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The lifetime of the battery significantly influences the acceptance of electric vehicles. Calendar aging contributes to the limited operating lifetime of lithium-ion batteries. Therefore, its consideration in addition to cyclical aging is essential to understand battery degradation. This study consequently examines the same graphite/NCA pouch cell that was the subject of previously published cyclic aging tests. The cells were aged at different temperatures and states of charge. The self-discharge was continuously monitored, and after each storage period, the remaining capacity and the impedance were measured. The focus of this publication is on the correlation of the measurements. An aging correlation is obtained that is valid for a wide range of temperatures and states of charge. The results show an accelerated capacity fade and impedance rise with increasing temperature, following the law of Arrhenius. However, the obtained data do also indicate that there is no path dependency, i.e., earlier periods at different temperature levels do not affect the present degradation rate. A large impact of the storage state of charge at 100% is evident, whereas the influence is small below 80%. Instead of the commonly applied square root of the time function, our results are in excellent agreement with an exponential function.

Alongside electrical loads, it is known that temperature has a strong influence on battery behavior and lifetime. Investigations have mainly been performed at homogeneous temperatures and non-homogeneous conditions in single cells have at best been simulated. This publication presents the development of a methodology and experimental setup to investigate the influence of thermal boundary conditions during the operation of lithium-ion cells. In particular, spatially inhomogeneous and transient thermal boundary conditions and periodical electrical cycles were superimposed in different combinations. This required a thorough design of the thermal boundary conditions applied to the cells. Unlike in other contributions that rely on placing cells in a climatic chamber to control ambient air temperature, here the cell surfaces and tabs were directly connected to individual cooling and heating plates. This improves the control of the cells’ internal temperature, even with high currents accompanied by strong internal heat dissipation. The aging process over a large number of electrical cycles is presented by means of discharge capacity and impedance spectra determined in repeated intermediate characterizations. The influence of spatial temperature gradients and temporal temperature changes on the cyclic degradation is revealed. It appears that the overall temperature level is indeed a decisive parameter for capacity fade during cyclic aging, while the intensity of a temperature gradient is not as essential. Furthermore, temperature changes can have a substantial impact and potentially lead to stronger degradation than spatial inhomogeneities.

Temperature has a significant influence on the behavior of batteries and their lifetime. There are several studies in literature that investigate the aging behavior under electrical load, but are limited to homogeneous, constant temperatures. This article presents an approach to quantifying cyclic aging of lithium-ion cells that takes into account complex thermal boundary conditions. It not only considers different temperature levels but also spatial and transient temperature gradients that can occur despite-or even due to-the use of thermal management systems. Capacity fade and impedance rise are used as measured quantities for degradation and correlated with the temperature boundary conditions during the aging process. The concept and definition of an equivalent aging temperature (EAT) is introduced to relate the degradation caused by spatial and temporal temperature inhomogeneities to similar degradation caused by a homogeneous steady temperature during electrical cycling. The results show an increased degradation at both lower and higher temperatures, which can be very well described by two superimposed exponential functions. These correlations also apply to cells that are cycled under the influence of spatial temperature gradients, both steady and transient. Only cells that are exposed to transient, but spatially homogeneous temperature conditions show a significantly different aging behavior. The concluding result is a correlation between temperature and aging rate, which is expressed as degradation per equivalent full cycle (EFC). This enables both temperature-dependent modeling of the aging behavior and its prediction.

Most battery cells are developed according to a standard design and optimized regarding their electrical properties. However, firstly, there is a demand for an individual cell design adapted to the application. Secondly, additional properties, for example, thermal and mechanical, are decisive for the cell behavior and should be considered in the overall design. Therefore, the present work introduces a model-based development tool for the holistic design of format-flexible battery cells, which are optimized for their future application, allowing for different cell geometries within one battery system. The different approaches and simulation models for the single design steps are presented, and the prediction of the electrochemical, electrical, and thermal behaviors of the cell and whole battery system is described. A key aspect here is the appropriate interconnection of the single models in a way that helps to narrow down the multitude of interacting parameters in a systematic manner and, thus, makes a holistic design possible. In a last step, the functionality of the tool is shown in a case study by means of an e-bike battery pack.

Batteries are pivotal for transitioning to a climate-friendly future, leading to a surge in battery research. Scopus (Elsevier) lists 14,388 papers that mention \"lithium-ion battery\" in 2023 alone, making it infeasible for individuals to keep up. This paper discusses strategies based on structured, semantic, and linked data to manage this information overload. Structured data follows a predefined, machine-readable format; semantic data includes metadata for context; linked data references other semantic data, forming a web of interconnected information. We use a battery-related ontology, BattINFO to standardise terms and enable automated data extraction and analysis. Our methodology integrates full-text search and machine-readable data, enhancing data retrieval and battery testing. We aim to unify commercial cell information and develop tools for the battery community such as manufacturer-independent cycling procedure descriptions and external memory for Large Language Models. Although only a first step, this approach significantly accelerates battery research and digitalizes battery testing, inviting community participation for continuous improvement. We provide the structured data and the tools to access them as open source.

