Quantitative Comparison of Different Approaches for Reconstructing the Carbon-Binder Domain from Tomographic Image Data of Cathodes in Lithium-Ion Batteries and Its Influence on Electrochemical Properties

It is well known that the spatial distribution of the carbon binder domain CBD offers a large potential to further optimize lithium ion batteries. However, it is challenging to reconstruct the CBD from tomographic image data obtained by synchrotron tomography. Herein, several approaches are considered to segment 3D image data of two different cathodes into three phases, namely, active material, CBD, and pores. More precisely, it is focused on global thresholding, a local closing approach based on energy dispersive X ray spectroscopy data, a k means clustering method, and a procedure based on a neural network that has been trained by correlative microscopy, i.e., based on data gained by synchrotron tomography and focused ion beam scanning electron microscopy data representing the same electrode. The impact of the considered segmentation approaches on morphological characteristics as well as on the resulting performance by spatially resolved transport simulations is quantified. Furthermore, experimentally determined electrochemical properties are used to identify an appropriate range for the effective transport parameter of the CBD. The developed methodology is applied to two differently manufactured cathodes, namely, an ultrathick unstructured cathode and a two layer cathode with varying CBD content in both layers. This comparison elucidates the impact of a specific structuring concept on the 3D microstructure of cathode

A network perspective on real-life threat, anxiety, and avoidance

Background: Anxiety, approach, and avoidance motivation crucially influence mental and physical health, especially when environments are stressful. The interplay between anxiety and behavioral motivation is modulated by multiple individual factors. This proof-of-concept study applies graph-theoretical network analysis to explore complex associations between self-reported trait anxiety, approach and avoidance motivation, situational anxiety, stress symptoms, perceived threat, perceived positive consequences of approach, and self-reported avoidance behavior in real-life threat situations. 'Methods: A total of 436 participants who were matched on age and gender (218 psychotherapy patients, 218 online-recruited nonpatients) completed an online survey assessing these factors in response to the COVID-19 pandemic. Results and Discussion: The resulting cross-sectional psychological network revealed a complex pattern with multiple positive (e.g., between trait anxiety, avoidance motivation, and avoidance behavior) and negative associations (e.g., between approach and avoidance motivation). The patient and online subsample networks did not differ significantly, however, descriptive differences may inform future research.</p

Three-Dimensional Visualization of Gas Evolution and Channel Formation inside a Lithium-Ion Battery

Gas generation within lithium ion batteries (LIBs) gives rise to safety concerns that question their applicability. By employing synchrotron X-ray imaging, the gas and channel evolution occurring in an operating LIB have been directly visualized in their inherent 3D state as a function of discharge and charge. Using the spatial 3D distribution of gas bubbles and channels, the active particles that dictate the performance of a functional LIB were identified and visualized in 3D. Delithiation and lithiation are interpreted as the process of activating particles continuously in a step-by-step way. The present work not only demonstrates the generation and evolution of gas within LIB in 3D, but also reveals the distribution of active particles for the first time. These fundamentally findings presented here shed light on a range of processes that could not previously be characterized in 3D and can provide practical guidance for the design of next-generation LIBs with improved safety

Combining delta C-13 measurements and ERT imaging: improving our understanding of competition at the crop-soil-hedge interface

© 2015, Springer International Publishing Switzerland. Background and aims: Hedgerow cropping decreases erosion in hillside agriculture but also competes for water and nutrients with crops. This study combined two methods for an improved understanding of water and nutrient competition at the crop-soil-hedge interface. Methods: δ13C isotopic discrimination in plants and soil electrical resistivity tomography (ERT) imaging were used in a field trial with maize monocropping (MM) vs. leucaena hedgerow intercropping with and without fertilizer (MHF+ and MHF−) in Thailand. Results: Hedges significantly reduced maize grain yield and aboveground biomass in rows close to hedgerows. ERT revealed water depletion was stronger in MM than in MHF+ and MHF- confirming time domain reflectometry and leaf area data. In MHF+, water depletion was higher in maize rows close to the hedge compared to rows distant to hedges and maize grain δ13C was significantly less negative in rows close to hedges (-10.33‰) compared to distant ones (-10.64‰). Lack of N increased grain δ13C in MHF- (-9.32‰, p ≤ 0.001). Both methods were correlated with each other (r = 0.66, p ≤ 0.001). Combining ERT with grain δ13C and %N allowed identifying that maize growth close to hedges was limited by N and not by water supply. Conclusion: Combining ERT imaging and 13C isotopic discrimination approaches improved the understanding of spatial-temporal patterns of competition at the hedge-soil-crop interface and allowed distinguishing between water and N competition in maize based hedgerow systems.status: publishe

Looking Deep inside the Cathode of Li-O2 Batteries: Unraveling the Local Distribution of Li2O2 with a Combined Experimental and Model-Based Approach

