Pullulan-1-Ethyl-3-Methylimidazolium Tetrafluoroborate Composite as a Water-Soluble Active Component of a Vibration Sensor.

In recent years, the issue of electronic waste production has gained significant attention. To mitigate the environmental impact of e-waste, one approach under consideration involves the development of biodegradable electronic devices or devices that dissolve in the environment at the end of their life cycle. This study presents results related to the creation of a sensor that effectively addresses both criteria. The device was constructed using a composite material formed by impregnating a pullulan membrane (a biodegradable water-soluble biopolymer) with 1-Ethyl-3-Methylimidazolium tetrafluoroborate (a water-soluble ionic liquid) and coating the product with a conductive silver-based varnish. Capitalizing on the piezoionic effect, the device has demonstrated functionality as a vibration sensor with a sensitivity of approximately 5.5 × 10-5 V/mm and a resolution of about 1 mm. The novelty of this study lies in the unique combination of materials. Unlike the use of piezoelectric materials, this combination allows for the production of a device that does not require an external potential difference generator to function properly as a sensor. Furthermore, the combination of a biopolymer, such as pullulan, and an ionic liquid, both readily soluble in water, in creating an active electronic component represents an innovation in the field of vibration sensors.

A Comparison among Different Strategies to Detect Potential Unstable Behaviors in Postural Sway.

Assistive Technology helps to assess the daily living and safety of frail people, with particular regards to the detection and prevention of falls. In this paper, a comparison is provided among different strategies to analyze postural sway, with the aim of detecting unstable postural status in standing condition as precursors of potential falls. Three approaches are considered: (i) a time-based features threshold algorithm, (ii) a time-based features Neuro-Fuzzy inference system, and (iii) a Neuro-Fuzzy inference fed by Discrete-Wavelet-Transform-based features. The analysis was performed across a wide dataset and exploited performance indexes aimed at assessing the accuracy and the reliability of predictions provided by the above-mentioned strategies. The results obtained demonstrate valuable performances of the three considered strategies in correctly distinguishing among stable and unstable postural status. However, the analysis of robustness against noisy data highlights better performance of Neuro-Fuzzy inference systems with respect to the threshold-based algorithm.

Investigation on the Role of Ionic Liquids in the Output Signal Produced by Bacterial Cellulose-Based Mechanoelectrical Transducers.

Green sensors are required for the realization of a sustainable economy. Biopolymer-derived composites are a meaningful solution to such a needing. Bacterial Cellulose (BC) is a green biopolymer, with significant mechanical and electrical properties. BC-based composites have been proposed to realize generating mechanoelectrical transductors. The transductors consist of a sheet of BC, impregnated of Ionic Liquids (ILs), and covered with two layers of Conducting Polymer (CP) as the electrodes. Charges accumulate at the electrodes when the transductor is bent. Generating sensors can produce either Open Circuit (OC) voltage or Short Circuit (SC) current. In the paper, the OC voltage and SC current, generated from BC-based composites, in a cantilever configuration and subjected to dynamic deformation are compared. The influence of ILs in the transduction performance, both in the case of OC voltage and SC current is investigated. Experimental investigations of structural, chemical, and mechanoelectrical transduction properties, when the composite is dynamically bent, are performed. The mechanoelectrical investigation has been carried on both in the time and in the frequency domains. Reported results show that no relevant changes can be obtained because of the use of IL when the OC voltage is considered. On the contrary, dramatic changes are observed for the case of SC current, whose value increases by about two orders of magnitude.

Green Energy Harvester from Vibrations Based on Bacterial Cellulose.

A bio-derived power harvester from mechanical vibrations is here proposed. The harvester aims at using greener fabrication technologies and reducing the dependence from carbon-based fossil energy sources. The proposed harvester consists mainly of biodegradable matters. It is based on bacterial cellulose, produced by some kind of bacteria, in a sort of bio-factory. The cellulose is further impregnated with ionic liquids and covered with conducting polymers. Due to the mechanoelectrical transduction properties of the composite, an electrical signal is produced at the electrodes, when a mechanical deformation is imposed. Experimental results show that the proposed system is capable of delivering electrical energy on a resistive load. Applications can be envisaged on autonomous or quasi-autonomous electronics, such as wireless sensor networks, distributed measurement systems, wearable, and flexible electronics. The production technology allows for fabricating the harvester with low power consumption, negligible amounts of raw materials, no rare elements, and no pollutant emissions.

An Eco-Friendly Disposable Plasmonic Sensor Based on Bacterial Cellulose and Gold.

In several application fields, plasmonic sensor platforms combined with bio-receptors are intensively used to obtain biosensors. Most of these commercial devices are based on a disposable chip. Usually a gold chip, functionalized with a specific bio-receptor, inside a costly sensor system, is used. In this work, we propose a low-cost and small-size sensor system, used for monitoring a disposable plasmonic chip, based on an innovative optical waveguide made of bacterial cellulose (BC). In particular, we have sputtered gold on the green slab waveguide that is able to excite localized surface plasmon resonance (LSPR). Experimental results are presented on the capabilities of using the BC-based composite as an eco-friendly plasmonic sensor platform, which could be exploited for realizing disposable biosensors. The sensor has been used with optical fibers and simple equipment. More specifically, the fibers connect the green disposable LSPR sensor with a light source and with a spectrometer. The novel plasmonic sensing approach has been tested using two different optical waveguide configurations of BC, with and without ions inside BC.

Design and control of an IPMC wormlike robot.

This paper presents an innovative wormlike robot controlled by cellular neural networks (CNNs) and made of an ionic polymer-metal composite (IPMC) self-actuated skeleton. The IPMC actuators, from which it is made of, are new materials that behave similarly to biological muscles. The idea that inspired the work is the possibility of using IPMCs to design autonomous moving structures. CNNs have already demonstrated their powerfulness as new structures for bio-inspired locomotion generation and control. The control scheme for the proposed IPMC moving structure is based on CNNs. The wormlike robot is totally made of IPMCs, and each actuator has to carry its own weight. All the actuators are connected together without using any other additional part, thereby constituting the robot structure itself. Worm locomotion is performed by bending the actuators sequentially from "tail" to "head," imitating the traveling wave observed in real-world undulatory locomotion. The activation signals are generated by a CNN. In the authors' opinion, the proposed strategy represents a promising solution in the field of autonomous and light structures that are capable of reconfiguring and moving in line with spatial-temporal dynamics generated by CNNs.

Identification of IPMC nonlinear model via single and multi-objective optimization algorithms.

Ionic Polymer-Metal Composites (IPMCs) are electro-active polymers transforming mechanical forces into electric signals and vice versa. This paper proposes an improved electro-mechanical grey-box model for IPMC membrane working as actuator. In particular the IPMC nonlinearity has been characterized through experimentation and included within the electric model. Moreover identification of the model parameters has been performed via optimization algorithms using both single- and multi-objective formulation. Minimization was attained via the Nelder-Mead simplex and the Genetic Algorithms considering as cost functions the error between the experimental and modeled absorbed current and the error between experimental and modeled displacement. The obtained results for the different formulations have been then compared.