Introduction Alzheimer’s disease (AD) is associated with the accumulation of β-amyloid (Aβ) as senile plaques in the brain, thus leading to neurodegeneration and cognitive impairment. Plaque formation depends not merely on the amount of generated Aβ peptides, but more importantly on their effective removal. Chronic infections with neurotropic pathogens, most prominently the parasite Toxoplasma ( T .) gondii , are frequent in the elderly, and it has been suggested that the resulting neuroinflammation may influence the course of AD. In the present study, we investigated how chronic T. gondii infection and resulting neuroinflammation affect plaque deposition and removal in a mouse model of AD. Results Chronic infection with T. gondii was associated with reduced Aβ and plaque load in 5xFAD mice. Upon infection, myeloid-derived CCR2 hi  Ly6C hi monocytes, CCR2 +  Ly6C int , and CCR2 +  Ly6C low mononuclear cells were recruited to the brain of mice. Compared to microglia, these recruited mononuclear cells showed highly increased phagocytic capacity of Aβ ex vivo . The F4/80 +  Ly6C low macrophages expressed high levels of Triggering Receptor Expressed on Myeloid cells 2 (TREM2), CD36, and Scavenger Receptor A1 (SCARA1), indicating phagocytic activity. Importantly, selective ablation of CCR2 +  Ly6C hi monocytes resulted in an increased amount of Aβ in infected mice. Elevated insulin-degrading enzyme ( IDE ), matrix metalloproteinase 9 ( MMP9 ), as well as immunoproteasome subunits β 1i/LMP2 , β2i/MECL-1 , and β5i/LMP7 mRNA levels in the infected brains indicated increased proteolytic Aβ degradation. Particularly, LMP7 was highly expressed by the recruited mononuclear cells in the brain, suggesting a novel mechanism of Aβ clearance. Conclusions Our results indicate that chronic Toxoplasma infection ameliorates β-amyloidosis in a murine model of AD by activation of the immune system, specifically by recruitment of Ly6C hi monocytes and by enhancement of phagocytosis and degradation of soluble Aβ. Our findings provide evidence for a modulatory role of inflammation-induced Aβ phagocytosis and degradation by newly recruited peripheral immune cells in the pathophysiology of AD.

Introduction Alzheimer's disease (AD) is associated with the accumulation of [beta]-amyloid (A[beta]) as senile plaques in the brain, thus leading to neurodegeneration and cognitive impairment. Plaque formation depends not merely on the amount of generated A[beta] peptides, but more importantly on their effective removal. Chronic infections with neurotropic pathogens, most prominently the parasite Toxoplasma (T .) gondii , are frequent in the elderly, and it has been suggested that the resulting neuroinflammation may influence the course of AD. In the present study, we investigated how chronic T.â¯gondii infection and resulting neuroinflammation affect plaque deposition and removal in a mouse model of AD. Results Chronic infection with T.â¯gondii was associated with reduced A[beta] and plaque load in 5xFAD mice. Upon infection, myeloid-derived CCR2.sup.hiâ¯Ly6C.sup.hi monocytes, CCR2.sup.+â¯Ly6C.sup.int, and CCR2.sup.+â¯Ly6C.sup.low mononuclear cells were recruited to the brain of mice. Compared to microglia, these recruited mononuclear cells showed highly increased phagocytic capacity of A[beta] ex vivo . The F4/80.sup.+â¯Ly6C.sup.low macrophages expressed high levels of Triggering Receptor Expressed on Myeloid cells 2 (TREM2), CD36, and Scavenger Receptor A1 (SCARA1), indicating phagocytic activity. Importantly, selective ablation of CCR2.sup.+â¯Ly6C.sup.hi monocytes resulted in an increased amount of A[beta] in infected mice. Elevated insulin-degrading enzyme (IDE ), matrix metalloproteinase 9 (MMP9 ), as well as immunoproteasome subunits [beta]1i/LMP2 , [beta]2i/MECL-1 , and [beta]5i/LMP7 mRNA levels in the infected brains indicated increased proteolytic A[beta] degradation. Particularly, LMP7 was highly expressed by the recruited mononuclear cells in the brain, suggesting a novel mechanism of A[beta] clearance. Conclusions Our results indicate that chronic Toxoplasma infection ameliorates [beta]-amyloidosis in a murine model of AD by activation of the immune system, specifically by recruitment of Ly6C.sup.hi monocytes and by enhancement of phagocytosis and degradation of soluble A[beta]. Our findings provide evidence for a modulatory role of inflammation-induced A[beta] phagocytosis and degradation by newly recruited peripheral immune cells in the pathophysiology of AD. Keywords: Alzheimer's disease, Toxoplasma gondii, Chronic infection, Ly6C.sup.hi monocytes, A[beta] clearance