Ultra-Sensitive Piezo-Resistive Sensors Constructed with Reduced Graphene Oxide/Polyolefin Elastomer (RGO/POE) Nanofiber Aerogels.

Flexible wearable pressure sensors have received extensive attention in recent years because of the promising application potentials in health management, humanoid robots, and human machine interfaces. Among the many sensory performances, the high sensitivity is an essential requirement for the practical use of flexible sensors. Therefore, numerous research studies are devoted to improving the sensitivity of the flexible pressure sensors. The fiber assemblies are recognized as an ideal substrate for a highly sensitive piezoresistive sensor because its three-dimensional porous structure can be easily compressed and can provide high interconnection possibilities of the conductive component. Moreover, it is expected to achieve high sensitivity by raising the porosity of the fiber assemblies. In this paper, the three-dimensional reduced graphene oxide/polyolefin elastomer (RGO/POE) nanofiber composite aerogels were prepared by chemical reducing the graphene oxide (GO)/POE nanofiber composite aerogels, which were obtained by freeze drying the mixture of the GO aqueous solution and the POE nanofiber suspension. It was found that the volumetric shrinkage of thermoplastic POE nanofibers during the reduction process enhanced the compression mechanical strength of the composite aerogel, while decreasing its sensitivity. Therefore, the composite aerogels with varying POE nanofiber usage were prepared to balance the sensitivity and working pressure range. The results indicated that the composite aerogel with POE nanofiber/RGO proportion of 3:3 was the optimal sample, which exhibits high sensitivity (ca. 223 kPa-1) and working pressure ranging from 0 to 17.7 kPa. In addition, the composite aerogel showed strong stability when it is either compressed with different frequencies or reversibly compressed and released 5000 times

Big Data and Reliability Applications: The Complexity Dimension

Big data features not only large volumes of data but also data with complicated structures. Complexity imposes unique challenges in big data analytics. Meeker and Hong (2014, Quality Engineering, pp. 102-116) provided an extensive discussion of the opportunities and challenges in big data and reliability, and described engineering systems that can generate big data that can be used in reliability analysis. Meeker and Hong (2014) focused on large scale system operating and environment data (i.e., high-frequency multivariate time series data), and provided examples on how to link such data as covariates to traditional reliability responses such as time to failure, time to recurrence of events, and degradation measurements. This paper intends to extend that discussion by focusing on how to use data with complicated structures to do reliability analysis. Such data types include high-dimensional sensor data, functional curve data, and image streams. We first provide a review of recent development in those directions, and then we provide a discussion on how analytical methods can be developed to tackle the challenging aspects that arise from the complexity feature of big data in reliability applications. The use of modern statistical methods such as variable selection, functional data analysis, scalar-on-image regression, spatio-temporal data models, and machine learning techniques will also be discussed.Comment: 28 pages, 7 figure

Overview of sensors suitable for active flow control methods

Hlavným cieľom tejto bakalárskej práce bolo vytvorenie prehľadu vyvíjaných a už aplikovaných senzorov pre účely aktívneho riadenia prúdov. Senzory musia splňovať niektoré podmienky, preto výber senzorov bol naviazaný na reálnych výsledkoch testovacích programov, popis ktorých tvorí prvú časť tejto bakalárskej práce. Opis technológie a princíp fungovania senzorov je popísaný v druhej časti tejto práce.The main purpose of this bachelor thesis was to create the overview of the sensors developed for the future active flow control applications and overview the sensors already used in the active flow control applications. The sensors have to fulfil several requirements, so selection for the overview was based on the real flight test programs results, which were described in the first part of the thesis. The sensors technology description and operation principles were included in the second part of the thesis

Hydrostatic compression on polypropylene foam

Models currently used to simulate the impact behaviour of polymeric foam at high strain rates use data from mechanical tests. Uniaxial compression is the most common mechanical test used, but the results from this test alone are insufficient to characterise the foam response to three-dimensional stress states. A new experimental apparatus for the study of the foam behaviour under a state of hydrostatic stress is presented. A flywheel was modified to carry out compression tests at high strain rates, and a hydrostatic chamber designed to obtain the variation of stress with volumetric strain, as a function of density and deformation rate. High speed images of the sample deformation under pressure were analysed by image processing. Hydrostatic compression tests were carried out, on polypropylene foams, both quasi statically and at high strain rates. The stress–volumetric strain response of the foam was determined for samples of foam of density from 35 to 120 kg/m3, loaded at two strain rates. The foam response under hydrostatic compression shows a non-linear elastic stage, followed by a plastic plateau and densification. These were characterised by a compressibility modulus (the slope of the initial stage), a yield stress and a tangent modulus. The foam was transversely isotropic under hydrostatic compression

Closed-loop control of product properties in metal forming

Metal forming processes operate in conditions of uncertainty due to parameter variation and imperfect understanding. This uncertainty leads to a degradation of product properties from customer specifications, which can be reduced by the use of closed-loop control. A framework of analysis is presented for understanding closed-loop control in metal forming, allowing an assessment of current and future developments in actuators, sensors and models. This leads to a survey of current and emerging applications across a broad spectrum of metal forming processes, and a discussion of likely developments.Engineering and Physical Sciences Research Council (Grant ID: EP/K018108/1)This is the final version of the article. It first appeared from Elsevier via https://doi.org/10.1016/j.cirp.2016.06.00

A flexible and highly sensitive pressure sensor based on a PDMS foam coated with graphene nanoplatelets

The demand for high performance multifunctional wearable devices is more and more pushing towards the development of novel low-cost, soft and flexible sensors with high sensitivity. In the present work, we describe the fabrication process and the properties of new polydimethylsiloxane (PDMS) foams loaded with multilayer graphene nanoplatelets (MLGs) for application as high sensitive piezoresistive pressure sensors. The effective DC conductivity of the produced foams is measured as a function of MLG loading. The piezoresistive response of the MLG-PDMS foam-based sensor at different strain rates is assessed through quasi-static pressure tests. The results of the experimental investigations demonstrated that sensor loaded with 0.96 wt.% of MLGs is characterized by a highly repeatable pressure-dependent conductance after a few stabilization cycles and it is suitable for detecting compressive stresses as low as 10 kPa, with a sensitivity of 0.23 kPa−1, corresponding to an applied pressure of 70 kPa. Moreover, it is estimated that the sensor is able to detect pressure variations of ~1 Pa. Therefore, the new graphene-PDMS composite foam is a lightweight cost-effective material, suitable for sensing applications in the subtle or low and medium pressure ranges

Electric-field-induced alignment of electrically neutral disk-like particles: modelling and calculation

This work reveals a torque from electric field to electrically neutral flakes that are suspended in a higher electrical conductive matrix. The torque tends to rotate the particles toward an orientation with its long axis parallel to the electric current flow. The alignment enables the anisotropic properties of tiny particles to integrate together and generate desirable macroscale anisotropic properties. The torque was obtained from thermodynamic calculation of electric current free energy at various microstructure configurations. It is significant even when the electrical potential gradient becomes as low as 100 v/m. The changes of electrical, electroplastic and thermal properties during particles alignment were discussed