RESEARCH ON SPUTTERING PHENOMENA, SURFACE STABILITY AND VOLTAGE BREAKDOWN FOR ALKALI-COATED REFRACTORY ELECTRODES.
Sputtering, surface stability and voltage breakdown for alkali-coated refractory electrodes
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Sputtering, surface stability and voltage breakdown for alkali-coated refractory electrodes
The anode and cathode of a 30-kW class arcjet engine have been sectioned and analyzed. This arcjet was operated for a total time of 573 hours at power levels between 25 and 30 kW with ammonia at flow rates of 0.25 and 0.27 gm/s. The accumulated run time was sufficient to clearly establish erosion patterns and their causes. The type of electron emission from various parts of the cathode surface was made clear by Scanning Electron Microscope analysis. A Scanning Electron Microscope was used to study recrystallization on the hot anode surface. These electrodes were made of 2 percent thoriated tungsten and the surface thorium content and gradient perpendicular to the surfaces was determined by quantitative microprobe analysis. The results of this material analysis on the electrodes and recommendations for improving electrode operational life time are presented.
The anode and cathode of a 30 kW class arcjet engine were sectioned and analyzed. This arcjet was operated for a total time of 573 hr at power levels between 25 and 30 kW with ammonia at flow rates of 0.25 and 0.27 gm/s. The accumulated run time was sufficient to clearly establish erosion patterns and their causes. The type of electron emission from various parts of the cathode surface was made clear by scanning electron microscope analysis. A scanning electron microscope was used to study recrystallization on the hot anode surface. These electrodes were made of 2 percent thoriated tungsten and the surface thorium content and gradient perpendicular to the surfaces was determined by quantitative microprobe analysis. The results of this material analysis on the electrodes and recommendations for improving electrode operational life time are presented.
The practical application of high-capacity Li-rich cathode materials is hindered by capacity fading and voltage decay. The capacity fading and voltage decay could be effectively overcome by using water-soluble guar gum (GG) binder instead of traditional polyvinylidene fluoride (PVDF). However, the specific role of the GG binder is not clear yet, though the GG binder can significantly improve the electrochemical performance of Li-rich cathode. To understand the effect of GG binder on the morphology, microstructure of electrode and electrode/electrolyte interfaces, ex-situ scanning electron microscope (SEM), transmission electron microscope (TEM), X-ray adsorption near edge spectroscopy (XANES), in-situ electrochemical impedance spectroscopy (EIS) were applied to comparatively study the charge-discharge processes of Li-rich Li 1.2 Ni 0.2 Mn 0.6 O 2 cathode when using GG and PVDF as binders. The results indicate that the GG binder can prevent electrode crack and active material loss, ascribing to the strong mechanical adhesion of GG binder with active material particles and current collector. It has found that the GG binder can also induce the formation of a uniform layer on Li 1.2 Ni 0.2 Mn 0.6 O 2 particles’ surface. As a consequence, both the electrolyte decomposition and the electrode corrosion were significantly inhibited. The strong chelation between Mn 2+ and polar OH group restrain Mn ion dissolution, which contributes to surface structural transformation mitigation. Here, our study reveals the role of water-soluble GG binder in reducing capacity fading and voltage decay of Li-rich material and is of great importance in design functional binders for high-performance Li-rich electrodes.
Understanding the formation of the solid-electrolyte interphase (SEI) in lithium-ion batteries (LIBs) is an ongoing area of research due to its high degree of complexity and the difficulties encountered by experimental studies. Herein, we investigate the initial stage of SEI growth, the reduction reaction of ethylene carbonate (EC), from both a thermodynamic and kinetic approach with theory and molecular simulation. We employed both the potential distribution theorem (PDT) and the SMD implicit solvent model to EC solvation for the estimation of reduction potentials of Li$^+$, EC, and Li$^+$-solvating EC (s-EC), as well as reduction rate constants of EC and s-EC. We find that solvation effects greatly influence these quantities of interest, particularly the Li$^+$/Li reference electrode potential in EC solvent. Further, we also compute the inner- and outer-sphere reorganization energies for both EC and s-EC at the interface of liquid EC and a hydroxyl-terminated graphite surface, where total reorganization energies are predicted to be 76.6 and 88.9 kcal/mol, respectively. With the computed reorganization energies, we estimate reduction rate constants across a range of overpotentials and show that EC has a larger electron transfer rate constant than s-EC at equilibrium, despite s-EC being more thermodynamically favorable. Furthermore, this manuscript demonstrates how ion solvation effects largely govern the prediction of reduction potentials and electron transfer rate constants at the electrode-electrolyte interface.
