---
library_name: pytorch
tags:
- materials-science
- graph-ml
- alignn
- bandgap-prediction
- screening
- density-functional-theory
- closed-loop-discovery
- arxiv:2606.16133
license: other
license_name: invdesmobility-research-artifact-license
license_link: https://huggingface.co/DreamLufei/invDesMobility-alignn-bandgap-nonmetal/blob/main/LICENSE
datasets:
- DreamLufei/invDesMobility-data
---

# InvDesMobility ALIGNN Bandgap/Nonmetal Screening Model

This repository contains the ALIGNN model used in InvDesMobility for surrogate
bandgap prediction and nonmetal screening before expensive first-principles
mobility validation.

## Paper and Repositories

- Paper: InvDesMobility: a reliability-gated first-principles feedback framework for closed-loop materials discovery
- arXiv: https://arxiv.org/abs/2606.16133
- Project page: https://dreamlufei.github.io/invDesMobility/
- GitHub: https://github.com/DreamLufei/invDesMobility
- Loop repository: https://github.com/DreamLufei/invdesmobility_loop
- Mobility workflow: https://github.com/DreamLufei/2d-mobility
- Zenodo: https://doi.org/10.5281/zenodo.20475023

## Files

- `last_model.pt`: trained ALIGNN checkpoint used by the screening script.
- `config.json`: required ALIGNN model and graph-construction configuration.

`config.json` is not a disposable log file. It defines the ALIGNN architecture
and inference graph parameters needed to reconstruct the model before loading
the checkpoint.

## Intended Use

Use this model to rank/filter generated 2D candidate structures by predicted
bandgap/nonmetal behavior inside the InvDesMobility screening pipeline.

## Training Data

The model was trained as a surrogate bandgap model for the project screening
workflow. See the `invDesMobility` repository and the companion data archive for
the associated dataset preparation scripts and records.

## Training Parameters

The included `config.json` records the training and inference settings, including
ALIGNNAtomWise architecture, cutoff, neighbor strategy, batch size, optimizer,
learning rate, and split ratios.

## Evaluation

Standalone training/validation/test prediction tables for this bandgap surrogate
are not duplicated in this model repository. In InvDesMobility it is used as an
intermediate nonmetal/bandgap screen, and the corresponding screening outputs
are distributed in the companion `DreamLufei/invDesMobility-data` archive.

The model should be audited through those screening records together with the
downstream deterministic DFT validation results, rather than treated as a final
electronic-structure benchmark.

## Limitations

This is a surrogate screening model. Final electronic structure and carrier
mobility claims require downstream DFT validation. The model should not be used
as a replacement for first-principles band-structure calculations.