A deep neural network is constructed to yield in principle exact exchange–correlation potential. It requires merely the electron densities of small molecules and ions and yet can determine the exchange–correlation potentials of large molecules. We train and validate the neural network based on the data for H2 and HeH+ and subsequently determine the ground-state electron density of stretched HeH+, linear H3 +, and H–He–He–H2+. Moreover, the deep neural network is proven to model the van der Waals interaction by being trained and validated on a data set containing He2. Comparisons to B3LYP are given to illustrate the accuracy and transferability of the neural network.

Electrochemical conversion of nitrate to ammonia offers an efficient approach to reducing nitrate pollutants and a potential technology for low-temperature and low-pressure ammonia synthesis. However, the process is limited by multiple competing reactions and NO3− adsorption on cathode surfaces. Here, we report a Fe/Cu diatomic catalyst on holey nitrogen-doped graphene which exhibits high catalytic activities and selectivity for ammonia production. The catalyst enables a maximum ammonia Faradaic efficiency of 92.51% (−0.3 V(RHE)) and a high NH3 yield rate of 1.08 mmol h−1 mg−1 (at − 0.5 V(RHE)). Computational and theoretical analysis reveals that a relatively strong interaction between NO3− and Fe/Cu promotes the adsorption and discharge of NO3− anions. Nitrogen-oxygen bonds are also shown to be weakened due to the existence of hetero-atomic dual sites which lowers the overall reaction barriers. The dual-site and hetero-atom strategy in this work provides a flexible design for further catalyst development and expands the electrocatalytic techniques for nitrate reduction and ammonia synthesis.

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Aqueous zinc ion batteries (AZIBs) with high safety, low cost, and eco‐friendliness advantages show great potential in large‐scale energy storage systems. However, their practical application is hindered by low Columbic efficiency and unstable zinc anode resulting from the side reactions and deterioration of zinc dendrites. Herein, tripropylene glycol (TG) is chosen as a dual‐functional organic electrolyte additive to improve the reversibility of AZIBs significantly. Importantly, ab initio molecular dynamics theoretical simulations and experiments such as in situ electrochemical impedance spectroscopy, and synchrotron radiation‐based in situ Fourier transform infrared spectroscopy confirm that TG participates in the solvation sheath of Zn2+, regulating overpotential and inhibiting side reactions; meanwhile, TG inhibits the deterioration of dendrites and modifies the direction of zinc deposition by constructing an adsorbed layer on the zinc anode. Consequently, a Zn‐MnO2 full cell with TG electrolyte exhibited a specific capacity of 124.48 mAh g‐1 after 1000 cycles at a current density of 4 A g‐1. This quantitative regulation for suitable solvation sheath and adsorbed layer on zinc anode, and its easy scalability of the process can be of immediate benefit for the dendrite‐free, high‐performance, and low‐cost energy storage systems.