Bidirectional thermo-regulating hydrogel composite for autonomic thermal homeostasis.

Thermal homeostasis is an essential physiological function for preserving the optimal state of complex organs within the human body. Inspired by this function, here, we introduce an autonomous thermal homeostatic hydrogel that includes infrared wave reflecting and absorbing materials for improved heat trapping at low temperatures, and a porous structure for enhanced evaporative cooling at high temperatures. Moreover, an optimized auxetic pattern was designed as a heat valve to further amplify heat release at high temperatures. This homeostatic hydrogel provides effective bidirectional thermoregulation with deviations of 5.04 °C ± 0.55 °C and 5.85 °C ± 0.46 °C from the normal body temperature of 36.5 °C, when the external temperatures are 5 °C and 50 °C, respectively. The autonomous thermoregulatory characteristics of our hydrogel may provide a simple solution to people suffering from autonomic nervous system disorders and soft robotics that are susceptible to sudden temperature fluctuations.

Geometrically engineered rigid island array for stretchable electronics capable of withstanding various deformation modes.

Integration of rigid components in soft polymer matrix is considered as the most feasible architecture to enable stretchable electronics. However, a method of suppressing cracks at the interface between soft and rigid materials due to excessive and repetitive deformations of various types remains a formidable challenge. Here, we geometrically engineered Ferris wheel-shaped islands (FWIs) capable of effectively suppressing crack propagation at the interface under various deformation modes (stretching, twisting, poking, and crumpling). The optimized FWIs have notable increased strain at failure and fatigue life compared with conventional circle- and square-shaped islands. Stretchable electronics composed of various rigid components (LED and coin cell) were demonstrated using intrinsically stretchable printed electrodes. Furthermore, electronic skin capable of differentiating various tactile stimuli without interference was demonstrated. Our method enables stretchable electronics that can be used under various geometrical forms with notable enhanced durability, enabling stretchable electronics to withstand potentially harsh conditions of everyday usage.

Bending Sensor Based on Controlled Microcracking Regions for Application toward Wearable Electronics and Robotics.

A soft bending sensor based on the inverse pyramid structure is demonstrated, revealing that it can effectively suppress microcrack formation in designated regions, thus allowing the cracks to open gradually with bending in a controlled manner. Such a feature enabled the bending sensor to simultaneously have a wide dynamic range of bending strain (0.025-5.4%), high gauge factor (∼74), and high linearity (R2 ∼ 0.99). Furthermore, the bending sensor can capture repeated instantaneous changes in strain and various types of vibrations, owing to its fast response time. Moreover, the bending direction can be differentiated with a single layer of the sensor, and using an array of sensors integrated on a glove, object recognition was demonstrated via machine learning. Finally, a self-monitoring proprioceptive ionic electroactive polymer (IEAP) actuator capable of operating in liquid was demonstrated. Such features of our bending sensor will enable a simple and effective way of detecting sophisticated motion, thus potentially advancing wearable healthcare monitoring electronics and enabling proprioceptive soft robotics.

Hetero-Dimensional 2D Ti3C2Tx MXene and 1D Graphene Nanoribbon Hybrids for Machine Learning-Assisted Pressure Sensors.

Hybridization of low-dimensional components with diverse geometrical dimensions should offer an opportunity for the discovery of synergistic nanocomposite structures. In this regard, how to establish a reliable interfacial interaction is the key requirement for the successful integration of geometrically different components. Here, we present 1D/2D heterodimensional hybrids via dopant induced hybridization of 2D Ti3C2Tx MXene with 1D nitrogen-doped graphene nanoribbon. Edge abundant nanoribbon structures allow a high level nitrogen doping (∼6.8 at%), desirable for the strong coordination interaction with Ti3C2Tx MXene surface. For piezoresistive pressure sensor application, strong adhesion between the conductive layers and at the conductive layer/elastomer interface significantly diminishes the sensing hysteresis down to 1.33% and enhances the sensing stability up to 10 000 cycles at high pressure (100 kPa). Moreover, large-area pressure sensor array reveals a high potential for smart seat cushion-based posture monitoring application with high accuracy (>95%) by exploiting machine learning algorithm.

Deep-Learning-Based Deconvolution of Mechanical Stimuli with Ti3C2Tx MXene Electromagnetic Shield Architecture via Dual-Mode Wireless Signal Variation Mechanism.

Passive component-based soft resonators have been spotlighted in the field of wearable and implantable devices due to their remote operation capability and tunable properties. As the output signal of the resonator-based wireless communication device is given in the form of a vector (i.e., a spectrum of reflection coefficient), multiple information can, in principle, be stored and interpreted. Herein, we introduce a device that can deconvolute mechanical stimuli from a single wireless signal using dual-mode operation, specifically enabled by the use of Ti3C2Tx MXene. MXene's strong electromagnetic shielding effect enables the resonator to simultaneously measure pressure and strain without overlapping its output signal, unlike other conductive counterparts that are deficient in shielding ability. Furthermore, convolutional neural-network-based deep learning was implemented to predict the pressure and strain values from unforeseen output wireless signals. Our MXene-integrated wireless device can also be utilized as an on-skin mechanical stimuli sensor for rehabilitation monitoring after orthopedic surgery. The dual-mode signal variation mechanism enabled by integration of MXene allows wireless communication systems to efficiently handle various information simultaneously, through which multistimuli sensing capability can be imparted into passive component-based wearable and implantable electrical devices.

