Polydopamine/SWCNT Ink Functionalization of Silk Fabric to Obtain Electroconductivity at a Low Percolation Threshold.

This study presents the functionalization of silk fabric with SWCNT ink. The first step was the formation of a polydopamine (PDA) thin coating on the silk fabric to allow for effective bonding of SWCNTs. PDA formation was carried out directly on the fabric by means of polymerization of dopamine in alkali conditions. The Silk/PDA fabric was functionalized with SWCNT ink of different SWCNT concentrations by using the dip-coating method. IR and Raman analyses show that the dominant ß-sheet structure of silk fibroin after the functionalization process remains unchanged. The heat resistance is even slightly improved. The hydrophobic silk fabric becomes hydrophilic after functionalization due to the influence of PDA and the surfactant in SWCNT ink. The ink significantly changes the electrical properties of the silk fabric, from insulating to conductive. The volume resistance changes by nine orders of magnitude, from 2.4 × 1012 Ω to 2.3 × 103 Ω for 0.12 wt.% of SWCNTs. The surface resistance changes by seven orders of magnitude, from 2.1 × 1012 Ω to 2.4 × 105 Ω for 0.17 wt.% of SWCNTs. The volume and surface resistance thresholds are determined to be about 0.05 wt.% and 0.06 wt.%, respectively. The low value of the percolation threshold indicates efficient functionalization, with high-quality ink facilitating the formation of percolation paths through SWCNTs and the influence of the PDA linker.

Design of Stretchable and Conductive Self-Adhesive Hydrogels as Flexible Sensors by Guar-Gum-Enabled Dynamic Interactions.

The limited elasticity and inadequate bonding of hydrogels made from guar gum (GG) significantly hinder their widespread implementation in personalized wearable flexible electronics. In this study, we devise GG-based self-adhesive hydrogels by creating an interpenetrating network of GG cross-linked with acrylic, 4-vinylphenylboronic acid, and Ca2+. With the leverage of the dynamic interactions (hydrogen bonds, borate ester bonds, and coordination bonds) between -OH in GG and monomers, the hydrogel exhibits a high stretchability of 700%, superior mechanical stress of 110 kPa, and robust adherence to several substrates. The adhesion strength of 54 kPa on porcine skin is obtained. Furthermore, the self-adhesive hydrogel possesses stable conductivity, an elevated gauge factor (GF), and commendable durability. It can be affixed to the human body as a strain sensor to obtain precise monitoring of human movement behavior. Our research offers possibilities for the development of GG-based hydrogels and applications in wearable electronics and medical monitoring.

Next-Generation Cardiac Interfacing Technologies Using Nanomaterial-Based Soft Bioelectronics.

Cardiac interfacing devices are essential components for the management of cardiovascular diseases, particularly in terms of electrophysiological monitoring and implementation of therapies. However, conventional cardiac devices are typically composed of rigid and bulky materials and thus pose significant challenges for effective long-term interfacing with the curvilinear surface of a dynamically beating heart. In this regard, the recent development of intrinsically soft bioelectronic devices using nanocomposites, which are fabricated by blending conductive nanofillers in polymeric and elastomeric matrices, has shown great promise. The intrinsically soft bioelectronics not only endure the dynamic beating motion of the heart and maintain stable performance but also enable conformal, reliable, and large-area interfacing with the target cardiac tissue, allowing for high-quality electrophysiological mapping, feedback electrical stimulations, and even mechanical assistance. Here, we explore next-generation cardiac interfacing strategies based on soft bioelectronic devices that utilize elastic conductive nanocomposites. We first discuss the conventional cardiac devices used to manage cardiovascular diseases and explain their undesired limitations. Then, we introduce intrinsically soft polymeric materials and mechanical restraint devices utilizing soft polymeric materials. After the discussion of the fabrication and functionalization of conductive nanomaterials, the introduction of intrinsically soft bioelectronics using nanocomposites and their application to cardiac monitoring and feedback therapy follow. Finally, comments on the future prospects of soft bioelectronics for cardiac interfacing technologies are discussed.

Injectable conductive hydrogel remodeling microenvironment and mimicking neuroelectric signal transmission after spinal cord injury.

