Artificial intelligence has become indispensable in modern life, but its energy consumption has become a significant concern due to its huge storage and computational demands. Artificial intelligence algorithms are mainly based on deep learning algorithms, relying on the backpropagation of convolutional neural networks or binary neural networks. While these algorithms aim to simulate the learning process of the human brain, their low bio-fidelity and the separation of storage and computing units lead to significant energy consumption. The human brain is a remarkable computing machine with extraordinary capabilities for recognizing and processing complex information while consuming very low power. Tunneling magnetoresistance (TMR)-based devices, namely magnetic tunnel junctions (MTJs), have great advantages in simulating the behavior of biological synapses and neurons. This is not only because MTJs can simulate biological behavior such as spike-timing dependence plasticity and leaky integrate-fire, but also because MTJs have intrinsic stochastic and oscillatory properties. These characteristics improve MTJs' bio-fidelity and reduce their power consumption. MTJs also possess advantages such as ultrafast dynamics and non-volatile properties, making them widely utilized in the field of neuromorphic computing in recent years. We conducted a comprehensive review of the development history and underlying principles of TMR, including a detailed introduction to the material and magnetic properties of MTJs and their temperature dependence. We also explored various writing methods of MTJs and their potential applications. Furthermore, we provided a thorough analysis of the characteristics and potential applications of different types of MTJs for neuromorphic computing. TMR-based devices have demonstrated promising potential for broad application in neuromorphic computing, particularly in the development of spiking neural networks. Their ability to perform on-chip learning with ultra-low power consumption makes them an exciting prospect for future advances in the era of the internet of things.
Ultrasound (US) is a kind of acoustic wave with frequency higher than 20 kHz. Learning from the echo detection ability of bats and dolphins, scientists applied US for clinical imaging by sending out US waves and detecting echoes with shifted intensities and frequencies from human tissue. US has long played a critical role in noninvasive, real-time, low-cost and portable diagnostic imaging. With the in-depth study of US in multidisciplinary fields, US and US-responsive materials have shown practical value in not only disease diagnosis, but also disease treatment. In this review, we introduce the recently proposed and representative US-responsive materials for biomedical applications, including diagnostic and therapeutic applications. We focused on US-mediated physicochemical therapies, such as sonodynamic therapy, high-intensity focused US ablation, sonothermal therapy, thrombolysis, etc, and US-controlled delivery of chemotherapeutics, gases, genes, proteins and bacteria. We conclude with the current challenges facing the clinical translation of smart US-responsive materials and prospects for the future development of US medicine.
Despite the efforts devoted to the identification of new electrode materials with higher specific capacities and electrolyte additives to mitigate the well-known limitations of current lithium-ion batteries, this technology is believed to have almost reached its energy density limit. It suffers also of a severe safety concern ascribed to the use of flammable liquid-based electrolytes. In this regard, solid-state electrolytes (SSEs) enabling the use of lithium metal as anode in the so-called solid-state lithium metal batteries (SSLMBs) are considered as the most desirable solution to tackle the aforementioned limitations. This emerging technology has rapidly evolved in recent years thanks to the striking advances gained in the domain of electrolyte materials, where SSEs can be classified according to their core chemistry as organic, inorganic, and hybrid/composite electrolytes. This strategic review presents a critical analysis of the design strategies reported in the field of SSEs, summarizing their main advantages and disadvantages, and providing a future perspective toward the rapid development of SSLMB technology.
Abstract: The traditional von Neumann structure computers cannot meet the demands of high-speed big data processing; therefore, neuromorphic computing has received a lot of interest in recent years. Brain-inspired neuromorphic computing has the advantages of low power consumption, high speed and high accuracy. In human brains, the data transmission and processing are realized through synapses. Artificial synaptic devices can be adopted to mimic the biological synaptic functionalities. Nanowire (NW) is an important building block for nanoelectronics and optoelectronics, and many efforts have been made to promote the application of NW-based synaptic devices for neuromorphic computing. Here, we will introduce the current progress of NW-based synaptic memristors and synaptic transistors. The applications of NW-based synaptic devices for neuromorphic computing will be discussed. The challenges faced by NW-based synaptic devices will be proposed. We hope this perspective will be beneficial for the application of NW-based synaptic devices in neuromorphic systems.
