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A stable lithium‐metal electrode can enable the shift from the Li‐ion batteries to the next generation chemistries such as Li−S and Li−O2 with significant gains in the energy density and sustainability. This transition, however, is hindered by the dendrite formation, high chemical reactivity, and volume changes of the Li electrode. Although recent advancements in computational and experimental research have deepened our understanding of these issues, the primary obstacles to the commercialization of the lithium‐metal batteries (LMBs) still persist. To address these challenges, a synergistic approach that combines computational and experimental strategies shows great promise. In this regard, this paper reviews the current experimental and theoretical understanding of the lithium‐metal electrodes in view of the initiation and growth mechanisms of the lithium dendrites and interface instability. Leveraging the strengths of both approaches can offer a holistic insight into the LMB performance and guide the development of innovative designs for electrolytes and electrodes that can enhance the stability and performance of the LMBs. [ABSTRACT FROM AUTHOR]

The performance sensitivity of the solid‐state lithium cells to the synergistic interactions of the charge‐transport and mechanical properties of the electrolyte is well acknowledged in the literature, but the quantitative insights therein are very limited. Here, the charge‐transport and mechanical properties of a polymerized ionic‐liquid‐based solid electrolyte are reported. The transference number and diffusion coefficient of lithium in the concentrated solid electrolyte are measured as a function of concentration and stack pressure. The elastoplastic behavior of the electrolyte is quantified under compression, within a home‐made setup, to substantiate the impact of stack pressure on the stability of the Li/electrolyte interface in the symmetric lithium cells. The results spotlight the interaction between the concentration and thickness of the solid electrolyte and the stack pressure in determining the polarization and stability of the solid‐state lithium batteries during extended cycling. [ABSTRACT FROM AUTHOR]

The Incremental Capacity (IC) is a rich source of data for the state‐of‐health estimation of lithium‐ion batteries. This data is typically collected during a low C‐rate (dis)charge of the battery which is not representative of many real‐world applications outside the research laboratories. Here, this limitation is showcased to be mitigated by employing a new feature‐extraction technique applied to a large dataset including 105 batteries with cycle lives ranging from 158 to 1637 cycles. The state‐of‐health of these batteries is successfully predicted with a mean‐absolute‐percentage error below 0.7 % by using three regression models of support vector regressor, multi‐layer perceptron, and random forest. The methodologies proposed in this work facilitate the development of accurate IC‐based state‐of‐health predictors for lithium‐ion batteries in on‐board applications. [ABSTRACT FROM AUTHOR]

A combination of experiments and physics‐based modeling is used to highlight the complex interaction among the adjustable design parameters of porous electrodes in determining the capacity and rate performance of lithium‐ion batteries (LIBs). A series of 52 LiMn2O4 electrodes are prepared with loading and porosity in the range of 10 to 30 mg cm−2 and 0.2 to 0.5, respectively, and cycled at different C‐rates in front of Li. A detailed polarization analysis of the 96 discharge profiles points to the absence of any ubiquitous sharp and universal correlation between the lumped macroscopic indexes such as the electrode thickness and the battery performance. The results call for a careful attention to the nonlinear response of the LIBs to the design variations and the significance of big data analysis to reveal the peculiar interrelationships between the battery performance and the detailed features of the electrodes such as the configuration and spatial distribution of the (in)active particles. [ABSTRACT FROM AUTHOR]

A possible strategy to give a simultaneous boost to the energy and power attributes of the current generation of lithium‐ion batteries is developing thick porous electrodes with a high loading of active material alongside optimal percolation networks for the ions and electrons. However high the insertion capacity and kinetics of the single particle lithium‐insertion materials, the energy and power density of the cell can be capped by the ionic and electronic transport limitations in the porous electrode. In this work, a physical picture grounded in experiment and theory is proposed to spotlight and quantify the pivotal role of the micro‐scale porosity and active‐material loading in determining the tortuosity, effective transport properties, and performance limitations of porous electrodes. The outcome is a phenomenological picture coupled with a theoretical framework for the deconvolution of the relative shares of the electronic and ionic transport limitations over short and long ranges regarding the performance limitation of lithium‐ion batteries. [ABSTRACT FROM AUTHOR]

Cover Feature: An Incremental Capacity Analysis-based State-of-health Estimation Model for Lithium-ion Batteries in High-power Applications (Batteries & Supercaps 9/2023) Battery, incremental capacity, state of health Keywords: battery; incremental capacity; state of health EN battery incremental capacity state of health 1 1 1 09/11/23 20230901 NES 230901 B The Cover Feature b illustrates the crucial role of the battery storage systems in the energy transition towards the smart cities. [Extracted from the article]

Liposomes are known to be promising nanoparticles (NPs) for drug delivery applications. Among the different types of self-assembled NPs, liposomes stand out for their non-toxic nature and their possession of dual hydrophilic-hydrophobic domains. The advantages of liposomes include the ability to solubilize hydrophobic drugs, the ability to incorporate different hydrophilic and lipophilic drugs at the same time, lessening the exposure of host organs to potentially toxic drugs and allowing modification of the surface by a variety of different chemical groups. This modification of the surface, or of the individual constituents, may be used to achieve two important goals. First, ligands for active targeting can be attached that are recognized by cognate receptors overexpressed on the target cells of tissues. Second, modification can be used to impart a stimulus-responsive or “smart” character to the liposomes, whereby the cargo is released on demand only when certain internal stimuli (pH, reducing agents, specific enzymes) or external stimuli [light, magnetic field, or ultrasound (US)] are present. Here, we review the field of smart liposomes for drug delivery applications. [ABSTRACT FROM AUTHOR]

