Kernels and Graphs on M25 + H (parent repository)

Beskrivning

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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Publiceringsår

2023

Typ av data

Upphovspersoner

Fysiikan laitos

Häkkinen, Hannu - Upphovsperson

Malola, Sami - Upphovsperson

Informaatioteknologian tiedekunta

Kärkkäinen, Tommi Orcid -palvelun logo - Upphovsperson

Matemaattis-luonnontieteellinen tiedekunta

Pihlajamäki, Antti - Upphovsperson, Rättighetsinnehavare

Projekt

Övriga uppgifter

Vetenskapsområden

Data- och informationsvetenskap; Fysik; Kemi

Språk

engelska

Öppen tillgång

Öppet

Licens

Creative Commons Attribution 4.0 International (CC BY 4.0)

Nyckelord

machine learning

Ämnesord

nanopartiklar, katalys, maskininlärning, nanovetenskaper, katalysatorer (ämnen), nanomaterial

Temporal täckning

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