PVDF Hybrid Nanocomposites with Graphene and Carbon Nanotubes and Their Thermoresistive and Joule Heating Properties.

In recent years, conductive polymer nanocomposites have gained significant attention due to their promising thermoresistive and Joule heating properties across a range of versatile applications, such as heating elements, smart materials, and thermistors. This paper presents an investigation of semi-crystalline polyvinylidene fluoride (PVDF) nanocomposites with 6 wt.% carbon-based nanofillers, namely graphene nanoplatelets (GNPs), multi-walled carbon nanotubes (MWCNTs), and a combination of GNPs and MWCNTs (hybrid). The influence of the mono- and hybrid fillers on the crystalline structure was analyzed by X-ray diffraction (XRD) and differential scanning calorimetry (DSC). It was found that the nanocomposites had increased amorphous fraction compared to the neat PVDF. Furthermore, nanocomposites enhanced the ß phase of the PVDF by up to 12% mainly due to the presence of MWCNTs. The resistive properties of the nanocompositions were weakly affected by the temperature in the analyzed temperature range of 25-100 °C; nevertheless, the hybrid filler composites were proven to be more sensitive than the monofiller ones. The Joule heating effect was observed when 8 and 10 V were applied, and the compositions reached a self-regulating effect at around 100-150 s. In general, the inclusion in PVDF of nanofillers such as GNPs and MWCNTs, and especially their hybrid combinations, may be successfully used for tuning the self-regulated Joule heating properties of the nanocomposites.

Soft Self-Regulating Heating Elements for Thermoplastic Elastomer-Based Electronic Skin Applications.

Resistive heating elements can be of particular interest for many applications, such as e-skin. In this study, soft heating elements were developed by combining thermoplastic polyurethane (TPU) with carbon black. In contrast to previous studies on thermoplastic polymer-based thermistors, the heating elements could endure elongations above 100%. Due to the high melting point of the TPU and the carbon filler, the thermistors could be heated up to 180°C without significant deformation. The heating elements were extruded on TPU substrates using material extrusion additive manufacturing in one-step process. Self-regulating behavior to control the maximum temperature was achieved with the application of two different voltages (20 and 25 V) and different current thresholds, between 100 and 800 mA. The heating performance was adjusted by changing the geometry of the sensing elements; an increase in cross section resulted in a lower current density and lower temperature. For the heating elements, variation of the additive manufacturing parameters such as offset, layer height, nozzle speed, and extrusion multiplier resulted in a different width/height aspect ratio of the cross section of the extruded lines, affecting the initial resistivity of the thermistor. Orientation of the carbon filler during extrusion process is one reason for the small change of the longitudinal conductivity of the heating elements. The resulting skin with the integrated heating elements allowed the possibility to perform the in situ heating for the localized healing of structural damage, while maintaining the softness required for the application of soft robotic electronic skin.

Bioprinting of Stable Bionic Interfaces Using Piezoresistive Hydrogel Organoelectronics.

Bionic tissues offer an exciting frontier in biomedical research by integrating biological cells with artificial electronics, such as sensors. One critical hurdle is the development of artificial electronics that can mechanically harmonize with biological tissues, ensuring a robust interface for effective strain transfer and local deformation sensing. In this study, a highly tissue-integrative, soft mechanical sensor fabricated from a composite piezoresistive hydrogel. The composite not only exhibits exceptional mechanical properties, with elongation at the point of fracture reaching up to 680%, but also maintains excellent biocompatibility across multiple cell types. Furthermore, the material exhibits bioadhesive qualities, facilitating stable cell adhesion to its surface. A unique advantage of the formulation is the compatibility with 3D bioprinting, an essential technique for fabricating stable interfaces. A multimaterial sensorized 3D bionic construct is successfully bioprinted, and it is compared to structures produced via hydrogel casting. In contrast to cast constructs, the bioprinted ones display a high (87%) cell viability, preserve differentiation ability, and structural integrity of the sensor-tissue interface throughout the tissue development duration of 10 d. With easy fabrication and effective soft tissue integration, this composite holds significant promise for various biomedical applications, including implantable electronics and organ-on-a-chip technologies.

