Kernels and Graphs on M25 + H (parent repository)

Description

The repository contains codes related to article "Graphs and Kernelized Learning Applied to Interactions of Hydrogen with Doped Gold Nanoparticle Electrocatalysts". There are two main types of codes: codes to transform a catalytic system of protected gold nanoparticle and a single hydrogen atom into a graph-based representation, and codes to run kernel-based machine learning methods to predict interaction energies between the nanoparticle and the hydrogen atom. This is the metadata for the parent repository of the codes. Updates and possible corrections are documented in the GitLab project, where the material saved and shared. The GitLab project can be found and downloaded from the following address: https://gitlab.jyu.fi/mlnovcat-aneepihl/kernels-and-graphs-on-m25-h
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Year of publication

2023

Type of data

Authors

Fysiikan laitos

Häkkinen, Hannu - Creator

Malola, Sami - Creator

Informaatioteknologian tiedekunta

Kärkkäinen, Tommi Orcid -palvelun logo - Creator

Matemaattis-luonnontieteellinen tiedekunta

Pihlajamäki, Antti - Creator, Rights holder

Project

Other information

Fields of science

Computer and information sciences; Physical sciences; Chemical sciences

Language

English

Open access

Open

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

Keywords

machine learning

Subject headings

Temporal coverage

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Related to this research data