Severe spinal cord injury (SCI) leads to dysregulated neuroinflammation and cell apoptosis, resulting in axonal die-back and the loss of neuroelectric signal transmission. While biocompatible hydrogels are commonly used in SCI repair, they lack the capacity to support neuroelectric transmission. To overcome this limitation, we developed an injectable silk fibroin/ionic liquid (SFMA@IL) conductive hydrogel to assist neuroelectric signal transmission after SCI in this study. The hydrogel can form rapidly in situ under ultraviolet (UV) light. The mechanical supporting and neuro-regenerating properties are provided by silk fibroin (SF), while the conductive capability is provided by the designed ionic liquid (IL). SFMA@IL showed attractive features for SCI repair, such as anti-swelling, conductivity, and injectability. In vivo, SFMA@IL hydrogel used in rats with complete transection injuries was found to remodel the microenvironment, reduce inflammation, and facilitate neuro-fiber outgrowth. The hydrogel also led to a notable decrease in cell apoptosis and the achievement of scar-free wound healing, which saved 45.6 ± 10.8 % of spinal cord tissue in SFMA@IL grafting. Electrophysiological studies in rats with complete transection SCI confirmed SFMA@IL's ability to support sensory neuroelectric transmission, providing strong evidence for its signal transmission function. These findings provide new insights for the development of effective SCI treatments.

Recent trends in core/shell nanoparticles: their enzyme-based electrochemical biosensor applications.

Improving novel and efficient biosensors for determining organic/inorganic compounds is a challenge in analytical chemistry for clinical diagnosis and research in biomedical sciences. Electrochemical enzyme-based biosensors are one of the commercially successful groups of biosensors that make them highly appealing because of their low cost, high selectivity, and sensitivity. Core/shell nanoparticles have emerged as versatile platforms for developing enzyme-based electrochemical biosensors due to their unique physicochemical properties and tunable surface characteristics. This study provides a comprehensive review of recent trends and advancements in the utilization of core/shell nanoparticles for the development of enzyme-based electrochemical biosensors. Moreover, a statistical evaluation of the studies carried out in this field between 2007 and 2023 is made according to the preferred electrochemical techniques. The recent applications of core/shell nanoparticles in enzyme-based electrochemical biosensors were summarized to quantify environmental pollutants, food contaminants, and clinical biomarkers. Additionally, the review highlights recent innovations and strategies to improve the performance of enzyme-based electrochemical biosensors using core/shell nanoparticles. These include the integration of nanomaterials with specific functions such as hydrophilic character, chemical and thermal stability, conductivity, biocompatibility, and catalytic activity, as well as the development of new hybrid nanostructures and multifunctional nanocomposites.

Prevention of Leakage in Machine Learning Prediction for Polymer Composite Properties.

Machine learning (ML) has facilitated property prediction for intricate materials by integrating materials and experimental features such as processing and measurement conditions. However, ML models designed for material properties have often disregarded a common issue of "leakage," resulting in an overestimation of model performance and a decrease in model transferability. This issue can arise from biases inherent in multiple data points obtained from the same experimental group. We provide a critical examination and prevention method of leakage in property prediction for polymer composites. Our proposed method utilizes data partitioning based on the experimental group to ensure that data from the same group are not mixed in both the training and test sets. Evaluation results highlight that the conventional random partitioning unintentionally inflates ML performance through the misuse of experimental features for leaking data bias within the same experimental group rather than explaining the physical causality. In contrast, the proposed method enables the leakage-free utilization of experimental features to improve prediction accuracy while ensuring model transferability. Specifically, when integrating experimental features with polymer and filler features, the conventional method overestimates the prediction performance of electrical conductivity in reducing RMSE by 26% depending on leakage, whereas the proposed method achieves a reduction in RMSE by 5% without leakage. These findings offer valuable guidance for the effective utilization of experimental features in data-driven materials science.

3D Printing Silk Fibroin/Polyacrylamide Triple-Network Composite Hydrogels with Stretchability, Conductivity, and Strain-Sensing Ability as Bionic Electronic Skins.

