From 93ced703d3b0fe0eee3494738c89f559af3c80f1 Mon Sep 17 00:00:00 2001
From: Luigi Sbailo <sbailo@fhi-berlin.mpg.de>
Date: Wed, 9 Dec 2020 09:48:56 +0100
Subject: [PATCH] Update metainfo
---
metainfo.json | 24 ++++++++------
tetradymite_PRM2020.ipynb | 69 +++++++--------------------------------
2 files changed, 26 insertions(+), 67 deletions(-)
diff --git a/metainfo.json b/metainfo.json
index 79de625..899385c 100644
--- a/metainfo.json
+++ b/metainfo.json
@@ -1,34 +1,38 @@
{
"authors": [
- "Sbailo, Luigi",
- "Ghiringhelli, Luca M."
+ "Sbailò, Luigi",
+ "Purcell, Thomas A. R.",
+ "Ghiringhelli, Luca M.",
+ "Scheffler, Matthias"
],
"email": "ghiringhelli@fhi-berlin.mpg.de",
- "title": "Artificial intelligence for high-throughput discovery of topological insulators",
- "description": "In this tutorial... ",
+ "title": "Discovery of new topological insulators in alloyed tetradymites",
+ "description": "Learn how to find descriptive parameters (short formulas) that predict whether alloyed materials are topological or trivial insulators, using the example of tetradymites. This notebook is based on the algorithm 'sure independence screening and sparsifying operator' (SISSO) that enables to search for optimal descriptor by scanning huge feature spaces.",
"url": "https://gitlab.mpcdf.mpg.de/nomad-lab/analytics-tetradymite-PRM2020",
"link": "https://analytics-toolkit.nomad-coe.eu/hub/user-redirect/notebooks/tutorials/tetradymite_PRM2020.ipynb",
"link_public": "https://analytics-toolkit.nomad-coe.eu/public/user-redirect/notebooks/tutorials/tetradymite_PRM2020.ipynb",
- "updated": "2020-26-08",
+ "updated": "2020-12-09",
"flags":{
"featured": true,
"top_of_list": false
},
"labels": {
"application_keyword": [
- "Something"
+ "Tetradymites",
+ "Topological insulators"
],
"application_section": [
- "Something"
+ "Timely artificial-intelligence applications to Materials Science"
],
"application_system": [
- "Something"
+ "Tetradymites"
],
"category": [
- "Something"
+ "Tutorial"
],
"data_analytics_method": [
- "Something"
+ "SISSO",
+ "Classification"
],
"platform": [
"jupyter"
diff --git a/tetradymite_PRM2020.ipynb b/tetradymite_PRM2020.ipynb
index 395e431..0f1f4b0 100644
--- a/tetradymite_PRM2020.ipynb
+++ b/tetradymite_PRM2020.ipynb
@@ -19,7 +19,7 @@
"\n",
" \n",
" <div style=\"text-align:center\">\n",
- " <b><font size=\"6.4\">Discovery of new topological insulators in alloyed tetradymites with symbolic regression combined with compressed sensing (SISSO).\n",
+ " <b><font size=\"6.4\">Discovery of new topological insulators in alloyed tetradymites\n",
" </font></b> \n",
" </div>\n",
"\n",
@@ -92,7 +92,7 @@
},
{
"cell_type": "code",
- "execution_count": 29,
+ "execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-03T16:51:20.970400Z",
@@ -100,37 +100,7 @@
},
"init_cell": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<script>\n",
- " code_show=true; \n",
- " function code_toggle() {\n",
- " if (code_show)\n",
- " {\n",
- " $('div.input').hide();\n",
- " } \n",
- " else \n",
- " {\n",
- " $('div.input').show();\n",
- " }\n",
- " code_show = !code_show\n",
- " } \n",
- " $( document ).ready(code_toggle);\n",
- " window.runCells(\"startup\");\n",
- "</script>\n",
- "The Python code for this notebook is by default hidden for easier reading.\n",
- "To toggle on/off the code, click <a href=\"javascript:code_toggle()\">here</a>.\n"
- ],
- "text/plain": [
- "<IPython.core.display.HTML object>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"%%HTML\n",
"<script>\n",
@@ -155,7 +125,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-03T16:27:16.278570Z",
@@ -170,7 +140,7 @@
},
{
"cell_type": "code",
- "execution_count": 30,
+ "execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-03T16:51:20.988129Z",
@@ -209,7 +179,7 @@
},
{
"cell_type": "code",
- "execution_count": 31,
+ "execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-03T16:51:21.019833Z",
@@ -279,7 +249,7 @@
},
{
"cell_type": "code",
- "execution_count": 32,
+ "execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-03T16:51:21.154094Z",
@@ -323,7 +293,7 @@
},
{
"cell_type": "code",
- "execution_count": 33,
+ "execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-03T16:51:21.173521Z",
@@ -391,7 +361,7 @@
},
{
"cell_type": "code",
- "execution_count": 34,
+ "execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-03T16:51:21.204474Z",
@@ -531,7 +501,7 @@
},
{
"cell_type": "code",
- "execution_count": 35,
+ "execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-03T16:51:21.475170Z",
@@ -540,22 +510,7 @@
"init_cell": true,
"scrolled": false
},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "88675c3ce6594422ae31faaabc0b1b30",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "VBox(children=(HBox(children=(VBox(children=(Label(value=''), Checkbox(value=True, disabled=True, indent=False…"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"cb_layout = widgets.Layout(width = '15px')\n",
"thin_layout = widgets.Layout(width = '100px')\n",
@@ -659,7 +614,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.9"
+ "version": "3.8.3"
}
},
"nbformat": 4,
--
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