Theoretical calculations enable scientific breakthroughs

In aqueous batteries, Prussian blue and its analogues (PBA/PBAs) are very attractive: open structure, rapid diffusion, and low cost. However, in actual battery applications, many systems exhibit significant capacity degradation within a few dozen cycles. One common reason is the dissolution of transition metals: once metal ions like Mn/Fe begin to enter the electrolyte, the framework gradually becomes hollow/defective, causing a simultaneous drop in capacity and voltage plateau.

This 2022 ACS Energy Letters work may not be "new" in itself, but it demonstrates how to use theoretical calculations to break down experimental phenomena into essential microscopic dynamic steps and clearly reveal the mechanism using quantifiable indicators.

Theoretical calculations are an essential part of publishing papers, but producing good calculation results is only the first step. What impresses editors, reviewers, and readers is often the ability to organize complex physical images into a clear, beautiful, and logical diagram. In this issue, we've selected eight examples of computational graphs published in top journals such as Nature and Nature Energy, focusing on their strengths in graphic layout, color schemes, mechanism representation, and the integration of data and diagrams. We'll see how DFT, AIMD, MD, CI-NEB, COMSOL, or machine learning results can be transformed into more aesthetically pleasing, sophisticated, and publishable research graphs.

In battery development, experimental testing can tell us about macroscopic polarization and rate performance; however, how ions move within the membrane pores/interfaces often requires molecular dynamics (MD) to "see and explain."

In battery membrane research, MD primarily undertakes three core tasks:

1. Visualizing transport paths: Visualizing the abstract "ion channels," intuitively showing whether ions creep along polymer chains or diffuse freely in water-filled channels.

2. Quantifying selectivity mechanisms: Calculating the migration rate and flux ratio of different ions in the membrane through non-equilibrium (NEMD) simulations of applied external fields, directly quantifying membrane selectivity.

3. Analyzing solvation effects: Accurately calculating the coordination number of ions, revealing the energy cost of "desolvation" or "water-carrying migration."