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Anodic oxygen evolution reaction (OER) is recognized as kinetic bottleneck in water electrolysis. Transition metal sites with high valence states can accelerate the reaction kinetics to offer highly intrinsic activity, but suffer from thermodynamic formation barrier. Here, we show subtle engineering of highly oxidized Ni 4+ species in surface reconstructed (oxy)hydroxides on multicomponent FeCoCrNi alloy film through interatomically electronic interplay. Our spectroscopic investigations with theoretical studies uncover that Fe component enables the formation of Ni 4+ species, which is energetically favored by the multistep evolution of Ni 2+ →Ni 3+ →Ni 4+ . The dynamically constructed Ni 4+ species drives holes into oxygen ligands to facilitate intramolecular oxygen coupling, triggering lattice oxygen activation to form Fe-Ni dual-sites as ultimate catalytic center with highly intrinsic activity. As a result, the surface reconstructed FeCoCrNi OER catalyst delivers outstanding mass activity and turnover frequency of 3601 A g metal −1 and 0.483 s −1 at an overpotential of 300 mV in alkaline electrolyte, respectively. Electrocatalytic water oxidation is facilitated by high valence states, but these are challenging to achieve at low applied potentials. Here, authors report a multicomponent FeCoCrNi alloy with dynamically formed Ni 4+ species to offer high catalytic activity via lattice oxygen activation mechanism.

Stretchable electronics find widespread uses in a variety of applications such as wearable electronics, on-skin electronics, soft robotics and bioelectronics. Stretchable electronic devices conventionally built with elastomeric thin films show a lack of permeability, which not only impedes wearing comfort and creates skin inflammation over long-term wearing but also limits the design form factors of device integration in the vertical direction. Here, we report a stretchable conductor that is fabricated by simply coating or printing liquid metal onto an electrospun elastomeric fibre mat. We call this stretchable conductor a liquid-metal fibre mat. Liquid metal hanging among the elastomeric fibres self-organizes into a laterally mesh-like and vertically buckled structure, which offers simultaneously high permeability, stretchability, conductivity and electrical stability. Furthermore, the liquid-metal fibre mat shows good biocompatibility and smart adaptiveness to omnidirectional stretching over 1,800% strain. We demonstrate the use of a liquid-metal fibre mat as a building block to realize highly permeable, multifunctional monolithic stretchable electronics. Coating of liquid metals on electrospun elastomeric fibre mats leads to the realization of conducting buckled meshes that can be stretched up to 1,800% strain while preserving both stable electrical properties and permeability to air and moisture.

Neuromorphic visual systems have considerable potential to emulate basic functions of the human visual system even beyond the visible light region. However, the complex circuitry of artificial visual systems based on conventional image sensors, memory and processing units presents serious challenges in terms of device integration and power consumption. Here we show simple two-terminal optoelectronic resistive random access memory (ORRAM) synaptic devices for an efficient neuromorphic visual system that exhibit non-volatile optical resistive switching and light-tunable synaptic behaviours. The ORRAM arrays enable image sensing and memory functions as well as neuromorphic visual pre-processing with an improved processing efficiency and image recognition rate in the subsequent processing tasks. The proof-of-concept device provides the potential to simplify the circuitry of a neuromorphic visual system and contribute to the development of applications in edge computing and the internet of things.

Craniosynostosis is a major congenital craniofacial disorder characterized by the premature fusion of cranial suture(s). Patients with severe craniosynostosis often have impairments in hearing, vision, intracranial pressure and/or neurocognitive functions. Craniosynostosis can result from mutations, chromosomal abnormalities or adverse environmental effects, and can occur in isolation or in association with numerous syndromes. To date, surgical correction remains the primary treatment for craniosynostosis, but it is associated with complications and with the potential for re-synostosis. There is, therefore, a strong unmet need for new therapies. Here, we provide a comprehensive review of our current understanding of craniosynostosis, including typical craniosynostosis types, their clinical manifestations, cranial suture development, and genetic and environmental causes. Based on studies from animal models, we present a framework for understanding the pathogenesis of craniosynostosis, with an emphasis on the loss of postnatal suture mesenchymal stem cells as an emerging disease-driving mechanism. We evaluate emerging treatment options and highlight the potential of mesenchymal stem cell-based suture regeneration as a therapeutic approach for craniosynostosis.