Carbon-based, high surface area gas diffusion electrodes (GDEs) are commonly used as cathodes in Li-O2 batteries. These GDEs provide an sufficient amount of active sites to deposit the main discharge product, Li2O2. Despite the fast electron transfer at the electrode surface to form Li2O2, experimental results show that the very high theoretical energy densities of Li-O2 batteries cannot be achieved at the moment. Instead of the desired formation of high amounts of soluble LiO2, predominantly insoluble Li2O2 precipitates at the active sites of the cathode during discharge. Unfortunately Li2O2 is poorly conductive for electrons, which leads to a low amount of deposited Li2O2 per active site and a fast passivation of the cathode. Thus, only the cathode surface area and not the pore volume is utilized by Li2O2, which explains the discrepancy between theory and experiments. Furthermore, the precipitation leads to continuous changes in porosity, available active surface area and predominant reaction pathway. For this reason a detailed analysis of the distribution of Li2O2 at all points in the GDE and of the factors that influence the Li2O2 morphology is needed to overcome performance limitations. [1]In this work, we elucidate how the local distribution of Li2O2 inside the GDE and its particle size evolve as a function of discharge current density. We apply a powerful combination of experimental and model-based analysis. To the best of our knowledge, this is the first study on the cathode surface utilization by Li2O2 and its particle sizes performed for different locations and states of discharge (SOD). The impact of the distribution and the resulting changes in transport resistance and active surface area on the battery performance are derived thereof. In the experimental part, decreasing capacities and Li2O2 particle sizes are observed for increasing discharge current densities (see SEM analysis of discharged battery cathodes in fig. 1 a)). Furthermore, the experimental results show that particle precipitation starts mainly at the side of the cathode that faces the oxygen reservoir of the battery (see fig. 1 b)). Discharging a battery at low current densities leads to a uniform cathode surface coverage by Li2O2 even at low SOD whereas discharging at high current densities yields a gradient of blocked active sites through the cathode. Simulations based on a physical GDE model show that a two-step reaction mechanism with the soluble species LiO2 as reaction intermediate can quantitatively explain the experimental findings. Depending on the current density, either a chemical or an electrochemical particle growth process predominates, which leads to the distinct different particle size distributions (see fig. 1 c) and d)). The strong dependence of capacity on the current density is related to different capacities per carbon cathode surface area at the end of discharge. At high discharge rates and thereby lowered potential more nucleation takes place. As a result, the particle number is higher and the average size smaller. Due to the surface volume ratio, smaller particles entail lower capacities per cathode surface area. The results point out that even at moderate current densities the battery capacity is limited by the surface area of the GDE and not by the concentration of dissolved O2 in the liquid electrolyte. Therefore, the solubility and reaction kinetics of the reaction intermediate LiO2 play a crucial role to enhance Li2O2 particle size and with it the obtainable discharge capacity. The presented results provide detailed insight into the cathode surface utilization and the underlying processes that limit the performance of GDEs in Li-O2 batteries. In the end, the study will help to achieve higher discharge capacities for this type of battery and thus will propel the ongoing research and the efforts in commercialization of metal-oxygen batteries

Preparation of (ethylene)-(propylene)-triaminepentaacetic acid derivatives for use in the production of pharmaceutical agents

The invention relates to a novel class of ligands, complexes comprising such ligands and a metal ion, and adducts of these metal complexes and a macromolecule. Pharmaceutical compositions and methods of making and using the ligand-metal complexes are also described. The invention also relates to the use of macromolecular adducts for enhancement of diagnostic imaging. In particular, the invention relates to (ethylene)-(propylene)-triaminepentaacetic acid (EPTPA) derivatives, a process for their production, and their use for the production of pharmaceutical agents for NMR diagnosis or radiodiagnosis or radiotherapy

Microstructure-Resolved Impedance Simulations for the Characterization of Li-Ion Battery Electrodes

The production of Li-Ion battery electrodes is a highly interconnected process and many parameters determine the functionality of the final battery cell. Therefore, characterization techniques are very important to monitor the quality of the electrodes and to analyze deviations in electrode performance. The impedance of the porous electrode is a characteristic performance indicator, relatively easy to measure, and the corresponding spectra provide a comprehensive overview of characteristic timescales of different processes. For a detailed analysis impedance spectra are commonly evaluated integrally with the help of equivalent circuit models. However, often the performance of the electrode is affected by local structural inhomogeneities due to compression in the calendering process or an unfavorable binder and/or carbon black distribution. For instance, it was found that harsh drying conditions cause binder migration to the electrode surface and consequently reduce the rate capability1. In this contribution we interpret impedance spectra of Li-ion battery positive electrodes with the help of 3D microstructure-resolved simulations2. This allows us to study in detail the effect of local structural inhomogeneities on the electrode impedance and, thus, performance. NMC electrodes with different thickness and density were prepared and characterized electrochemically by galvanostatic cycling and electrochemical impedance spectroscopy. Impedance spectra were recorded on symmetrical cells3 which are especially advantageous for the characterization of electrode transport properties. Reconstructions of the electrodes were created with the help of synchrotron tomography and a 3D stochastic structure generator4. The resulting microstructures are then input to microstructure-resolved electrochemical simulations. With the help of our simulations we are able to extract the contribution of the carbon black and binder network to the overall pore transport resistance by comparing our simulations to the experimental data. Additionally, we use different models for the spatial distribution of binder and carbon black to mimic different drying conditions and investigate the effect on the electrode impedance and cell performance