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Recent advances in MXene (Ti 3 C 2 T x ) fibers, prepared from electrically conductive and mechanically strong MXene nanosheets, address the increasing demand of emerging yet promising electrode materials for the development of textile-based devices and beyond. However, to reveal the full potential of MXene fibers, reaching a balance between electrical conductivity and mechanical property is still the fundamental challenge, mainly due to the difficulties to further compact the loose MXene nanosheets. In this work, we demonstrate a continuous and controllable route to fabricate ultra-compact MXene fibers with an in-situ generated protective layer via the synergy of interfacial interactions and thermal drawing-induced stresses. The resulting ultra-compact MXene fibers with high orientation and low porosity exhibit not only excellent tensile strength and ultra-high toughness, but also high electrical conductivity. Then, we construct meter-scale MXene textiles using these ultra-compact fibers to achieve high-performance electromagnetic interference shielding and personal thermal management, accompanied by the high mechanical durability and stability even after multiple washing cycles. The demonstrated generic strategy can be applied to a broad range of nanostructured materials to construct functional fibers for large-scale applications in both space and daily lives. Forming compact layered nanostructures is key to achieving continuous MXene fibers with electrical and mechanical properties. Here, authors demonstrate ultra-compact high-performance MXene fibers via a controllable synergy of interfacial interactions and thermal drawing-induced stresses.

Electromagnetic source characterisation requires accurate volume conductor models representing head geometry and the electrical conductivity field. Head tissue conductivity is often assumed from previous literature, however, despite extensive research, measurements are inconsistent. A meta-analysis of reported human head electrical conductivity values was therefore conducted to determine significant variation and subsequent influential factors. Of 3121 identified publications spanning three databases, 56 papers were included in data extraction. Conductivity values were categorised according to tissue type, and recorded alongside methodology, measurement condition, current frequency, tissue temperature, participant pathology and age. We found variation in electrical conductivity of the whole-skull, the spongiform layer of the skull, isotropic, perpendicularly- and parallelly-oriented white matter (WM) and the brain-to-skull-conductivity ratio (BSCR) could be significantly attributed to a combination of differences in methodology and demographics. This large variation should be acknowledged, and care should be taken when creating volume conductor models, ideally constructing them on an individual basis, rather than assuming them from the literature. When personalised models are unavailable, it is suggested weighted average means from the current meta-analysis are used. Assigning conductivity as: 0.41 S/m for the scalp, 0.02 S/m for the whole skull, or when better modelled as a three-layer skull 0.048 S/m for the spongiform layer, 0.007 S/m for the inner compact and 0.005 S/m for the outer compact, as well as 1.71 S/m for the CSF, 0.47 S/m for the grey matter, 0.22 S/m for WM and 50.4 for the BSCR.

The thermoelectric properties of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) and tellurium-PEDOT:PSS (Te-PEDOT:PSS) hybrid composites were enhanced via simple chemical treatment. The performance of thermoelectric materials is determined by their electrical conductivity, thermal conductivity and Seebeck coefficient. Significant enhancement of the electrical conductivity of PEDOT:PSS and Te-PEDOT:PSS hybrid composites from 787.99 and 11.01 to 4839.92 and 334.68 S cm −1 , respectively was achieved by simple chemical treatment with H 2 SO 4 . The power factor of the developed materials could be effectively tuned over a very wide range depending on the concentration of the H 2 SO 4 solution used in the chemical treatment. The power factors of the developed thermoelectric materials were optimized to 51.85 and 284 μW m −1 K −2 , respectively, which represent an increase of four orders of magnitude relative to the corresponding parameters of the untreated thermoelectric materials. Using the Te-PEDOT:PSS hybrid composites, a flexible thermoelectric generator that could be embedded in textiles was fabricated by a printing process. This thermoelectric array generates a thermoelectric voltage of 2 mV using human body heat.

Innovations in soft material synthesis and fabrication technologies have led to the development of integrated soft electronic devices. Such soft devices offer opportunities to interact with biological cells, mimicking their soft environment. However, existing fabrication technologies cannot create the submicron-scale, soft transducers needed for healthcare and medical applications involving single cells. This work presents a nanofabrication strategy to create submicron-scale, all-soft electronic devices based on eutectic gallium-indium alloy (EGaIn) using a hybrid method utilizing electron-beam lithography and soft lithography. The hybrid lithography process is applied to a biphasic structure, comprising a metallic adhesion layer coated with EGaIn, to create soft nano/microstructures embedded in elastomeric materials. Submicron-scale EGaIn thin-film patterning with feature sizes as small as 180 nm and 1 μm line spacing was achieved, resulting in the highest resolution EGaIn patterning technique to date. The resulting soft and stretchable EGaIn patterns offer a currently unrivaled combination of resolution, electrical conductivity, and electronic/wiring density. Though all-soft electronic devices with liquid metals are attractive due to the material’s compatibility with patterning methods, obtaining sub-micron patterns remains a challenge. Here, the authors report a hybrid lithography process to realize all-soft submicron-scale devices based on EGaIn.