Solar‐driven overall water splitting based on metal sulfide semiconductor photocatalysts remains as a challenge owing to the strong charge recombination and deficient catalytic active sites. Additionally, significant inhibition of back reactions, especially the oxidation of sulfide ions during the photocatalytic water oxidation catalysis, is an arduous task that requires an efficient photogenerated hole transfer dynamics. Here, a ternary dumbbell‐shaped catalyst based on RuO2/CdS/MoS2 with spatially separated catalytic sites is developed to achieve simultaneous production of hydrogen and oxygen under simulated solar‐light without any sacrificial agents. Particularly, MoS2 nanosheets anchored on the two ends of CdS nanowires are identified as a reduction cocatalyst to accelerate hydrogen evolution, while RuO2 nanoparticles as an oxidation cocatalyst are deposited onto the sidewalls of CdS nanowires to facilitate oxygen evolution kinetics. The density functional theory simulations and ultrafast spectroscopic results reveal that photogenerated electrons and holes directionally migrate to MoS2 and RuO2 catalytic sites, respectively, thus achieving efficient charge carrier separation. The design of ternary dumbbell structure guarantees metal sulfides against photocorrosion and thus extends their range in solar water splitting. The ternary dumbbell‐like RuO2/CdS/MoS2 photocatalyst with selective attachment of reduction and oxidation cocatalysts enables water splitting into H2 and O2. The critical aspect is the spatially separated distribution of MoS2 and RuO2 dual cocatalysts, which not only achieves photogenerated electron–hole pairs separation, but also protects CdS from photocorrosion by holes.

Moisture-electric generators (MEGs) has emerged as promising green technology to achieve carbon neutrality in next-generation energy suppliers, especially combined with ecofriendly materials. Hitherto, challenges remain for MEGs as direct power source in practical applications due to low and intermittent electric output. Here we design a green MEG with high direct-current electricity by introducing polyvinyl alcohol-sodium alginate-based supramolecular hydrogel as active material. A single unit can generate an improved power density of ca. 0.11 mW cm −2 , a milliamp-scale short-circuit current density of ca. 1.31 mA cm −2 and an open-circuit voltage of ca. 1.30 V. Such excellent electricity is mainly attributed to enhanced moisture absorption and remained water gradient to initiate ample ions transport within hydrogel by theoretical calculation and experiments. Notably, an enlarged current of ca. 65 mA is achieved by a parallel-integrated MEG bank. The scalable MEGs can directly power many commercial electronics in real-life scenarios, such as charging smart watch, illuminating a household bulb, driving a digital clock for one month. This work provides new insight into constructing green, high-performance and scalable energy source for Internet-of-Things and wearable applications. The emerging moisture-electric harvester suffers from insufficient power output. Here, the authors report a green, efficient, and scalable moisture-electric generator by introducing polyvinyl alcohol-sodium alginate hydrogel as active material.

The development of continuous conducting polymer fibres is essential for applications ranging from advanced fibrous devices to frontier fabric electronics. The use of continuous conducting polymer fibres requires a small diameter to maximize their electroactive surface, microstructural orientation, and mechanical strength. However, regularly used wet spinning techniques have rarely achieved this goal due primarily to the insufficient slenderization of rapidly solidified conducting polymer molecules in poor solvents. Here we report a good solvent exchange strategy to wet spin the ultrafine polyaniline fibres. The slow diffusion between good solvents distinctly decreases the viscosity of protofibers, which undergo an impressive drawing ratio. The continuously collected polyaniline fibres have a previously unattained diameter below 5 µm, high energy and charge storage capacities, and favorable mechanical performance. We demonstrated an ultrathin all-solid organic electrochemical transistor based on ultrafine polyaniline fibres, which operated as a tactile sensor detecting pressure and friction forces at different levels. Strong, electroactive and ultrafine conducting polymer fibres are prepared at the large scale by a modified wet spinning strategy. The obtained ultrafine polyaniline fibres are qualified to build tactile organic electrochemical transistors.