Neuromorphic Processing of Pressure Signal Using Integrated Sensor-Synaptic Device Capable of Selective and Reversible Short- and Long-Term Plasticity Operation.

To mimic the tactile sensing properties of the human skin, signals from tactile sensors need to be processed in an efficient manner. The integration of the tactile sensor with a neuromorphic device can potentially address this issue, as the neuromorphic device has both signal processing and memory capability through which parallel and efficient processing of information is possible. In this article, an intelligent haptic perception device (IHPD) is presented that combines pressure sensing with an organic electrochemical transistor-based synaptic device into a simple device architecture. More importantly, the IHPD is capable of rapid and reversible switching between short-term plasticity (STP) and long-term plasticity (LTP) operation through which accelerated learning, processing of new information, and distinctive operation of STP and LTP are possible. Various types of pressure information such as magnitude, rate, and duration were processed utilizing STP by which error-tolerant perception was demonstrated. Meanwhile, memorization and learning of pressure through a stepwise change in a conductive state was demonstrated using LTP. These demonstrations present unique approaches to process and learn tactile information, which can potentially be utilized in various electronic skin applications in the future.

Parallel Signal Processing of a Wireless Pressure-Sensing Platform Combined with Machine-Learning-Based Cognition, Inspired by the Human Somatosensory System.

Inspired by the human somatosensory system, pressure applied to multiple pressure sensors is received in parallel and combined into a representative signal pattern, which is subsequently processed using machine learning. The pressure signals are combined using a wireless system, where each sensor is assigned a specific resonant frequency on the reflection coefficient (S11 ) spectrum, and the applied pressure changes the magnitude of the S11 pole with minimal frequency shift. This allows the differentiation and identification of the pressure applied to each sensor. The pressure sensor consists of polypyrrole-coated microstructured poly(dimethylsiloxane) placed on top of electrodes, operating as a capacitive sensor. The high dielectric constant of polypyrrole enables relatively high pressure-sensing performance. The coils are vertically stacked to enable the reader to receive the signals from all of the sensors simultaneously at a single location, analogous to the junction between neighboring primary neurons to a secondary neuron. Here, the stacking order is important to minimize the interference between the coils. Furthermore, convolutional neural network (CNN)-based machine learning is utilized to predict the applied pressure of each sensor from unforeseen S11 spectra. With increasing training, the prediction accuracy improves (with mean squared error of 0.12), analogous to humans' cognitive learning ability.

Electronic Skin: Recent Progress and Future Prospects for Skin-Attachable Devices for Health Monitoring, Robotics, and Prosthetics.

Recent progress in electronic skin or e-skin research is broadly reviewed, focusing on technologies needed in three main applications: skin-attachable electronics, robotics, and prosthetics. First, since e-skin will be exposed to prolonged stresses of various kinds and needs to be conformally adhered to irregularly shaped surfaces, materials with intrinsic stretchability and self-healing properties are of great importance. Second, tactile sensing capability such as the detection of pressure, strain, slip, force vector, and temperature are important for health monitoring in skin attachable devices, and to enable object manipulation and detection of surrounding environment for robotics and prosthetics. For skin attachable devices, chemical and electrophysiological sensing and wireless signal communication are of high significance to fully gauge the state of health of users and to ensure user comfort. For robotics and prosthetics, large-area integration on 3D surfaces in a facile and scalable manner is critical. Furthermore, new signal processing strategies using neuromorphic devices are needed to efficiently process tactile information in a parallel and low power manner. For prosthetics, neural interfacing electrodes are of high importance. These topics are discussed, focusing on progress, current challenges, and future prospects.

Highly Uniform and Low Hysteresis Piezoresistive Pressure Sensors Based on Chemical Grafting of Polypyrrole on Elastomer Template with Uniform Pore Size.

Sensor-to-sensor variability and high hysteresis of composite-based piezoresistive pressure sensors are two critical issues that need to be solved to enable their practical applicability. In this work, a piezoresistive pressure sensor composed of an elastomer template with uniformly sized and arranged pores, and a chemically grafted conductive polymer film on the surface of the pores is presented. Compared to sensors composed of randomly sized pores, which had a coefficient of variation (CV) in relative resistance change of 69.65%, our sensors exhibit much higher uniformity with a CV of 2.43%. This result is corroborated with finite element simulation, which confirms that with increasing pore size variability, the variability in sensor characteristics also increases. Furthermore, our devices exhibit negligible hysteresis (degree of hysteresis: 2%), owing to the strong chemical bonding between the conductive polymer and the elastomer template, which prevents their relative sliding and displacement, and the porosity of the elastomer that enhances elastic behavior. Such features of the sensor render it highly feasible for various practical applications in the near future.

