Electronic skins are essential for real-time health monitoring and tactile perception in robots. Although the use of soft elastomers and microstructures have improved the sensitivity and pressure-sensing range of tactile sensors, the intrinsic viscoelasticity of soft polymeric materials remains a long-standing challenge resulting in cyclic hysteresis. This causes sensor data variations between contact events that negatively impact the accuracy and reliability. Here, we introduce the Tactile Resistive Annularly Cracked E-Skin (TRACE) sensor to address the inherent trade-off between sensitivity and hysteresis in tactile sensors when using soft materials. We discovered that piezoresistive sensors made using an array of three-dimensional (3D) metallic annular cracks on polymeric microstructures possess high sensitivities (> 107 Ω ⋅ kPa−1), low hysteresis (2.99 ± 1.37%) over a wide pressure range (0–20 kPa), and fast response (400 Hz). We demonstrate that TRACE sensors can accurately detect and measure the pulse wave velocity (PWV) when skin mounted. Moreover, we show that these tactile sensors when arrayed enabled fast reliable one-touch surface texture classification with neuromorphic encoding and deep learning algorithms.

self-repair in order to survive and thrive. Soft to hard tissues can self-regenerate when injured, including the skin and bones. [6] Some of the living tissues, such as nails and bones, can even continuously remodeling themselves, removing the damaged tissues unintentionally and replaced by newly grown tissues. However, unlike regenerative and remodeling capabilities in nature, robots are made from nonliving synthetic materials such as polymers and metals. Hence, as we develop robots to have greater autonomy and capabilities, having the ability to self-heal or self-repair is becoming more critical, if not, essential, especially from an environmental sustainability point of view. [2,[7][8][9][10][11] The term self-healing materials, also often referred to as self-mending or selfrepairing materials, are materials that can regain some or most of its original material properties when damaged. In synthetic materials, the self-healing materials repair their damage without regenerative origins. As these selfhealing materials undergo self-repair, they regain their original intended functions through the recovery of the desired material properties, without an increase in original mass.As the number of self-healing materials is growing at a rapid clip, we first establish a brief history in this review to help the reader gain a broader perspective on self-healing materials. We emphasize on self-healing materials that recover their mechanical properties, because mechanical properties often dictate the possible applications. Figure 1 highlights the various selfhealing materials from high modulus to low modulus materials that can be used for robotic applications.There are two broad classifications for self-healing materials: a) autonomic versus nonautonomic self-healing materials; b) intrinsic versus extrinsic self-healing. [8] These self-healing materials can recover their properties either autonomously, i.e., without significant external intervention, much like human tissues; or they can also heal with external intervention, such as when some external environment changes cause temperature increment or via various triggers such as mechanical stimuli. Intrinsic self-healing materials do not need external healing agents, while extrinsic self-healing materials contain external healing agents for the healing of the matrix materials. In addition to those classifications, we will provide new insights on classifying these materials further into this review.In Section 2, we discuss various types of smart biomimetic robots where self-healing materials can be beneficial. Section 3 Robots are increasingly assisting humans in performing various tasks. Like special agents with elite skills, they can venture to distant locations and adverse environments, such as the deep sea and outer space. Micro/nanobots can also act as intrabody agents for healthcare applications. Self-healing materials that can autonomously perform repair functions are useful to address the unpredictability of the environment and the increasing drive toward the autonom...

Mechanical replacement prosthetics have advanced in both esthetics and mechanical functions, but still require progress in attaining full natural functionality via tactile feedback. Through bioinspiration of the somatosensory system, recent works in the development of materials and technologies at three critical interfaces have shown great advancements: skin‐inspired multifunctionality at the prosthetic level using flexible electronics, artificial transmission of the biosignals between the prosthesis and nervous system, and stimulation and recording of these signals with mechanically compliant, implantable neural interfaces. Herein, a systematic study of the artificial skin sensation pathways for the prosthetic interfaces is discussed together with the current state‐of‐the‐art technologies and prospective strategies to enable the complete sensory feedback loop in prosthetics through the use of biomimetic sensing platforms, artificial synapses, and neural interrogation electronics.

Skin-like sensors that transduce tactile pressures and vibrations with minimal environment variation on performance are crucial in robotic sensing and prosthetic skins. However, sensor performance variations under varying environmental conditions, such as temperature and humidity, are common in piezoresistive sensors because of their intrinsic materials properties. Moreover, the viscoelasticity of soft elastomers causes strain response in a time-dependent fashion, which poses sensor limitations in high-frequency tactile tasks, such as texture recognition. In this work, we demonstrate a new environment-robust tactile sensor via an interfacial engineering process for uniform graphene coating on microstructured elastomers. The sensor enables reliable pressure response over a range of temperature (25−60 °C) and humidity (30−90% relative humidity) conditions, with resistance variations less than 5% and 3%, respectively. It is also able to detect vibrations with frequency up to 1500 Hz. Moreover, our sensor shows ultra-high durability, with high sensitivity and low hysteresis preserved after 1 million cycles. We demonstrate applications with the sensor in epidermal signal monitoring at different arteries, as well as accurate (>95%) surface texture recognition in combination with machine learning.

Nature has taught us fascinating strategies to design materials such that they exhibit superior and novel properties. Shells of mantis club have protein fibres arranged in a 3D helicoidal architecture that give them remarkable strength and toughness, enabling them to absorb high-impact energy. This complex architecture is now possible to replicate with the recent advances in additive manufacturing. In this paper, we used melt electrospinning to fabricate 3D polycaprolactone (PCL) fibrous design to mimic the natural helicoidal structures found in the shells of the mantis shrimp’s dactyl club. To improve the tensile deformation behavior of the structures, the surface of each layer of the samples were treated with carboxyl and amino groups. The toughness of the surface-treated helicoidal sample was found to be two times higher than the surface-treated unidirectional sample and five times higher than the helicoidal sample without surface treatment. Free amino groups (NH2) were introduced on the surface of the fibres and membrane via surface treatment to increase the interaction and adhesion among the different layers of membranes. We believe that this represents a preliminary feasibility in our attempt to mimic the 3D helicoidal architectures at small scales, and we still have room to improve further using even smaller fibre sizes of the modeled architectures. These lightweight synthetic analogue materials enabled by electrospinning as an additive manufacturing methodology would potentially display superior structural properties and functionalities such as high strength and extreme toughness.