arXiv subjects

Ying Shirley Meng

Publications and source records attributed to Ying Shirley Meng.

At least 19 recordsLinked to original sources

arXiv2026

Millimeter-Scale, Atomically Controlled 2D Topological Insulators Revealed by Multimodal Spectroscopy

Quantum spin Hall insulators, or synonymously known as 2D topological insulators, are crucial 2D systems hosting topologically protected edge states. The working temperature of this topological quantum phase is dictated by the inverted bandgap. However, the previously identified large-gap 2D topological insulators are either extremely chemically unstable, or cannot be made with atomistic precision over macroscopic scales. Here, we establish two-quintuple-layer Bi2Te3 and MnBi2Te4/Bi2Te3 heterostructures as atomically controlled, millimeter-scale 2D topological insulators, enabled by precision layer-by-layer growth that yields a carpet-like morphology extending coherently over macroscopic distances. This carpet-like growth mode renders the films amenable to mechanical exfoliation and subsequent wet or dry transfer. Multimodal spectroscopies and microscopies reveal the integer-layer tuned electronic structure of (Bi2Te3)n with excellent agreement to theory. Photon-energy-dependent photoemission and time-resolved photoemission identify band inversion and band dynamics, respectively, while scanning tunneling spectroscopy resolves topological edge states, characteristic of the 2D topological insulator phase. Thickness- and photon-energy-dependent photoemission further validates MnBi2Te4/Bi2Te3 as a robust 2D topological insulator. The large inverted gaps of ~100 meV in (Bi2Te3)2 and ~150 meV in MnBi2Te4/Bi2Te3 suggest operation near ambient temperature. These results define a scalable materials platform for next-generation, low-loss quantum and energy-efficient devices.

cond-mat.mtrl-sci↗

arXiv2025

Deep Learning Assisted Prediction of Electrochemical Lithiation State in Spinel Lithium Titanium Oxide Thin Films

Machine Learning (ML) and Deep Learning (DL) based framework have evolved rapidly and generated considerable interests for predicting the properties of materials. In this work, we utilize ML-DL framework to predict the electrochemical lithiation state and associated electrical conductivity of spinel Li4Ti5O12 (LTO) thin films using Raman spectroscopy data. Raman spectroscopy, with its rapid, non-destructive, and high-resolution capabilities, is leveraged to monitor dynamic electrochemical changes in LTO films. A comprehensive dataset of 3,272 Raman spectra, representing lithiation states from 0% to 100%, was collected and preprocessed using advanced techniques including cosmic ray removal, smoothing, baseline correction, normalization, and data augmentation. Classical machine learning models such as Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Random Forest (RF) were evaluated alongside a Convolutional Neural Network (CNN). While traditional models achieved moderate to high accuracy, they struggled with generalization and noise sensitivity. In contrast, the CNN demonstrated superior performance, achieving over 99.5% accuracy and robust predictions on unseen samples. The CNN model effectively captured non-linear spectral features and showed resilience to experimental variability. This pipeline not only enables accurate lithiation state classification but also facilitates conductivity estimation, offering a scalable approach for real-time battery material characterization and potential extension to other spectroscopic datasets.

cond-mat.mtrl-sci↗

arXiv2025

Deep learning assisted high resolution microscopy image processing for phase segmentation in functional composite materials

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.

cs.CV↗

arXiv2024

Guidelines for Correlative Imaging and Analysis of Reactive Lithium Metal Battery Materials

To unlock the full potential of lithium metal batteries, a deep understanding of lithium metal reactivity and its solid electrolyte interphase is essential. Correlative imaging, combining focused ion beam and electron microscopy offers a powerful approach for multi-scale characterization. However, the extreme reactivity of lithium metal and its SEI presents challenges in investigating deposition and stripping mechanisms. In this work, we systematically evaluated the storage stability of lithium metal in glovebox before and after electrochemical deposition. We then assessed different FIB ion sources for their impact on lithium metal lamella preparation for transmission electron microscopy. Furthermore, we examined cryogenic-TEM transfer methods, optimizing for minimal contamination during sample handling. Contrary to prior assumptions, we demonstrate that high resolution imaging of pure lithium metal at room temperature is achievable using inert gas transfer with an electron dose rate exceeding 1000 e/A2/s, without significant detectable damage. In contrast, SEI components, such as Li2CO3 and LiF display much greater sensitivity to electron beams, requiring cryogenic conditions and precise dose control for nano/atomic scale imaging. We quantified electron dose limits for these SEI components to track their structural evolution under irradiation. Based on these findings, we propose a robust protocol for lithium metal sample handling - from storage to atomic-level characterization - minimizing damage and contamination. This work paves the way for more accurate and reproducible studies, accelerating the development of next-generation lithium metal batteries by ensuing the preservation of native material properties during analysis.

