Theoretical calculations enable scientific breakthroughs

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.

Interfacial water is a core foundation for reactions in electrocatalysis. Today, this article introduces a classic work frequently mentioned in the field of interfacial water—an article published in Nature in 2021 by Professor Li Jianfeng's team. The article focuses on interfacial water on single-crystal Pd surfaces under HER conditions, innovatively combining in-situ SHINERS Raman spectroscopy, single-crystal electrochemistry, and theoretical calculations. For the first time, it directly observes the structural change of interfacial water from disorder to order at actual reaction potentials, and further connects this change to the interfacial interaction of Na⁺, the water dissociation process, and HER activity.

Many electrolyte research papers, on the surface, seem to focus on just one thing: changing a solvent molecule.

However, those that truly get published in high-level journals are rarely as simple as "I changed the molecule, so the performance is better." Rather, they demonstrate whether the authors can elevate this molecular change to a new structural concept, a new interface mechanism, and a complete, verifiable chain of theoretical calculations.

In battery research, the construction of coatings, such as artificial solid electrolyte interfaces (ASEI) or porous framework coatings on electrode surfaces, is a popular research topic.

To thoroughly explain the mechanism of action of coatings in an article, molecular dynamics (MD) simulations are an indispensable tool. It is worth noting that the focus of MD calculations differs depending on the pore size. This article, based on five high-level papers, extracts the MD calculations of coatings into two core physical dimensions according to the material's pore size:

● Microporous systems (pore size < 1 nm): Focusing on desolvation barriers and the "dynamic shuttle" of ions within the coating.

● Mesoporous and hierarchical pore systems (pore size > 2 nm): Focusing on local solvation structures, long-range diffusion behavior, and the synergistic effect of hierarchical channels.

Anyone who has used agencies to perform electrolyte kinetic simulations knows that calculating the molecular dynamics (MD) of an electrolyte typically costs several times more than calculating binding energy, electrostatic potential, adsorption energy, and other parameters.

Many people think that MD simulation is simply running a testing software program—you input molecules, click "Run," and get the graph. However, in reality, there's a lot of preparatory work required before "Running." How much work is involved, what data needs to be prepared before hiring someone to perform the calculation, and what results can you get afterward? This article will provide a detailed explanation.