The growing market for electric vehicles and portable electronics requires the reliability assessment of Li-ion batteries, especially in terms of nonlinear capacity degradation. For this purpose, a flexible health prognostic approach for nonlinear battery aging is proposed by leveraging temporal transfer learning. In contrast to existing prediction methods, our approach provides an unsupervised segmentation approach that characterizes the temporal distribution of nonlinear aging trajectories, which is proven to be associated with the loss of active materials. Subsequently, the temporal domain features are aligned with adaptively adjusted weight alongside the capacity decay trend, followed by the domain loss calculation and nonlinear aging prediction. Three battery datasets based on different cell types and conditions undertake the validation of model adaptability. The experiments demonstrate outstanding performance in accurate health prognostic when collaboratively learning

P2-type cobalt-free MnNi-based layered oxides are promising cathode materials for sodium-ion batteries (SIBs) due to their high reversible capacity and well chemical stability. However, the phase transformations during repeated (dis)charge steps lead to rapid capacity decay and deteriorated Na+ diffusion kinetics. Moreover, the electrode manufacturing based on polyvinylidene difluoride (PVDF) binder system has been reported with severely defluorination issue as well as the energy intensive and expensive process due to the use of toxic and volatile N-methyl-2-pyrrolidone (NMP) solvent. It calls for designing a sustainable, better performing, and cost-effective binder for positive electrode manufacturing. In this work, we investigated inorganic sodium metasilicate (SMS) as a viable binder in conjunction with P2-Na0.67Mn0.55Ni0.25Fe0.1Ti0.1O2 (NMNFT) cathode material for SIBs. The NMNFT-SMS electrode delivered a superior electrochemical performance compared to carboxy methylcellulose (CMC) and PVDF based electrodes with a reversible capacity of ~161 mAh/g and retaining ~83 % after 200 cycles. Lower cell impedance and faster Na+ diffusion was also observed in this binder system. Meanwhile, with the assistance of TEM technique, SMS is suggested to form a uniform and stable nanoscale layer over the cathode particle surface, protecting the particle from exfoliation/cracking due to electrolyte attack. It effectively maintained the electrode connectivity and suppressed early phase transitions during cycling as confirmed by operando XRD study. With these findings, SMS binder can be proposed as a powerful multifunctional binder to enable positive electrode manufacturing of SIBs and to overall reduce battery manufacturing costs.

Moran Balaish, Helge S. Stein, Arghya Bhowmik, and John M. Gregoire introduce the Journal of Materials Chemistry A themed collection on advancing energy materials through high throughput experiments and computation.

The discovery and optimization of new materials for energy storage are essential for a sustainable future. High-throughput experimentation (HTE) using a scanning droplet cell (SDC) is suitable for the rapid screening of prospective material candidates and effective variation of investigated parameters over a millimeter-scale area. Herein, we explore the transition and challenges for SDC electrochemistry from aqueous toward aprotic electrolytes and address pitfalls related to reproducibility in such high-throughput systems. Specifically, we explore whether reproducibilities comparable to those for millimeter half-cells are achievable on the millimeter half-cell level than for full cells. To study reproducibility in half-cells as a first screening step, this study explores the selection of appropriate cell components, such as reference electrodes (REs) and the use of masking techniques for working electrodes (WEs) to achieve consistent electrochemically active areas. Experimental results on a Li-Au model anode system show that SDC, coupled with a masking approach and subsequent optical microscopy, can mitigate issues related to electrolyte leakage and yield good reproducibility. The proposed methodologies and insights contribute to the advancement of high-throughput battery research, enabling the discovery and optimization of future battery materials with improved efficiency and efficacy.

Electrolyte additives in liquid electrolyte batteries can trigger the formation of a protective interphase (SEI) atthe electrodes that aims to suppress side reactions at the electrodes. Studies of varying amounts of additives have been done over the last years, providing a comprehensive understanding of the impact of the electrolyte formulation on the lifetime of the cells. However, these studies mostly focus on the variation of the mass fraction of additive in the electrolyte while disregarding the ratio (radd) of the additive's amount of substance (nadd) to the electrode area (Aelectrode). Herein we utilize our extremely accurate automatic battery assembly system (AUTOBASS) to vary electrode area and amount of substance of the additive. The data provides strong evidence that reporting the mass ratios of electrolyte components is insufficient and the mol of additive relative to the electrodes’ area should be reported. Herein, the two most utilized additives, namely fluoroethylene carbonate (FEC) and vinylene carbonate (VC) were studied. Each additive was varied from 0.1 wt.-% - 3.0 wt.-% for VC, and 5 wt.-% - 15 wt.-% for FEC for two mass loadings of 1 mAh/cm2 and 3 mAh/cm2. To engage the community to find better descriptors, such as the proposed radd, we publish the dataset alongside this manuscript.