cond-mat.mtrl-sci↗

arXiv2024

Grain Selection Growth of Soft Metal in Electrochemical Processes

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<x<0.79) seed layer, improving the critical current density at room temperature for anode-free Li solid-state batteries through the control of grain selection growth.

cond-mat.mtrl-sci↗

arXiv2024

Preservation of Topological Surface States in Millimeter-Scale Transferred Membranes

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.

cond-mat.mtrl-sci↗

arXiv2023

Operando real-space imaging of a structural phase transformation in a high-voltage electrode

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.

cond-mat.mtrl-sci↗

arXiv2023

Elucidating Dynamic Conductive State Changes in Amorphous Lithium Lanthanum Titanate for Resistive Switching Devices

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.

physics.app-ph↗

arXiv2023

Quantitative Analysis of Sodium Metal Deposition and Interphase in Na Metal Batteries

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.

physics.app-ph↗

arXiv2023

Recycling Silicon Scrap for Spherical Si-C composite as High-Performance Lithium-ion Battery Anodes

The growth of the semiconductor and solar industry has been exponential in the last two decades due to the computing and energy demands of the world. Silicon (Si) is one of the main constituents for both sectors and, thus, is used in large quantities. As a result, a lot of Si waste is generated mainly by these two industries. For a sustainable world, the circular economy is the key; thus, the waste produced must be upcycled/recycled/reused to complete the circular chain. Herein, we show that an upcycled/recycled Si can be used with carbon as a composite anode material, with high Si content (~40 wt.%) and loading of 3-4 mAh/cm^2 for practical use in lithium-ion batteries. The unique spherical jackfruit-like structure of the Si-C composite can minimize the total lithium inventory loss compared to the conventional Si-C composite and pure Si, resulting in superior electrochemical performance. The superior electrochemical performance of Si-C composites enables the cell energy density of ~325 Wh/kg (with NMC cathode) and ~260 Wh/kg (with LFP cathode), respectively. The results demonstrate that Si-based industrial waste can be upcycled for high-performance Li-ion battery anodes through a controllable, scalable, and energy-efficient route.

cond-mat.mtrl-sci↗

arXiv2023

Elucidating the Role of Prelithiation in Si-based Anodes for Interface Stabilization

Prelithiation as a facile and effective method to compensate the lithium inventory loss in the initial cycle has progressed considerably both on anode and cathode sides. However, much less research has been devoted to the prelithiation effect on the interface stabilization for long-term cycling of Si-based anodes. An in-depth quantitative analysis of the interface that form during the prelithiation of SiO$_x$ is presented here and the results are compared with prelithiaton of Si anodes. Local structure probe combined with detailed electrochemical analysis reveals that a characteristic mosaic interface is formed on both prelithiated SiO$_x$ and Si anodes. This mosaic interface containing multiple lithium silicates phases, is fundamentally different from the solid electrolyte interface (SEI) formed without prelithiation. The ideal conductivity and mechanical properties of lithium silicates enable improved cycling stability of both prelithiated anodes. With a higher ratio of lithium silicates due to the oxygen participation, prelithiated SiO$_{1.3}$ anode improves the initial coulombic efficiency to 94% in full cell and delivers good cycling retention after hundreds cycles under lean electrolyte conditions. The insights provided in this work could be used to further optimize high Si loading based anode in future high energy density batteries.

physics.chem-ph↗

arXiv2023

Freestanding LiPON: from Fundamental Study to Uniformly Dense Li Metal Deposition Under Zero External Pressure

