## 3 Results  
### Dataset Analysis  
Table 1 presents a comparative analysis between our target electrolyte dataset and datasets from other studies in different domains. The performance of the NPVAE model, which focuses on natural products, was validated in previous studies through experiments on two datasets: the Polymer Evaluation dataset and the Natural Product dataset [54; 58]. The NPVAE model evaluated its reconstruction performance using the Polymer dataset and assessed its generative capability on more complex natural products by utilizing the Drugbank dataset along with a separately collected Drug-and-Natural-Product dataset. The Natural Product dataset and the Polymer dataset consist of relatively large and complex molecules compared to the organic molecule dataset QM9 [59], as presented in Table 1. This comparison helps identify differences in dataset size and the distribution of molecular complexity between the electrolyte dataset and those used in other studies. The molecular weight and HOMO/LUMO distributions of four datasets--the Natural Product dataset, the Polymer dataset, the QM9 dataset comprising large organic molecules, and the Custom Electrolyte dataset consisting of potential electrolyte candidates--were compared. The QM9 dataset contains organic molecules from a wide range of domains, the Polymer dataset focuses on novel materials for solar cell development, and the Drug-and-Natural-Product dataset is centered on drug and natural product molecules.  
The QM9 dataset contains the largest number of molecular data points but has the narrowest molecular weight range. This suggests that, compared to the QM9 dataset, the other datasets include a smaller absolute number of molecular data points but encompass a more diverse range of molecules. However, the electrolyte dataset is specifically designed to include strong candidate molecules for the development of lithium-ion battery electrolytes, which is the primary objective of this study.  
Figure 3 illustrates the distribution of HOMO/LUMO values for molecules in the QM9 dataset(blue) and the Electrolyte dataset(red). Although the QM9 dataset contains approximately 8 times more molecular data, the Electrolyte dataset demonstrates a greater diversity in the distribution of HOMO/LUMO values. The QM9 dataset has a larger number of data points compared to the red electrolyte dataset, but its distribution is concentrated within a narrower range. On the other hand, the electrolyte dataset is evenly distributed across a wider range. This indicates that the electrolyte dataset consists of more diverse molecules tailored to electrolyte characteristics compared to the QM9.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Dataset** & \begin{tabular}{c} **Minimum** \\ **(Min)** \\ \end{tabular} & \
\begin{tabular}{c} **Maximum** \\ **(Max)** \\ \end{tabular} &
\begin{tabular}{c} **Average** \\ **(Avg)** \\ \end{tabular} & **Molecules** \\ \hline QM9 & 16 & 152 & 122 & 133,885 \\ Polymer & 83 & 1768 & 766 & 17,124 \\ Drug-and-Natural-Product & 3 & 8272 & 379 & 10,597 \\ Electrolyte & 9 & 705 & 183 & 17,271 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of molecular weight distributions across datasets.