Solid electrolytes have been considered as a promising approach for Li dendrite prevention because of their high mechanical strength and high Li transference number. However, recent reports indicate ...that Li dendrites also form in Li2S‐P2S5 based sulfide electrolytes at current densities much lower than that in the conventional liquid electrolytes. The methods of suppressing dendrite formation in sulfide electrolytes have rarely been reported because the mechanism for the “unexpected” dendrite formation is unclear, limiting the successful utilization of high‐energy Li anode with these electrolytes. Herein, the authors demonstrate that the Li dendrite formation in Li2S‐P2S5 glass can be effectively suppressed by tuning the composition of the solid electrolyte interphase (SEI) at the Li/electrolyte interface through incorporating LiI into the electrolyte. This approach introduces high ionic conductivity but electronic insulation of LiI in the SEI, and more importantly, improves the mobility of Li atoms, promoting the Li depositon at the interface and thus suppresses dendrite growth. It is shown that the critical current density is improved significantly after incorporating LiI into Li2S‐P2S5 glass, reaching 3.90 mA cm−2 at 100 °C after adding 30 mol% LiI. Stable cycling of the Li‐Li cells for 200 h is also achieved at 1.50 mA cm−2 at 100 °C.
The dendrite suppression capability of Li2S‐P2S5 glass electrolyte can be improved significantly by LiI incorporation, and the 70(0.75Li2S‐0.25P2S5)‐30LiI (LPS30I) electrolyte exhibits the highest capability for dendrite suppression. The critical current density of LPS30I reaches 3.90 mA cm−2 at 100 °C, and the Li/LPS30I/Li cell could cycle 200 h at 1.50 mA cm−2 at 100 °C.
Objective: Estimation of the discharge pattern of motor units by electromyography (EMG) decomposition has been applied for neurophysiologic investigations, clinical diagnosis, and human-machine ...interfacing. However, most of the methods for EMG decomposition are currently applied offline. Here, we propose an approach for high-density surface EMG decomposition in real-time. Methods: A real-time decomposition scheme including two sessions, offline training and online decomposition, is proposed based on the convolutional kernel compensation algorithm. The estimation parameters, separation vectors and the thresholds for spike extraction, are first computed during offline training, and then they are directly applied to estimate motor unit spike trains (MUSTs) during the online decomposition. The estimation parameters are updated with the identification of new discharges to adapt to non-stationary conditions. The decomposition accuracy was validated on simulated EMG signals by convolving synthetic MUSTs with motor unit action potentials (MUAPs). Moreover, the accuracy of the online decomposition was assessed from experimental signals recorded from forearm muscles using a signal-based performance metrics (pulse-to-noise ratio, PNR). Main results: The proposed algorithm yielded a high decomposition accuracy and robustness to non-stationary conditions. The accuracy of MUSTs identified from simulated EMG signals was <inline-formula><tex-math notation="LaTeX">></tex-math></inline-formula>80% for most conditions. From experimental EMG signals, on average, 12 <inline-formula><tex-math notation="LaTeX">\pm</tex-math></inline-formula> 2 MUSTs were identified from each electrode grid with PNR of 25.0 <inline-formula><tex-math notation="LaTeX">\pm</tex-math></inline-formula> 1.8 dB, corresponding to an estimated decomposition accuracy <inline-formula><tex-math notation="LaTeX">></tex-math></inline-formula>75%. Conclusion and Significance: These results indicate the feasibility of real-time identification of motor unit activities non-invasively during variable force contractions, extending the potential applications of high-density EMG as a neural interface.
The long application life and stable performance of stretchable electronics have been putting forward requirements for both higher mechanical properties and better self‐healing ability of polymeric ...substrates. However, for self‐healing materials, simultaneously improving stretchability and robustness is still challenging. Here, by incorporating sliding crosslinker (polyrotaxanes) and hydrogen bonds into a polymer, a highly stretchable and self‐healable elastomer with good mechanical strength is achieved. The elastomer exhibits very high stretchability, such that it can be stretched to 2800% with a fracture strength of 1.05 MPa. Moreover, the elastomer can achieve nearly complete self‐healing (93%) at 55 °C. Next, tensile tests under different temperatures, step extension experiments, and in situ small angle X‐ray scattering confirm that the excellent stretchability is attributed to the combined effects of sliding cyclodextrins along guest chains and hydrogen bonds. Furthermore, a strain sensor by coating the single‐wall carbon nanotubes onto the surface of the elastic substrate is fabricated.
A new strategy, by incorporating sliding crosslinks and hydrogen bonds into a polymer to achieve a highly stretchable and self‐healable elastomer with good mechanical strength, is reported in this work.