Conversion-type cathodes, such as sulfur, FeS 2 , and FeF 3 , offer high theoretical capacities in solid-state lithium batteries but are hindered by substantial volume changes during cycling, leading to interfacial contact loss, crack formation, and microstructural degradation. Here, we investigate the relationships between electrochemical, mechanical, and structural evolution in solid-state electrode composites with these three active materials. Using real-time stack-pressure monitoring, synchrotron X-ray absorption spectroscopy, and electrokinetic modeling, we elucidate how stress evolution is linked to reversible and irreversible redox reactions. Nonlinear stack pressure evolution in cells with sulfur, FeS 2 , and FeF 3 electrode composites is found to arise from material-specific volume changes, the balance of volume change between the working and counter electrode, and the formation of distinct reaction intermediates. The three materials exhibit distinct stack pressure evolution, which is closely related to the different reaction processes in the materials, as demonstrated with X-ray absorption spectroscopy measurements. Through mesoscale modeling, we relate the experimental measurements to species evolution at the particle scale and track the dynamic coexistence of intermediate phases. Our findings highlight the importance of designing for volume changes of a given active material in solid-state battery systems.
La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3-δ (LSCF) is a common cathode material for intermediate temperature solid oxide fuel cells due to its excellent oxygen reduction reaction catalytic activity. However, the Cr-poisoning effect is a severe issue causing its electrochemical performance degrada-tion. To develop a LSCF-based cathode with excellent Cr-tolerance, LaCrO 3 -coated LSCF core-shell structured (LCr@LSCF) cathode was prepared via solution infiltration method. After coated by LCr shell, the long-term stability and Cr-tolerance were obviously improved, at the price of sacrificing some electrochemical performance. As a result, the development of LCr@LSCF cathode with eye-catching Cr-tolerance is of great significance to the commercialization of LSCF.
The major cause for capacity fading of silicon nanoparticle (SiNP)-based electrodes is the immense pressure applied toward the conductive networks during the charge/discharge process. While numerous efforts have been devoted to investigating different types of polymer binders, the rational design of an adhesive binder with pressure sensitivity has rarely been reported. Herein, a series of pressure-sensitive adhesives (PSAs) synthesized via copolymerization of 2-ethylhexyl acrylate (2-EHA) and acrylic acid (AA) are evaluated as polymer binders for SiNP-based electrodes. The balance between the density of interaction groups and viscoelastic properties is systematically investigated for efficient binding performance. The SiNP-based electrode using PSA with 20 mol % of 2-EHA (Si-PSA-20%) exhibits excellent electrochemical performance, achieving a capacity retention of 83% at the 100th cycle compared with 54% for Si-PAA after activation. Si-PSA-20% also delivers a superior cycling performance at a high current density (1731 mAh g –1 after 350 cycles vs 719 mAh g –1 after 150 cycles for Si-PAA, 1.8 A g –1 ) and at high mass loading of active materials (capacity retention of 74 vs 38% for Si-PAA after 100 cycles, SiNP content ~1.2 mg cm –2 ). Atomic force microscopy (AFM), peel tests, and Car–Parrinello molecular dynamics (CPMD) simulations are employed to understand their binder performance. The novel design and systematical investigation of PSAs as binders will definitely be appealing for not only the Si electrode but also for other high-energy-density electrode materials.
Understanding ion intercalation at electrode–electrolyte interfaces is key to the development of energy storage and water desalination. Here, we investigate Li + kinetics at a prototypical interface between graphite anodes and an organic electrolyte, and we elucidate key factors that determine ion transport, using first-principles methodology coupling ab initio molecular dynamics simulations with a solvation model. We show that surface chemical composition significantly influences the kinetics of ion intercalation from the liquid into graphite. We find that this is partly related to the ion desolvation process, which varies notably for different graphite surface chemical terminations. In addition, interfacial polarization is found to play an important role in determining energy barriers for ion transfer. We also discuss the impact of electrode potentials, which is often neglected in conventional first-principles calculations despite being a key factor in device configurations. Our study provides insights into the coupling of electronic and ionic effects of interfacial chemistry on ion transport at complex electrode–electrolyte interfaces.