Organic radical polymers can have much higher electrical conductivities than anticipated Organic radical polymers have unusual electronic properties, with potential applications in batteries, electronics, and memory storage ( 1 – 3 ). The first nitroxide-based organic radical polymer, reported by Okawara and co-workers in 1972 ( 4 ), has since been used as an electroactive material in battery electrodes ( 5 ). With recent explorations into organic radical polymers for thermoelectrics and electronics ( 2 , 6 ), the electrical conductivity of these materials has become a center of interest. On page 1391 of this issue, Joo et al. ( 7 ) add an important facet to this discussion by demonstrating the highest reported conductivity for an organic radical polymer.

The technological improvement in the field of physics, chemistry, electronics, nanotechnology, biology, and molecular biology has contributed to the development of various electrochemical biosensors with a broad range of applications in healthcare settings, food control and monitoring, and environmental monitoring. In the past, conventional biosensors that have employed bioreceptors, such as enzymes, antibodies, Nucleic Acid (NA), etc., and used different transduction methods such as optical, thermal, electrochemical, electrical and magnetic detection, have been developed. Yet, with all the progresses made so far, these biosensors are clouded with many challenges, such as interference with undesirable compound, low sensitivity, specificity, selectivity, and longer processing time. In order to address these challenges, there is high need for developing novel, fast, highly sensitive biosensors with high accuracy and specificity. Scientists explore these gaps by incorporating nanoparticles (NPs) and nanocomposites (NCs) to enhance the desired properties. Graphene nanostructures have emerged as one of the ideal materials for biosensing technology due to their excellent dispersity, ease of functionalization, physiochemical properties, optical properties, good electrical conductivity, etc. The Integration of the Internet of Medical Things (IoMT) in the development of biosensors has the potential to improve diagnosis and treatment of diseases through early diagnosis and on time monitoring. The outcome of this comprehensive review will be useful to understand the significant role of graphene-based electrochemical biosensor integrated with Artificial Intelligence AI and IoMT for clinical diagnostics. The review is further extended to cover open research issues and future aspects of biosensing technology for diagnosis and management of clinical diseases and performance evaluation based on Linear Range (LR) and Limit of Detection (LOD) within the ranges of Micromolar µM (10−6), Nanomolar nM (10−9), Picomolar pM (10−12), femtomolar fM (10−15), and attomolar aM (10−18).

Precise prediction of water quality parameters plays a significant role in making an early alert of water pollution and making better decisions for the management of water resources. As one of the influential indicative parameters, electrical conductivity (EC) has a crucial role in calculating the proportion of mineralization. In this study, the integration of an adaptive hybrid of differential evolution and particle swarm optimization (A-DEPSO) with adaptive neuro fuzzy inference system (ANFIS) model is adopted for EC prediction. The A-DEPSO method uses unique mutation and crossover processes to correspondingly boost global and local search mechanisms. It also uses a refreshing operator to prevent the solution from being caught inside the local optimal solutions. This study uses A-DEPSO optimizer for ANFIS training phase to eliminate defects and predict accurately the EC water quality parameter every month at the Maroon River in the southwest of Iran. Accordingly, the recorded dataset originated from the Tange-Takab station from 1980 to 2016 was operated to develop the ANFIS-A-DEPSO model. Besides, the wavelet analysis was jointed to the proposed algorithm in which the original time series of EC was disintegrated into the sub-time series through two mother wavelets to boost the prediction certainty. In the following, the comparison between statistical metrics of the standalone ANFIS, least-square support vector machine (LSSVM), multivariate adaptive regression spline (MARS), generalized regression neural network (GRNN), wavelet-LSSVM (WLSSVM), wavelet-MARS (W-MARS), wavelet-ANFIS (W-ANFIS) and wavelet-GRNN (W-GRNN) models was implemented. As a result, it was apparent that not only was the W-ANFIS-A-DEPSO model able to rise remarkably the EC prediction certainty, but W-ANFIS-A-DEPSO (R = 0.988, RMSE = 53.841, and PI = 0.485) also had the edge over other models with Dmey mother in terms of EC prediction. Moreover, the W-ANFIS-A-DEPSO can improve the RMSE compared to the standalone ANFIS-DEPSO model, accounting for 80%. Hence, this model can create a closer approximation of EC value through W-ANFIS-A-DEPSO model, which is likely to act as a promising procedure to simulate the prediction of EC data.