Rapid formation of carbon nanotubes-natural rubber films cured with glutaraldehyde for reducing percolation threshold concentration.

Carbon nanotubes (CNTs) filled natural rubber (NR) composites with various CNT contents at 0, 1, 2, 3, 4 and 5 phr were prepared by latex mixing method using glutaraldehyde as curing agent. This work aims to improve the electrical and mechanical properties of CNT filled NR vulcanizates. The CNT dispersion of NR composites was clarified using dispersion grader, optical microscopy and scanning electron microscopy. The electrical properties of NR composites in the existing of CNT networks were studied by following the well-known percolation theory. It was observed that the NR composites exhibited low percolation threshold at 0.98 phr of CNT. Moreover, a three-dimensional network formation of CNT in the NR composites was observed and it is indicated by the t-value of 1.67. The mechanical properties of NR composites in terms of modulus, tensile strength and hardness properties were increased upon the addition of CNT to the optimum mechanical properties at 1 phr of CNT. Therefore, the present work is found the novelty of the study that the conductive rubber latex film can be produced using GA as low-temperature curing agent which enhanced good electrical properties. Moreover, this work is found to be beneficial in case of conductive rubber latex film that requires high modulus at low strain. The additional advantage of this system is the curing process occurs at low-temperature using GA and it can be easily processed.

Preceramic Polymers for Additive Manufacturing of Silicate Ceramics.

The utilization of preceramic polymers (PCPs) to produce both oxide and non-oxide ceramics has caught significant interest, owing to their exceptional characteristics. Diverse types of polymer-derived ceramics (PDCs) synthesized by using various PCPs have demonstrated remarkable characteristics such as exceptional thermal stability, resistance to corrosion and oxidation at elevated temperatures, biocompatibility, and notable dielectric properties, among others. The application of additive manufacturing techniques to produce PDCs opens up new opportunities for manufacturing complex and unconventional ceramic structures with complex designs that might be challenging or impossible to achieve using traditional manufacturing methods. This is particularly advantageous in industries like aerospace, automotive, and electronics. In this review, various categories of preceramic polymers employed in the synthesis of polymer-derived ceramics are discussed, with a particular focus on the utilization of polysiloxane and polysilsesquioxanes to generate silicate ceramics. Further, diverse additive manufacturing techniques adopted for the fabrication of polymer-derived silicate ceramics are described.

Sensorized Skin With Biomimetic Tactility Features Based on Artificial Cross-Talk of Bimodal Resistive Sensory Inputs.

Tactility in biological organisms is a faculty that relies on a variety of specialized receptors. The bimodal sensorized skin, featured in this study, combines soft resistive composites that attribute the skin with mechano- and thermoreceptive capabilities. Mimicking the position of the different natural receptors in different depths of the skin layers, a multi-layer arrangement of the soft resistive composites is achieved. However, the magnitude of the signal response and the localization ability of the stimulus change with lighter presses of the bimodal skin. Hence, a learning-based approach is employed that can help achieve predictions about the stimulus using 4500 probes. Similar to the cognitive functions in the human brain, the cross-talk of sensory information between the two types of sensory information allows the learning architecture to make more accurate predictions of localization, depth, and temperature of the stimulus contiguously. Localization accuracies of 1.8 mm, depth errors of 0.22 mm, and temperature errors of 8.2 °C using 8 mechanoreceptive and 8 thermoreceptive sensing elements are achieved for the smaller inter-element distances. Combining the bimodal sensing multilayer skins with the neural network learning approach brings the artificial tactile interface one step closer to imitating the sensory capabilities of biological skin.

Soft Wearable Piezoresistive Sensors Based on Natural Rubber Fabricated with a Customized Vat-Based Additive Manufacturing Process.

