Machine Learning Based Lifetime Prediction of Lithium-Ion Cells

Precise lifetime predictions for lithium‐ion cells are crucial for efficient battery development and thus enable profitable electric vehicles and a sustainable transformation towards zero‐emission mobility. However, limitations remain due to the complex degradation of lithium‐ion cells, strongly influenced by cell design as well as operating and storage conditions. To overcome them, a machine learning framework is developed based on symbolic regression via genetic programming. This evolutionary algorithm is capable of inferring physically interpretable models from cell aging data without requiring domain knowledge. This novel approach is compared against established approaches in case studies, which represent common tasks of lifetime prediction based on cycle and calendar aging data of 104 automotive lithium‐ion pouch‐cells. On average, predictive accuracy for extrapolations over storage time and energy throughput is increased by 38% and 13%, respectively. For predictions over other stress factors, error reductions of up to 77% are achieved. Furthermore, the evolutionary generated aging models meet requirements regarding applicability, generalizability, and interpretability. This highlights the potential of evolutionary algorithms to enhance cell aging predictions as well as insights

Frequency dependent specific heat of viscous silica

We apply the Mori-Zwanzig projection operator formalism to obtain an expression for the frequency dependent specific heat c(z) of a liquid. By using an exact transformation formula due to Lebowitz et al., we derive a relation between c(z) and K(t), the autocorrelation function of temperature fluctuations in the microcanonical ensemble. This connection thus allows to determine c(z) from computer simulations in equilibrium, i.e. without an external perturbation. By considering the generalization of K(t) to finite wave-vectors, we derive an expression to determine the thermal conductivity \lambda from such simulations. We present the results of extensive computer simulations in which we use the derived relations to determine c(z) over eight decades in frequency, as well as \lambda. The system investigated is a simple but realistic model for amorphous silica. We find that at high frequencies the real part of c(z) has the value of an ideal gas. c'(\omega) increases quickly at those frequencies which correspond to the vibrational excitations of the system. At low temperatures c'(\omega) shows a second step. The frequency at which this step is observed is comparable to the one at which the \alpha-relaxation peak is observed in the intermediate scattering function. Also the temperature dependence of the location of this second step is the same as the one of the $\alpha-$peak, thus showing that these quantities are intimately connected to each other. From c'(\omega) we estimate the temperature dependence of the vibrational and configurational part of the specific heat. We find that the static value of c(z) as well as \lambda are in good agreement with experimental data.Comment: 27 pages of Latex, 8 figure

Influence of genetic variations in TLR4 and TIRAP/Mal on the course of sepsis and pneumonia and cytokine release: an observational study in three cohorts

Introduction: It has been proposed that individual genetic variation contributes to the course of severe infections and sepsis. Recent studies of single nucleotide polymorphisms (SNPs) within the endotoxin receptor and its signaling system showed an association with the risk of disease development. This study aims to examine the response associated with genetic variations of TLR4, the receptor for bacterial LPS, and a central intracellular signal transducer (TIRAP/Mal) on cytokine release and for susceptibility and course of severe hospital acquired infections in distinct patient populations. Methods: Three intensive care units in tertiary care university hospitals in Greece and Germany participated. 375 and 415 postoperative patients and 159 patients with ventilator associated pneumonia (VAP) were included. TLR4 and TIRAP/Mal polymorphisms in 375 general surgical patients were associated with risk of infection, clinical course and outcome. In two prospective studies, 415 patients following cardiac surgery and 159 patients with newly diagnosed VAP predominantly caused by Gram-negative bacteria were studied for cytokine levels in-vivo and after ex-vivo monocyte stimulation and clinical course. Results: Patients simultaneously carrying polymorphisms in TIRAP/Mal and TLR4 and patients homozygous for the TIRAP/Mal SNP had a significantly higher risk of severe infections after surgery (odds ratio (OR) 5.5; confidence interval (CI): 1.34 - 22.64; P = 0.02 and OR: 7.3; CI: 1.89 - 28.50; P < 0.01 respectively). Additionally we found significantly lower circulating cytokine levels in double-mutant individuals with ventilator associated pneumonia and reduced cytokine production in an ex-vivo monocyte stimulation assay, but this difference was not apparent in TIRAP/Mal-homozygous patients. In cardiac surgery patients without infection, the cytokine release profiles were not changed when comparing different genotypes. Conclusions: Carriers of mutations in sequential components of the TLR signaling system may have an increased risk for severe infections. Patients with this genotype showed a decrease in cytokine release when infected which was not apparent in patients with sterile inflammation following cardiac surgery

Nucleic acid recognition by Toll-like receptors is coupled to stepwise processing by cathepsins and asparagine endopeptidase

TLR3, TLR7, and TLR9 are cleaved in the same step-wise manner in all immune cell types examined