Efforts in oxygen evolution catalyst development have significantly increased and often use rotating disk electrode half-cells to evaluate intrinsic kinetics and screen materials for short-term durability. Standardizing rotating disk electrode test protocols is critical to experimental accuracy, to realistically assess their potential impact at a device level and to assess how different catalyst approaches and concepts are prioritized. The goal of this study is to provide standardized test protocols and suggest best practices to help reduce variability in ex situ materials characterization in the broader community. Specifically, these protocols focus on test cleanliness and materials choices, including how electrodes are prepared and tested, and the impact on activity observations.
Electrification of the transportation sector relies on radical re-imagining of energy storage technologies to provide affordable, high energy density, durable and safe systems. Next generation energy storage systems will need to leverage high energy density anodes and high voltage cathodes to achieve the required performance metrics (longer vehicle range, long life, production costs, safety). Solid-state batteries (SSBs) are promising materials technology for achieving these metrics by enabling these electrode systems due to the underlying material properties of the solid electrolyte (viz. mechanical strength, electrochemical stability, ionic conductivity). Electro-chemo-mechanical degradation in SSBs detrimentally impact the Coulombic efficiencies, capacity retention, durability and safety in SSBs restricting their practical implementation. Solid|solid interfaces in SSBs are hot-spots of dynamics that contribute to the degradation of SSBs. Characterizing and understanding the processes at the solid|solid interfaces in SSBs is crucial towards designing of resilient, durable, high energy density SSBs. This work provides a comprehensive and critical summary of the SSB characterization with a focus on in situ and operando studies. Additionally, perspectives on experimental design, emerging characterization techniques and data analysis methods are provided. Furthermore, this work provides a thorough analysis of current status of SSB characterization as well as highlights important avenues for future work.
A flexible, porous battery separator includes a coating applied to a porous, flexible substrate. The coating comprises: (1) a thermoplastic rubber-based resin which is insoluble and unreactive in the alkaline electrolyte, (2) a polar organic plasticizer which is reactive with the alkaline electrolyte to produce a reaction product which contains a hydroxyl group and/or a carboxylic acid group, and (3) a mixture of polar particulate filler materials which are unreactive with the electrode. The mixture comprises at least one first filler material having a surface area of greater than 25 sq meters/gram, at last one second filler material having a surface area of 10 to 25 sq meters/gram. The volume of the mixture of filler materials is less than 45% of the total volume of the fillers and the binder. The filler surface area per gram of binder is about 20 to 60 sq meters/gram, and the amount of plasticizer is sufficient to coat each filler particle.
A method to determine the potential of zero charge of an unpowdered semiconductor material is presented. The semiconductor material is used as the working electrode of a standard three electrode photoelectrochemical cell. The onset potential of the semiconductor material is measured at several different cell temperatures. The slope of the graph of onset potential versus temperature is used to compute the potential of zero charge.
High capacity silicon based anode active materials are described for lithium ion batteries. These materials are shown to be effective in combination with high capacity lithium rich cathode active materials. Supplemental lithium is shown to improve the cycling performance and reduce irreversible capacity loss for at least certain silicon based active materials. In particular silicon based active materials can be formed in composites with electrically conductive coatings, such as pyrolytic carbon coatings or metal coatings, and composites can also be formed with other electrically conductive carbon components, such as carbon nanofibers and carbon nanoparticles. Additional alloys with silicon are explored.
