A Simple Model Relating Gauge Factor to Filler Loading in Nanocomposite Strain Sensors

Quantifying the effect of nanosheet dimensions on the piezoresistive response of printed graphene nanosheet networks

Printed networks of 2D nanosheets have found a range of applications in areas including electronic devices, energy storage systems and sensors. For example, the ability to print graphene networks onto flexible substrates enables the production of high-performance strain sensors. The network resistivity is known to be sensitive to the nanosheet dimensions which implies the piezoresistance might also be size-dependent. In this study, the effect of nanosheet thickness on the piezoresistive response of nanosheet networks has been investigated. To achieve this, we liquid-exfoliated graphene nanosheets which were then subjected to centrifugation-based size selection followed by spray deposition onto flexible substrates. The resultant devices show increasing resistivity and gauge factor with increasing nanosheet thickness. We analyse the resistivity versus thickness data using a recently reported model and develop a new model to fit the gauge factor versus thickness data. This analysis allowed us to differentiate between the effect of strain on inter-nanosheet junctions and the straining of the individual nanosheets within the network. Surprisingly, our data implies the nanosheets themselves to display a negative piezo response.

3D Printing of Anisotropic Piezoresistive Pressure Sensors for Directional Force Perception

Anisotropic pressure sensors are gaining increasing attention for next-generation wearable electronics and intelligent infrastructure owing to their sensitivity in identifying different directional forces. 3D printing technologies have unparalleled advantages in the design of anisotropic pressure sensors with customized 3D structures for realizing tunable anisotropy. 3D printing has demonstrated few successes in utilizing piezoelectric nanocomposites for anisotropic recognition. However, 3D-printed anisotropic piezoresistive pressure sensors (PPSs) remain unexplored despite their convenience in saving the poling process. This study pioneers the development of an aqueous printable ink containing waterborne polyurethane elastomer. An anisotropic PPS featuring tailorable flexibility in macroscopic 3D structures and microscopic pore morphologies is created by adopting direct ink writing 3D printing technology. Consequently, the desired directional force perception is achieved by programming the printing schemes. Notably, the printed PPS demonstrated excellent deformability, with a relative sensitivity of 1.22 (kPa*wt. %)-1 over a substantial pressure range (2.8 to 8.1 kPa), approximately fivefold than that of a state-of-the-art carbon-based PPS. This study underscores the versatility of 3D printing in customizing highly sensitive anisotropic pressure sensors for advanced sensing applications that are difficult to achieve using conventional measures.

A novel electrical depercolation model for stretchable nanocomposite strain sensors

Flexible strain sensors have been subject to intense research efforts in recent years, in an attempt to overcome the limitations of their rigid counterparts and find use in demanding applications. In this work, the effective calibration of resistive-type, stretchable strain sensors is discussed. A new model for the piezoresistive response of stretchable polymer nanocomposite strain sensors is presented which facilitates calibration over the full conducting strain range of the material. This offers the potential to vastly improve the practical working range of sensors made using soft conductive nanocomposites, as well as to obtain key information towards improvement of sensing performance. The model has been successfully applied to multiple experimental measurements on silicone rubber (SR) nanocomposites reinforced with reduced graphene oxide (rGO) over a range of filler loadings. The effect of parameters such as filler dimensions, filler orientation and dispersion state is discussed, while predictions on sensitivity and working range are made on the basis of interparticle distance modelling.

Performance analysis of solution-processed nanosheet strain sensors-a systematic review of graphene and MXene wearable devices

Nanotechnology has led to the realisation of many potentialInternet of Thingsdevices that can be transformative with regards to future healthcare development. However, there is an over saturation of wearable sensor review articles that essentially quote paper abstracts without critically assessing the works. Reported metrics in many cases cannot be taken at face value, with researchers overly fixated on large gauge factors. These facts hurt the usefulness of such articles and the very nature of the research area, unintentionally misleading those hoping to progress the field. Graphene and MXenes are arguably the most exciting organic and inorganic nanomaterials for polymer nanocomposite strain sensing applications respectively. Due to their combination of cost-efficient, scalable production and device performances, their potential commercial usage is very promising. Here, we explain the methods for colloidal nanosheets suspension creation and the mechanisms, metrics and models which govern the electromechanical properties of the polymer-based nanocomposites they form. Furthermore, the many fabrication procedures applied to make these nanosheet-based sensing devices are discussed. With the performances of 70 different nanocomposite systems from recent (post 2020) publications critically assessed. From the evaluation of these works using universal modelling, the prospects of the field are considered. Finally, we argue that the realisation of commercial nanocomposite devices may in fact have a negative effect on the global climate crisis if current research trends do not change.

