Li dendrite penetration, and associated microcrack propagation, at high current densities is one main challenge to the stable cycling of solid-state batteries. The interfacial decomposition reaction between Li dendrite and a solid electrolyte was recently used to suppress Li dendrite penetration through a novel effect of “dynamic stability”. Here we use a two-parameter space to classify electrolytes and propose that the effect may require the electrolyte to occupy a certain region in the space, with the principle of delicately balancing the two property metrics of a sufficient decomposition energy with the Li metal and a low critical mechanical modulus. Furthermore, in our computational prediction prepared using a combination of high-throughput computation and machine learning, we show that the positions of electrolytes in such a space can be controlled by the chemical composition of the electrolyte; the compositions can also be attained by experimental synthesis using core–shell microstructures. The designed electrolytes following this principle further demonstrate stable long cycling from 10 000 to 20 000 cycles at high current densities of 8.6–30 mA/cm 2 in solid-state batteries, while in contrast the control electrolyte with a nonideal position in the two-parameter space showed a capacity decay that was faster by at least an order of magnitude due to Li dendrite penetration.

Sulfide‐based lithium superionic conductors often show higher Li‐ion conductivity than other types of electrolyte materials. This work unveils a unique Li‐ion conductive behavior in these materials through the perspective of anharmonic coupling assisted Li‐ion diffusion. Li hopping events can happen simultaneously with various types of lattice dynamics, while only a statistically important synchronization of motions may indicate coupling. This method enables a direct evaluation of the coupling strength between these motions, which more fundamentally decides if a specific type of lattice motion is really anharmonically coupled to the Li hopping event and whether the coupling can facilitate the Li diffusion. By a new ab initio computational approach, this work unveils a unique phenomenon in prototype sulfide electrolytes in comparison with typical halide ones, that Li‐ion conduction can be boosted by the anharmonic coupling of low‐frequency Li phonon modes with high‐frequency anion stretching or flexing phonon modes, rather than the low‐frequency rotational modes. The coupling pushes Li ions toward the diffusion channels for reduced diffusion barriers. The result from the lower temperature range (≈0–300 K) of simulation can also be more relevant to the application of solid‐state batteries.

Predicting the performance of rechargeable batteries in real time is of great importance to battery research and industrial production, and hence has been a long pursuit. Previously, sophisticated apparatus is required to measure indicator properties of performance, while machine learning approaches based on feature engineering procedures require a priori expertise that is challenged by the complicated environment of real‐world applications. Here, for a more effective real‐time prediction of battery life and failure, a novel end‐to‐end unsupervised machine learning approach is shown; this approach is free from feature engineering and uses only the raw images of the charge–discharge voltage profiles. This model enables unsupervised real‐time automatic extraction of latent physical factors that control the performance of Na‐ion batteries to classify good or bad cycling performance by using only the voltage profile of the first cycle. This model can also monitor the safety of Li‐metal battery systems by giving warnings when the battery is approaching a failure. With the beyond expert‐level prediction ability, the abovementioned framework can be a promising prototype to further develop and enable high accuracy predictions of battery performance for real‐world applications in the future.

Recently, charge density fluctuations or charge fluxes attract strong interests in understanding the unconventional superconductivity. In this paper, a new emergent configuration in cuprates is identified by density functional theory simulations, called the charge pseudoplane, which exhibits the property of confining the dynamic charge fluxes for higher superconducting transition temperatures. It further redefines the fundamental collective excitation in cuprates as pQon with the momentumdependent and ultrafast localization-delocalization duality. It is shown that both pseudogap and superconducting phases can be born from and intertwined through the charge flux confinement property of the charge pseudoplane region. Our experimental simulations based on the new picture provide good agreements with previous angle resolved photoemission spectroscopy and scanning tunneling microscopy results. Our work thus opens a new perspective into the origin of the pseudogap phase and other related phases in cuprates, and further provides a critical descriptor to search and design higher temperature superconductors.

Layered sodium metal oxide cathodes have much broader choice of transition metal elements than the Li counterparts. A reversible Cu2+/3+ redox couple has recently been introduced in such Na cathodes. To study the role of Cu, here P2‐type layered Na0.75Mn0.6Fe0.2(CuxNi0.2‐x)O2 compounds have been designed, synthesized and investigated. It shows the high initial capacity of 206 mAh/g and good capacity retention. Reversible oxygen redox activity is observed in our experiments. Our DFT calculations suggest that Cu can stabilize the oxygen redox by modifying the electronic structure together with Fe at high voltages. In addition, the strong P′2 transition observed at low voltages is induced by Jahn‐Teller active Cu2+ with two competing effects of enhanced Na ion diffusivity and reduced electronic conductivity.