The formation of the solid electrolyte interphase (SEI) on HC composite electrodes plays a crucial role in enhancing the performance and operational stability of sodium (Na+) ion batteries. It has been demonstrated that for HC anodes improved electrochemical performance, e. g., increase in coulombic efficiency (CE) and improved rate performance have been achieved in ether-based electrolytes. Here, we investigate spray-coated HC composite electrodes charged at low and high current rates in 1 M sodium hexafluorophosphate (NaPF6) in diglyme using half-cell experiments. The pristine and cycled HC anodes were examined in terms of conductivity and their electrochemical properties after cycling. In 1 M NaPF6 ether-based electrolyte, the spray-coated HC composite electrodes (film thickness approx. 22.0 mu m with an active mass loading of approx. 2.0 mg cm(-2)) reached a discharge capacity of 431 mA h g(-1) at 0.1 C that stays constant for 40 cycles, which is substantially higher than that obtained in carbonate-based electrolytes. We investigated the formed interphase using conductive atomic force microscopy (c-AFM), scanning electrochemical microscopy (SECM), X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary-ion mass spectrometry (ToF-SIMS), revealing distinct differences for longer cycling and at varying current rates which indicates that the properties of the formed SEI layers are influenced by the formation conditions.

Layered oxides constitute one of the most promising cathode materials classes for large-scale sodium-ion batteries because of their high specific capacity, scalable synthesis, and low cost. However, their practical use is limited by their low energy density, physicochemical instability, and poor cycling stability. Aiming to mitigate these shortcomings, in this work, we synthesized polycrystalline (PC) and single-crystal (SC) P2-type Na0.67-δMn0.67Ni0.33O2 (NMNO) cathode materials through a solid-state route and evaluated their physicochemical and electrochemical performance. The SC-NMNO cathode with a large mean primary particle size (D50) of 12.7 μm was found to exhibit high cycling stability leading to 47% higher capacity retention than PC-NMNO after 175 cycles at 1C rate in the potential window 4.2-1.5 V. This could be attributed to the effective mitigation of parasitic side reactions at the electrode-electrolyte interface and suppressed intergranular cracking induced by anisotropic volume changes. This is confirmed by the lower volume variation of SC-NMNO (ΔV ∼ 1.0%) compared to PC-NMNO (ΔV ∼ 1.4%) upon charging to 4.2 V. Additionally, the SC-NMNO cathode displayed slightly higher thermal stability compared to PC-NMNO. Both cathodes exhibited good chemical stability against air and water exposure, thus enabling material storage/handling in the ambient atmosphere as well as making them suitable for aqueous processing. In this regard, PC-NMNO was investigated with two low-cost aqueous binders, carboxymethyl cellulose, and sodium trimetaphosphate, which exhibited higher binding strength and displayed excellent electrochemical performance compared to PVDF, which could potentially lead to significant cost reduction in electrode manufacturing.

Conventional electrolytes for aluminum metal batteries are highly corrosive because they must remove the Al 2 O 3 layer to enable plating and stripping. However, such corrosiveness impacts the stability of all cell parts, thus hampering the real application of aluminum-metal batteries. The urea/NMA/Al(OTF) 3 electrolyte is a non-corrosive alternative to the conventional [EMImCl]: AlCl 3 ionic liquid electrolyte (ILE). Unfortunately, this electrolyte demonstrates poor Al plating/stripping, probably because (being not corrosive) it cannot remove the Al 2 O 3 passivation layer. This work proves that no plating/stripping occurs on the Al electrode despite modifying the Al surface. We highlight how urea/NMA/Al(OTF) 3 electrolyte and the state of the Al electrode surface impact the interphase layer formation and, consequently, the likelihood and reversibility of Al plating/stripping. We point up the requirement for carefully drying electrolyte mixture and components, as water results in hydrogen evolution reaction and creation of an insulating interphase layer containing Al(OH) 3 , AlF 3 , and re-passivated Al oxide, which finally blocks the path for the possible Al plating/stripping.

Alkyl chain length influences ionicity, conductivity, and viscosity of lithium imidazole salts.

