision with which stimuli are encoded. In an orientation change detection task, we find that encoding precision does not only depend on an experimentally controlled reliability parameter (shape), but also exhibits additional variability. In spite of variability in precision, human subjects seem to take into account precision near-optimally on a trial-to-trial and item-to-item basis. Our results offer a new conceptualization of the encoding of sensory information and highlight the brain's remarkable ability to incorporate knowledge of uncertainty during complex perceptual decision-making.

| S-EPMC3387023 | biostudies-literature

Periodical propagation of torsion in polymer gels.

Project description:Gel actuators have potential in soft robotics. Although gel actuators can realize various motions like contraction, expansion, and bending, most require external inputs such as batteries and circuits. Herein we propose a periodical torsional motion hydrogel driven by chemical energy from the Belousov-Zhabotinsky (BZ) reaction. Our BZ gel system exhibits autonomous motion without a battery. The elastic moduli of the redox states of the BZ gel are investigated using stress-strain analysis. An experimental system, which integrates the BZ gel and two PDMS (dimethylpolysiloxane) rotators, is designed to evaluate torsion angles. The experimental pre-twist angle dependence of the rotary motion is compared with a theoretical rotation model. The results agree qualitatively. This study should contribute to the development of soft actuators without external components.

| S-EPMC9537306 | biostudies-literature

Single-Component Electroactive Polymer Architectures for Non-Enzymatic Glucose Sensing.

Project description:Organic mixed ionic-electronic conductors (OMIECs) have emerged as promising materials for biological sensing, owing to their electrochemical activity, stability in an aqueous environment, and biocompatibility. Yet, OMIEC-based sensors rely predominantly on the use of composite matrices to enable stimuli-responsive functionality, which can exhibit issues with intercomponent interfacing. In this study, an approach is presented for non-enzymatic glucose detection by harnessing a newly synthesized functionalized monomer, EDOT-PBA. This monomer integrates electrically conducting and receptor moieties within a single organic component, obviating the need for complex composite preparation. By engineering the conditions for electrodeposition, two distinct polymer film architectures are developed: pristine PEDOT-PBA and molecularly imprinted PEDOT-PBA. Both architectures demonstrated proficient glucose binding and signal transduction capabilities. Notably, the molecularly imprinted polymer (MIP) architecture demonstrated faster stabilization upon glucose uptake while it also enabled a lower limit of detection, lower standard deviation, and a broader linear range in the sensor output signal compared to its non-imprinted counterpart. This material design not only provides a robust and efficient platform for glucose detection but also offers a blueprint for developing selective sensors for a diverse array of target molecules, by tuning the receptor units correspondingly.

| S-EPMC11251565 | biostudies-literature

Control of neural stem cell survival by electroactive polymer substrates.

Project description:Stem cell function is regulated by intrinsic as well as microenvironmental factors, including chemical and mechanical signals. Conducting polymer-based cell culture substrates provide a powerful tool to control both chemical and physical stimuli sensed by stem cells. Here we show that polypyrrole (PPy), a commonly used conducting polymer, can be tailored to modulate survival and maintenance of rat fetal neural stem cells (NSCs). NSCs cultured on PPy substrates containing different counter ions, dodecylbenzenesulfonate (DBS), tosylate (TsO), perchlorate (ClO(4)) and chloride (Cl), showed a distinct correlation between PPy counter ion and cell viability. Specifically, NSC viability was high on PPy(DBS) but low on PPy containing TsO, ClO(4) and Cl. On PPy(DBS), NSC proliferation and differentiation was comparable to standard NSC culture on tissue culture polystyrene. Electrical reduction of PPy(DBS) created a switch for neural stem cell viability, with widespread cell death upon polymer reduction. Coating the PPy(DBS) films with a gel layer composed of a basement membrane matrix efficiently prevented loss of cell viability upon polymer reduction. Here we have defined conditions for the biocompatibility of PPy substrates with NSC culture, critical for the development of devices based on conducting polymers interfacing with NSCs.

| S-EPMC3073951 | biostudies-literature

Dynamically Tuneable Reflective Structural Coloration with Electroactive Conducting Polymer Nanocavities.

Project description:Dynamic control of structural colors across the visible spectrum with high brightness has proven to be a difficult challenge. Here, this is addressed with a tuneable reflective nano-optical cavity that uses an electroactive conducting polymer (poly(thieno[3,4-b]thiophene)) as spacer layer. Electrochemical doping and dedoping of the polymer spacer layer provides reversible tuning of the cavity's structural color throughout the entire visible range and beyond. Furthermore, the cavity provides high peak reflectance that varies only slightly between the reduced and oxidized states of the polymer. The results indicate that the polymer undergoes large reversible thickness changes upon redox tuning, aided by changes in optical properties and low visible absorption. The electroactive cavity concept may find particular use in reflective displays, by opening for tuneable monopixels that eliminate limitations in brightness of traditional subpixel-based systems.

| S-EPMC11469130 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data