Stochasticity of Pores Interconnectivity in Li–O2 Batteries and its Impact on the Variations in Electrochemical Performance

While large dispersions in electrochemical performance have been reported for lithium oxygen batteries in the literature, they have not been investigated in any depth. The variability in the results is often assumed to arise from differences in cell design, electrode structure, handling and cell preparation at different times. An accurate theoretical framework turns out to be needed to get a better insight into the mechanisms underneath and to interpret experimental results. Here, we develop and use a pore network model to simulate the electrochemical performance of three-dimensionally resolved lithium−oxygen cathode mesostructures obtained from TXM nanocomputed tomography. We apply this model to the 3D reconstructed object of a Super P carbon electrode and calculate discharge curves, using identical conditions, for four different zones in the electrode and their reversed configurations. The resulting galvanostatic discharge curves show some dispersion, (both in terms of capacity and overpotential) which we attribute to the way pores are connected with each other. Based on these results, we propose that the stochastic nature of pores interconnectivity and the microscopic arrangement of pores can lead, at least partially, to the variations in electrochemical results observed experimentally

Anisotropic nanomaterials: structure, growth, assembly, and functions

Comprehensive knowledge over the shape of nanomaterials is a critical factor in designing devices with desired functions. Due to this reason, systematic efforts have been made to synthesize materials of diverse shape in the nanoscale regime. Anisotropic nanomaterials are a class of materials in which their properties are direction-dependent and more than one structural parameter is needed to describe them. Their unique and fine-tuned physical and chemical properties make them ideal candidates for devising new applications. In addition, the assembly of ordered one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) arrays of anisotropic nanoparticles brings novel properties into the resulting system, which would be entirely different from the properties of individual nanoparticles. This review presents an overview of current research in the area of anisotropic nanomaterials in general and noble metal nanoparticles in particular. We begin with an introduction to the advancements in this area followed by general aspects of the growth of anisotropic nanoparticles. Then we describe several important synthetic protocols for making anisotropic nanomaterials, followed by a summary of their assemblies, and conclude with major applications

Operando monitoring of the solution-mediated discharge and charge processes in a Na-O2 battery using liquid-electrochemical transmission electron microscopy

Although in sodium–oxygen (Na–O2) batteries show promise as high-energy storage systems, this technology is still the subject of intense fundamental research, owing to the complex reaction by which it operates. To understand the formation mechanism of the discharge product, sodium superoxide (NaO2), advanced experimental tools must be developed. Here we present for the first time the use of a Na–O2 microbattery using a liquid aprotic electrolyte coupled with fast imaging transmission electron microscopy to visualize, in real time, the mechanism of NaO2 nucleation/growth. We observe that the formation of NaO2 cubes during reduction occurs by a solution-mediated nucleation process. Furthermore, we unambiguously demonstrate that the subsequent oxidation of NaO2 of which little is known also proceeds via a solution mechanism. We also provide insight into the cell electrochemistry via the visualization of an outer shell of parasitic reaction product, formed through chemical reaction at the interface between the growing NaO2 cubes and the electrolyte, and suggest that this process is responsible for the poor cyclability of Na–O2 batteries. The assessment of the discharge–charge mechanistic in Na–O2 batteries through operando electrochemical transmission electron microscopy visualization should facilitate the development of this battery technology

Artificial neural network approach for multiphase segmentation of battery electrode nano-CT images

International audienceThe segmentation of tomographic images of the battery electrode is a crucial processing step, which will have an additional impact on the results of material characterization and electrochemical simulation. However, manually labeling X-ray CT images (XCT) is time-consuming, and these XCT images are generally difficult to segment with histographical methods. We propose a deep learning approach with an asymmetrical depth encode-decoder convolutional neural network (CNN) for real-world battery material datasets. This network achieves high accuracy while requiring small amounts of labeled data and predicts a volume of billions voxel within few minutes. While applying supervised machine learning for segmenting real-world data, the ground truth is often absent. The results of segmentation are usually qualitatively justified by visual judgement. We try to unravel this fuzzy definition of segmentation quality by identifying the uncertainty due to the human bias diluted in the training data. Further CNN trainings using synthetic data show quantitative impact of such uncertainty on the determination of material's properties. Nano-XCT datasets of various battery materials have been successfully segmented by training this neural network from scratch. We will also show that applying the transfer learning, which consists of reusing a well-trained network, can improve the accuracy of a similar dataset