Abstract: Transition metal dichalcogenides (TMDs) are a class of materials with various useful properties, and it is worthwhile to have a thorough evaluation of the characteristics of the TMDs, most importantly, their structural stability and exfoliability, in a systematic fashion. Here, by employing high-throughput first-principles calculations, we investigate the vast phase space of TMDs, including 16 bulk phases and 6 monolayer phases for all possible TMD combinations [comprising (3d, 4d, 5d) transition-metal cations and (S, Se, Te) anions], totaling 1386 compounds. Through the 'bird-view' of the as-large-as-possible configurational and chemical space of TMDs, our work presents comprehensive energy landscapes to elucidate the thermodynamic stability as well as the exfoliability of TMDs, which are of vital importance for future synthesis and exploration towards large-scale industrial applications.
Despite the potential advantages promised by solid-state batteries, the success of solid-state electrolytes has not yet been fully realised. This is due in part to the lower ionic conductivity of solid electrolytes. In many solid superionic conductors, grain boundaries are found to be ionically resistive and hence contribute to this lower ionic conductivity. Additionally, in spite of the hope that solid electrolytes would inhibit lithium filaments, in most scenarios their growth is still observed, and in some polycrystalline systems this is suggested to occur along grain boundaries. It is apparent that grain boundaries affect the performance of solid-state electrolytes, however a deeper understanding is lacking. In this perspective, the current theories relating to grain boundaries in solid-state electrolytes are explored, as well as addressing some of the challenges which arise when trying to investigate their role. Glasses are presented as a possible solution to reduce the effect of grain boundaries in electrolytes. Future research directions are suggested which will aid in both understanding the role of grain boundaries, and diminishing their contribution in cases where they are detrimental.
Based on symmetry analysis and lattice model calculations, we demonstrate that Dirac nodal line (DNL) can stably exist in two-dimensional (2D) nonmagnetic as well as antiferromagnetic systems. We focus on the situations where the DNLs are enforced by certain symmetries and the degeneracies on the DNLs are inevitable even if spin–orbit coupling is strong. After thorough analysis, we find that five space groups, namely 51, 54, 55, 57 and 127, can enforce the DNLs in 2D nonmagnetic semimetals, and four type-III magnetic space groups (51.293, 54.341, 55.355, 57.380) plus eight type-IV magnetic space groups (51.299, 51.300, 51.302, 54.348, 55.360, 55.361, 57.387 and 127.396) can enforce the DNLs in 2D antiferromagnetic semimetals. By breaking these symmetries, the different 2D topological phases can be obtained. Furthermore, by the first-principles electronic structure calculations, we predict that monolayer YB4C4 is a good material platform for studying the exotic properties of 2D symmetry-enforced Dirac node-line semimetals.
Efficient water splitting for H2 evolution over semiconductor photocatalysts is highly attractive in the ﬁeld of clean energy. It is of great significance to construct heterojunctions, among which the direct Z-scheme nanocomposite photocatalyst provides effective separation of photo-generated carriers to boost the photocatalytic performance. Herein, Z-scheme hydrated tungsten trioxide/ZnIn2S4 is fabricated via an in-situ hydrothermal method where ZnIn2S4 nanosheets are grown on WO3⋅xH2O. The close contact between WO3⋅0.5H2O and WO3⋅0.33H2O as well as ZnIn2S4 improve the charge carrier separation and migration in the photocatalyst, where the strong reducing electrons in the conduction band of ZnIn2S4 and the strong oxidizing holes in the valence band of WO3⋅0.33H2O are retained, leading to enhanced photocatalytic hydrogen production. The obtained WO3⋅xH2O/ZnIn2S4 shows an excellent H2 production rate of 7200 μmol g-1h-1, which is 11 times higher than pure ZnIn2S4. To the best of our knowledge, this value is higher than most of the WO3-based noble metal-free semiconductor photocatalysts. The improved stability and activity are attributed to the formation of the Z-scheme heterojunction, which can markedly accelerate the interfacial charge separation for surface reaction. This work offers a promising strategy towards the design of efficient Z-scheme photocatalyst to suppress electron-hole recombination and optimize redox potential.