All-inorganic solid-state sodium–sulfur batteries (ASSBs) are promising technology for stationary energy storage due to their high safety, high energy, and abundant resources of both sodium and ...sulfur. However, current ASSB shows poor cycling and rate performances mainly due to the huge electrode/electrolyte interfacial resistance arising from the insufficient triple-phase contact among sulfur active material, ionic conductive solid electrolyte, and electronic conductive carbon. Herein, we report an innovative approach to address the interfacial problem using a Na3PS4–Na2S–C (carbon) nanocomposite as the cathode for ASSBs. Highly ionic conductive Na3PS4 contained in the nanocomposite can function as both solid electrolyte and active material (catholyte) after mixing with electronic conductive carbon, leading to an intrinsic superior electrode/electrolyte interfacial contact because only a two-phase contact is required for the charge transfer reaction. Introducing nanosized Na2S into the nanocomposite cathode can effectively improve the capacity. The homogeneous distribution of nanosized Na2S, Na3PS4, and carbon in the nanocomposite cathode could ensure a high mixed (ionic and electronic) conductivity and a sufficient interfacial contact. The Na3PS4-nanosized Na2S–carbon nanocomposite cathode delivered a high initial discharge capacity of 869.2 mAh g–1 at 50 mA g–1 with great cycling and rate capabilities at 60 °C, representing the best performance of ASSBs reported to date and therefore constituting a significant step toward high-performance ASSBs for practical applications.
Soft dielectric elastomer actuators (DEAs) exhibit interesting muscle-like behavior for the development of soft robots. However, it is challenging to model these soft actuators due to their material ...nonlinearity, nonlinear electromechanical coupling, and time-dependent viscoelastic behavior. Most recent studies on DEAs focus on issues of mechanics, physics, and material science, while much less importance is given to quantitative characterization of DEAs. In this paper, we present a detailed experimental investigation probing the voltage-induced electromechanical response of a soft DEA that is subjected to cyclic loading and propose a general constitutive modeling approach to characterize the time-dependent response, based on the principles of nonequilibrium thermodynamics. In this paper, some of the key observations are found as follows: 1) Creep exhibits the drift phenomenon, and is dominant during the first three cycles. The creep decreases over time and becomes less dominant after the first few cycles; 2) a significant amount of hysteresis is observed during all cycles and it becomes repeatable after the first few cycles; 3) the peak of the displacement is shifted from the peak of the voltage signal and occurs after it. To account for these viscoelastic phenomena, a constitutive model is developed by employing several dissipative nonequilibrium mechanisms. The quantitative comparisons of the experimental and simulation results demonstrate the effectiveness of the developed model. This modeling approach can be useful for control of a viscoelastic DEA and paves the way to emerging applications of soft robots.
Advanced myoelectric prosthetic hands are currently limited due to the lack of sufficient signal sources on amputation residual muscles and inadequate real-time control performance. This paper ...presents a novel human-machine interface for prosthetic manipulation that combines the advantages of surface electromyography (EMG) and near-infrared spectroscopy (NIRS) to overcome the limitations of myoelectric control. Experiments including 13 able-bodied and three amputee subjects were carried out to evaluate both offline classification accuracy (CA) and online performance of the forearm motion recognition system based on three types of sensors (EMG-only, NIRS-only, and hybrid EMG-NIRS). The experimental results showed that both the offline CA and realtime performance for controlling a virtual prosthetic hand were significantly (p <; 0.05) improved by combining EMG and NIRS. These findings suggest that fusion of EMG and NIRS is feasible to improve the control of upper-limb prostheses, without increasing the number of sensor nodes or complexity of signal processing. The outcomes of this study have great potential to promote the development of dexterous prosthetic hands for transradial amputees.
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•We design and fabricate a modularized, pneumatically actuated RFiSFA through multi-material 3D printing.•We develop an 11-DoF anthropomorphic hand with one thumb and four fingers ...made of 12 RFiSFAs.•We evaluate the motion and force performance of the fingers and the dexterity of the hand.
