Citing eOn

Please cite the eOn software through its Zenodo record [CITE_1]. The concept DOI 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.

@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 Goswami [CITE_2]. 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): Goswami et al. [CITE_3].

  • Adaptive pruning and optimal transport for Gaussian process saddle searches (use_prune and related keys under [GPR Dimer]): Goswami and Jónsson [CITE_4].

  • Any nudged elastic band run (job = nudged_elastic_band), including off-path climbing image NEB (OCI-NEB) with Hessian eigenmode alignment: Goswami et al. [CITE_5].

  • Benchmarking saddle searches, and rotation removal in the dimer (remove_rotation): Goswami [CITE_6].

  • Background on Gaussian process acceleration of saddle and minimum searches: Goswami [CITE_7].

  • NEB workflows with eOn and machine-learned potentials: Goswami [CITE_8].

  • Two-dimensional RMSD plots of NEB paths: Goswami [CITE_9].

  • Metatomic potentials in eOn, including the NEB runs: Bigi et al. [CITE_10].

Older papers

These describe the original EON code and the methods it started from, oldest first: kinetic Monte Carlo without a lattice [CITE_11], adaptive kinetic Monte Carlo [CITE_12], long time scale simulation of a grain boundary [CITE_13], the distributed EON2 code [CITE_14], and the 2014 software paper [CITE_15].

The pages for each method, such as Adaptive kinetic Monte Carlo, Dimer method and Nudged elastic band, cite the papers those methods come from.

References

[CITE_1]

Rohit Goswami, Sam Chill, Rye Terrell, Graeme Henkelman, Matthew Welborn, Liang Zhang, Andreas Pedersen, t-brink, Erik Edelmann, Jean Claude, Alejandro, Sung Hoon Jung, Seyed Alireza Ghasemi, chemist29, satishskamath, Maxim, Tobias Dijkhuis, and via9a. TheochemUI/eOn. Zenodo, 2026. Concept DOI, resolves to the latest release. URL: https://doi.org/10.5281/zenodo.18529495, doi:10.5281/zenodo.18529495.

[CITE_2]

Rohit Goswami. Efficient exploration of chemical kinetics. October 2025. arXiv:2510.21368, doi:10.48550/arXiv.2510.21368.

[CITE_3]

Rohit Goswami, Maxim Masterov, Satish Kamath, Alejandro Peña-Torres, and Hannes Jónsson. Efficient Implementation of Gaussian Process Regression Accelerated Saddle Point Searches with Application to Molecular Reactions. Journal of Chemical Theory and Computation, 21(16):7935–7943, July 2025. doi:10.1021/acs.jctc.5c00866.

[CITE_4]

Rohit Goswami and Hannes Jónsson. Adaptive Pruning for Increased Robustness and Reduced Computational Overhead in Gaussian Process Accelerated Saddle Point Searches. ChemPhysChem, 27(4):e202500730, February 2026. doi:10.1002/cphc.202500730.

[CITE_5]

Rohit Goswami, Miha Gunde, and Hannes Jónsson. Enhanced climbing image nudged elastic band method with hessian eigenmode alignment. Frontiers in Chemistry, 14:1807063, 2026. arXiv:2601.12630, doi:10.3389/fchem.2026.1807063.

[CITE_6]

Rohit Goswami. Bayesian hierarchical models for quantitative estimates for performance metrics applied to saddle search algorithms. AIP Advances, 15(8):085210, August 2025. doi:10.1063/5.0283639.

[CITE_7]

Rohit Goswami. A tutorial review of Bayesian optimization with Gaussian processes to accelerate stationary point searches. ACS Physical Chemistry Au, 6(4):633–664, May 2026. doi:10.1021/acsphyschemau.6c00038.

[CITE_8]

Rohit Goswami. Reproducible orchestration of best practices for reaction path optimization with the nudged elastic band. MethodsX, 16:103899, June 2026. doi:10.1016/j.mex.2026.103899.

[CITE_9]

Rohit Goswami. Two-dimensional RMSD projections for reaction path visualization and validation. MethodsX, 16:103851, June 2026. doi:10.1016/j.mex.2026.103851.

[CITE_10]

Filippo Bigi, Joseph W. Abbott, Philip Loche, Arslan Mazitov, Davide Tisi, Marcel F. Langer, Alexander Goscinski, Paolo Pegolo, Sanggyu Chong, Rohit Goswami, Pol Febrer, Sofiia Chorna, Matthias Kellner, Michele Ceriotti, and Guillaume Fraux. Metatensor and metatomic: foundational libraries for interoperable atomistic machine learning. The Journal of Chemical Physics, 164(6):064113, February 2026. doi:10.1063/5.0304911.

[CITE_11]

Graeme Henkelman and Hannes Jónsson. Long time scale kinetic Monte Carlo simulations without lattice approximation and predefined event table. The Journal of Chemical Physics, 115(21):9657–9666, November 2001. doi:10.1063/1.1415500.

[CITE_12]

Lijun Xu and Graeme Henkelman. Adaptive kinetic Monte Carlo for first-principles accelerated dynamics. The Journal of Chemical Physics, 129(11):114104, September 2008. doi:10.1063/1.2976010.

[CITE_13]

Andreas Pedersen, Graeme Henkelman, Jakob Schiøtz, and Hannes Jónsson. Long time scale simulation of a grain boundary in copper. New Journal of Physics, 11(7):073034, July 2009. doi:10.1088/1367-2630/11/7/073034.

[CITE_14]

Andreas Pedersen and Hannes Jónsson. Distributed implementation of the adaptive kinetic Monte Carlo method. Mathematics and Computers in Simulation, 80(7):1487–1498, March 2010. doi:10.1016/j.matcom.2009.02.010.

[CITE_15]

Samuel T Chill, Matthew Welborn, Rye Terrell, Liang Zhang, Jean-Claude Berthet, Andreas Pedersen, Hannes Jónsson, and Graeme Henkelman. EON: software for long time simulations of atomic scale systems. Modelling and Simulation in Materials Science and Engineering, 22(5):055002, July 2014. doi:10.1088/0965-0393/22/5/055002.