Lithium phosphorus oxygen nitrogen (LiPON) as solid electrolyte discovered by Bates et al in the 1990s is an important part of all-solid-state thin-film battery (ASSTFB) due to its wide electrochemical stability window and negligible low electronic conductivity. However, the ionic conductivity of LiPON about 2 × 10−6 S cm−1 at room temperature is much lower than that of other types of solid electrolytes, which seriously limits the application of ASSTFBs. This review summarizes the research and progress in ASSTFBs based on LiPON, in the solid-state electrolyte of LiPON-derivatives with adjustable chemical compositions of the amorphous structure for the improvement of the ionic conductivity and electrochemical stability, in the critical interface issues between LiPON and electrodes, and in preparation methods for LiPON. This review is helpful for people to understand the interface characteristics and various preparation methods of LiPON in ASSTFBs. The key issues to be addressed concern how to develop solid-state electrolyte films with high conductivity and high-quality interface engineering as well as large-scale preparation technology, so as to realize the practical application of highly integrated ASSTFBs.
Helium-3 (3He) is a noble gas that has critical applications in scientific research and promising application potential as clean fusion energy. It is thought that the lunar regolith contains large amounts of helium, but it is challenging to extract because most helium atoms are reserved in defects of crystals or as solid solutions. Here, we find large amounts of helium bubbles in the glassy surface layer of ilmenite particles that were brought back by the Chang’E-5 mission. The special disordered atomic packing structure of glasses should be the critical factor for capturing the noble helium gas. The reserves in bubbles do not require heating to high temperatures to be extracted. Mechanical methods at ambient temperatures can easily break the bubbles. Our results provide insights into the mechanism of helium gathering on the moon and offer guidance on future in situ extraction.
To fill the gap between accurate (and expensive) ab initio calculations and efficient atomistic simulations based on empirical interatomic potentials, a new class of descriptions of atomic interactions has emerged and been widely applied; i.e. machine learning potentials (MLPs). One recently developed type of MLP is the deep potential (DP) method. In this review, we provide an introduction to DP methods in computational materials science. The theory underlying the DP method is presented along with a step-by-step introduction to their development and use. We also review materials applications of DPs in a wide range of materials systems. The DP Library provides a platform for the development of DPs and a database of extant DPs. We discuss the accuracy and efficiency of DPs compared with ab initio methods and empirical potentials.
Solid-state batteries (SSBs) are a promising next step in electrochemical energy storage but are plagued by a number of problems. In this study, we demonstrate the recurring issue of mechanical degradation because of volume changes in layered Ni-rich oxide cathode materials in thiophosphate-based SSBs. Specifically, we explore superionic solid electrolytes of different crystallinity, namely glassy 1.5Li2S-0.5P2S5-LiI and argyrodite Li6PS5Cl, with emphasis on how they affect the cyclability of slurry-cast cathodes with NCM622 (60% Ni) or NCM851005 (85% Ni). The application of a combination of ex situ and in situ analytical techniques helped to reveal the benefits of using a solid electrolyte with a low Young's modulus. Through a synergistic interplay of (electro)chemical and (chemo)mechanical effects, the glassy solid electrolyte employed in this work was able to achieve robust and stable interfaces, enabling intimate contact with the cathode material while at the same time mitigating volume changes. Our results emphasize the importance of considering chemical, electrochemical, and mechanical properties to realize long-term cycling performance in high-loading SSBs.
In the crucial area of sustainable energy storage, solid-state batteries (SSBs) with nonflammable solid electrolytes stand out due to their potential benefits of enhanced safety, energy density, and cycle life. However, the complexity within the composite cathode determines that fabricating an ideal electrode needs to link chemistry (atomic scale), materials (microscopic/mesoscopic scale), and electrode system (macroscopic scale). Therefore, understanding solid-state composite cathodes covering multiple scales is of vital importance for the development of practical SSBs. In this review, the challenges and basic knowledge of composite cathodes from the atomic scale to the macroscopic scale in SSBs are outlined with a special focus on the interfacial structure, charge transport, and mechanical degradation. Based on these dilemmas, emerging strategies to design a high-performance composite cathode and advanced characterization techniques are summarized. Moreover, future perspectives toward composite cathodes are discussed, aiming to facilitate the develop energy-dense SSBs.