Owing to the integrated muscular, ligamentous and skeletal structures and coupled degrees of freedom (DoFs), it is a long-term challenge in the field of robotics to design an anthropomorphic hand that mimics the biological structures and dexterous motions of human hands. In this paper, we present pneumatical, multi-material 3D-printed, modularized rigid-flexible integrated soft finger actuators (RFiSFAs) that can be directly assembled to an anthropomorphic hand. First, we introduce the mechanism of the RFiSFA with a pneumatic bellow chamber and a joint structure, and investigate the influence of the chamber material and the bellow number on the flexion angles and output forces performances of the RFiSFA. Next, we design and fabricate a 2-DoF flexion finger with two serial RFiSFAs and a 3-DoF thumb with two serial RFiSFAs and two parallel RFiSFAs. Then, we perform tests to characterize the motion and force performance of the fingers and thumb. Finally, we integrate and assemble an 11-DoF anthropomorphic hand with four flexion fingers and one thumb, and experimental results demonstrate the capability of the hand in grasping objects with different dimensions, shapes and textures.
Surface electromyography (EMG) signals are inevitably contaminated by various noise components, including powerline interference (PLI), baseline wandering (BW), and white Gaussian noise (WGN). These ...noises directly degrade the efficiency of EMG processing and affect the accuracy and robustness of further applications. Currently, most of the EMG filters only target one category of noise. Here, we propose a novel filter to remove all three types of noise. The noisy EMG signal is first decomposed into an ensemble of band-limited modes using variational mode decomposition (VMD). Each category of noise is located within specific modes and is separately removed in sub-bands. In particular, WGN is suppressed by soft thresholding with a noise level-dependent threshold. The denoising performance was assessed from simulated and experimental signals using three performance metrics: the root mean square error (<inline-formula><tex-math notation="LaTeX">\operatorname{RMSE}</tex-math></inline-formula>), the improvement in signal-to-noise ratio (<inline-formula><tex-math notation="LaTeX">\operatorname{SNR}_{\text{imp}}</tex-math></inline-formula>), and the percentage reduction in the correlation coefficient (<inline-formula><tex-math notation="LaTeX">\eta</tex-math></inline-formula>). Other methods, including traditional infinite impulse response (IIR) filters, empirical mode decomposition (EMD) method, and ensemble empirical mode decomposition (EEMD) method, were examined for comparison. The proposed method achieved the best performance to remove BW or WGN. It also effectively reduced PLI noise when the signal-to-noise ratio (SNR) was low. The SNR was improved by 18.6, 19.2, and 8.0 dB for EMG signals corrupted with PLI, BW, and WGN at <inline-formula><tex-math notation="LaTeX">-</tex-math></inline-formula>6 dB SNR, respectively. The experimental results illustrated that noise was completely removed from resting states, and obvious spikes were distinguished from action states. For two of the ten subjects, the improved SNR reached 20 dB. This study explores the special characteristics of VMD and demonstrates the feasibility of using the VMD-based filter to denoise EMG signals. The proposed filter is efficient at removing three categories of noise and can be used for any application that requires EMG signal filtering at the preprocessing stage, such as gesture recognition and EMG decomposition.
The myoelectric upper-limb prosthetic manipulation is inherently limited by the unreliable sensor-skin interface. This paper presents a hybrid approach to overcome the limitation of electromyography ...(EMG) through mechanomyography (MMG) assisted myoelectric sensing. An integrated hybrid sensor system was developed for simultaneous EMG and MMG measurement. The hybrid system formed a platform to capture muscular activations in different frequencies. To evaluate the effectiveness of hybrid EMG-MMG sensing, hand motion experiments have been carried out on seven able-bodied and two transradial amputee subjects. It convincingly demonstrated, a significantly (p <; 0.01) improved classification accuracy (CA). Furthermore, the CA was compensated by 8.7% ~ 33.7% in the presence of 2 ~ 3 fault EMG channels. These results suggest that MMG assisted myoelectric sensing can improve the control performance and robustness. It has great potential to promote the clinical application of multi-functional prosthetic hand with hybrid EMG-MMG sensor system.
Neuroprosthetic hands are typically heavy (over 400 g) and expensive (more than US$10,000), and lack the compliance and tactile feedback of human hands. Here, we report the design, fabrication and ...performance of a soft, low-cost and lightweight (292 g) neuroprosthetic hand that provides simultaneous myoelectric control and tactile feedback. The neuroprosthesis has six active degrees of freedom under pneumatic actuation, can be controlled through the input from four electromyography sensors that measure surface signals from residual forearm muscles, and integrates five elastomeric capacitive sensors on the fingertips to measure touch pressure so as to enable tactile feedback by eliciting electrical stimulation on the skin of the residual limb. In a set of standardized tests performed by two individuals with transradial amputations, we show that the soft neuroprosthetic hand outperforms a conventional rigid neuroprosthetic hand in speed and dexterity. We also show that one individual with a transradial amputation wearing the soft neuroprosthetic hand can regain primitive touch sensation and real-time closed-loop control.
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