Electronic skins have received increasing attention due to their great application potential in wearable electronics. Meanwhile, tremendous efforts are still needed for the fabrication of multifunctional composite hydrogels with complex structures for electronic skins via simple methods. In this work, a novel three-dimensional (3D) printing composite hydrogel with stretchability, conductivity, and strain-sensing ability is produced using a one-step photocuring method to achieve a dual-signal response of the electronic skin. The composite hydrogel exhibits a triple-network structure composed of silk microfibers (SMF), regenerated silk fibroin (RSF), and polyacrylamide (PAM). The establishment of triple networks is based on the electrostatic interaction between SMF and RSF, as well as the chemically cross-linked RSF and PAM. Thanks to its specific structure and components, the composite hydrogel possesses enhanced mechanical properties (elastic modulus of 140 kPa, compressive stress of 21 MPa, and compression modulus of 600 kPa) and 3D printability while retaining stretchability and flexibility. The interaction between negatively charged SMF and cations in phosphate-buffered saline endows the composite hydrogel with good conductivity and strain-sensing ability after immersion in a low-concentration (10 mM) salt solution. Moreover, the 3D printing composite hydrogel scaffold successfully realizes real-time monitoring. Therefore, the proposed hydrogel-based ionic sensor is promising for skin tissue engineering, real-time monitoring, soft robotics, and human-machine interfaces.

Developing excellent plantar pressure sensors for monitoring human motions by using highly compressible and resilient PMMA conductive iongels.

Based on real-time detection of plantar pressure, gait recognition could provide important health information for rehabilitation administration, fatigue prevention, and sports training assessment. So far, such researches are extremely limited due to lacking of reliable, stable and comfortable plantar pressure sensors. Herein, a strategy for preparing high compression strength and resilience conductive iongels has been proposed by implanting physically entangled polymer chains with covalently cross-linked networks. The resulting iongels have excellent mechanical properties including nice compliance (young's modulus < 300 kPa), high compression strength (>10 MPa at a strain of 90 %), and good resilience (self-recovery within seconds). And capacitive pressure sensor composed by them possesses excellent sensitivity, good linear response even under very small stress (∼kPa), and long-term durability (cycles > 100,000) under high-stress conditions (133 kPa). Then, capacitive pressure sensor arrays have been prepared for high-precision detection of plantar pressure spatial distribution, which also exhibit excellent sensing performances and long-term stability. Further, an extremely sensitive and fast response plantar pressure monitoring system has been designed for monitoring plantar pressure of foot at different postures including upright, forward and backward. The system achieves real-time tracking and monitoring of changes of plantar pressure during different static and dynamic posture processes. And the characteristics of plantar pressure information can be digitally and photography displayed. Finally, we propose an intelligent framework for real-time detection of plantar pressure by combining electronic insoles with data analysis system, which presents excellent applications in sport trainings and safety precautions.

Prediction models for bioavailability of Cu and Zn during composting: Insights into machine learning.

Bioavailability assessment of heavy metals in compost products is crucial for evaluating associated environmental risks. However, existing experimental methods are time-consuming and inefficient. The machine learning (ML) method has demonstrated excellent performance in predicting heavy metal fractions. In this study, based on the conventional physicochemical properties of 260 compost samples, including compost time, temperature, electrical conductivity (EC), pH, organic matter (OM), total phosphorus (TP), total nitrogen, and total heavy metal contents, back propagation neural network, gradient boosting regression, and random forest (RF) models were used to predict the dynamic changes in bioavailable fractions of Cu and Zn during composting. All three models could be used for effective prediction of the variation trend in bioavailable fractions of Cu and Zn; the RF model showed the best prediction performance, with the prediction level higher than that reported in related studies. Although the key factors affecting changes among fractions were different, OM, EC, and TP were important for the accurate prediction of bioavailable fractions of Cu and Zn. This study provides simple and efficient ML models for predicting bioavailable fractions of Cu and Zn during composting, and offers a rapid evaluation method for the safe application of compost products.

The Future of Graphene: Preparation from Biomass Waste and Sports Applications.

