Quantifying Inactive Lithium in Lithium Metal Batteries

Inactive lithium (Li) formation is the immediate cause of capacity loss and catastrophic failure of Li metal batteries. However, the chemical component and the atomic level structure of inactive Li have rarely been studied due to the lack of effective diagnosis tools to accurately differentiate and quantify Li+ in solid electrolyte interphase (SEI) components and the electrically isolated unreacted metallic Li0, which together comprise the inactive Li. Here, by introducing a new analytical method, Titration Gas Chromatography (TGC), we can accurately quantify the contribution from metallic Li0 to the total amount of inactive Li. We uncover that the Li0, rather than the electrochemically formed SEI, dominates the inactive Li and capacity loss. Using cryogenic electron microscopies to further study the microstructure and nanostructure of inactive Li, we find that the Li0 is surrounded by insulating SEI, losing the electronic conductive pathway to the bulk electrode. Coupling the measurements of the Li0 global content to observations of its local atomic structure, we reveal the formation mechanism of inactive Li in different types of electrolytes, and identify the true underlying cause of low Coulombic efficiency in Li metal deposition and stripping. We ultimately propose strategies to enable the highly efficient Li deposition and stripping to enable Li metal anode for next generation high energy batteries

The Complex Role of Aluminium Contamination in Nickel-Rich Layered Oxide Cathodes for Lithium-Ion Batteries

Abstract: A major challenge for lithium‐ion batteries based on nickel‐rich layered oxide cathodes is capacity fading. While chemo‐mechanical degradation and/or structural transformation are widely considered responsible for degradation, a comprehensive understanding of this process is still not complete. For the stable performance of these cathode materials, aluminium (Al) plays a crucial role, not only as a current collector but also as substitutional element for the transition metals in the cathodes and a protective oxide coating (as Al2O3). However, excess Al can be detrimental due to both its redox inactive nature in the cathode and the insulating nature of Al2O3. In this work, we report an analysis of the Al content in two different types of nickel‐rich manganese cobalt oxide cathode materials after battery cycling. Our results indicate a significant thickening of Al‐containing phases on the surface of the NMC811 electrode. Similar results are observed from commercial batteries (a mixture of NMC532 and LiMn2O4) that were analysed before use and at the end of life, where Al‐containing phases were found to increase significantly at surfaces and grain boundaries. Considering the detrimental effects of the excess Al in the nickel‐rich cathodes, our observation of increased Al content via battery cycling is believed to bring a new perspective to the ongoing discussions regarding the capacity fading phenomenon of nickel‐rich layered oxide materials as part of their complex degradation mechanisms

Observation and Quantification of Nanoscale Processes in Lithium Batteries by Operando Electrochemical (S)TEM

An operando electrochemical stage for the transmission electron microscope has been configured to form a “Li battery” that is used to quantify the electrochemical processes that occur at the anode during charge/discharge cycling. Of particular importance for these observations is the identification of an image contrast reversal that originates from solid Li being less dense than the surrounding liquid electrolyte and electrode surface. This contrast allows Li to be identified from Li-containing compounds that make up the solid-electrolyte interphase (SEI) layer. By correlating images showing the sequence of Li electrodeposition and the evolution of the SEI layer with simultaneously acquired and calibrated cyclic voltammograms, electrodeposition, and electrolyte breakdown processes can be quantified directly on the nanoscale. This approach opens up intriguing new possibilities to rapidly visualize and test the electrochemical performance of a wide range of electrode/electrolyte combinations for next generation battery systems

Principal component analysis of ensemble recordings reveals cell assemblies at high temporal resolution

Simultaneous recordings of many single neurons reveals unique insights into network processing spanning the timescale from single spikes to global oscillations. Neurons dynamically self-organize in subgroups of coactivated elements referred to as cell assemblies. Furthermore, these cell assemblies are reactivated, or replayed, preferentially during subsequent rest or sleep episodes, a proposed mechanism for memory trace consolidation. Here we employ Principal Component Analysis to isolate such patterns of neural activity. In addition, a measure is developed to quantify the similarity of instantaneous activity with a template pattern, and we derive theoretical distributions for the null hypothesis of no correlation between spike trains, allowing one to evaluate the statistical significance of instantaneous coactivations. Hence, when applied in an epoch different from the one where the patterns were identified, (e.g. subsequent sleep) this measure allows to identify times and intensities of reactivation. The distribution of this measure provides information on the dynamics of reactivation events: in sleep these occur as transients rather than as a continuous process