Piezoresistive sensors for monitoring human motions are essential for the prevention and treatment of injury. Natural rubber is a material of renewable origin that can be used for the development of soft wearable sensors. In this study, natural rubber was combined with acetylene black to develop a soft piezoresistive sensing composite for monitoring the motion of human joints. An additive manufacturing technique based on stereolithography was used, and it was seen that the sensors produced with the method could detect even small strains (<10%) successfully. With the same sensor composite fabricated by mold casting, it was not possible to detect low strains reliably. TEM microscopy revealed that the distribution of the filler was not homogeneous for the cast samples, suggesting a directionality of the conductive filler network. For the sensors fabricated through the stereolithography-based method, a homogeneous distribution could be achieved. Based on mechano-electrical characterization, it was seen that the samples produced with AM combined the ability to endure large elongations with a monotonic sensor response. Under dynamic conditions, the sensor response of the samples produced by 3D printing showed lower drift and lower signal relaxation. The piezoresistive sensors were examined for monitoring the motion of the human finger joints. By increasing the bending angle of the sensor, it was possible to increase the sensitivity of the response. With the renewable origin of natural rubber and manufacturing method, the featured sensors can expand the applicability of soft flexible electronics in biomedical applications and devices.

3D Printable Soft Sensory Fiber Networks for Robust and Complex Tactile Sensing.

The human tactile system is composed of multi-functional mechanoreceptors distributed in an optimized manner. Having the ability to design and optimize multi-modal soft sensory systems can further enhance the capabilities of current soft robotic systems. This work presents a complete framework for the fabrication of soft sensory fiber networks for contact localization, using pellet-based 3D printing of piezoresistive elastomers to manufacture flexible sensory networks with precise and repeatable performances. Given a desirable soft sensor property, our methodology can design and fabricate optimized sensor morphologies without human intervention. Extensive simulation and experimental studies are performed on two printed networks, comparing a baseline network to one optimized via an existing information theory based approach. Machine learning is used for contact localization based on the sensor responses. The sensor responses match simulations with tunable performances and good localization accuracy, even in the presence of damage and nonlinear material properties. The potential of the networks to function as capacitive sensors is also demonstrated.

Charged-cellulose nanofibrils as a nutrient carrier in biodegradable polymers for enhanced efficiency fertilizers.

An enhanced efficiency fertilizer (EEF) is essential for sustainable agriculture, and here, we evaluated cellulose nanofibrils (CNF) as a nutrient carrier dispersed in biodegradable polymeric matrices. CNF were functionalized with negative (CNF-) and positive (CNF+) charges to improve (i) the CNF-nutrient and (ii) the CNF-polymeric matrix interactions. The CNF encapsulated the KNO3 nutrient by spray drying (microcapsules) and then inserted into a poly (hydroxybutyrate)/starch-based matrix by melt-compounding (tablets). These materials were morphologically, structurally, and thermally characterized before and after biodegradation. Nutrient release profiles showed the microcapsules released the nutrients for up to 1 h, while the tablets did for 8 h in water and over 80 days in soil. Tablets with CNF- released NO3- faster than K+, and those with CNF+ behaved inversely. Besides, the biodegradation efficiencies were up to 75 % in 120 days. The CNF charges affected nutrient release and the matrix biodegradation, ensuring the matrices were harmless to the environment.

Processing of Self-Healing Polymers for Soft Robotics.

Soft robots are, due to their softness, inherently safe and adapt well to unstructured environments. However, they are prone to various damage types. Self-healing polymers address this vulnerability. Self-healing soft robots can recover completely from macroscopic damage, extending their lifetime. For developing healable soft robots, various formative and additive manufacturing methods have been exploited to shape self-healing polymers into complex structures. Additionally, several novel manufacturing techniques, noted as (re)assembly binding techniques that are specific to self-healing polymers, have been created. Herein, the wide variety of processing techniques of self-healing polymers for robotics available in the literature is reviewed, and limitations and opportunities discussed thoroughly. Based on defined requirements for soft robots, these techniques are critically compared and validated. A strong focus is drawn to the reversible covalent and (physico)chemical cross-links present in the self-healing polymers that do not only endow healability to the resulting soft robotic components, but are also beneficial in many manufacturing techniques. They solve current obstacles in soft robots, including the formation of robust multi-material parts, recyclability, and stress relaxation. This review bridges two promising research fields, and guides the reader toward selecting a suitable processing method based on a self-healing polymer and the intended soft robotics application.