Lithium phosphorus oxynitride (LiPON) is a well-known amorphous thin film solid electrolyte that has been extensively studied in the last three decades. Despite the promises to pair with Li metal anode and various cathode materials, the presence of rigid substrate and LiPONs unique amorphous, air-sensitive nature set limitations to comprehensively understand its intrinsic properties for future development and applications. This work demonstrates a methodology to synthesize LiPON in a freestanding form that exhibits remarkable flexibility and a Young s modulus of ~33 GPa. Solid-state nuclear magnetic resonance (ss-NMR) and differential scanning calorimetry (DSC) results with unprecedented high signal-to-noise ratio could be obtained with such freestanding LiPON (FS-LiPON), revealing the Li-LiPON interface bonding environments quantitatively and a well-defined glass transition temperature for LiPON. Combining interfacial stress and a seeding layer, FS-LiPON demonstrates a uniform and fully dense Li metal deposition without the aid of external pressure. Such a FS-LiPON film offers new opportunities for fundamental study of LiPON material and associated interfaces, and provides perspectives for interface engineering in bulk solid-state battery.

cond-mat.mtrl-sci↗

arXiv2023

Key Parameters in Determining the Reactivity of Lithium Metal Battery

Lithium (Li) metal anodes are essential for developing next-generation high-energy-density batteries. Numerous concerns on the potential safety hazards of the Li metal have been brought up before its massive application in commercialized battery packs. However, few investigations have been performed to systematically evaluate the reactivity of Li metal anode in full cell level. Here, differential scanning calorimetry (DSC) with in situ Fourier-transform infrared spectroscopy (FTIR) are used to quantitatively investigate the Li metal reactivity. Lithiated graphite (Li-Gr) and lithiated silicon (Li-Si) are also studied as the comparison samples. The reactivity of the plated Li when coupled with different electrolyte composition, morphology, and atmosphere is systematically studied. More importantly, the reactivity of Li metal full cell with different cathode materials (NMC622, LFP and LNMO) has been compared. It was found that all cell components, including electrolyte composition, Li morphology, the control of inactive Li accumulation and cathode stability, are essential in controlling the reactivity of the plated Li. After optimizing these conditions, the Li metal full cell shows no significant thermal reaction up to 400C. This work identifies the key parameters in controlling the reactivity of the plated Li and may facilitate lithium metal battery design and manufacturing in the coming future.

physics.chem-ph↗

arXiv2022

Synthetic control of structure and conduction properties in Na-Y-Zr-Cl solid electrolytes

In the development of low cost, sustainable, and energy-dense batteries, chloride-based compounds are promising catholyte materials for solid-state batteries owing to their high Na-ion conductivities and oxidative stabilities. The ability to further improve Na-ion conduction, however, requires an understanding of the impact of long-range and local structural features on transport in these systems. In this study, we leverage different synthesis methods to control polymorphism and cation disorder in Na-Y-Zr-Cl solid electrolytes and interrogate the impact on Na-ion conduction. We demonstrate the existence of a more conductive P2$_1$/n polymorph of Na$_2$ZrCl$_6$ formed upon ball milling. In Na$_3$YCl$_6$, the R$\bar{3}$ polymorph is shown to be more conductive than its P2$_1$/n counterpart owing to the presence of intrinsic vacancies and disorder on the Y sublattice. Transition metal ordering in the Na$_{2.25}$Y$_{0.25}$Zr$_{0.75}$Cl$_6$ composition strongly impacts Na-ion transport, where a greater mixing of Y$^{3+}$ and Zr$^{4+}$ on the transition metal sublattice facilitates ion migration through partial activation of Cl rotations at relevant temperatures. Overall, Na-ion transport sensitively depends on the phases and transition metal distributions stabilized during synthesis. These results are likely generalizable to other halide compositions and indicate that achieving control over the synthetic protocol and resultant structure is key in the pursuit of improved catholytes for high voltage solid-state sodium-ion batteries.

cond-mat.mtrl-sci↗

arXiv2022

Suppressing chemical corrosions of lithium metal anodes

The lithium (Li) metal anode is essential for next generation high energy density rechargeable Li metal batteries. Although extensive studies have been performed to prolong the cycle life of Li metal batteries, the calendar life, which associates with chemical corrosion of Li metal in liquid electrolytes, has not been quantitatively understood. Here, by combing the Titration Gas Chromatography (TGC) method and Cryogenic Focused Ion Beam (Cryo-FIB), we established a quantitative relationship between the chemical corrosion rate and electrochemically deposited Li morphology in various liquid electrolyte systems. We identified that the corrosion rate is dominated by the porosity of the deposited Li. The larger the porosity of deposited Li has, the faster the corrosion rate will be. We further proposed strategies to mitigate the chemical corrosion on Li thus to extend the calendar life of Li metal batteries. By strictly controlling the stacking pressure during Li plating, Li deposits with ultra-low porosity can be achieved, suppressing the corrosion rate to 0.08% per day compared with 1.71% per day of the high-porosity Li.

