Bamboo-mixer: A Unified Predictive and Generative Solution for Liquid Electrolyte Formulation.
This repository contains the official model of the paper A Unified Predictive and Generative Solution for Liquid Electrolyte Formulation.
Introduction
bamboo-mixer introduces a unified method to not only predict electrolyte properties accurately such as conductivity and anion ratio, but also allows conditional generation of electrolyte formulation based on target properties.
This innovation provides a generative workflow to design molecular mixture beyond electrolyte. The generated samples from the workflow are tested and proved further with experimental validation.
Checkpoints
Folder | Description |
---|---|
ckpts/mono |
Checkpoint used for single-molecule property prediction. |
ckpts/formula |
Checkpoints used for electrolyte property prediction. |
ckpts/generator |
Checkpoints used for conditional generation. |
Datasets
Folder | Description |
---|---|
dataset |
Electrolyte property dataset with conductivity and anion ratio labels |
How to Use
see https://github.com/ByteDance-Seed/bamboo_mixer
Where to send questions or comments about the model: https://github.com/Bytedance-Seed/bamboo_mixer/issues
Citation
If bamboo-mixer is helpful, please help to โญ the repo.
If you find this project useful for your research, please consider citing our paper:
@misc{yang2025unifiedpredictivegenerativesolution,
title={A Unified Predictive and Generative Solution for Liquid Electrolyte Formulation},
author={Zhenze Yang and Yifan Wu and Xu Han and Ziqing Zhang and Haoen Lai and Zhenliang Mu and Tianze Zheng and Siyuan Liu and Zhichen Pu and Zhi Wang and Zhiao Yu and Sheng Gong and Wen Yan},
year={2025},
eprint={2504.18728},
archivePrefix={arXiv},
primaryClass={cond-mat.mtrl-sci},
url={https://arxiv.org/abs/2504.18728},
}