A novel method for characterizing and visualizing the progression of waves along the walls of the carotid artery is presented. The new approach is noninvasive and able to simultaneously capture the spatial and the temporal propagation ofwavy patterns along the walls of the carotid artery in a completely automatedmanner. Spatiotemporal and spatiospectral 2Dmaps describing these patterns (in both the spatial and the frequency domains, resp.) were generated and analyzed by visual inspection as well as automatic feature extraction and classification. Three categories of cases were considered: pathological elderly, healthy elderly, and healthy young cases. Automatic differentiation, between cases of these three categories, was achieved with a sensitivity of 97.1% and a specificity of 74.5%. Two features were proposed and computed to measure the homogeneity of the spatiospectral 2D map which presents the spectral characteristics of the carotid arterywall'swavymotion patternwhich are related to the physical, mechanical (e.g., elasticity), and physiological properties and conditions along the artery. These results are promising and confirmthe potential of the proposed method in providing useful information which can help in revealing the physiological condition of the cardiovascular system. [ABSTRACT FROM AUTHOR]

Purpose – The aim of the research project which resulted in this work is to achieve a cost-effective approach for instantaneous hyperspectral imaging. Design/methodology/approach – This paper presents a simulation study and an experimental evaluation of a novel imaging spectroscopy technique, where multi-channel image data are acquired instantaneously and transformed into spectra by using a statistical modelling approach. A digital colour camera equipped with an additional colour filter array was used to acquire an instantaneous single image that was demosaicked to generate a multi-channel image. A statistical transformation approach was employed to convert this image into a hyperspectral one. Findings – The feasibility of this method was investigated through extensive simulation and experimental tasks where promising results were obtained. Practical implications – The small size of the initially acquired single instantaneous image makes this approach useful for applications where video-rate hyperspectral imaging is required. Originality/value – For the first time, a simplified prototype of this novel imaging spectroscopy technique was built and evaluated experimentally. And the results were compared with those of a more ideal simulation study. Recommendations for how to improve the prototype were also suggested as a result of the comparison between the simulation and the prototype evaluation results. [ABSTRACT FROM AUTHOR]

A new method proposed and coined by the authors as the homo-separation of variables method is utilized to solve systems of linear and nonlinear fractional partial differential equations (FPDEs). The new method is a combination of two well-established mathematical methods, namely, the homotopy perturbation method (HPM) and the separation of variables method. When compared to existing analytical and numerical methods, the method resulting from our approach shows that it is capable of simplifying the target problem at hand and reducing the computational load that is required to solve it, considerably. The efficiency and usefulness of this new general-purpose method is verified by several examples, where different systems of linear and nonlinear FPDEs are solved. [ABSTRACT FROM AUTHOR]

This paper presents a sensitivity analysis of using instantaneous multichannel two-dimensional (2D) imaging to achieve instantaneous 2D imaging spectroscopy. A simulated multiple-filter mosaic was introduced and used to acquire multichannel data which were transformed into spectra. The feasibility of two different transformation approaches (the concrete pseudoinverse approach and a statistical approach) was investigated through extensive experimental tasks. A promising statistical method was identified to be used for accurate estimation of spectra from multichannel data. Comparison between estimated and measured spectra shows that higher estimation accuracy can be achieved when using a larger number of usable multiple-filter combinations in the mosaic. [ABSTRACT FROM AUTHOR]

A new more efficient variant of a recently developed algorithm for unsupervised fuzzy clustering is introduced. A Weighted Incremental Neural Network (WINN) is introduced and used for this purpose. The new approach is called FC-WINN (Fuzzy Clustering using WINN). The WINN algorithm produces a net of nodes connected by edges, which reflects and preserves the topology of the input data set. Additional weights, which are proportional to the local densities in input space, are associated with the resulting nodes and edges to store useful information about the topological relations in the given input data set. A fuzziness factor, proportional to the connectedness of the net, is introduced in the system. A watershed-like procedure is used to cluster the resulting net. The number of the resulting clusters is determined by this procedure. Only two parameters must be chosen by the user for the FC-WINN algorithm to determine the resolution and the connectedness of the net. Other parameters that must be specified are those which are necessary for the used incremental neural network, which is a modified version of the Growing Neural Gas algorithm (GNG). The FC-WINN algorithm is computationally efficient when compared to other approaches for clustering large high-dimensional data sets. [ABSTRACT FROM AUTHOR]

Porous Electrodes: Demystifying Charge Transport Limitations in the Porous Electrodes of Lithium-Ion Batteries (Adv. Keywords: charge transport; heterogeneity; lithium-ion batteries; porous electrodes EN charge transport heterogeneity lithium-ion batteries porous electrodes 1 1 1 12/17/20 20201215 NES 201215 In article number 2002492, Mohammadhosein Safari and co-workers discuss the impact of formulation on the effective charge-transport properties of porous electrodes. Charge transport, heterogeneity, lithium-ion batteries, porous electrodes. [Extracted from the article]