The efficacy of anti-programmed cell death protein 1 (PD-1) immunotherapy in various cancers, including gastric cancer (GC), needs to be potentiated by more effective targeting to enhance therapeutic efficacy or identifying accurate biomarkers to predict clinical responses. Here, we attempted to identify molecules predicting or/and promoting anti-PD-1 therapeutic response in advanced GC (AGC). The transcriptome of AGC tissues from patients with different clinical responses to anti-PD-1 immunotherapy and GC cells was analyzed by RNA sequencing. The protein and mRNA levels of the major facilitator superfamily domain containing 2A (MFSD2A) in GC cells were assessed via quantitative real-time polymerase chain reaction, Western blotting, and immunohistochemistry. Additionally, the regulation of anti-PD-1 response by MFSD2A was studied in tumor-bearing mice. Cytometry by Time-of-Flight, multiple immunohistochemistry, and flow cytometry assays were used to explore immunological responses. The effects of MFSD2A on lipid metabolism in mice cancer tissue and GC cells was detected by metabolomics. Higher expression of MFSD2A in tumor tissues of AGC patients was associated with better response to anti-PD-1 immunotherapy. Moreover, MFSD2A expression was lower in GC tissues compared to adjacent normal tissues, and its expression was inversely correlated with GC stage. The overexpression of MFSD2A in GC cells enhanced the efficacy of anti-PD-1 immunotherapy in vivo by reprogramming the tumor microenvironment (TME), characterized by increased CD8 T cell activation and reduced its exhaustion. MFSD2A inhibited transforming growth factor β1 (TGFβ1) release from GC cells by suppressing cyclooxygenase 2 (COX2)-prostaglandin synthesis, which consequently reprogrammed TME to promote anti-tumor T cell activation. MFSD2A potentially serves as a predictive biomarker for anti-PD-1 immunotherapy response in AGC patients. MFSD2A may be a promising therapeutic target to potentiate the efficacy of anti-PD-1 immunotherapy by reprogramming the TME to promote T cells activation.

An image-sensor array has been developed that acts as its own artificial neural network to capture and identify optical images simultaneously, processing the information rapidly without needing to convert it to a digital format. An array of photosensors that acts as an artificial neural network.

The increasing power consumption in the existing computation architecture presents grand challenges for the performance and reliability of very‐large‐scale integrated circuits. Inspired by the characteristics of the human brain for processing complicated tasks with low power, neuromorphic computing is intensively investigated for decreasing power consumption and enriching computation functions. Hardware implementation of neuromorphic computing with emerging devices substantially reduces power consumption down to a few mW cm−2, compared with the central processing unit based on conventional Si complementary metal–oxide semiconductor (CMOS) technologies (50–100 W cm−2). Herein, a brief introduction on the characteristics of neuromorphic computing is provided. Then, emerging devices for low‐power neuromorphic computing are overviewed, e.g., resistive random access memory with low power consumption (< pJ) per synaptic event. A few computation models for artificial neural networks (NNs), including spiking neural network (SNN) and deep neural network (DNN), which boost power efficiency by simplifying the computing procedure and minimizing memory access are discussed. A few examples for system‐level demonstration are described, such as mixed synchronous–asynchronous and reconfigurable convolution neuron network (CNN)–recurrent NN (RNN) for low‐power computing. Neuromorphic computing is intensively investigated for decreasing power consumption and enriching computation functions. A brief introduction on the characteristics of neuromorphic computing and an overview on emerging devices for low‐power neuromorphic computing are provided, and a few computation models for artificial neural networks and a few examples for system‐level demonstration are discussed and described.