Kernels and Graphs on M25 + H

Beskrivning

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 a snapshot of the code dataset that has been taken on 06.06.2023. A more detailed description of the data and the address to the GitLab repository for the latest version of the code can be found from the parent dataset of this data publication.
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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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