Introduction

This work is mainly focused on the essential physical, chemical, and material properties and special functionalities of certain batteries, including the important theoretical simulations and high-resolution experimental measurements. Concerning lithium-ion batteries (LIBs), the first-principles method (VASP calculations) and the machine learning (the SMILES format combined with the neural network) are available in fully exploring the diversified phenomena of cathode, anode, and electrolyte (solid and liquid states). Part of theoretical predictions is consistent with the measured results. As for the high-technique experiments, they are utilized to efficiently synthesize the anode (un-doped/doped/porous graphenes and nanocarbons) and electrolyte (gel polymer and ionic liquid (IL)) materials of LIBs, silicon (Si)-nanowire-based hybrid solar cells, and perovskite ones. How to greatly enhance their performance is investigated in detail. The emergent issues are under the current studies.