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Transitioning from polycrystalline to single-crystalline nickel-rich cathodes has garnered considerable attention in both academia and industry, driven by advantages of high tap density and enhanced mechanical properties. However, cathodes with high nickel content (>70%) suffer from substantial capacity degradation, which poses a challenge to their commercial viability. Leveraging multiscale spatial resolution diffraction and imaging techniques, we observe that lattice rotations occur universally in single-crystalline cathodes and play a pivotal role in the structure degradation. These lattice rotations prove unrecoverable and govern the accumulation of adverse lattice distortions over repeated cycles, contributing to structural and mechanical degradation and fast capacity fade. These findings bridge the previous knowledge gap that exists in the mechanistic link between fast performance failure and atomic-scale structure degradation.

Lithium-ion batteries play a crucial role in decarbonizing transportation and power grids, but their reliance on high-cost, earth-scarce cobalt in the commonly employed high-energy layered Li(NiMnCo)O 2 cathodes raises supply-chain and sustainability concerns. Despite numerous attempts to address this challenge, eliminating Co from Li(NiMnCo)O 2 remains elusive, as doing so detrimentally affects its layering and cycling stability. Here, we report on the rational stoichiometry control in synthesizing Li-deficient composite-structured LiNi 0.95 Mn 0.05 O 2 , comprising intergrown layered and rocksalt phases, which outperforms traditional layered counterparts. Through multiscale-correlated experimental characterization and computational modeling on the calcination process, we unveil the role of Li-deficiency in suppressing the rocksalt-to-layered phase transformation and crystal growth, leading to small-sized composites with the desired low anisotropic lattice expansion/contraction during charging and discharging. As a consequence, Li-deficient LiNi 0.95 Mn 0.05 O 2 delivers 90% first-cycle Coulombic efficiency, 90% capacity retention, and close-to-zero voltage fade for 100 deep cycles, showing its potential as a Co-free cathode for sustainable Li-ion batteries., (© 2024. The Author(s).)

X-ray fluorescence mapping (XRF) is a highly efficient and non-invasive technique for quantifying material composition with micro and nanoscale spatial resolutions. Quantitative XRF analysis, however, confronts challenges from the long-lasting problem called self-absorption. Moreover, correcting two-dimensional XRF mapping datasets is particularly difficult because it is an ill-posed inverse problem. Here we report a semi-empirical method that can effectively correct 2D XRF mapping data. The correction error is generally less than 10% from a comprehensive evaluation of the accuracy in various configurations. The proposed method was applied to quantify the composition distribution around the grain boundaries in an electrochemically corroded stainless steel sample. Highly localized Cr enrichment was found around the crack sites, which was invisible before the absorption correction., (© 2023. The Author(s).)

With the proliferation of multi-modal data generated by various sensors, unsupervised multi-modal hashing retrieval has been extensively studied due to its advantages in storage, retrieval efficiency, and label independence. However, there are still two obstacles to existing unsupervised methods: (1) As existing methods cannot fully capture the complementary and co-occurrence information of multi-modal data, existing methods suffer from inaccurate similarity measures. (2) Existing methods suffer from unbalanced multi-modal learning and data semantic structure being corrupted in the process of hash codes binarization. To address these obstacles, we devise an effective CLIP-based Adaptive Graph Attention Network (CAGAN) for large-scale unsupervised multi-modal hashing retrieval. Firstly, we use the multi-modal model CLIP to extract fine-grained semantic features, mine similar information from different perspectives of multi-modal data and perform similarity fusion and enhancement. In addition, this paper proposes an adaptive graph attention network to assist the learning of hash codes, which uses an attention mechanism to learn adaptive graph similarity across modalities. It further aggregates the intrinsic neighborhood information of neighboring data nodes through a graph convolutional network to generate more discriminative hash codes. Finally, this paper employs an iterative approximate optimization strategy to mitigate the information loss in the binarization process. Extensive experiments on three benchmark datasets demonstrate that the proposed method significantly outperforms several representative hashing methods in unsupervised multi-modal retrieval tasks.