Recent trends in tissue engineering technology have switched to electrical potentials generated through bioactive scaffolds regarding their appropriate effects on cell behaviors. Preparing a piezo-electrical stimuli scaffold with high electrical conductivity for bone and cartilage tissue regeneration is the ultimate goal of the present study. Here, Barium Titanate nanoparticles (BaTiO 3 NPs) were used as piezoelectric material and highly conductive binary doped Polyaniline nanoparticles (PANI NPs) were synthesized by oxidative polymerization. Polycaprolactone (PCL) was applied as carrier substrate polymer and conductive spun nanofibrous scaffolds of PCL/PANI composites were prepared in two different amounts of PANI (3 and 5 wt.%). The conductivity of PCL/PANI nanofibers has been analyzed by standard four probes test. Based on the obtained results, the PCL/PANI5 (with 5 wt.% PANI) was selected due to the superior electrical conductivity of 8.06 × 10 –4  s cm  - 1 . Moreover, the piezoelectric nanofibrous scaffolds of PCL/BT composite were electrospun in three different amounts of BT (20, 30, and 40 wt.%). To investigate the synergic effect of conductive PANI and piezoelectric BT, ternary nanocomposite scaffolds of PCL/PANI/BT were prepared using the dual jet electrospinning technique. The piezoelectric properties have been analyzed by determining the produced voltage. The morphological assessment, contact angle, mechanical test, and MTT assay have been conducted to evaluate other properties including biocompatibility of nanofibrous scaffolds. The PCL/PANI5/BT40 composite resulted in an unprecedented voltage of 1.9 Volt. SEM results confirm that BT NPs have been distributed and embedded inside PCL fibers quite appropriately. Also, the chosen scaffolds were homogeneously intertwined and possessed an average fiber diameter of 288 ± 180 nm, and a contact angle of 92 ± 7°, making it a desirable surface for cell attachment and protein interactions. Moreover, Young’s modulus, ultimate tensile stress, and elongation were obtained as 11 ± 1 MPa, 5 ± 0.6 MPa, and 109 ± 15% respectively. Obtained results assert the novel potential of piezo-electrical stimuli conductive nanocomposite scaffold for tissue engineering applications.

A lanthanum oxide (La2O3)-ZnO nanostructured material was synthesized in the proposed study with different La2O3 concentrations, 0.001 g to 5 g (named So to S7), using the combustion method. X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transformation infrared spectroscopy (FT-IR) were utilized for investigating the structure, morphology, and spectral studies of the La2O3- ZnO nanomaterials, respectively. The results obtained from previous techniques support ZnO’s growth from crystalline to nanoparticles’ fine structure by changing the concentrations of lanthanum oxide (La2O3) dopants in the host matrix. The percentage of ZnO doped with La- influences the ZnO photocatalytic activity. SEM analysis confirmed the grain size ranged between 81 and 138 nm. Furthermore, UV-Vis diffuse reflectance spectroscopy was performed to verify the effects of La2O3 dopants on the linear optical properties of the nano-composite oxides. There was a variation in the energy bandgaps of La2O3-ZnO nanocomposites, increasing the weight concentrations of lanthanum dopants. The AC electrical conductivity, dielectric properties, and current–voltage properties support the enactment of the electrical characteristics of the ZnO nanoparticles by adding La2O3. All the samples under investigation were used for photodegradation with Rhodamine B (RhB) and Methylene Blue (MB). In less than 30 min of visible light irradiation, S4 (0.5 g) La2O3-ZnO reached 99% of RhB and MB degradation activity. This study showed the best photocatalytic effect for RhB and MB degradation of 0.13 and 0.11 min−1 by 0.5 g La2O3-ZnO. Recycling was performed five times for the nanocatalysts that displayed up to 98 percent catalytic efficiency for RhB and MB degradation in 30 min. The prepared La2O3-ZnO nanostructured composites are considered novel candidates for various applications in biomedical and photocatalytic studies.

Until now, few sp 2 carbon materials simultaneously exhibit superior performance for specific surface area (SSA) and electrical conductivity at bulk state. Thus, it is extremely important to make such materials at bulk scale with those two outstanding properties combined together. Here, we present a simple and green but very efficient approach using two standard and simple industry steps to make such three-dimensional graphene-based porous materials at the bulk scale, with ultrahigh SSA (3523 m 2 /g) and excellent bulk conductivity. We conclude that these materials consist of mainly defected/wrinkled single layer graphene sheets in the dimensional size of a few nanometers, with at least some covalent bond between each other. The outstanding properties of these materials are demonstrated by their superior supercapacitor performance in ionic liquid with specific capacitance and energy density of 231 F/g and 98 Wh/kg, respectively, so far the best reported capacitance performance for all bulk carbon materials.