Fast charging is considered to be a key requirement for widespread economic success of electric vehicles. Current lithium‐ion batteries (LIBs) offer high energy density enabling sufficient driving range, but take considerably longer to recharge than traditional vehicles. Multiple properties of the applied anode, cathode, and electrolyte materials influence the fast‐charging ability of a battery cell. In this review, the physicochemical basics of different material combinations are considered in detail, identifying the transport of lithium inside the electrodes as the crucial rate‐limiting steps for fast‐charging. Lithium diffusion within the active materials inherently slows down the charging process and causes high overpotentials. In addition, concentration polarization by slow lithium‐ion transport within the electrolyte phase in the porous electrodes also limits the charging rate. Both kinetic effects are responsible for lithium plating observed on graphite anodes. Conclusions drawn from potential and concentration profiles within LIB cells are complemented by extensive literature surveys on anode, cathode, and electrolyte materials—including solid‐state batteries. The advantages and disadvantages of typical LIB materials are analyzed, resulting in suggestions for optimum properties on the material and electrode level for fast‐charging applications. Finally, limitations on the cell level are discussed briefly as well.

The critical role in surface reactions and heterogeneous catalysis of metal atoms with low coordination numbers, such as found at atomic steps and surface defects, is firmly established. But despite the growing availability of tools that enable detailed in situ characterization, so far it has not been possible to document this role directly. Surface properties can be mapped with high spatial resolution, and catalytic conversion can be tracked with a clear chemical signature; however, the combination of the two, which would enable high-spatial-resolution detection of reactions on catalytic surfaces, has rarely been achieved. Single-molecule fluorescence spectroscopy has been used to image and characterize single turnover sites at catalytic surfaces, but is restricted to reactions that generate highly fluorescing product molecules. Herein the chemical conversion of N-heterocyclic carbene molecules attached to catalytic particles is mapped using synchrotron-radiation-based infrared nanospectroscopy with a spatial resolution of 25 nanometres, which enabled particle regions that differ in reactivity to be distinguished. These observations demonstrate that, compared to the flat regions on top of the particles, the peripheries of the particles-which contain metal atoms with low coordination numbers-are more active in catalysing oxidation and reduction of chemically active groups in surface-anchored N-heterocyclic carbene molecules.

This paper presents the computer program D+ (https://scholars.huji.ac.il/ uriraviv/book/d-0), where the reciprocal-grid (RG) algorithm is implemented. D+ efficiently computes, at high-resolution, the X-ray scattering curves from complex structures that are isotropically distributed in random orientations in solution. Structures are defined in hierarchical trees in which subunits can be represented by geometric or atomic models. Repeating subunits can be docked into their assembly symmetries, describing their locations and orientations in space. The scattering amplitude of the entire structure can be calculated by computing the amplitudes of the basic subunits on 3D reciprocal-space grids, moving up in the hierarchy, calculating the RGs of the larger structures, and repeating this process for all the leaves and nodes of the tree. For very large structures (containing over 100 protein subunits), a hybrid method can be used to avoid numerical artifacts. In the hybrid method, only grids of smaller subunits are summed and used as subunits in a direct computation of the scattering amplitude. D+ can accurately analyze both small-and wide-angle solution X-ray scattering data. This article describes how D+ applies the RG algorithm, accounts for rotations and translations of subunits, processes atomic models, accounts for the contribution of the solvent as well as the solvation layer of complex structures in a scalable manner, writes and accesses RGs, interpolates between grid points, computes numerical integrals, enables the use of scripts to define complicated structures, applies fitting algorithms, accounts for several coexisting uncorrelated populations, and accelerates computations using GPUs. D+ may also account for different X-ray energies to analyze anomalous solution X-ray scattering data. An accessory tool that can identify repeating subunits in a Protein Data Bank file of a complex structure is provided. The tool can compute the orientation and translation of repeating subunits needed for exploiting the advantages of the RG algorithm in D+. A Python wrapper (https://scholars. huji.ac.il/uriraviv/book/python-api) is also available, enabling more advanced computations and integration of D+ with other computational tools. Finally, a large number of tests are presented. The results of D+ are compared with those of other programs when possible, and the use of D+ to analyze solution scattering data from dynamic microtubule structures with different protofilament number is demonstrated. D+ and its source code are freely available for academic users and developers (https://bitbucket.org/uriraviv/public-dplus/src/ master/).

Ni-rich layered oxide LiNi1 – x – y Co x Mn y O2 (1 – x – y > 0.5) materials are favorable cathode materials in advanced Li-ion batteries for electromobility applications because of their high initial discharge capacity. However, they suffer from poor cycling stability because of the formation of cracks in their particles during operation. Here, we present improved structural stability, electrochemical performance, and thermal durability of LiNi0.85Co0.1Mn0.05O2(NCM85). The Nb-doped cathode material, Li­(Ni0.85Co0.1Mn0.05)0.997Nb0.003O2, has enhanced cycling stability at different temperatures, outstanding capacity retention, improved performance at high discharge rates, and a better thermal stability compared to the undoped cathode material. The high electrochemical performance of the doped material is directly related to the structural stability of the cathode particles. We further propose that Nb-doping in NCM85 improves material stability because of partial reduction of the amount of Jahn–Teller active Ni3+ ions and formation of strong bonds between the dopant and the oxygen ions, based on density functional theory calculations. Structural studies of the cycled cathodes reveal that doping with niobium suppresses the formation of cracks during cycling, which are abundant in the undoped cycled material particles. The Nb-doped NCM85 cathode material also displayed superior thermal characteristics. The coherence between the improved electrochemical, structural, and thermal properties of the doped material is discussed and emphasized.

<div>In this paper, we present our new computer program, D+, which uses the reciprocal-grid (RG) algorithm to efficiently compute X-ray scattering curves from solutions of complex structures at high-resolution. Structures are defined in hierarchical trees in which subunits can be represented by geometric or atomic models. Repeating subunits can be docked into their assembly symmetries, describing their locations and orientations in space. The scattering amplitude of the entire structure can be calculated by computing the amplitudes of the basic subunits on 3D reciprocal-space grids, moving up in the hierarchy, calculating the RGs of the larger structures, and by repeating this process for all the leaves and nodes of the tree. For very large structures, a Hybrid method can be used to avoid numerical artifacts. In the Hybrid method, only grids of smaller subunits are summed and used as subunits in a direct computation of the scattering amplitude. D+ can accurately analyze both small- and wide-angle solution X-ray scattering data. We present how D+ applies the RG algorithm, accounts for rotations and translations of subunits, processes atomic models, accounts for the contribution of the solvent as well as the solvation layer of complex structures in a scalable manner, writes and accesses RGs, interpolates between grid points, computes numerical integrals, enables the use of scripts to define complicated structures, applies fitting algorithms, accounts for several coexisting uncorrelated populations, and accelerates computations using GPUs. D+ may also account for different X-ray energies to analyze anomalous solution X-ray scattering data. An accessory tool that can identify repeating subunits in a protein data bank (PDB) file of a complex structure is provided. The tool can compute the orientation and translation of repeating subunits needed for exploiting the advantages of the RG algorithm in D+. In addition, a python wrapper is also available, enabling more advanced computations and integration of D+ with other computational tools. Finally, we present a large number of tests and compare the results of D+ with other programs when possible and demonstrate the use of D+ to analyze solution scattering data from dynamic microtubule structures with different protofilament number. D+ and its source code are freely available (https://scholars.huji.ac.il/uriraviv/software/d-software) for academic users and developers. </div>