Understanding the mechanisms leading to the degradation of alloys in molten salts at elevated temperatures is significant for developing several key energy generation and storage technologies, including concentrated solar and next-generation nuclear power plants. Specifically, the fundamental mechanisms of different types of corrosion leading to various morphological evolution characteristics for changing reaction conditions between the molten salt and alloy remain unclear. In this work, the three-dimensional (3D) morphological evolution of Ni-20Cr in KCl-MgCl 2 is studied at 600 °C by combining in situ synchrotron X-ray and electron microscopy techniques. By further comparing different morphology evolution characteristics in the temperature range of 500-800 °C, the relative rates between diffusion and reaction at the salt-metal interface lead to different morphological evolution pathways, including intergranular corrosion and percolation dealloying. In this work, the temperature-dependent mechanisms of the interactions between metals and molten salts are discussed, providing insights for predicting molten salt corrosion in real-world applications.

The high volatility of the price of cobalt and the geopolitical limitations of cobalt mining have made the elimination of Co a pressing need for the automotive industry 1 . Owing to their high energy density and low-cost advantages, high-Ni and low-Co or Co-free (zero-Co) layered cathodes have become the most promising cathodes for next-generation lithium-ion batteries 2,3 . However, current high-Ni cathode materials, without exception, suffer severely from their intrinsic thermal and chemo-mechanical instabilities and insufficient cycle life. Here, by using a new compositionally complex (high-entropy) doping strategy, we successfully fabricate a high-Ni, zero-Co layered cathode that has extremely high thermal and cycling stability. Combining X-ray diffraction, transmission electron microscopy and nanotomography, we find that the cathode exhibits nearly zero volumetric change over a wide electrochemical window, resulting in greatly reduced lattice defects and local strain-induced cracks. In-situ heating experiments reveal that the thermal stability of the new cathode is significantly improved, reaching the level of the ultra-stable NMC-532. Owing to the considerably increased thermal stability and the zero volumetric change, it exhibits greatly improved capacity retention. This work, by resolving the long-standing safety and stability concerns for high-Ni, zero-Co cathode materials, offers a commercially viable cathode for safe, long-life lithium-ion batteries and a universal strategy for suppressing strain and phase transformation in intercalation electrodes., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Three-dimensional bicontinuous porous materials formed by dealloying contribute significantly to various applications including catalysis, sensor development and energy storage. This work studies a method of molten salt dealloying via real-time in situ synchrotron three-dimensional X-ray nano-tomography. Quantification of morphological parameters determined that long-range diffusion is the rate-determining step for the dealloying process. The subsequent coarsening rate was primarily surface diffusion controlled, with Rayleigh instability leading to ligament pinch-off and creating isolated bubbles in ligaments, while bulk diffusion leads to a slight densification. Chemical environments characterized by X-ray absorption near edge structure spectroscopic imaging show that molten salt dealloying prevents surface oxidation of the metal. In this work, gaining a fundamental mechanistic understanding of the molten salt dealloying process in forming porous structures provides a nontoxic, tunable dealloying technique and has important implications for molten salt corrosion processes, which is one of the major challenges in molten salt reactors and concentrated solar power plants.

High-nickel content cathode materials offer high energy density. However, the structural and surface instability may cause poor capacity retention and thermal stability of them. To circumvent this problem, nickel concentration-gradient materials have been developed to enhance high-nickel content cathode materials' thermal and cycling stability. Even though promising, the fundamental mechanism of the nickel concentration gradient's stabilization effect remains elusive because it is inseparable from nickel's valence gradient effect. To isolate nickel's valence gradient effect and understand its fundamental stabilization mechanism, we design and synthesize a LiNi 0.8 Mn 0.1 Co 0.1 O 2 material that is compositionally uniform and has a hierarchical valence gradient. The nickel valence gradient material shows superior cycling and thermal stability than the conventional one. The result suggests creating an oxidation state gradient that hides the more capacitive but less stable Ni 3+ away from the secondary particle surfaces is a viable principle towards the optimization of high-nickel content cathode materials.

Lithium-sulfur batteries are paid much attention owing to their high specific capacity and energy density. However, their practical applications are impeded by poor electrochemical performance due to the dissolved polysulfides. The concentration of soluble polysulfides has a linear relationship with the internal heat generation. The issue of heat transport inside lithium-sulfur batteries is often overlooked. Here, we designed a functional separator that not only had a high thermal conductivity of 0.65 W m -1 K -1 but also alleviated the diffusion of dissolved active materials to the lithium anode, improving the electrochemical performance and safety issue. Lithium-sulfur batteries with the functional separator have a specific capacity of 1,126.4 mAh g -1 at 0.2 C, and the specific capacity can be remained up to 893.5 mAh g -1 after 100 cycles. Pouch Cells with high sulfur loading also showed a good electrochemical performance under a lean electrolyte condition of electrolyte/sulfur (E/S) = 3 μL mg -1 ., Competing Interests: The authors declare no competing interests., (© 2020 The Author(s).)

Single-crystal cathode materials for lithium-ion batteries have attracted increasing interest in providing greater capacity retention than their polycrystalline counterparts. However, after being cycled at high voltages, these single-crystal materials exhibit severe structural instability and capacity fade. Understanding how the surface structural changes determine the performance degradation over cycling is crucial, but remains elusive. Here, we investigate the correlation of the surface structure, internal strain, and capacity deterioration by using operando X-ray spectroscopy imaging and nano-tomography. We directly observe a close correlation between surface chemistry and phase distribution from homogeneity to heterogeneity, which induces heterogeneous internal strain within the particle and the resulting structural/performance degradation during cycling. We also discover that surface chemistry can significantly enhance the cyclic performance. Our modified process effectively regulates the performance fade issue of single-crystal cathode and provides new insights for improved design of high-capacity battery materials.

Trees are used by animals, humans and machines to classify information and make decisions. Natural tree structures displayed by synapses of the brain involves potentiation and depression capable of branching and is essential for survival and learning. Demonstration of such features in synthetic matter is challenging due to the need to host a complex energy landscape capable of learning, memory and electrical interrogation. We report experimental realization of tree-like conductance states at room temperature in strongly correlated perovskite nickelates by modulating proton distribution under high speed electric pulses. This demonstration represents physical realization of ultrametric trees, a concept from number theory applied to the study of spin glasses in physics that inspired early neural network theory dating almost forty years ago. We apply the tree-like memory features in spiking neural networks to demonstrate high fidelity object recognition, and in future can open new directions for neuromorphic computing and artificial intelligence.

Understanding the growth pathway of faceted alloy nanoparticles at the atomic level is crucial to morphology control and property tuning. Yet, it remains a challenge due to complexity of the growth process and technical limits of modern characterization tools. We report a combinational use of multiple cutting-edge in situ techniques to study the growth process of octahedral Pt 3 Ni nanoparticles, which reveal the particle growth and facet formation mechanisms. Our studies confirm the formation of octahedral Pt 3 Ni initiates from Pt nuclei generation, which is followed by continuous Pt reduction that simultaneously catalyzes Ni reduction, resulting in mixed alloy formation with moderate elemental segregation. Carbon monoxide molecules serve as a facet formation modulator and induce Ni segregation to the surface, which inhibits the (111) facet growth and causes the particle shape to evolve from a spherical cluster to an octahedron as the (001) facet continues to grow.

In situ microscopy of colloidal nanocrystal growth offers a unique opportunity to acquire direct and straightforward data for assessing classical growth models. Here, we observe the growth trajectories of individual Ag nanoparticles in solution using in situ scanning transmission electron microscopy. For the first time, we provide experimental evidence of growth rates of Ag nanoparticles in the presence of Pt in solution that are significantly faster than predicted by Lifshitz-Slyozov-Wagner theory. We attribute these observed anomalous growth rates to the synergistic effects of the catalytic properties of Pt and the electron beam itself. Transiently reduced Pt atoms serve as active sites for Ag ions to grow, thereby playing a key role in controlling the growth kinetics. Electron beam illumination greatly increases the local concentration of free radicals, thereby strongly influencing particle growth rate and the resulting particle morphology. Through a systematic investigation, we demonstrate the feasibility of utilizing these synergistic effects for controlling the growth rates and particle morphologies at the nanoscale. Our findings not only expand the current scope of crystal growth theory, but may also lead to a broader scientific application of nanocrystal synthesis.