At present, the main raw material for producing graphene is graphite ore. However, researchers actively seek alternative resources due to their high cost and environmental problems. Biomass waste has attracted much attention due to its carbon-rich structure and renewability, emerging as a potential raw material for graphene production to be used in sports equipment. However, further progress is required on the quality of graphene produced from waste biomass. This paper, therefore, summarizes the properties, structures, and production processes of graphene and its derivatives, as well as the inherent advantages of biomass waste-derived graphene. Finally, this paper reviews graphene's importance and application prospects in sports since this wonder material has made sports equipment available with high-strength and lightweight quality. Moreover, its outstanding thermal and electrical conductivity is exploited to prepare wearable sensors to collect more accurate sports data, thus helping to improve athletes' training levels and competitive performance. Although the large-scale production of biomass waste-derived graphene has yet to be realized, it is expected that its application will expand to various other fields due to the associated low cost and environmental friendliness of the preparation technique.

Intelligent perceptual textiles based on ionic-conductive and strong silk fibers.

Endowing textiles with perceptual function, similar to human skin, is crucial for the development of next-generation smart wearables. To date, the creation of perceptual textiles capable of sensing potential dangers and accurately pinpointing finger touch remains elusive. In this study, we present the design and fabrication of intelligent perceptual textiles capable of electrically responding to external dangers and precisely detecting human touch, based on conductive silk fibroin-based ionic hydrogel (SIH) fibers. These fibers possess excellent fracture strength (55 MPa), extensibility (530%), stable and good conductivity (0.45 S·m-1) due to oriented structures and ionic incorporation. We fabricated SIH fiber-based protective textiles that can respond to fire, water, and sharp objects, protecting robots from potential injuries. Additionally, we designed perceptual textiles that can specifically pinpoint finger touch, serving as convenient human-machine interfaces. Our work sheds new light on the design of next-generation smart wearables and the reshaping of human-machine interfaces.

Solvent-Free and Cost-Efficient Fabrication of a High-Performance Nanocomposite Sensor for Recording of Electrophysiological Signals.

Carbon nanotube (CNT)-based nanocomposites have found applications in making sensors for various types of physiological sensing. However, the sensors' fabrication process is usually complex, multistep, and requires longtime mixing and hazardous solvents that can be harmful to the environment. Here, we report a flexible dry silver (Ag)/CNT/polydimethylsiloxane (PDMS) nanocomposite-based sensor made by a solvent-free, low-temperature, time-effective, and simple approach for electrophysiological recording. By mechanical compression and thermal treatment of Ag/CNT, a connected conductive network of the fillers was formed, after which the PDMS was added as a polymer matrix. The CNTs make a continuous network for electrons transport, endowing the nanocomposite with high electrical conductivity, mechanical strength, and durability. This process is solvent-free and does not require a high temperature or complex mixing procedure. The sensor shows high flexibility and good conductivity. High-quality electroencephalography (EEG) and electrooculography (EOG) were performed using fabricated dry sensors. Our results show that the Ag/CNT/PDMS sensor has comparable skin-sensor interface impedance with commercial Ag/AgCl-coated dry electrodes, better performance for noninvasive electrophysiological signal recording, and a higher signal-to-noise ratio (SNR) even after 8 months of storage. The SNR of electrophysiological signal recording was measured to be 26.83 dB for our developed sensors versus 25.23 dB for commercial Ag/AgCl-coated dry electrodes. Our process of compress-heating the functional fillers provides a universal approach to fabricate various types of nanocomposites with different nanofillers and desired electrical and mechanical properties.

Multi-Functional Nano-Doped Hollow Fiber from Microfluidics for Sensors and Micromotors.

Nano-doped hollow fiber is currently receiving extensive attention due to its multifunctionality and booming development. However, the microfluidic fabrication of nano-doped hollow fiber in a simple, smooth, stable, continuous, well-controlled manner without system blockage remains challenging. In this study, we employ a microfluidic method to fabricate nano-doped hollow fiber, which not only makes the preparation process continuous, controllable, and efficient, but also improves the dispersion uniformity of nanoparticles. Hydrogel hollow fiber doped with carbon nanotubes is fabricated and exhibits superior electrical conductivity (15.8 S m-1), strong flexibility (342.9%), and versatility as wearable sensors for monitoring human motions and collecting physiological electrical signals. Furthermore, we incorporate iron tetroxide nanoparticles into fibers to create magnetic-driven micromotors, which provide trajectory-controlled motion and the ability to move through narrow channels due to their small size. In addition, manganese dioxide nanoparticles are embedded into the fiber walls to create self-propelled micromotors. When placed in a hydrogen peroxide environment, the micromotors can reach a top speed of 615 µm s-1 and navigate hard-to-reach areas. Our nano-doped hollow fiber offers a broad range of applications in wearable electronics and self-propelled machines and creates promising opportunities for sensors and actuators.