cond-mat.mtrl-sci↗

arXiv2022

Methods pressure control apparatus for lithium metal battery

Lithium (Li) metal anodes are essential for developing next-generation high-energy-density batteries. However, Li dendrite/whisker formation caused short-circuiting issue and short cycle life have prevented lithium metal from being viably used in rechargeable batteries. Numerous works have been done to study how to regulate the Li growth in electrochemical cycling by using external stacking forces. While it is widely agreed that stack pressure positively affects the lithium plating/stripping process, the optimized pressure range provided by different works varies greatly because of the difference in the pressure control setup. In this work, a pressure control apparatus is designed for Li metal batteries with liquid and solid-state electrolytes (SSE). With considerations of minimizing cell to cell variation, a reusable split cell and pressure load cell are made for testing electrochemical cells with high precision pressure control. The capability of the designed setup is demonstrated by studying the pressure effect on the Li plating/stripping process.

cond-mat.mtrl-sci↗

arXiv2022

Unraveling the stable cathode electrolyte interface in all solid-state thin-film battery operating at 5V

Spinel-type LiNi0.5Mn1.5O4 (LNMO) is one of the most promising 5 V-class cathode materials for Li-ion batteries that can achieve high energy density and low production costs. However, in liquid electrolyte cells, the high voltage causes continuous cell degradation through the oxidative decomposition of carbonate-based liquid electrolytes. In contrast, some solid-state electrolytes have a wide electrochemical stability range and can withstand the required oxidative potential. In this work, a thin-film battery consisting of a LNMO cathode with a solid lithium phosphorus oxynitride (LiPON) electrolyte is tested and their interface before and after cycling is characterized. With Li metal as the anode, this system can deliver stable performance for 600 cycles with an average Coulombic efficiency > 99%. Neutron depth profiling indicates a slight overlithiated layer at the interface prior to cycling; a result that is consistent with the excess charge capacity measured during the first cycle. Cryogenic electron microscopy further reveals intimate contact between LNMO and LiPON without noticeable structure and chemical composition evolution after extended cycling, demonstrating the superior stability of LiPON against a high voltage cathode. Consequently, we propose design guidelines for interface engineering that could accelerate the commercialization of a high voltage cell with solid or liquid electrolytes.

cond-mat.mtrl-sci↗

arXiv2021

Bridging Nano and Micro-scale X-ray Tomography for Battery Research by Leveraging Artificial Intelligence

X-ray Computed Tomography (X-ray CT) is a well-known non-destructive imaging technique where contrast originates from the materials' absorption coefficients. Novel battery characterization studies on increasingly challenging samples have been enabled by the rapid development of both synchrotron and laboratory-scale imaging systems as well as innovative analysis techniques. Furthermore, the recent development of laboratory nano-scale CT (NanoCT) systems has pushed the limits of battery material imaging towards voxel sizes previously achievable only using synchrotron facilities. Such systems are now able to reach spatial resolutions down to 50 nm. Given the non-destructive nature of CT, in-situ and operando studies have emerged as powerful methods to quantify morphological parameters, such as tortuosity factor, porosity, surface area, and volume expansion during battery operation or cycling. Combined with powerful Artificial Intelligence (AI)/Machine Learning (ML) analysis techniques, extracted 3D tomograms and battery-specific morphological parameters enable the development of predictive physics-based models that can provide valuable insights for battery engineering. These models can predict the impact of the electrode microstructure on cell performances or analyze the influence of material heterogeneities on electrochemical responses. In this work, we review the increasing role of X-ray CT experimentation in the battery field, discuss the incorporation of AI/ML in analysis, and provide a perspective on how the combination of multi-scale CT imaging techniques can expand the development of predictive multiscale battery behavioral models.

cond-mat.mtrl-sci↗