Advancements in artificial intelligence (AI) for science are continually expanding the value proposition for automation in materials and chemistry experiments. The advent of hierarchical decision-making also motivates automation of not only the individual measurements but also the coordination among multiple research workflows. In a typical lab or network of labs, workflows need to independently start and stop operation while also sharing resources such as centralized or multi-functional equipment. A new paradigm in instrument control is needed to realize the combination of independence with respect to periods of operation and interdependence with respect to shared resources. We present Hierarchical Experimental Laboratory Automation and Orchestration with asynchronous programming (HELAO-async), which is implemented via the Python asyncio package by abstracting each resource manager and experiment orchestrator as a FastAPI server. This framework enables coordinated workflows of adaptive experiments, which will elevate Materials Acceleration Platforms (MAPs) from islands of accelerated discovery to the AI emulation of team science.

Amorphous Al2 O3 film that naturally exists on any Al substrate is a critical bottleneck for the cyclic performance of metallic Al in rechargeable Al batteries. The so-called electron/ion insulator Al oxide slows down the anode's activation and hinders Al plating/stripping. The Al2 O3 film induces different surface properties (roughness and microstructure) on the metal. Al foils present two optically different sides (shiny and non-shiny), but their surface properties and influence on plating and stripping have not been studied so far. Compared to the shiny side, the non-shiny one has a higher (~28 %) surface roughness, and its greater concentration of active sites (for Al plating and stripping) yields higher current densities. Immersion pretreatments in Ionic-Liquid/AlCl3 -based electrolyte with various durations modify the surface properties of each side, forming an electrode-electrolyte interphase layer rich in Al, Cl, and N. The created interphase layer provides more tunneling paths for better Al diffusion upon plating and stripping. After 500 cycles, dendritic Al deposition, generated active sites, and the continuous removal of the Al metal and oxide cause accelerated local corrosion and electrode pulverization. We highlight the mechanical surface properties of cycled Al foil, considering the role of immersion pretreatment and the differences between the two sides.

Inorganic aqueous binders (IAB) are an emerging class of aqueous binders. They offer exceptional physicochemical properties like intrinsic ionic conductivity, high thermal stability (>1000°C), and environmental benignity making them attractive. In a previous study, we found that graphite anode shows improved electrochemical performance with these binders as compared to conventional PVDF binder for lithium-ion batteries (LIB). However, the cyclic performance of graphite-IAB at a higher rate (e.g., 1C) showed a declining trend. We attributed it to the poor binding strength between graphite and IAB due to insufficient functional groups in graphite. Therefore in this report, SiOx-based surface coatings of graphite are employed to improve its rate capability with silicate-based IAB by providing functional silicon oxide polymorphs on the coated graphite as an intermediate layer. The nature and structural arrangement of these coatings are investigated by tip-enhanced Raman spectroscopy (TERS), X-ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM). Optimized SiOx-coated graphite (GS) with sodium metasilicate binder leads to excellent cyclic stability with a capacity retention of >90% at 20C for more than 4000 cycles. A high specific capacity of >315 mAhg-1 at 2C, stable for over 1000 cycles, is achieved for GS with IAB. The improved performance of the coated graphite is attributed to ameliorated binding with IAB as well as stable solid electrolyte interphase. We propose inorganic aqueous binders in combination with SiOx-coated graphite as an approach to realize a stable anode for LIB.

Solid electrolyte interphases (SEIs) form as reduction products at the electrodes and strongly affect battery performance and safety. Because SEI formation poses a highly nonlinear, complex multi‐physics problem over various lengths and time scales, traditional modeling approaches struggle to characterize SEI evolution solely with existing physical properties. To improve the characterization of SEIs, it proposes a data‐driven strategy for a virtual material design that learns to represent and characterize SEI formation with physical and data‐driven properties from kinetic Monte Carlo simulations. A Variational AutoEncoder with a property regressor learns data‐driven properties, which represent SEI configurations and correlate with physical target properties. This new neural network design encodes the high‐dimensional structural and reaction spaces into a lower‐dimensional latent space, while the property regressor orders the latent space by physical target properties. The model achieves high correlation scores between target and predicted properties from latent representations, thereby proving that the data‐driven properties enrich the expressiveness of SEI characterizations.

The efficient utilization of resources in accelerated materials science necessitates flexible, reconfigurable software-defined research workflows. We demonstrate a brokering approach to modular and asynchronous research orchestration to integrate multiple laboratories in a cooperative multitenancy platform across disciplines and modalities. To the best of our knowledge, this constitutes the first internationally distributed materials acceleration platform (MAP) linked via a passive brokering server, which is demonstrated through a battery electrolyte workflow capable of determining density, viscosity, ionic conductivity, heat capacity, diffusion coefficients, transference numbers, and radial distribution functions that ran in five countries over the course of 2 weeks. We discuss the lessons learned from multitenancy and fault tolerance and chart a way to a universal battery MAP with fully ontology-linked schemas and cost-aware orchestration.