A liquid metal/polypyrrole electrospun TPU composite conductive network for highly sensitive strain sensing in human motion monitoring.

Developing soft wearable sensors with high sensitivity, low cost, and a wide monitoring range is crucial for monitoring human health. Despite advances in strain sensor technology, achieving high sensitivity and a wide operating range in a single device remains a major challenge in its design and preparation. Herein, a liquid metal (LM) is innovatively ultrasonically anchored to the gaps and surfaces of thermoplastic polyurethane (TPU) electrospun fibers, and then a conductive pathway is constructed through polypyrrole (PPy) self-polymerization to prepare a composite film. The strain sensor developed by ultrasonic anchoring and original polymerization technology shows a high strain coefficient (GF = 4.36 at 12.5% strain) and a low detection limit (less than 1% strain). Importantly, this sensor can monitor joint motion and subtle skin deformations in real time. In addition, the integration of strain sensors and N95 masks enables real-time monitoring of human respiration.

Smart Graphene Textiles for Biopotential Monitoring: Laser-Tailored Electrochemical Property Enhancement.

While most of the research in graphene-based materials seeks high electroactive surface area and ion intercalation, here, we show an alternative electrochemical behavior that leverages graphene's potential in biosensing. We report a novel approach to fabricate graphene/polymer nanocomposites with near-record conductivity levels of 45 Ω sq-1 and enhanced biocompatibility. This is realized by laser processing of graphene oxide in a sandwich structure with a thin (100 µm) polyethylene terephthalate film on a textile substrate. Such hybrid materials exhibit high conductivity, low polarization, and stability. In addition, the nanocomposites are highly biocompatible, as evidenced by their low cytotoxicity and good skin adhesion. These results demonstrate the potential of graphene/polymer nanocomposites for smart clothing applications.

Designing process and analysis of a new SOI-MESFET structure with enhanced DC and RF characteristics for high-frequency and high-power applications.

This research introduces a new designing process and analysis of an innovative Silicon-on-Insulator Metal-Semiconductor Field-Effect (SOI MESFET) structure that demonstrates improved DC and RF characteristics. The design incorporates several modifications to control and reduce the electric field concentration within the channel. These modifications include relocating the transistor channel to sub-regions near the source and drain, adjusting the position of the gate electrode closer to the source, introducing an aluminum layer beneath the channel, and integrating an oxide layer adjacent to the gate. The results show that the AlOx-MESFET configuration exhibits a remarkable increase of 128% in breakdown voltage and 156% in peak power. Furthermore, due to enhanced conductivity and a significant reduction in gate-drain capacitance, there is a notable improvement of 53% in the cut-off frequency and a 28% increase in the maximum oscillation frequency. Additionally, the current gain experiences a boost of 15%. The improved breakdown voltage and peak power make it suitable for applications requiring robust performance under high voltage and power conditions. The increased maximum oscillation frequency and cut-off frequency make it ideal for high-frequency applications where fast signal processing is crucial. Moreover, the enhanced current gain ensures efficient amplification of signals. The introduced SOI MESFET structure with its modifications offers significant improvements in various performance metrics. It provides high oscillation frequency, better breakdown voltage and good cut-off frequency, and current gain compared to the traditional designs. These enhancements make it a highly desirable choice for applications that demand high-frequency and high-power capabilities.

Progress and Perspective in harnessing MXene-carbon-based composites (0-3D): Synthesis, performance, and applications.