Single Molecule In Vivo Analysis of Toll-Like Receptor 9 and CpG DNA Interaction

Toll-like receptor 9 (TLR9) activates the innate immune system in response to oligonucleotides rich in CpG whereas DNA lacking CpG could inhibit its activation. However, the mechanism of how TLR9 interacts with nucleic acid and becomes activated in live cells is not well understood. Here, we report on the successful implementation of single molecule tools, constituting fluorescence correlation/cross-correlation spectroscopy (FCS and FCCS) and photon count histogram (PCH) with fluorescence lifetime imaging (FLIM) to study the interaction of TLR9-GFP with Cy5 labeled oligonucleotide containing CpG or lacking CpG in live HEK 293 cells. Our findings show that i) TLR9 predominantly forms homodimers (80%) before binding to a ligand and further addition of CpG or non CpG DNA does not necessarily increase the proportion of TLR9 dimers, ii) CpG DNA has a lower dissociation constant (62 nM±9 nM) compared to non CpG DNA (153 nM±26 nM) upon binding to TLR9, suggesting that a motif specific binding affinity of TLR9 could be an important factor in instituting a conformational change-dependant activation, and iii) both CpG and non CpG DNA binds to TLR9 with a 1∶2 stoichiometry in vivo. Collectively, through our findings we establish an in vivo model of TLR9 binding and activation by CpG DNA using single molecule fluorescence techniques for single cell studies

An essential role for the N-terminal fragment of Toll-like receptor 9 in DNA sensing

Toll-like receptor 9 (TLR9) is an innate immune sensor for microbial DNA that erroneously responds to self DNA in autoimmune disease. To prevent autoimmune responses, Toll-like receptor 9 is excluded from the cell surface and silenced until the N-terminal half of the ectodomain (TLR9N) is cleaved off in the endolysosome. Truncated Toll-like receptor 9 (TLR9C) senses ingested microbial DNA, although the precise role of the truncation remains controversial. Here we show that TLR9 is expressed on the surface of splenic dendritic cells. Following the cleavage of TLR9 in the endolysosome, N-terminal half of the ectodomain remains associated with truncated TLR9, forming the complex TLR9N + C. The TLR9-dependent cytokine production by Tlr9(-/-) dendritic cells is rescued by a combination of TLR9N and TLR9C, but not by TLR9C alone. These results demonstrate that the TLR9N + C complex is a bona fide DNA sensor

Oxide‐Based Solid‐State Batteries: A Perspective on Composite Cathode Architecture

The garnet-type phase Li$_7$La$_3$Zr$_2$O$_{12}$ (LLZO) attracts significant attention as an oxide solid electrolyte to enable safe and robust solid-state batteries (SSBs) with potentially high energy density. However, while significant progress has been made in demonstrating compatibility with Li metal, integrating LLZO into composite cathodes remains a challenge. The current perspective focuses on the critical issues that need to be addressed to achieve the ultimate goal of an all-solid-state LLZO-based battery that delivers safety, durability, and pack-level performance characteristics that are unobtainable with state-of-the-art Li-ion batteries. This perspective complements existing reviews of solid/solid interfaces with more emphasis on understanding numerous homo- and heteroionic interfaces in a pure oxide-based SSB and the various phenomena that accompany the evolution of the chemical, electrochemical, structural, morphological, and mechanical properties of those interfaces during processing and operation. Finally, the insights gained from a comprehensive literature survey of LLZO–cathode interfaces are used to guide efforts for the development of LLZO-based SSBs

Strategies towards enabling lithium metal in batteries: interphases and electrodes

Despite the continuous increase in capacity, lithium-ion intercalation batteries are approaching their performance limits. As a result, research is intensifying on next-generation battery technologies. The use of a lithium metal anode promises the highest theoretical energy density and enables use of lithium-free or novel high-energy cathodes. However, the lithium metal anode suffers from poor morphological stability and Coulombic efficiency during cycling, especially in liquid electrolytes. In contrast to solid electrolytes, liquid electrolytes have the advantage of high ionic conductivity and good wetting of the anode, despite the lithium metal volume change during cycling. Rapid capacity fade due to inhomogeneous deposition and dissolution of lithium is the main hindrance to the successful utilization of the lithium metal anode in combination with liquid electrolytes. In this perspective, we discuss how experimental and theoretical insights can provide possible pathways for reversible cycling of twodimensional lithium metal. Therefore, we discuss improvements in the understanding of lithium metal nucleation, deposition, and stripping on the nanoscale. As the solid–electrolyte interphase (SEI) plays a key role in the lithium morphology, we discuss how the proper SEI design might allow stable cycling. We highlight recent advances in conventional and (localized) highly concentrated electrolytes in view of their respective SEIs. We also discuss artificial interphases and three-dimensional host frameworks, which show prospects of mitigating morphological instabilities and suppressing large shape change on the electrode level

Methylthioadenosine reprograms macrophage activation through adenosine receptor stimulation

Regulation of inflammation is necessary to balance sufficient pathogen clearance with excessive tissue damage. Central to regulating inflammation is the switch from a pro-inflammatory pathway to an anti-inflammatory pathway. Macrophages are well-positioned to initiate this switch, and as such are the target of multiple therapeutics. One such potential therapeutic is methylthioadenosine (MTA), which inhibits TNFα production following LPS stimulation. We found that MTA could block TNFα production by multiple TLR ligands. Further, it prevented surface expression of CD69 and CD86 and reduced NF-KB signaling. We then determined that the mechanism of this action by MTA is signaling through adenosine A2 receptors. A2 receptors and TLR receptors synergized to promote an anti-inflammatory phenotype, as MTA enhanced LPS tolerance. In contrast, IL-1β production and processing was not affected by MTA exposure. Taken together, these data demonstrate that MTA reprograms TLR activation pathways via adenosine receptors to promote resolution of inflammation. © 2014 Keyel et al