Microstructured Porous Pyramid-Based Ultrahigh Sensitive Pressure Sensor Insensitive to Strain and Temperature.

An ultrahigh sensitive capacitive pressure sensor based on a porous pyramid dielectric layer (PPDL) is reported. Compared to that of the conventional pyramid dielectric layer, the sensitivity was drastically increased to 44.5 kPa-1 in the pressure range <100 Pa, an unprecedented sensitivity for capacitive pressure sensors. The enhanced sensitivity is attributed to a lower compressive modulus and larger change in an effective dielectric constant under pressure. By placing the pressure sensors on islands of hard elastomer embedded in a soft elastomer substrate, the sensors exhibited insensitivity to strain. The pressure sensors were also nonresponsive to temperature. Finally, a contact resistance-based pressure sensor is also demonstrated by chemically grafting PPDL with a conductive polymer, which also showed drastically enhanced sensitivity.

Highly Ordered 3D Microstructure-Based Electronic Skin Capable of Differentiating Pressure, Temperature, and Proximity.

Electronic skin are devices that mimic the functionalities of human skin, which require high sensitivity, large dynamic range, high spatial uniformity, low-cost and large-area processability, and the capacity to differentiate various external inputs. We herein introduce a versatile droplet-based microfluidic-assisted emulsion self-assembly process to generate three-dimensional microstructure-based high-performance capacitive and piezoresistive pressure sensors for electronic skin applications. Our technique can generate uniformly sized micropores that are self-assembled in an orderly close-packed manner over a large area, which results in high spatial uniformity. The size of the micropores can easily be tuned from 100 to 500 µm, through which sensitivity and dynamic range were controlled as high as 0.86 kPa-1 and up to 100 kPa. Our device can be printed on curvilinear surfaces and be molded into various shapes. We furthermore demonstrate that by simultaneously utilizing capacitive and piezoresistive pressure sensors, we can distinguish between pressure and temperature, or between pressure and proximity. These demonstrations make our process and sensors highly useful for a wide variety of electronic skin applications.

Pressure Insensitive Strain Sensor with Facile Solution-Based Process for Tactile Sensing Applications.

Tactile sensors that can mechanically decouple, and therefore differentiate, various tactile inputs are highly important to properly mimic the sensing capabilities of human skin. Herein, we present an all-solution processable pressure insensitive strain sensor that utilizes the difference in structural change upon the application of pressure and tensile strain. Under the application of strain, microcracks occur within the multiwalled carbon nanotube (MWCNT) network, inducing a large change in resistance with gauge factor of ∼56 at 70% strain. On the other hand, under the application of pressure to as high as 140 kPa, negligible change in resistance is observed, which can be attributed to the pressure working primarily to close the pores, and hence minimally changing the MWCNT network conformation. Our sensor can easily be coated onto irregularly shaped three-dimensional objects (e.g., robotic hand) via spray coating, or be attached to human joints, to detect bending motion. Furthermore, our sensor can differentiate between shear stress and normal pressure, and the local strain can be spatially mapped without the use of patterned electrode array using electrical impedance tomography. These demonstrations make our sensor highly useful and important for the future development of high performance tactile sensors.

[Transurethral enucleation plus pneumo-cystostomy rotary cut for large benign prostatic hyperplasia].

OBJECTIVE: To investigate the feasibility, effectiveness and practicability of transurethral enucleation plus pneumocystostomy rotary cut (TUE + PCRC) for large benign prostatic hyperplasia (BPH). METHODS: We performed TUE + PCRC for 26 BPH patients aged 62 - 85 years with the prostate volume of 80 - 165 ml. We conducted transurethral enucleation of the hyperplastic prostate glands and pushed them into the bladder, followed by bladder puncture for pneumo-cystostomy rotary cut. RESULTS: All the surgical procedures were successfully accomplished, with the mean surgical time of 41 (32 - 54) minutes and intraoperative blood loss < 60 ml in all the cases. Twenty-three of the patients were followed up for 2 - 8 months, which revealed no stricture of the urethra or any other severe complications. Compared with the preoperative baseline, significant improvement was achieved in the IPSS (6.5 +/- 2.2 vs 26.2 +/- 2.4), QOL (1.4 +/- 0.9 vs 4.6 +/- 1.2) and Qmax ([5.8 +/- 1.0 ] vs [19.6 +/- 2.8] ml/s) of the patients after surgery (P < 0.01). CONCLUSION: TUE + PCRC, with its advantages of short operation time and less severe complications, is a safe and effective approach to the management of large BPH.

[X-ray guided internal urethroplasty with PlasmaKinetic electrodes for urethratresia].

OBJECTIVE: To evaluate endourethral surgery for urethratresia under the X-ray guide. METHODS: We performed transurethral urethroplasty for 11 patients with urethratresia using the PlasmaKinetic electrodes under the guidance of C arm xanthippe. RESULTS: In the 11 cases, operations were all successful, 9 achieved smooth urination and 2 needed regular urethral dilation. CONCLUSION: X-ray guided internal urethroplasty with PlasmaKinetic electrodes is a simple and efficient treatment for urethratresia.