The high ionic conductivity and good oxidation stability of halide-based solid electrolytes evoke strong interest in this class of materials. Nonetheless, the superior oxidative stability compared to sulfides comes at the expense of limited stability toward reduction and instability against metallic lithium anodes, which hinders their practical use. In this context, the gradual fluorination of Li2ZrCl6-xFx (0 ≤ x ≤ 1.2) is proposed to enhance the stability toward lithium-metal anodes. The mechanochemically synthesized fluorine-substituted compounds show the expected distorted local structure (M2-M3 site disorder) and significant change in the overall Li-ion migration barrier. Theoretical calculations reveal an approximate minimum energy path for Li2ZrCl6-xFx (x = 0 and 0.5) with an increase in the Li+ migration energy barrier for Li2ZrCl5.5F0.5 in comparison to Li2ZrCl6. However, it is found that the fluorine-substituted compound exhibits substantially lower polarization after 800 h of lithium stripping and plating owing to enhanced interfacial stability against the lithium metal, as revealed by density functional theory and ex situ X-ray photoelectron spectroscopy, thanks to the formation of a fluorine-rich passivating interphase.

Materials acceleration platforms (MAPs) operate on the paradigm of integrating combinatorial synthesis, high-throughput characterization, automatic analysis, and machine learning. Within these MAPs, one or multiple autonomous feedback loops may aim to optimize materials for certain functional properties or generate new insights. The scope of a given experiment campaign is defined by the range of experiment and analysis actions that are integrated into the experiment framework. Herein we present a method for integrating many actions within a hierarchical experimental laboratory automation and orchestration (HELAO) framework. We demonstrate the capability of orchestrating distributed research instruments that can incorporate data from experiments, simulations, and databases. HELAO interfaces laboratory hardware and software that are distributed across several computers and operating systems for executing experiments, data analysis, provenance tracking, and autonomous planning. Parallelization is an effective approach for accelerating knowledge generation provided that multiple instruments can be effectively coordinated, which we demonstrate with parallel electrochemistry experiments orchestrated by HELAO. Efficient implementation of autonomous research strategies requires device sharing, asynchronous multithreading, and full integration of data management in experiment orchestration, which to the best of our knowledge, is demonstrated for the first time herein.

Non-aqueous aprotic battery electrolytes, among other requirements, need to perform well over a wide range of temperatures in practical applications. Herein we present a one-shot active learning study to find all conductivity optima, confidence bounds, and relating trends in the temperature range from 30 °C to 60 °C. This optimization is enabled by a high-throughput formulation and characterization setup guided by one-shot active learning utilizing robust and heavily regularized polynomial regression. Whilst there is an initially good agreement for intermediate and low temperatures, there is a need for the active learning step to globally improve the model. Optimized electrolyte formulations likely correspond to the highest physically possible conductivities within this system when compared to literature data. A thorough error propagation analysis yields a fidelity assessment of conductivity measurements and electrolyte formulation.

Spatially resolved characterization of electrode surfaces or electrode-electrolyte interfaces is of fundamental interest in battery research to unravel the complex underlying physicochemical processes. Scanning probe microscopy (SPM) techniques and derived methods have recently gained importance in in situ or operando studies of battery electrodes. This minireview provides an overview on well-established and advanced SPM methods such as scanning electrochemical cell microscopy (SECCM) and hybrid atomic force microscopy-scanning electrochemical microscopy (AFM-SECM) and their future potential for in situ/operando studies providing correlated structure/reactivity information. Although, most studies so far are focusing on lithium (Li)-ion batteries, the potential for post-Li battery chemistries is clearly evident. Future approaches for rapid performance assessment using scanning droplet cell electrochemistry in combination with advanced scanning probe microscopy are proposed and contrasted with the emerging challenges in the characterization of novel battery chemistries, as SPM methods have not yet been much used in this research area.

The increasing global demand for high-quality and low-cost battery electrodes poses major challenges for battery cell production. As mechanical defects on the electrode sheets have an impact on the cell performance and their lifetime, inline quality control during electrode production is of high importance. Correlation of detected defects with process parameters provides the basis for optimization of the production process and thus enables long-term reduction of reject rates, shortening of the production ramp-up phase, and maximization of equipment availability. To enable automatic detection of visually detectable defects on electrode sheets passing through the process steps at a speed of 9 m/s, a You-Only-Look-Once architecture (YOLO architecture) for the identification of visual detectable defects on coated electrode sheets is demonstrated within this work. The ability of the quality assurance (QA) system developed here to detect mechanical defects in real time is validated by an exemplary integration of the architecture into the electrode manufacturing process chain at the Battery Lab Factory Braunschweig.