---
myst:
  html_meta:
    "description": "How to cite eOn: the Zenodo record, the method papers, and the older papers."
    "keywords": "eOn citation, Zenodo, cite eOn"
---
# Citing eOn

Please cite the eOn software through its Zenodo record
{cite:p}`cite-goswamiTheochemUIEOn2026`. The concept DOI
[10.5281/zenodo.18529495](https://doi.org/10.5281/zenodo.18529495) always
resolves to the latest release, and each release also has its own DOI on Zenodo.
GitHub reads the same reference from `CITATION.cff`. The entry below matches
`docs/source/bibtex/eonDocs.bib`, which these pages draw on.

```bibtex
@misc{goswamiTheochemUIEOn2026,
  title = {{{TheochemUI/eOn}}},
  author = {Goswami, Rohit and Chill, Sam and Terrell, Rye and Henkelman, Graeme and Welborn, Matthew and Zhang, Liang and Pedersen, Andreas and {t-brink} and Edelmann, Erik and Claude, Jean and {Alejandro} and Jung, Sung Hoon and Ghasemi, Seyed Alireza and {chemist29} and {satishskamath} and {Maxim} and Dijkhuis, Tobias and {via9a}},
  year = 2026,
  publisher = {Zenodo},
  howpublished = {Zenodo},
  doi = {10.5281/zenodo.18529495},
  url = {https://doi.org/10.5281/zenodo.18529495},
  note = {Concept DOI, resolves to the latest release}
}
```

## Papers on eOn 2.x and later

The rewrites behind eOn 2.x and 3.x, including the Gaussian process methods and
the socket and calculator interfaces, are covered in
{cite:t}`cite-goswamiEfficientExplorationChemical2025`.
For other eOn 2.x and later methods (AKMC, the dimer, Lanczos, and
minimization), please also cite Goswami's 2025 thesis.

If you use one of the methods below, please also cite the paper behind it.

- Gaussian process regression accelerated dimer
  (`min_mode_method = gprdimer`):
  {cite:t}`cite-goswamiEfficientImplementationGaussian2025`.
- Adaptive pruning and optimal transport for Gaussian process saddle searches
  (`use_prune` and related keys under `[GPR Dimer]`):
  {cite:t}`cite-goswamiAdaptivePruningIncreased2025b`.
- Any nudged elastic band run (`job = nudged_elastic_band`), including
  off-path climbing image NEB (OCI-NEB) with Hessian eigenmode alignment:
  {cite:t}`cite-goswamiEnhancedClimbingImage2026`.
- Benchmarking saddle searches, and rotation removal in the dimer
  (`remove_rotation`): {cite:t}`cite-goswamiBayesianHierarchicalModels2025a`.
- Background on Gaussian process acceleration of saddle and minimum searches:
  {cite:t}`cite-goswamiTutorialReviewBayesian2026`.
- NEB workflows with eOn and machine-learned potentials:
  {cite:t}`cite-goswamiReproducibleOrchestrationBest2026`.
- Two-dimensional RMSD plots of NEB paths:
  {cite:t}`cite-goswamiTwodimensionalRMSDProjections2026`.
- Metatomic potentials in eOn, including the NEB runs:
  {cite:t}`cite-bigiMetatensorMetatomicFoundational2026`.

## Older papers

These describe the original EON code and the methods it started from, oldest
first: kinetic Monte Carlo without a lattice
{cite:p}`cite-henkelmanLongTimeScale2001`, adaptive kinetic Monte Carlo
{cite:p}`cite-xuAdaptiveKineticMonte2008`, long time scale simulation of a
grain boundary {cite:p}`cite-pedersenLongTimeScale2009`, the distributed EON2
code {cite:p}`cite-pedersenDistributedImplementationAdaptive2010`, and the 2014
software paper {cite:p}`cite-chillEONSoftwareLong2014`.

The pages for each method, such as <project:user_guide/akmc.md>,
<project:user_guide/dimer.md> and <project:user_guide/neb.md>, cite the papers
those methods come from.

## References

```{bibliography}
---
style: unsrt
filter: docname in docnames
labelprefix: CITE_
keyprefix: cite-
---
```