MXene is recognized as a promising catalyst for versatile applications due to its abundant metal sites, physicochemical properties, and structural formation. This comprehensive review offers an in-depth analysis of the incorporation of carbon into MXene, resulting in the formation of MXene-carbon-based composites (MCCs). Pristine MXene exhibits numerous outstanding characteristics, such as its atomically thin 2D structure, hydrophilic surface nature, metallic electrical conductivity, and substantial specific surface area. The introduction of carbon guides the assembly of MCCs through electrostatic self-assembly, pairing positively charged carbon with negatively charged MXene. These interactions result in increased interlayer spacing, reduced ion/electron transport distances, and enhanced surface hydrophilicity. Subsequent sections delve into the synthesis methods for MCCs, focusing on MXene integrated with various carbon structures, including 0D, 1D, 2D, and 3D carbon. Comprehensive discussions explore the distinctive properties of MCCs and the unique advantages they offer in each application domain, emphasizing the contributions and advancements they bring to specific fields. Furthermore, this comprehensive review addresses the challenges encountered by MCCs across different applications. Through these analyses, the review promotes a deeper understanding of exceptional characteristics and potential applications of MCCs. Insights derived from this review can serve as guidance for future research and development efforts, promoting the widespread utilization of MCCs across a broad spectrum of disciplines and spurring future innovations.

Electrical Transport and Dynamics of Confined DNA through Highly Conductive 2D Graphene Nanochannels.

Confining DNA in nanochannels is an important approach to studying its structure and transportation dynamics. Graphene nanochannels are particularly attractive for studying DNA confinement due to their atomic flatness, precise height control, and excellent mechanical strength. Here, using femtosecond laser etching and wetting transfer, we fabricate graphene nanochannels down to less than 4.3 nm in height, with the length-to-height ratios up to 103. These channels exhibit high stability, low noise, and self-cleaning ability during the long-term ionic current recording. We report a clear linear relationship between DNA length and the residence time in the channel and further utilize this relationship to differentiate DNA fragments based on their lengths, ranging widely from 200 bps to 48.5 kbps. The graphene nanochannel presented here provides a potential platform for label-free analyses and reveals fundamental insights into the conformational dynamics of DNA and proteins in confined space.

Sensitivity volume as figure-of-merit for maximizing data importance in electrical impedance tomography.

Objective.Electrical impedance tomography (EIT) is a noninvasive imaging method whereby electrical measurements on the periphery of a heterogeneous conductor are inverted to map its internal conductivity. The EIT method proposed here aims to improve computational speed and noise tolerance by introducing sensitivity volume as a figure-of-merit for comparing EIT measurement protocols.Approach.Each measurement is shown to correspond to a sensitivity vector in model space, such that the set of measurements, in turn, corresponds to a set of vectors that subtend a sensitivity volume in model space. A maximal sensitivity volume identifies the measurement protocol with the greatest sensitivity and greatest mutual orthogonality. A distinguishability criterion is generalized to quantify the increased noise tolerance of high sensitivity measurements.Main result.The sensitivity volume method allows the model space dimension to be minimized to match that of the data space, and the data importance to be increased within an expanded space of measurements defined by an increased number of contacts.Significance.The reduction in model space dimension is shown to increasecomputational efficiency, accelerating tomographic inversion by several orders of magnitude, while the enhanced sensitivitytolerates higher noiselevels up to several orders of magnitude larger than standard methods.

Modulus-tunable multifunctional hydrogel ink with nanofillers for 3D-Printed soft electronics.

Seamless integration and conformal contact of soft electronics with tissue surfaces have emerged as major challenges in realizing accurate monitoring of biological signals. However, the mechanical mismatch between the electronics and biological tissues impedes the conformal interfacing between them. Attempts have been made to utilize soft hydrogels as the bioelectronic materials to realize tissue-comfortable bioelectronics. However, hydrogels have several limitations in terms of their electrical and mechanical properties. In this study, we present the development of a 3D-printable modulus-tunable hydrogel with multiple functionalities. The hydrogel has a cross-linked double network, which greatly improves its mechanical properties. Functional fillers such as XLG or functionalized carbon nanotubes (fCNT) can be incorporated into the hydrogel to provide tunable mechanics (Young's modulus of 10-300 kPa) and electrical conductivity (electrical conductivity of ∼20 S/m). The developed hydrogel exhibits stretchability (∼1000% strain), self-healing ability (within 5 min), toughness (400-731 kJ/m3) viscoelasticity, tissue conformability, and biocompatibility. Upon examining the rheological properties in the modulated region, hydrogels can be 3D printed to customize the shape and design of the bioelectronics. These hydrogels can be fabricated into ring-shaped strain sensors for wearable sensor applications.