Piezoresistive Fibers with Large Working Factors for Strain Sensing Applications

Piezoresistive fibers with large working factors remain of great interest for strain sensing applications involving large strains, yet difficult to achieve. Here, we produced strain-sensitive fibers with large working factors by dip-coating nanocomposite piezoresistive inks on surface-modified polyether block amide (PEBA) fibers. Surface modification of neat PEBA fibers was carried out with polydopamine (PDA) while nanocomposite conductive inks consisted of styrene-ethylene-butylene-styrene (SEBS) elastomer and carbon black (CB). As such, the deposition of piezoresistive coatings was enabled through nonconventional hydrogen-bonding interactions. The resultant fibers demonstrated well-defined piezoresistive linear relationships, which increased with CB filler loading in SEBS. In addition, gauge factors decreased with increasing CB mass fractions from ∼15 to ∼7. Furthermore, we used the fatigue theory to predict the endurance limit (C_e) of our fibers toward resistance signal stability. Such a piezoresistive performance allowed us to explore the application of our fibers as strain sensors for monitoring the movement of finger joints.

Printable Graphene-Sustainable Elastomer-Based Cross Talk Free Sensor for Point of Care Diagnostics

Developing sensors for monitoring physiological parameters such as temperature and strain for point of care (POC) diagnostics is critical for better care of the patients. Various commercial sensors are available to get the job done; however, challenges like the structural rigidity of such sensors confine their usage. As an alternative, flexible sensors have been looked upon recently. In most cases, flexible sensors cannot discriminate the signals from different stimuli. While there have been reports on the printable sensors providing cross-talk-free solutions, research related to developing sensors from a sustainable source providing discriminability between signals is not well-explored. Herein, we report the development of a stencil printable composition made of graphene and epoxidized natural rubber. The stencil printability index was vetted using rheological studies. Post usage, the developed sensor was dissolved in an organic solvent at room temperature. This, along with the choice of a sustainable elastomer, warrants the minimization of electronic waste and carbon footprint. The developed material demonstrated good conformability with the skin and could perceive and decouple the signals from temperature and strain without inducing any crosstalks. Using a representative volume element model, a comparison between experimental findings and computation studies was made. The developed sensors demonstrated gauge factors of -506 and 407 in the bending strain regimes of 0-0.04% and 0.04%-0.09%, respectively, while the temperature sensitivity was noted to be -0.96%/°C. The printed sensors demonstrated a multifunctional sensing behavior for monitoring various active physiological parameters ranging from temperature, strain, pulse, and breathing to auditory responses. Using a Bluetooth module, various parameters like temperature and strain could be monitored seamlessly in a smart-phone. The current development would be crucial to open new avenues to fabricate crosstalk-free sensors from sustainable sources for POC diagnostics.

Electromechanical Performance of Strain Sensors Based on Viscoelastic Conductive Composite Polymer Fibers

Flexible conductive polymer composite (CPC) fibers that show large changes in resistance with deformation have recently gained much attention as strain-sensing components for future wearable electronics. However, the electrical resistance of these materials decays with time during dynamic cyclic loading, a deformation performed to simulate their real application as strain sensors. Despite the extensive research on CPC fibers, the mechanism leading to this decay in the electromechanical response under repetitive cycles remains unreported. Herein, this behavior is investigated using fiber-based strain sensors wet spun from thermoplastic polyurethane (TPU) consisting of a carbonaceous hybrid conductive filler system of carbon black (CB) and carbon nanotubes (CNTs). We found electrical viscosity to predict the observed electromechanical resistance decay. This implies that cycling these materials enables the relaxation of both the polymer chains and the conductive network. In addition, the resulting piezoresistive fibers are sensitive to deformation in the region of low strain (gauge factor of 6.0 within 3.0% strain), remain conductive under 280.5% deformation, and are stable for more than 2000 cycles. Finally, we demonstrate the potential of TPU/CB-CNT fibers as strain sensors for monitoring human motion.

ZrB2/SiCN Thin-Film Strain Gauges for In-Situ Strain Detection of Hot Components

The in-situ strain/stress detection of hot components in harsh environments remains a challenging task. In this study, ZrB₂/SiCN thin-film strain gauges were fabricated on alumina substrates by direct writing. The effects of ZrB₂ content on the electrical conductivity and strain sensitivity of ZrB₂/SiCN composites were investigated, and based on these, thin film strain gauges with high electrical conductivity (1.71 S/cm) and a gauge factor of 4.8 were prepared. ZrB₂/SiCN thin-film strain gauges exhibit excellent static, cyclic strain responses and resistance stability at room temperature. In order to verify the high temperature performance of the ZrB₂/SiCN thin-film strain gauges, the temperature-resistance characteristic curves test, high temperature resistance stability test and cyclic strain test were conducted from 25 °C to 600 °C. ZrB₂/SiCN thin-film strain gauges exhibit good resistance repeatability and stability, and highly sensitive strain response, from 25 °C to 600 °C. Therefore, ZrB₂/SiCN thin-film strain gauges provide an effective approach for the measurement of in-situ strain of hot components in harsh environments.

