bamboo_mixer

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.

<p align="center"> <a href="https://arxiv.org/abs/2504.18728"> <img alt="Build" src="https://img.shields.io/badge/arXiv-2504.18728-b31b1b.svg"> </a> <a href="https://github.com/ByteDance-Seed/bamboo_mixer"> <img alt="Github" src="https://img.shields.io/badge/GitHub-Code-darkgreen.svg?logo=github"> </a> <a href="https://huggingface.co/ByteDance-Seed/bamboo_mixer"> <img alt="Build" src="https://img.shields.io/badge/🤗-HF%20Model-yellow"> </a> </p>

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

Datasets

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 ⭐ 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}, 
}