The AQVolt26 models and dataset are for non-commercial use. If you want to work with us or discuss obtaining a commercial license, please contact us directly at materials@sandboxaq.com.

AQVolt26: High-Temperature r²SCAN Halide Dataset for Universal ML Potentials and Solid-State Batteries

AQVolt26 Overview

Please see our blog and paper for more details about the impact of the models and dataset.

1. Dataset Details

The Parquet file can be loaded directly with the datasets library for fast browsing and filtering. Each file contains the following columns

Column Name	Data Type	Description	Example
`aqvolt_id`	string	unique ID for this dataset	`aqvolt_8228`
`elements`	list	unique elements that constitute the chemical system	['I', 'Li', 'Ag']
`composition`	dict	composition of the system with element names and counts	`{"Li": 1, "Ag": 1, "I": 2}`
`nsites`	int	number of atoms/sites in the system	4
`fmax`	float	maximum force magnitude on any single atom in eV/Å	124.672239
`coh_epa`	float	cohesive energy per atom in eV/atom	-3.204444
`energy`	float	raw total energy of the system from DFT in eV	-78.693561
`forces`	list	force on each atom from DFT in eV/Å	[[27.392877,46.40259,-112.425963],[-4.162302,-6.632746,22.376029],[-7.205259,-26.463429,29.300288],[-16.025316,-13.306415,60.749647]]
`stress`	list	stress on the the system in Voigt notation from DFT in eV/Å³	[-3.4061113623,-4.1051214103,-0.2551386621,0.1047948581,-1.1760257427,-0.6242689209]
`magmoms`	list	magnetic moments for each atom from DFT in µB	[-3.4061113623,-4.1051214103,-0.2551386621,0.1047948581,-1.1760257427,-0.6242689209]
`atoms`	dict	ASE atoms object in dictionary form	{"numbers":[3,47,53,53], "positions":[[0.80014419,2.29470219,4.40805324],[0.66855576,3.13222298,7.18433809],[0.988119,2.65086925,3.43464628],[0.71064203,4.11512436,5.0242587]], "cell":[[1.350821,1.615872,0.485419],[0,3.321595,0.485419],[0,0,6.916288]], "pbc":[true,true,true]}
`frame_id`	float	n^th frame from ab initio molecular dynamics (MD) or machine learning MD	391
`temperature`	float	temperature at which the configuration was generated	900
`metadata`	dict	additional information about the simulation conditions and structure origins	{"provenance": "materials_project", "halide_substitution": "F-I", "material_id": "mp-752767", "aimd": false, "sampled": true, "stuffed": false}

2. Dataset Usage Guide

This guide outlines the recommended steps to access a subset of the AQVolt26 dataset.

Before you begin, you need to install the necessary libraries and authenticate with Hugging Face. This is a one-time setup.

pip install datasets pandas jupyterlab ase --no-input

1. Create a Hugging Face Account: If you don't have one, create an account at huggingface.co.

2. Create an Access Token: Navigate to your Settings -> Access Tokens page or click here. Create a new token with at least read permissions. Copy this token to your clipboard.

3. Access via Jupyter Lab:

Open your terminal or command prompt and type

python -m ipykernel install --user --name=aqvolt --display-name="aqvolt"
jupyter lab

This will open a tab in your web browser. Open a new Jupyter notebook. Make sure that your notebook is using the Python environment where the packages installed above are located when selecting your kernel. To access the dataset, type the following into a cell

from datasets import load_dataset
dataset = load_dataset("SandboxAQ/aqvolt26-dataset-subset", split="test", token=<YOUR-TOKEN>)

filtered_dataset = dataset.filter(lambda x: "Cl" in x["elements"])
print(f"Found {len(filtered_dataset)} matching rows.")
155

from ase import Atoms
atoms_obj = Atoms(**filtered_dataset[0]['atoms'])

print(atoms_obj.get_volume())
282.5277092131659

3. How to Cite

If you use the AQVolt26 models or dataset in your research, please cite the following paper:

Jiyoon Kim, Chuhong Wang, Aayush R. Singh, Tyler Sours, Shivang Agarwal, AJ Nish, Paul Abruzzo, Ang Xiao, Omar Allam. (2026). AQVolt26: High-Temperature r2SCAN Halide Dataset for Universal ML Potentials and Solid-State Batteries. arXiv preprint arXiv:XXXX.XXXXX.

BibTeX Entry

@article{kim2026aqvolt26hightemperaturer2scanhalide,
      title={AQVolt26: High-Temperature r2SCAN Halide Dataset for Universal ML Potentials and Solid-State Batteries}, 
      author={Jiyoon Kim and Chuhong Wang and Aayush R. Singh and Tyler Sours and Shivang Agarwal and AJ Nish and Paul Abruzzo and Ang Xiao and Omar Allam},
      year={2026},
      eprint={2604.02524},
      archivePrefix={arXiv},
      primaryClass={cond-mat.mtrl-sci},
      url={https://arxiv.org/abs/2604.02524}, 
}

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Collection including SandboxAQ/aqvolt26-dataset-subset

AQVolt26

Collection

AQVolt26 models and dataset • 2 items • Updated about 14 hours ago

Paper for SandboxAQ/aqvolt26-dataset-subset

AQVolt26: High-Temperature r^2SCAN Halide Dataset for Universal ML Potentials and Solid-State Batteries

Paper • 2604.02524 • Published 6 days ago