Kernels and Graphs on M25 + H (parent repository)

Abstract
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
Main Authors
Format
Dataset
Published
2023
Subjects
Publication in research information system
Publisher
University of Jyväskylä
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202306073591Use this for linking
DOI
https://doi.org/10.17011/jyx/dataset/87525
Language
English
Contains publications
Citation
  • Pihlajamäki, Antti; Kärkkäinen, Tommi; Malola, Sami; Häkkinen, Hannu. (2023). Kernels and Graphs on M25 + H (parent repository). University of Jyväskylä. 10.17011/jyx/dataset/87525
License
CC BY 4.0Open Access
Funder(s)
Suomen Akatemia
Academy of Finland
Funding program(s)
Muut, SA
Others, AoF
Academy of Finland
Tietueella ei ole tiedostoja.
CopyrightPihlajamäki, Antti and University of Jyväskylä

Share