perovskite_prediction_double

perovskite_prediction_double/perovskite_prediction_double.demoinfo.yaml

+{
+  "id": "",
+  "type": "demos",
+  "attributes": {
+    "title": "New tolerance factor for perovskite stability",
+    "logicalPath": "/data/shared/tutorials/perovskite_prediction_double/perovskite_prediction_double.bkr",
+    "authors": ["Christopher Bartel", "Christopher Sutton", "Bryan Goldsmith", "Runhai Ouyang", "Charles Musgrave", "Luca Ghiringhelli", "Matthias Scheffler"],
+    "editLink": "/notebook-edit/data/shared/tutorialsNew/perovskite_prediction_double/perovskite_prediction_double.bkr",
+    "isPublic": true,
+    "username": "tutorialsNew",
+    "description": "A tool for predicting the probability that a given chemical formula will crystallize in a perovskite structure. This prediction is made using a newly developed tolerance factor (descriptor) which makes predictions based on automatically assigned ionic radii and oxidation states. Within this notebook, you can also visualize the probability of forming perovskite for any single or double perovskite formula as a function of the cationic radii.",
+    "created_at": "",
+    "updated_at": "",
+    "user_update": "November 12, 2018",
+    "top_of_list": false,
+    "featured": true,
+    "labels" : {
+        "category" : ["Demo"],
+        "platform" :  ["beaker"],
+        "language" :  ["python", "javascript"],
+        "data_analytics_method" : ["SISSO"],
+        "application_section" : ["Crystal structure prediction"],
+        "application_keyword": ["perovskites", "stability", "classification"],
+        "visualization" : [""],
+        "reference" : ["arXiv preprint arXiv:1801.07700"]
+    }
+  }
+}