Global haplotype partitioning for maximal associated SNP pairs

<p>Abstract</p> <p>Background</p> <p>Global partitioning based on pairwise associations of SNPs has not previously been used to define haplotype blocks within genomes. Here, we define an association index based on LD between SNP pairs. We use the Fisher's exact test to assess the statistical significance of the LD estimator. By this test, each SNP pair is characterized as associated, independent, or not-statistically-significant. We set limits on the maximum acceptable proportion of independent pairs within all blocks and search for the partitioning with maximal proportion of associated SNP pairs. Essentially, this model is reduced to a constrained optimization problem, the solution of which is obtained by iterating a dynamic programming algorithm.</p> <p>Results</p> <p>In comparison with other methods, our algorithm reports blocks of larger average size. Nevertheless, the haplotype diversity within the blocks is captured by a small number of tagSNPs. Resampling HapMap haplotypes under a block-based model of recombination showed that our algorithm is robust in reproducing the same partitioning for recombinant samples. Our algorithm performed better than previously reported models in a case-control association study aimed at mapping a single locus trait, based on simulation results that were evaluated by a block-based statistical test. Compared to methods of haplotype block partitioning, we performed best on detection of recombination hotspots.</p> <p>Conclusion</p> <p>Our proposed method divides chromosomes into the regions within which allelic associations of SNP pairs are maximized. This approach presents a native design for dimension reduction in genome-wide association studies. Our results show that the pairwise allelic association of SNPs can describe various features of genomic variation, in particular recombination hotspots.</p

Imaging the boundaries—innovative tools for microscopy of living cells and real-time imaging

Recently, light microscopy moved back into the spotlight, which is mainly due to the development of revolutionary technologies for imaging real-time events in living cells. It is truly fascinating to see enzymes “at work” and optically acquired images certainly help us to understand biological processes better than any abstract measurements. This review aims to point out elegant examples of recent cell-biological imaging applications that have been developed with a chemical approach. The discussed technologies include nanoscale fluorescence microscopy, imaging of model membranes, automated high-throughput microscopy control and analysis, and fluorescent probes with a special focus on visualizing enzyme activity, free radicals, and protein–protein interaction designed for use in living cells

Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals

peer-reviewedH.D.D., A.J.C., P.J.B. and B.J.H. would like to acknowledge the Dairy Futures Cooperative Research Centre for funding. H.P. and R.F. acknowledge funding from the German Federal Ministry of Education and Research (BMBF) within the AgroClustEr ‘Synbreed—Synergistic Plant and Animal Breeding’ (grant 0315527B). H.P., R.F., R.E. and K.-U.G. acknowledge the Arbeitsgemeinschaft Süddeutscher Rinderzüchter, the Arbeitsgemeinschaft Österreichischer Fleckviehzüchter and ZuchtData EDV Dienstleistungen for providing genotype data. A. Bagnato acknowledges the European Union (EU) Collaborative Project LowInputBreeds (grant agreement 222623) for providing Brown Swiss genotypes. Braunvieh Schweiz is acknowledged for providing Brown Swiss phenotypes. H.P. and R.F. acknowledge the German Holstein Association (DHV) and the Confederación de Asociaciones de Frisona Española (CONCAFE) for sharing genotype data. H.P. was financially supported by a postdoctoral fellowship from the Deutsche Forschungsgemeinschaft (DFG) (grant PA 2789/1-1). D.B. and D.C.P. acknowledge funding from the Research Stimulus Fund (11/S/112) and Science Foundation Ireland (14/IA/2576). M.S. and F.S.S. acknowledge the Canadian Dairy Network (CDN) for providing the Holstein genotypes. P.S. acknowledges funding from the Genome Canada project entitled ‘Whole Genome Selection through Genome Wide Imputation in Beef Cattle’ and acknowledges WestGrid and Compute/Calcul Canada for providing computing resources. J.F.T. was supported by the National Institute of Food and Agriculture, US Department of Agriculture, under awards 2013-68004-20364 and 2015-67015-23183. A. Bagnato, F.P., M.D. and J.W. acknowledge EU Collaborative Project Quantomics (grant 516 agreement 222664) for providing Brown Swiss and Finnish Ayrshire sequences and genotypes. A.C.B. and R.F.V. acknowledge funding from the public–private partnership ‘Breed4Food’ (code BO-22.04-011- 001-ASG-LR) and EU FP7 IRSES SEQSEL (grant 317697). A.C.B. and R.F.V. acknowledge CRV (Arnhem, the Netherlands) for providing data on Dutch and New Zealand Holstein and Jersey bulls.Stature is affected by many polymorphisms of small effect in humans1. In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes2,3. Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 × 10−8) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP–seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals