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Commit 81cd97f6 authored by Luigi Sbailo's avatar Luigi Sbailo
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CI: Update metainfo in the GUI

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...@@ -869,6 +869,44 @@ ...@@ -869,6 +869,44 @@
] ]
} }
}, },
{
"authors": [
"Foppa, Lucas",
"Ghiringhelli, Luca M.",
"Scheffler, Matthias"
],
"email": "foppa@fhi-berlin.mpg.de",
"title": "Learning Design Rules for Catalysts from High-Throughput Experimentation and Theory via Subgroup Discovery",
"description": "This tutorial explores the application of subgroup discovery (SGD) to an experimental-theoretical data set in order to identify rules on key physicochemical parameters that describe the materials and environmental conditions associated with outstanding performance in heterogeneous catalysis.",
"notebook_name": "sgd_propylene_oxidation_hte.ipynb",
"url": "https://gitlab.mpcdf.mpg.de/nomad-lab/analytics-sgd-propylene-oxidation-hte",
"link": "https://analytics-toolkit.nomad-coe.eu/hub/user-redirect/notebooks/tutorials/sgd_propylene_oxidation_hte.ipynb",
"link_public": "https://analytics-toolkit.nomad-coe.eu/public/user-redirect/notebooks/tutorials/sgd_propylene_oxidation_hte.ipynb",
"link_paper": "https://pubs.acs.org/doi/10.1021/acscatal.1c04793",
"link_doi_paper": "https://pubs.acs.org/doi/10.1021/acscatal.1c04793",
"updated": "2022-2-09",
"flags": {
"featured": true,
"top_of_list": false
},
"labels": {
"application_section": [
"Timely artificial-intelligence applications to Materials Science"
],
"application_system": [
"Heterogeneous catalysis"
],
"category": [
"advanced_tutorial"
],
"ai_methods": [
"Subgroup discovery"
],
"platform": [
"jupyter"
]
}
},
{ {
"authors": [ "authors": [
"Cs\u00e1nyi, G\u00e1bor", "Cs\u00e1nyi, G\u00e1bor",
......
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