Data · dataset · 2021
Optical absorption of metal oxides and results of machine learning predictions
Listed in CaltechDATA
CSV files that collectively contain optical absorption data from metal oxides with different cation elements compositions.
Description
The optical properties for each metal oxide composition are the 10-dimensional unitless absorption coefficient where the 10 dimensions correspond to equally-spaced ranges of photon energy spanning 1.39 eV to 3.11 eV. These data also include test-train splits for benchmarking machine learning models that predict the optical absorption, along with results obtained to-date with various machine learning models.
For each test-train split, data are normalized to 0 mean, unit variance.
Links
Where it is published
- CaltechDATA record data.caltech.edu/records/vt2ec-dzc10 ↗
landing page · from data caltech edu
- DOI doi.org/10.22002/d1.1878 ↗
DOI / persistent id · from data caltech edu
Catalogue records · 1
- InvenioRDM API data.caltech.edu/api/records/vt2ec-dzc10 ↗
metadata API · from data caltech edu
Topics
- Stated by source
- artificial intelligence · high throughput experimentation · machine learning · materials prediction · metal oxide · optical absorption
Provenance · 1 source records, 20 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| CaltechDATA | vt2ec-dzc10 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| concepts[field].anzsrc:group:4602 | mapping · data caltech edu | vocabulary-mapper@1.0.0 | keywords['artificial intelligence'] |
| concepts[field].anzsrc:group:4611 | mapping · data caltech edu | vocabulary-mapper@1.0.0 | keywords['machine learning'] |
| concepts[field].local:field:computer-science-ai | mapping · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| concepts[field].local:field:engineering | mapping · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| concepts[field].local:field:humanities | mapping · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| concepts[field].local:field:social-science | mapping · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| concepts[topic].invenio_subject:data_caltech_edu:artificial-intelligence | source · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| concepts[topic].invenio_subject:data_caltech_edu:high-throughput-experimentation | source · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| concepts[topic].invenio_subject:data_caltech_edu:machine-learning | source · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| concepts[topic].invenio_subject:data_caltech_edu:materials-prediction | source · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| concepts[topic].invenio_subject:data_caltech_edu:metal-oxide | source · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| concepts[topic].invenio_subject:data_caltech_edu:optical-absorption | source · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| description | source · data caltech edu | connector:data_caltech_edu@1.0.0 | /metadata/description |
| publication_date | source · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| title | source · data caltech edu | connector:data_caltech_edu@1.0.0 | /metadata/title |
| updated_date | source · data caltech edu | connector:data_caltech_edu@1.0.0 | |
| version_label | source · data caltech edu | connector:data_caltech_edu@1.0.0 |