Investigation of Electromechanical Properties on 3-D Printed Piezoelectric Composite Scaffold Structures.

Piezoelectric composites with 3-3 connectivity gathered attraction due to their potential application as an acoustic transducer in medical imaging, non-destructive testing, etc. In this contribution, piezoelectric composites were fabricated with a material extrusion-based additive manufacturing process (MEX), also well-known under the names fused deposition modeling (FDM), fused filament fabrication (FFF) or fused deposition ceramics (FDC). Thermoplastic filaments were used to achieve open and offset printed piezoelectric scaffold structures. Both scaffold structures were printed, debinded and sintered successfully using commercial PZT and BaTiO3 powder. For the first time, it could be demonstrated, that using the MEX processing method, closed pore ferroelectric structure can be achieved without pore-former additive. After ceramic processing, the PZT scaffold structures were impregnated with epoxy resin to convert them into composites with 3-3 connectivity. A series of composites with varying ceramic content were achieved by changing the infill parameter during the 3D printing process systematically, and their electromechanical properties were investigated using the electromechanical aix PES device. Also, the Figure of merit (FOM) of these composites was calculated to assess the potential of this material as a candidate for transducer applications. A maximum for the FOM at 25 vol.% of PZT could be observed in this study.

Supramolecular Self-Healing Sensor Fiber Composites for Damage Detection in Piezoresistive Electronic Skin for Soft Robots.

Self-healing materials can prolong the lifetime of structures and products by enabling the repairing of damage. However, detecting the damage and the progress of the healing process remains an important issue. In this study, self-healing, piezoresistive strain sensor fibers (ShSFs) are used for detecting strain deformation and damage in a self-healing elastomeric matrix. The ShSFs were embedded in the self-healing matrix for the development of self-healing sensor fiber composites (ShSFC) with elongation at break values of up to 100%. A quadruple hydrogen-bonded supramolecular elastomer was used as a matrix material. The ShSFCs exhibited a reproducible and monotonic response. The ShSFCs were investigated for use as sensorized electronic skin on 3D-printed soft robotic modules, such as bending actuators. Depending on the bending actuator module, the electronic skin was loaded under either compression (pneumatic-based module) or tension (tendon-based module). In both configurations, the ShSFs could be successfully used as deformation sensors, and in addition, detect the presence of damage based on the sensor signal drift. The sensor under tension showed better recovery of the signal after healing, and smaller signal relaxation. Even with the complete severing of the fiber, the piezoresistive properties returned after the healing, but in that case, thermal heat treatment was required. With their resilient response and self-healing properties, the supramolecular fiber composites can be used for the next generation of soft robotic modules.

Analysis of Styrene-Butadiene Based Thermoplastic Magnetorheological Elastomers with Surface-Treated Iron Particles.

Magnetorheological elastomers (MRE) are increasing in popularity in many applications because of their ability to change stiffness by applying a magnetic field. Instead of liquid-based 1 K and 2 K silicone, thermoplastic elastomers (TPE), based on styrene-butadiene-styrene block copolymers, have been investigated as matrix material. Three different carbonyl iron particles (CIPs) with different surface treatments were used as magneto active filler material. For the sample fabrication, the thermoplastic pressing method was used, and the MR effect under static and dynamic load was investigated. We show that for filler contents above 40 vol.-%, the linear relationship between powder content and the magnetorheological effect is no longer valid. We showed how the SiO2 and phosphate coating of the CIPs affects the saturation magnetization and the shear modulus of MRE composites. A combined silica phosphate coating resulted in a higher shear modulus, and therefore, the MR effect decreased, while coating with SiO2 only improved the MR effect. The highest performance was achieved at low deformations; a static MR effect of 73% and a dynamic MR effect of 126% were recorded. It was also shown that a lower melting viscosity of the TPE matrix helps to increase the static MR effect of anisotropic MREs, while low shear modulus is crucial for achieving high dynamic MR. The knowledge from TPE-based magnetic composites will open up new opportunities for processing such as injection molding, extrusion, and fused deposition modeling (FDM).