Lithium ion battery electrode manufacturing model accounting for 3D realistic shapes of active material particles

The demand for lithium ion batteries (LIBs) in the market has gradually risen, with production increasing and expected to be boosted through the massive emergence of gigafactories. To meet industrial needs, the development of digital twins designed to accelerate the optimization of LIB manufacturing processes is essential. We report here a new three-dimensional physics-based modeling workflow able to predict the influence of manufacturing parameters on the electrode microstructure. This novel modeling workflow accounts for real active material particle shapes obtained from X-ray micro-computed tomography, upgrading our previous models where the particles were considered to be spherical. The modeling workflow is supported on Coarse-Grained Molecular Dynamics simulating the slurry, its drying and the calendering of the electrode resulting from the drying simulation. This model enables to link the manufacturing parameters with the real microstructure of the electrodes and to better observe the effect of the former on the heterogeneity of the electrodes. By using as user case electrodes containing LiNi$_{0.33}$Co$_{0.33}$Mn$_{0.33}$O$_2$ as active material, the simulations allow us, among others, to observe the alteration of the electrode heterogeneity during the manufacturing process and the deformation of the secondary particles of active material

Iron oxide nanoparticle-containing main-chain liquid crystalline elastomer: towards soft magnetoactive networks:

A hybrid polymeric network has been achieved by using pre-functionalized 3.3 nm diameter iron oxide nanoparticles (NPs) as cross-linkers to reticulate mesogenic linear oligomers. A room-temperature smectic mesophase is induced in the network embedding NPs, and the magnetic properties remain almost unchanged, despite substantial changes of the environment around the ferrite cores

Sensitivity of the Inhomogeneous Magnetization Transfer Imaging Technique to Spinal Cord Damage in Multiple Sclerosis

International audienceBACKGROUND AND PURPOSE: The inhomogeneous magnetization transfer technique has demonstrated high specificity for myelin, and has shown sensitivity to multiple sclerosis-related impairment in brain tissue. Our aim was to investigate its sensitivity to spinal cord impairment in MS relative to more established MR imaging techniques (volumetry, magnetization transfer, DTI)

Size-dependent properties of magnetic iron oxide nanocrystals

The fine control of iron oxide nanocrystal sizes within the nanometre scale (diameters range from 2.5 to 14 nm) allows us to investigate accurately the size-dependence of their structural and magnetic properties. A study of the growth conditions of these nanocrystals obtained by thermal decomposition of an iron oleate precursor in high-boiling point solvents has been carried out. Both the type of solvent used and the ligand/precursor ratio have been systematically varied, and were found to be the key parameters to control the growth process. The lattice parameters of all the nanocrystals deduced from X-ray diffraction measurements are consistent with a structure of the type Fe(3-x)O(4), i.e. intermediate between magnetite and maghemite, which evolves toward the maghemite structure for the smallest sizes (x = 1/3). The evolution of the magnetic behavior with nanoparticle sizes emphasizes clearly the influence of the surface, especially on the saturation magnetization M(s) and the magneto-crystalline anisotropy K. Dipolar interactions and thermal dependence have been also taken into account in the study on the nanoscale size-effect of magnetic properties

Binder‐Free Cnt Cathodes for Li‐O 2 Batteries with More Than One Life

Funder: European Union's Horizon 2020Funder: U.S. Department of Energy; doi: http://dx.doi.org/10.13039/100000015Li‐O2 batteries (LOB) performance degradation ultimately occurs through the accumulation of discharge products and irreversible clogging of the porous electrode during the cycling. Electrode binder degradation in the presence of reduced oxygen species can result in additional coating of the conductive surface, exacerbating capacity fading. Herein, a facile method to fabricate free‐standing is established, binder‐free electrodes for LOBs in which multi‐wall carbon nanotubes form cross‐linked networks exhibiting high porosity, conductivity, and flexibility. These electrodes demonstrate high reproducibility upon cycling in LOBs. After cell death, efficient and inexpensive methods to wash away the accumulated discharge products are demonstrated, as reconditioning method. The second life usage of these electrodes is validated, without noticeable loss of performance. These findings aim to assist in the development of greener high energy density batteries while reducing manufacturing and recycling costs