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Soft metals like lithium and sodium play a critical role in battery technology owing to their high energy density. Texture formation by grain selection growth of soft metals during electrochemical processes is a crucial factor affecting power and safety. Developing a framework to understand and control grain growth is a multifaceted challenge. Here, a general thermodynamic theory and phase-field model are formulated to study grain selection growth of soft metals. Our study focuses on the interplay between surface energy and atomic mobility-related intrinsic strain energy in grain selection growth. Differences in grain selection growth arise from the anisotropy in surface energy and diffusion barrier of soft metal atoms. Our findings highlight the kinetic limitations of solid-state Li metal batteries, which originate from load stress-induced surface energy anisotropy. These insights lead to the development of an amorphous LixSi1-x (0.50

In the domain of battery research, the processing of high-resolution microscopy images is a challenging task, as it involves dealing with complex images and requires a prior understanding of the components involved. The utilization of deep learning methodologies for image analysis has attracted considerable interest in recent years, with multiple investigations employing such techniques for image segmentation and analysis within the realm of battery research. However, the automated analysis of high-resolution microscopy images for detecting phases and components in composite materials is still an underexplored area. This work proposes a novel workflow for detecting components and phase segmentation from raw high resolution transmission electron microscopy (TEM) images using a trained U-Net segmentation model. The developed model can expedite the detection of components and phase segmentation, diminishing the temporal and cognitive demands associated with scrutinizing an extensive array of TEM images, thereby mitigating the potential for human errors. This approach presents a novel and efficient image analysis approach with broad applicability beyond the battery field and holds potential for application in other related domains characterized by phase and composition distribution, such as alloy production.

Multi-photon hyperentangement is of fundamental importance in optical quantum information processing. Existing theory and experiment producing multi-photon hyperentangled states have until now relied on the outcome post-selection, a procedure where only the measurement results corresponding to the desired state are considered. Such approach severely limits the usefulness of the resulting hyperentangled states. We present the protocols of direct production of three- and four-photon hyperentanglement and extend the approach to an arbitrary number of photons through a straightforward cascade of spontaneous parametric down-conversion (SPDC) sources. The generated multi-photon hyperentangled states are encoded in polarization-spatial modes and polarization-time bin degrees of freedom, respectively. Numerical calculation shows that if the average photon number $\mu$ is set to 1, the down conversion efficiency is $7.6*10^{-6}$ and the repetition frequency of the laser is $10^9$ Hz, the number of the generation of three-photon and four-photon hyperentanglement after cascading can reach about $5.78*10^{-2}$ and $4.44*10^{-7}$ pairs per second, respectively. By eliminating the constraints of outcome post-selection, our protocols may represent important progresses for multi-photon hyperentangement generation and providing a pivotal role in future multi-party and high-capacity communication networks.

Ultrathin topological insulator membranes are building blocks of exotic quantum matter. However, traditional epitaxy of these materials does not facilitate stacking in arbitrary orders, while mechanical exfoliation from bulk crystals is also challenging due to the non-negligible interlayer coupling therein. Here we liberate millimeter-scale films of topological insulator Bi$_2$Se$_3$, grown by molecular beam epitaxy, down to 3 quintuple layers. We characterize the preservation of the topological surface states and quantum well states in transferred Bi$_{2}$Se$_{3}$ films using angle-resolved photoemission spectroscopy. Leveraging the photon-energy-dependent surface sensitivity, the photoemission spectra taken with $6$ eV and $21.2$ eV photons reveal a transfer-induced migration of the topological surface states from the top to the inner layers. By establishing clear electronic structures of the transferred films and unveiling the wavefunction relocation of the topological surface states, our work paves the physics foundation crucial for the future fabrication of artificially stacked topological materials with single-layer precision., Comment: 4 figures

La$_{3}$Ni$_{2}$O$_{7}$ has garnered widespread interest recently due to its high-temperature superconductivity under pressure, accompanied by charge density wave (CDW) ordering and metal-insulator (MI) transitions in the phase diagram. Here, we reveal with comprehensive calculations that La$_{3}$Ni$_{2}$O$_{7}$ possesses an antiferromagnetic ground state under both low and high pressures, with the strong Fermi surface nesting contributed by the flat band that leads to phonon softening and electronic instabilities. Several stable CDW orders with oxygen octahedral distortions are identified, which can trigger the MI transitions. The estimated CDW transition temperature ($\approx$120 K) at ambient pressure agrees nicely with experimental results. In the presence of apical oxygen vacancies, we identify two different phases, say, half distortion and full distortion phases, respectively, and their competition can lead to a pressure-induced MI transition, in good agreement with experimental observations. In addition, we find that the electron-phonon coupling is too small to contribute to superconductivity. These results appear to indicate an unconventional superconducting pairing mechanism mediated by antiferromagnetic fluctuations. A phase diagram that is consistent with the experimental results is given. The present results not only explain the origins of experimentally observed CDW and MI transitions, but also provide insight for deeply understanding the properties like superconductivity, CDW and the role of oxygen vacancies in pressurized La$_{3}$Ni$_{2}$O$_{7}$.

Discontinuous solid-solid phase transformations play a pivotal role in determining properties of rechargeable battery electrodes. By leveraging operando Bragg Coherent Diffractive Imaging (BCDI), we investigate the discontinuous phase transformation in LixNi0.5Mn1.5O4 within a fully operational battery. Throughout Li-intercalation, we directly observe the nucleation and growth of the Li-rich phase within the initially charged Li-poor phase in a 500 nm particle. Supported by the microelasticity model, the operando imaging unveils an evolution from a curved coherent to planar semi-coherent interface driven by dislocation dynamics. We hypothesize these dislocations exhibit a glissile motion that facilitates interface migration without diffusion of host ions, leaving the particle defect-free post-transformation. Our data indicates negligible kinetic limitations impacting the transformation kinetics, even at discharge rates as fast as C/2. This study underscores BCDI's capability to provide operando insights into nanoscale phase transformations, offering valuable guidance for electrochemical materials design and optimization.

As global energy demands escalate, and the use of non-renewable resources become untenable, renewable resources and electric vehicles require far better batteries to stabilize the new energy landscape. To maximize battery performance and lifetime, understanding and monitoring the fundamental mechanisms that govern their operation throughout their life cycle is crucial. Unfortunately, from the moment batteries are sealed until their end-of-life, they remain a black box, and our current knowledge of a commercial battery s health status is limited to current (I), voltage (V), temperature (T), and impedance (R) measurements, at the cell or even module level during use. Electrochemical models work best when the battery is new, and as state reckoning drifts leading to an over-reliance on insufficient data to establish conservative safety margins resulting in the systematic under-utilization of cells and batteries. While the field of operando characterization is not new, the emergence of techniques capable of tracking commercial battery properties under realistic conditions has unlocked a trove of chemical, thermal, and mechanical data that has the potential to revolutionize the development and utilization strategies of both new and used lithium-ion devices. In this review, we examine the latest advances in non-destructive operando characterization techniques, including electrical sensors, optical fibers, acoustic transducers, X-ray-based imaging and thermal imaging (IR camera or calorimetry), and their potential to improve our comprehension of degradation mechanisms, reduce time and cost, and enhance battery performance throughout its life cycle.

Exploration of novel resistive switching materials attracts attention to replace conventional Si-based transistors and to achieve neuromorphic computing that can surpass the limit of the current Von-Neumann computing for the time of Internet of Things (IoT). Materials priorly used to serve in batteries have demonstrated metal-insulator transitions upon an electrical biasing due to resulting compositional change. This property is desirable for future resistive switching devices. Amorphous lithium lanthanum titanate (a-LLTO) was originally developed as a solid-state electrolyte with relatively high lithium ionic conductivity and low electronic conductivity among oxide-type solid electrolytes. However, it has been suggested that electric conductivity of a-LLTO changes depending on oxygen content. In this work, the investigation of switching behavior of a-LLTO was conducted by employing a range of voltage sweep techniques, ultimately establishing a stable and optimal operating condition within the voltage window of -3.5 V to 3.5 V. This voltage range effectively balances the desirable trait of a substantial resistance change by three orders of magnitude with the imperative avoidance of LLTO decomposition. This switching behavior is also confirmed at nanodevice of Ni/LLTO/Ni through in-situ biasing inside focused-ion beam/scanning electron microscope (FIB-SEM). Experiment and computation with different LLTO composition shows that LLTO has two distinct conductivity states due to Ti reduction. The distribution of these two states is discussed using simplified binary model, implying the conductive filament growth during low resistance state. Consequently, our study deepens understanding of LLTO electronic properties and encourages the interdisciplinary application of battery materials for resistive switching devices.

Sodium-ion batteries exhibit significant promise as a viable alternative to current lithium-ion technologies owing to their sustainability, low cost per energy density, reliability, and safety. Despite recent advancements in cathode materials for this category of energy storage systems, the primary challenge in realizing practical applications of sodium-ion systems is the absence of an anode system with high energy density and durability. Although Na metal is the ultimate anode that can facilitate high-energy sodium-ion batteries, its use remains limited due to safety concerns and the high-capacity loss associated with the high reactivity of Na metal. In this study, titration gas chromatography is employed to accurately quantify the sodium inventory loss in ether- and carbonate-based electrolytes. Uniaxial pressure is developed as a powerful tool to control the deposition of sodium metal with dense morphology, thereby enabling high initial coulombic efficiencies. In ether-based electrolytes, the Na metal surface exhibits the presence of a uniform solid electrolyte interphase layer, primarily characterized by favorable inorganic chemical components with close-packed structures. The full cell, utilizing a controlled electroplated sodium metal in ether-based electrolyte, provides capacity retention of 91.84% after 500 cycles at 2C current rate and delivers 86 mAh/g discharge capacity at 45C current rate, suggesting the potential to enable Na metal in the next generation of sodium-ion technologies with specifications close to practical requirements.