First-Principles Study of Structural Transitions in LiNiO₂ and High-Throughput Screening for Long Life Battery

Abstract

Herein, we performed ab initio screening to identify the best doping of LiNiO2 to achieve improved cycle performance in lithium ion batteries. The interlayer interaction that dominates the c-axis contraction and overall performance was captured well by density functional theory using van der Waals exchange-correlation functionals. The screening indicated that Nb-doping is promising for improving cycle performance. To extract qualitative reasonings, we performed data analysis in a materials informatics manner to obtain a reasonable regression to reproduce the obtained results. LASSO analysis implied that the charge density between the layers in the discharged state is the dominant factor influencing cycle performance.

Modeling the Solid Electrolyte Interphase: Machine Learning as a Game Changer?

“…[315][316][317] Both of them have been successfully used in the materials science community and batteries as well. [22,318,319] In ML model development, we compromise between accuracy and explainability. Most accurate models (e.g., deep neural networks) are the least explainable, and the most explainable models (e.g., linear regression) have low accuracy.…”

Synergy of Binary Substitutions for Improving the Cycle Performance in LiNiO2 Revealed by Ab Initio Materials Informatics

“…Although there are several possi- bilities for doping positions and a delithiated structure for each substitution, only the most stable structure is chosen by comparing their energies. According to our previous study 37 , the cycle performance strongly correlates with the c-axis contraction, which is measured by the following quantity:…”

“…Very recently, we have investigated which unary substitutions improve the LNO cathode by computational screening. 37 Our findings are as follows: (i) DFT simulations must incorporate van der Waals (vdW) corrections in exchangecorrelation functionals adopted in order to describe the structural changes during electrochemical cycling; (ii) caxis contraction is more essential for the cycle characteristics; (iii) our descriptor analysis based on sparse modeling elucidates important descriptors correlating with the contraction. Finally, our AIMI approach indicated that Nb is the most promising candidate for the substitute element.…”

Two‐step solvothermal synthesis of high capacity LiNi0.8Co0.15Al0.05O2 cathode for Li‐ion batteries

“…Li-ion batteries (LIB) are characterized by long cycle life, high safety, high working voltage, and high capacity, which makes LIB applied to electric vehicles, portable electronics, defense industry, and has quickly become a hot topic for scientists in recent years. [3][4][5][6][7][8] Recently, studies on cathode materials for LIB are mainly focused on layered material (LiCoO 2 , [9,10] LiNiO 2 [11,12] ), spinel-type material (LiMn 2 O 4 ), [13,14] and olivine-type material (LiFePO 4 ). [15,16] The structural stability, working voltage range, and cycle performance of these cathode materials are greatly improved by cation doping and surface coating.…”

“…Recently, studies on cathode materials for LIB are mainly focused on layered material (LiCoO 2 , [ 9,10 ] LiNiO 2 [ 11,12 ] ), spinel‐type material (LiMn 2 O 4 ), [ 13,14 ] and olivine‐type material (LiFePO 4 ). [ 15,16 ] The structural stability, working voltage range, and cycle performance of these cathode materials are greatly improved by cation doping and surface coating.…”