Nacre-Inspired,Liquid Metal-Based Ultrasensitive Electronic Skin by Spatially Regulated Cracking Strategy

The realization of liquid metal-based wearable systems will be a milestone toward high-performance, integrated electronic skin. However, despite the revolutionary progress achieved in many other components of electronic skin, liquid metal-based flexible sensors still suffer from poor sensitivity due to the insufficient resistance change of liquid metal to deformation. Herein, a nacre-inspired architecture composed of a biphasic pattern (liquid metal with Cr/Cu underlayer) as “bricks” and strain-sensitive Ag film as “mortar” is developed, which breaks the long-standing sensitivity bottleneck of liquid metal-based electronic skin. With 2 orders of magnitude of sensitivity amplification while maintaining wide (>85%) working range, for the first time, liquid metal-based strain sensors rival the state-of-art counterparts. This liquid metal composite features spatially regulated cracking behavior. On the one hand, hard Cr cells locally modulate the strain distribution, which avoids premature cut-through cracks and prolongs the defect propagation in the adjacent Ag film. On the other hand, the separated liquid metal cells prevent unfavorable continuous liquid-metal paths and create crack-free regions during strain. Demonstrated in diverse scenarios, the proposed design concept may spark more applications of ultrasensitive liquid metal-based electronic skins, and reveals a pathway for sensor development via crack engineering.     

Hematite crystal growth in high-temperature lead-free multicomponent alkali borosilicate glass frit for red overglaze enamels

To elucidate the crystal growth process of hematite in high-temperature lead-free multicomponent alkali borosilicate glass, which is essentially important to control the color of red overglaze enamels, frit and hematite mixture is heat-treated and subjected to microscopic observations. Hematite particles slightly grew due to sintering at low temperature. Once the glass matrix formed near the softening point of frit, hematite dissolved into glass fluid. Hematite crystal growth concomitantly ensued with decrease in the number of hematite particles via Ostwald ripening as the temperature increased. The grown particles exhibited an anisotropic morphology with straight outlines reflecting crystal planes, the morphology of which is completely different from those grown by sintering and particles prior to heating. These results suggest that comprehensive understanding of frit and hematite from the perspectives of glass science and chemistry as well as powder technology are important to truly control the color of red overglaze enamels.     

Nitrate Additives Coordinated with Crown Ether Stabilize Lithium Metal Anodes in Carbonate Electrolyte

Lithium metal anodes (LMAs) are promising for next-generation batteries but have poor compatibility with the widely used carbonate-based electrolytes, which is a major reason for their severe dendrite growth and low Coulombic efficiency (CE). A nitrate additive to the electrolyte is an effective solution, but its low solubility in carbonates is a problem that can be solved using a crown ether, as reported. A rubidium nitrate additive coordinated with 18-crown-6 crown ether stabilizes the LMA in a carbonate electrolyte. The coordination promotes the dissolution of NO₃⁻ ions and helps form a dense solid electrolyte interface that is Li₃N-rich which guides uniform Li deposition. In addition, the Rb (18-crown-6)⁺ complexes are adsorbed on the dendrite tips, shielding them from Li deposition on the dendrite tips. A high CE of 97.1% is achieved with a capacity of 1 mAh cm⁻² in a half cell, much higher than when using the additive-free electrolyte (92.2%). Such an additive is very compatible with a nickel-rich ternary cathode at a high voltage, and the assembled full battery with a cathode material loading up to 10 mg cm⁻² shows an average CE of 99.8% over 200 cycles, indicating a potential for practical use.     

New insight into subcritical rupture of SiC-based filaments at intermediate temperatures (400–900 °C) under air

The delayed failure of SiC fibrous reinforcement has continuously been investigated to warrant the long term performances of Ceramic Matrix Composite (CMC). Chiefly assessed on multifilament tow samples to alleviate some handling difficulties, subcritical crack growth (SCG) parameters are however ruled by structural artifacts which hinder the identification of intrinsic filament behavior. In this paper, we propose to estimate the true filament parameters for 5 fiber types from bundle behavior using a recently communicated Monte Carlo algorithm integrating flaw and stress distributions through a deterministic fracture mechanics law under Paris’ formulation. So computed tow lifetime are broadly dispersed, encompassing raw data, and show a structure-dependent scale effect, revealed by n_filament>n_tow where n is the stress exponent. The relationship between SCG coefficient and chemical composition of the substrate is discussed and highlights the major effect of doping elements (Ti or Zr), oxygen or hydrogen content.     

Preparation and electrochemical characterization of Ti-based amorphous metallic glass with high strength

Ti-based amorphous metallic glasses have excellent mechanical, physical, and chemical properties, which is an important development direction and research hotspot of metal composite reinforcement. As a stable, simple, efficient, and large-scale preparation technology of metallic powders, the gas atomization process provides an effective way of preparing amorphous metallic glasses. In this study, the controllable fabrication of a Ti-based amorphous powder, with high efficiency, has been realized by using gas atomization. The scanning electron microscope, energy-dispersive spectrometer, and X-ray diffraction are used to analyze surface morphology, element distribution, and phase structure, respectively. A microhardness tester is used to measure the mechanical property. An electrochemical workstation is used to characterize corrosion behavior. The results show that as-prepared microparticles are more uniform and exhibit good amorphous characteristics. The mechanical test shows that the hardness of amorphous powder is significantly increased as compared with that before preparation, which has the prospect of being an important part of engineering reinforced materials. Further electrochemical measurement shows that the corrosion resistance of the as-prepared sample is also significantly improved. This study has laid a solid foundation for expanding applications of Ti-based metallic glasses, especially in heavy-duty and corrosive domains.     

Spatiotemporal Magnetocaloric Microenvironment for Guiding the Fate of Biodegradable Polymer Implants

The degradation behavior of implants is significantly important for bone repair. However, it is still unprocurable to spatiotemporally regulate the degradation of the implants to match bone ingrowth. In this paper, a magneto-controlled biodegradation model is established to explore the degradation behavior of magnetic scaffolds in a magnetothermal microenvironment generated by an alternating magnetic field (AMF). The results demonstrate that the scaffolds can be heated by magnetic nanoparticles (NPs) under AMF, which dramatically accelerated scaffold degradation. Especially, magnetic NPs modified by oleic acid with a better interface compatibility exhibit a greater heating efficiency to further facilitate the degradation. Furthermore, the molecular dynamics simulations reveal that the enhanced motion correlation between magnetic NPs and polymer matrix can accelerate the energy transfer. As a proof-of-concept, the feasibility of magneto-controlled degradation for implants is demonstrated, and an optimizing strategy for better heating efficiency of nanomaterials is provided, which may have great instructive significance for clinical medicine.     

Micro-expression recognition from local facial regions

MiE is a facial involuntary reaction that reflects the real emotion and thoughts of a human being. It is very difficult for a normal human to detect a Micro-Expression (MiE), since it is a very fast and local face reaction with low intensity. As a consequence, it is a challenging task for researchers to build an automatic system for MiE recognition. Previous works for MiE recognition have attempted to use the whole face, yet a facial MiE appears in a small region of the face, which makes the extraction of relevant features a hard task. In this paper, we propose a novel deep learning approach that leverages the locality aspect of MiEs by learning spatio-temporal features from local facial regions using a composite architecture of Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM). The proposed solution succeeds to extract relevant local features for MiEs recognition. Experimental results on benchmark datasets demonstrate the highest recognition accuracy of our solution with respect to state-of-the-art methods.