| Type | Group | Date | Project | Link | |
| XAS | Maria Chan; Miaofang Chi | 2026-08-12 15:40 | Revealing Local Structures through Machine-Learning-Fused Multimodal Spectroscopy | same cell | |
| TEM | Maria Chan; Miaofang Chi | 2026-08-12 15:40 | Revealing Local Structures through Machine-Learning-Fused Multimodal Spectroscopy | same cell | |
| DFT | Maria Chan; Miaofang Chi | 2026-08-12 15:40 | Revealing Local Structures through Machine-Learning-Fused Multimodal Spectroscopy | same cell |
| Material | Family | Role(s) | Ion |
|
LiNi0.8Mn0.1Co0.1O2
· NMC811
Including oxygen-vacancy and antisite-defect structures; EELS and XAS multimodal ML
|
Layered oxide
Cathode
|
Cathode | Li |
| LiNi0.7Mn0.2Co0.1O2 · NMC721 |
Layered oxide
Cathode
|
Cathode | Li |
| LiNi0.6Mn0.2Co0.2O2 · NMC622 |
Layered oxide
Cathode
|
Cathode | Li |
Declared for sample 2026_HailiJia_MariaChan_ACS.Nano_5c16942 — shared by every dataset on this sample.
| Model Name | XGBoost |
| Model Type | Trained using simulated XAS and applied to experimental data |
| Visibility | public |
| Publication Doi | 10.1021/acsnano.5c16942 |
| Institution Code | ESRA |
| Target Properties | Li content (regression); local coordination environment (classification); oxygen vacancy detection; Ni/Li antisite detection |
| Dft Training Level | SCAN+U for DFT, PBE for XAS |
| Training Dataset Name | NMC_fdmnes.json |
| Training Dataset Size | 851 structures, 35570 sites in total |