Variations of tunnelling resistance between CNTs with strain in composites: non-monotonicty and influencing factors

The electro-mechanical response of conductive carbon-nanotube(CNT)-polymer composites is vital when they are used as smart-sensing materials. Clarifying the variation trend of resistance with strain is the key to design and regulate the piezoresistive property of such material. Here, we present some finite element simulations to predict the electro-mechanical response using a geometrical model comprising two hollow cylindrical CNTs and a cuboid matrix. The electrical contact between CNTs is represented by some elements which account for quantum tunnelling effects and capture the sensitivity of conductivity to separation. Different from classical simulations using solid model or one-dimensional beam model, in which the tunnelling resistance between two CNTs changes monotonously with strain, the results in this work show that the trend is non-monotonic in some cases, i.e. it increases at first and then decreases with the uniaxial compressive strain when the elastic modulus of the matrix is high. In addition, factors affecting the different variation trends are discussed in details, which include geometric model, elastic modulus and Poisson's ratio of the matrix, and orientation angle.

A 3D-printed neuromorphic humanoid hand for grasping unknown objects

Compared with conventional von Neumann's architecture-based processors, neuromorphic systems provide energy-saving in-memory computing. We present here a 3D neuromorphic humanoid hand designed for providing an artificial unconscious response based on training. The neuromorphic humanoid hand system mimics the reflex arc for a quick response by managing complex spatiotemporal information. A 3D structural humanoid hand is first integrated with 3D-printed pressure sensors and a portable neuromorphic device that was fabricated by the multi-axis robot 3D printing technology. The 3D neuromorphic robot hand provides bioinspired signal perception, including detection, signal transmission, and signal processing, together with the biomimetic reflex arc function, allowing it to hold an unknown object with an automatically increased gripping force without a conventional controlling processor. The proposed system offers a new approach for realizing an unconscious response with an artificially intelligent robot.

Quantifying the Piezoresistive Mechanism in High-Performance Printed Graphene Strain Sensors

Printed strain sensors will be important in applications such as wearable devices, which monitor breathing and heart function. Such sensors need to combine high sensitivity and low resistance with other factors such as cyclability, low hysteresis, and minimal frequency/strain-rate dependence. Although nanocomposite sensors can display a high gauge factor (G), they often perform poorly in the other areas. Recently, evidence has been growing that printed, polymer-free networks of nanoparticles, such as graphene nanosheets, display very good all-round sensing performance, although the details of the sensing mechanism are poorly understood. Here, we perform a detailed characterization of the thickness dependence of piezoresistive sensors based on printed networks of graphene nanosheets. We find both conductivity and gauge factor to display percolative behavior at low network thickness but bulk-like behavior for networks above ∼100 nm thick. We use percolation theory to derive an equation for gauge factor as a function of network thickness, which well-describes the observed thickness dependence, including the divergence in gauge factor as the percolation threshold is approached. Our analysis shows that the dominant contributor to the sensor performance is not the effect of strain on internanosheet junctions but the strain-induced modification of the network structure. Finally, we find these networks display excellent cyclability, hysteresis, and frequency/strain-rate dependence as well as gauge factors as high as 350.

Printable G-Putty for Frequency- and Rate-Independent, High-Performance Strain Sensors

While nanocomposite electromechanical sensors are expected to display reasonable conductivity and high sensitivity, little consideration is given to eliminating hysteresis and strain rate/frequency dependence from their response. For example, while G-putty, a composite of graphene and polysiloxane, has very high electromechanical sensitivity, its extreme viscoelasticity renders it completely unsuitable for real sensors due to hysteretic and rate-/frequency-dependent effects. Here it is shown that G-putty can be converted to an ink and printed into patterned thin films on elastic substrates. A partial graphene-polymer phase segregation during printing increases the thin-film conductivity by ×10⁶ compared to bulk, while the mechanical effects of the substrate largely suppress hysteresis and completely remove strain rate and frequency dependence. This allows the fabrication of practical, high-gauge-factor, wearable sensors for pulse measurements as well as patterned sensors for low-signal vibration sensing.