Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.

Nitrogen-doped graphitic carbon materials hosting single-atom iron (Fe-N-C) are major non-precious metal catalysts for the oxygen reduction reaction (ORR). The nitrogen-coordinated Fe sites are described as the first coordination sphere. As opposed to the good performance in ORR, that in the oxygen evolution reaction (OER) is extremely poor due to the sluggish O-O coupling process, thus hampering the practical applications of rechargeable zinc (Zn)-air batteries. Herein, we succeed in boosting the OER activity of Fe-N-C by additionally incorporating phosphorus atoms into the second coordination sphere, here denoted as P/Fe-N-C. The resulting material exhibits excellent OER activity in 0.1 M KOH with an overpotential as low as 304 mV at a current density of 10 mA cm^-2. Even more importantly, they exhibit a remarkably small ORR/OER potential gap of 0.63 V. Theoretical calculations using first-principles density functional theory suggest that the phosphorus enhances the electrocatalytic activity by balancing the *OOH/*O adsorption at the FeN₄ sites. When used as an air cathode in a rechargeable Zn-air battery, P/Fe-N-C delivers a charge-discharge performance with a high peak power density of 269 mW cm^-2, highlighting its role as the state-of-the-art bifunctional oxygen electrocatalyst.

Batteries are the most widely used energy storage devices, and the lithium‐ion battery is the most heavily commercialized and most widely used battery type in the industry. However, the current rapid development of society requires a major advancement in battery materials to achieve high capacity, long life cycle, low cost, and reliable safety. Therefore, many new efficient energy storage materials and battery systems are being developed and explored, and their working mechanisms must be clearly understood before industrial application. In recent years, density functional theory (DFT) has been employed in the energy storage field and has made significant contributions to the understanding of electrochemical reaction mechanisms and to virtual screening of promising energy storage materials. In this review, the applications of DFT to battery materials are summarized and exemplified by some representative and up‐to‐date studies in the literature. The main focuses in this review include the following: 1) structural stability estimation by cohesive energy, formation energy, Gibbs free energy, and phonon dispersion spectra calculations; 2) the Gibbs free energy calculations for electrochemical reactions, corresponding open‐circuit voltage, and theoretical capacity predictions of batteries; 3) the analyses of molecule orbitals, band structures, density of states (DOS), and charge distribution of battery materials; 4) ion transport kinetics in battery materials; 5) simulations of adsorption processes. We conclude the review with the discussion of the assessments and validation of the popular functionals against several benchmarks, and a few suggestions have been given for the selection of density functionals for battery material systems.

The long-standing issue of lithium dendrite growth during repeated deposition or dissolution processes hinders the practical use of lithium-metal anodes for high-energy density batteries. Here, we demonstrate a promising lithiophilic–lithiophobic gradient interfacial layer strategy in which the bottom lithiophilic zinc oxide/carbon nanotube sublayer tightly anchors the whole layer onto the lithium foil, facilitating the formation of a stable solid electrolyte interphase, and prevents the formation of an intermediate mossy lithium corrosion layer. Together with the top lithiophobic carbon nanotube sublayer, this gradient interfacial layer can effectively suppress dendrite growth and ensure ultralong-term stable lithium stripping/plating. This strategy is further demonstrated to provide substantially improved cycle performance in copper current collector, 10 cm² pouch cell and lithium–sulfur batteries, which, coupled with a simple fabrication process and wide applicability in various materials for lithium-metal protection, makes the lithiophilic–lithiophobic gradient interfacial layer a favored strategy for next-generation lithium-metal batteries.

It is a considerably promising strategy to produce fuels and high‐value chemicals through an electrochemical conversion process in the green and sustainable energy systems. Catalysts for electrocatalytic reactions, including hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), nitrogen reduction reaction (NRR), carbon dioxide reduction reaction (CO₂RR), play a significant role in the advanced energy conversion technologies, such as water splitting devices, fuel cells, and rechargeable metal‐air batteries. Developing low‐cost and highly efficient electrocatalysts is closely related to establishing the composition–structure–activity relationships and fundamental understanding of catalytic mechanisms. Density functional theory (DFT) is emerging as an important computational tool that can provide insights into the relationship between the electrochemical performances and physical/chemical properties of catalysts. This article presents a review on the progress of the DFT, and the computational simulations, within the framework of DFT, for the electrocatalytic processes, as well as the computational designs and virtual screenings of new electrocatalysts. Some useful descriptors and analysis tools for evaluating the electrocatalytic performances are highlighted, including formation energies, d‐band model, scaling relation, e_g orbital occupation, and free energies of adsorption. Furthermore, the remaining questions and perspectives for the development of DFT for electrocatalysis are also proposed.