Rapid, in-situ Li-ion battery state-of-health (SOH) quantification is challenging. Li-ion battery aging can vary significantly with chemistry, operating conditions, cycling demands, electrode design, and operation history. As a cell ages, optimal and safe operating conditions need to be adapted to account for battery degradation by tracking critical aging modes such as loss-of-lithium-inventory (LLI), loss-of-active-material (LAM) in either electrode, and/or impedance rise. This manuscript describes a framework for identifying battery aging modes in-operando using fast-rate voltage charge/discharge responses. The framework uses a physically based Li-ion battery model to produce synthetic high-rate responses at aged states. The aging model is calibrated against experimental data from cells with different electrode loadings and cycled under a variety of fast-charging conditions (1 h, 15 min, 10 min, and 7 min charging). The synthetically generated high-rate responses at aged states are then used to train a deep-learning model to identify real cell state-of-health from fast charge/discharge battery voltage responses. The synthetically trained deep-learning model performance is validated by comparing to standard incremental capacity analysis and half-cell measurements. Finally, the framework demonstrates the benefits of using high-rate physics-based models to generate synthetic data for training deep-learning models.
Conventionally, rechargeable lithium cells employ a pure lithium anode. To overcome problems associated with the pure lithium electrode, it has been proposed to replace the conventional electrode with an alternative material having a greater stability with respect to the cell electrolytes. For this reason, several graphitic and coke based carbonaceous materials were evaluated as candidate anode materials...In this paper, we summarize the results of the studies on Li-ion cell development.
Li-ion Batteries (LIB), one of the most efficient energy storage devices, are used extensively in many industrial applications. These batteries consist of electrodes that are put together with heterogeneous material compositions. Imaging data of these battery electrodes obtained from X-ray tomography can explain the distribution of material constituents and allow reconstructions to study electron transport pathways. Such reconstructions of material constituents help quantify various associated properties of electrodes (e.g., volume-specific surface area, porosity) which determine the performance of batteries. These images often suffer from low image contrast between multiple material constituents, hence making it difficult for humans to distinguish and characterize these constituents through visual inspection. A minor error in detecting distributions of the material constituents can lead to magnified errors in the calculated parameters of material properties (e.g., porosity). We present MatPhase, a novel hierarchical curriculum learning technique to address the complex task of estimating material constituent distribution in battery electrodes. MatPhase comprises three modules: (i) an uncertainty-aware global model trained to yield inferences conditioned upon global knowledge of material distribution, (ii) a local model to capture relatively more fine-grained (local) distributional signals, (iii) an aggregator model to appropriately fuse the local and global effects towards obtaining the final distribution. On average, MatPhase improves prediction up to 8.5% relative to other sophisticated modeling pipelines and state-of-the-arts (SOTA) object detection models employed in the performance comparison.
The rapid rise of AI has exposed significant limitations in conventional Von Neumann computing architecture, particularly in regard to speed and energy efficiency. To address these challenges, researchers are exploring a brain-inspired neuromorphic architecture that mimics biological neural networks, enabling massive parallel processing with reduced power consumption for complex AI computational demands. Recent interest has focused on utilizing battery electrodes and solid electrolyte materials for their resistive switching properties in developing a neuromorphic architecture. These properties are precisely tuned through local- and bulk-level chemical composition modifications via voltage bias stimuli. In this study, we demonstrate fabricating a three-terminal lithium-ion electrochemical transistor based on lithium titanium oxide (Li 4 Ti 5 O 12 ), a popular lithium-ion battery anode material. We deposited and characterized LTO thin films using RF sputtering, demonstrating a 6 orders of magnitude increase in electronic conductivity upon lithiation, with conductivity plateauing after 20% lithiation. Density functional theory calculations revealed transformation from the insulating to conducting state, supported by experimental characterization through X-Ray Photoelectron Spectroscopy (XPS) and Direct Current (DC) polarization analyses. The fabricated transistor consisted of LTO as the channel layer, gold as source/drain terminals, lithium phosphorus oxynitride (LiPON) as the lithium-ion conductor, and copper as the gate terminal. The device exhibited clear hysteresis in transfer characteristics due to lithium insertion/extraction processes. Long-term potentiation (LTP) and long-term depression (LTD) measurements showed an asymmetric ratio of 1.425 and maximum/minimum conductance ratio of 7.83. When implemented in a deep neural network (DNN) for MNIST handwritten digit recognition, the device achieved 92.03% accuracy over 20 training epochs. Detailed transport mechanism analysis revealed the crucial role of oxygen vacancies and interface effects in device operation. Our preliminary findings establish LTO-based lithium-ion electrochemical transistors as promising candidates for energy-efficient neuromorphic computing applications, offering potential solutions to traditional Von Neumann architecture limitations.