Sensorized Robotic Skin Based on Piezoresistive Sensor Fiber Composites Produced with Injection Molding of Liquid Silicone.

Soft robotics and flexible electronics are rising in popularity and can be used in many applications. However, there is still a need for processing routes that allow the upscaling in production for functional soft robotic parts in an industrial scale. In this study, injection molding of liquid silicone is suggested as a fabrication method for sensorized robotic skin based on sensor fiber composites. Sensor fibers based on thermoplastic elastomers with two different shore hardness (50A and 70A) are combined with different silicone materials. A mathematical model is used to predict the mechanical load transfer from the silicone matrix to the fiber and shows that the matrix of the lowest shore hardness should not be combined with the stiffer fiber. The sensor fiber composites are fixed on a 3D printed robotic finger. The sensorized robotic skin based on the composite with the 50A fiber in combination with pre-straining gives good sensor performance as well as a large elasticity. It is proposed that a miss-match in the mechanical properties between fiber sensor and matrix should be avoided in order to achieve low drift and relaxation. These findings can be used as guidelines for material selection for future sensor integrated soft robotic systems.

Fabrication of a Soft Robotic Gripper With Integrated Strain Sensing Elements Using Multi-Material Additive Manufacturing.

With the purpose of making soft robotic structures with embedded sensors, additive manufacturing techniques like fused deposition modeling (FDM) are popular. Thermoplastic polyurethane (TPU) filaments, with and without conductive fillers, are now commercially available. However, conventional FDM still has some limitations because of the marginal compatibility with soft materials. Material selection criteria for the available material options for FDM have not been established. In this study, an open-source soft robotic gripper design has been used to evaluate the FDM printing of TPU structures with integrated strain sensing elements in order to provide some guidelines for the material selection when an elastomer and a soft piezoresistive sensor are combined. Such soft grippers, with integrated strain sensing elements, were successfully printed using a multi-material FDM 3D printer. Characterization of the integrated piezoresistive sensor function, using dynamic tensile testing, revealed that the sensors exhibited good linearity up to 30% strain, which was sufficient for the deformation range of the selected gripper structure. Grippers produced using four different TPU materials were used to investigate the effect of the Shore hardness of the TPU on the piezoresistive sensor properties. The results indicated that the in situ printed strain sensing elements on the soft gripper were able to detect the deformation of the structure when the tentacles of the gripper were open or closed. The sensor signal could differentiate between the picking of small or big objects and when an obstacle prevented the tentacles from opening. Interestingly, the sensors embedded in the tentacles exhibited good reproducibility and linearity, and the sensitivity of the sensor response changed with the Shore hardness of the gripper. Correlation between TPU Shore hardness, used for the gripper body and sensitivity of the integrated in situ strain sensing elements, showed that material selection affects the sensor signal significantly.

Antistatic Fibers for High-Visibility Workwear: Challenges of Melt-Spinning Industrial Fibers.

Safety workwear often requires antistatic protection to prevent the build-up of static electricity and sparks, which can be extremely dangerous in a working environment. In order to make synthetic antistatic fibers, electrically conducting materials such as carbon black are added to the fiber-forming polymer. This leads to unwanted dark colors in the respective melt-spun fibers. To attenuate the undesired dark color, we looked into various possibilities including the embedding of the conductive element inside a dull side-by-side bicomponent fiber. The bicomponent approach, with an antistatic compound as a minor element, also helped in preventing the severe loss of tenacity often caused by a high additive loading. We could melt-spin a bicomponent fiber with a specific resistance as low as 0.1 Ωm and apply it in a fabric that fulfills the requirements regarding the antistatic properties, luminance and flame retardancy of safety workwear.

Effect of the Elastomer Matrix on Thermoplastic Elastomer-Based Strain Sensor Fiber Composites.