As x-ray and electron tomography is pushed further into the nanoscale, the limitations of rotation stages become more apparent, leading to challenges in the alignment of the acquired projection images. Here we present an approach for rapid post-acquisition alignment of these projections to obtain high quality three-dimensional images. Our approach is based on a joint estimation of alignment errors, and the object, using an iterative refinement procedure. With simulated data where we know the alignment error of each projection image, our approach shows a residual alignment error that is a factor of a thousand smaller, and it reaches the same error level in the reconstructed image in less than half the number of iterations. We then show its application to experimental data in x-ray and electron nanotomography.

Here, we report photocatalytic CO2 reduction with water to produce methanol using TiO2-passivated InP nanopillar photocathodes under 532 nm wavelength illumination. In addition to providing a stable photocatalytic surface, the TiO2-passivation layer provides substantial enhancement in the photoconversion efficiency through the introduction of O vacancies associated with the nonstoichiometric growth of TiO2 by atomic layer deposition. Plane wave-density functional theory (PW-DFT) calculations confirm the role of oxygen vacancies in the TiO2 surface, which serve as catalytically active sites in the CO2 reduction process. PW-DFT shows that CO2 binds stably to these oxygen vacancies and CO2 gains an electron (-0.897e) spontaneously from the TiO2 support. This calculation indicates that the O vacancies provide active sites for CO2 absorption, and no overpotential is required to form the CO2(-) intermediate. The TiO2 film increases the Faraday efficiency of methanol production by 5.7× to 4.79% under an applied potential of -0.6 V vs NHE, which is 1.3 V below the E(o)(CO2/CO2(-)) = -1.9 eV standard redox potential. Copper nanoparticles deposited on the TiO2 act as a cocatalyst and further improve the selectivity and yield of methanol production by up to 8-fold with a Faraday efficiency of 8.7%.

Engineering silicon into nanostructures has been a well-adopted strategy to improve the cyclic performance of silicon as a lithium-ion battery anode. Here, we show that the electrode performance can be further improved by alloying silicon with germanium. We have evaluated the electrode performance of SixGe1-x nanoparticles (NPs) with different compositions. Experimentally, SixGe1-x NPs with compositions approaching Si50Ge50 are found to have better cyclic retention than both Si-rich and Ge-rich NPs. During the charge/discharge process, NP merging and Si-Ge homogenization are observed. In addition, a distinct morphology difference is observed after 100 cycles, which is believed to be responsible for the different capacity retention behavior. The present study on SixGe1-x alloy NPs sheds light on the development of Si-based electrode materials for stable operation in lithium-ion batteries (e.g., through a comprehensive design of material structure and chemical composition). The investigation of composition-dependent morphology evolution in the delithiated Li-SiGe ternary alloy also significantly broadens our understanding of dealloying in complex systems, and it is complementary to the well-established understanding of dealloying behavior in binary systems (e.g., Au-Ag alloys).

In this communication, we successfully synthesized a new SnO(2) nanoarchitecture: extremely thin sheets, with minimum thicknesses of 1.5-3.0 nm. The products were prepared through a facile hydrothermal treatment using tin dichloride as the precursor. Planar or scrolled SnO(2) sheets were carefully examined by transmission electron microscopy. The assemblies of these sheets have a high BET surface area of 180.3 m(2)/g and extraordinarily large pore volume of 1.028 cm(3)/g. They also exhibit a high lithium storage capacity and excellent cyclability due to its nanometer-sized frame and breathable characteristic.