In this study, a thermoplastic elastomer sensor fiber was embedded in an elastomer matrix. The effect of the matrix material on the sensor properties and the piezoresistive behavior of the single fiber-matrix composite system was investigated. For all composites, cycling test (dynamic test) and the relaxation behavior at different strains (quasi-static test) were investigated. In all cases, dynamic properties and quasi-static significantly changed after embedding, compared to the pure fiber. The composite with the silicone elastomer PDMS (Polydimethylsiloxane) as matrix material exhibited deviation from linear response of the resistivity at low strains and proved an unsuitable choice compared to natural rubber. The addition of a spring construct in the embedded sensor fiber natural rubber composite improved the linearity at low strains but increased the mechanical and electrical hysteresis of the soft matter sensor composite. Using pre-vulcanized natural rubber improved linearity at low strains and reduced significantly the stress and relative resistance relaxation as well as the resistance hysteresis, especially if the resistance remained low. In both cases of the pre-vulcanized rubber and the spring structure, the piezoresistive behavior was improved, and at the same time, the stiffness of the system was increased indicating that using a stiffer matrix can be a strategy for improving the sensor properties.

Draw-spun, photonically annealed Ag fibers as alternative electrodes for flexible CIGS solar cells.

We explore the feasibility of Ag fiber meshes as electron transport layer for high-efficiency flexible Cu(In,Ga)Se2 (CIGS) solar cells. Woven meshes of Ag fibers after UV illumination and millisecond flash-lamp treatment results in a sheet resistance of 17 Ω/sq and a visible transmittance above 85%. Conductive Ag meshes are integrated into flexible CIGS cells as transparent conductive electrode (TCE) alone or together with layers of Al-doped ZnO (AZO) with various thickness of 0…900 nm. The Ag mesh alone is not able to function as a current collector. If used together with a thin AZO layer (50 nm), the Ag mesh markedly improves the fill factor and cell efficiency, in spite of the adverse mesh shadowing. When Ag mesh is combined with thicker (200 nm or 900 nm) AZO layers, no improvements in photovoltaic parameters are obtained. When comparing a hybrid TCE consisting of 50 nm AZO and Ag fiber mesh with a thick 900 nm reference AZO device, an improved charge carrier collection in the near-infrared range is observed. Regardless of the AZO thickness, the presence of Ag mesh slows down cell degradation upon mechanical tensile stress, which could be interesting for implementation into flexible thin film CIGS modules.

Piezoresistive Soft Condensed Matter Sensor for Body-Mounted Vital Function Applications.

A soft condensed matter sensor (SCMS) designed to measure strains on the human body is presented. The hybrid material based on carbon black (CB) and a thermoplastic elastomer (TPE) was bonded to a textile elastic band and used as a sensor on the human wrist to measure hand motion by detecting the movement of tendons in the wrist. Additionally it was able to track the blood pulse wave of a person, allowing for the determination of pulse wave peaks corresponding to the systole and diastole blood pressures in order to calculate the heart rate. Sensor characterization was done using mechanical cycle testing, and the band sensor achieved a gauge factor of 4-6.3 while displaying low signal relaxation when held at a strain levels. Near-linear signal performance was displayed when loading to successively higher strain levels up to 50% strain.

SVAS3: Strain Vector Aided Sensorization of Soft Structures.

Soft material structures exhibit high deformability and conformability which can be useful for many engineering applications such as robots adapting to unstructured and dynamic environments. However, the fact that they have almost infinite degrees of freedom challenges conventional sensory systems and sensorization approaches due to the difficulties in adapting to soft structure deformations. In this paper, we address this challenge by proposing a novel method which designs flexible sensor morphologies to sense soft material deformations by using a functional material called conductive thermoplastic elastomer (CTPE). This model-based design method, called Strain Vector Aided Sensorization of Soft Structures (SVAS3), provides a simulation platform which analyzes soft body deformations and automatically finds suitable locations for CTPE-based strain gauge sensors to gather strain information which best characterizes the deformation. Our chosen sensor material CTPE exhibits a set of unique behaviors in terms of strain length electrical conductivity, elasticity, and shape adaptability, allowing us to flexibly design sensor morphology that can best capture strain distributions in a given soft structure. We evaluate the performance of our approach by both simulated and real-world experiments and discuss the potential and limitations.