| Votes | By | Price | Discipline | Year Launched |
| FIZ Karlsruhe | FREE | Interdisciplinary |
Description
Features
Offers
Reviews
ICSD is a specialised database managed by FIZ Karlsruhe – Leibniz‑Institute for Information Infrastructure that provides the largest curated collection of inorganic crystal‐structure data in the world. It focuses on materials that are inorganic (elements, minerals, intermetallics, ceramics) rather than organic compounds.
Why it matters
- For disciplines such as materials science, solid‐state chemistry, crystallography and geology, knowing the precise atomic and structural parameters of crystalline solids is essential for understanding, modelling or predicting properties. ICSD provides those structural datasets.
- It supports reproducible research and data mining: the entries include atomic coordinates, space groups, unit cells, site occupations, and enable computational workflows.
- It is a trustworthy resource with strong curation and quality control.
Key features & advantages
- Contains hundreds of thousands of entries (for example, ICSD recently reported over 327,000 structures) with annual updates.
- Each record includes: chemical formula, atomic coordinates, space group, unit‐cell parameters, mineral group or classification, and often physical/chemical keywords.
- Searchable web/desktop interfaces and API for integration into institutional workflows.
- Includes theoretical structures (simulated/computed) in addition to experimental ones — expanding utility for materials discovery.
Limitations & things to watch
- Access typically requires an institutional subscription or licence, not all features may be open‐access.
- Although extremely comprehensive, coverage may still have gaps (especially for very new materials or unpublished structures).
- Proper use requires domain expertise: using the data requires understanding crystallography (space groups, symmetry, site occupancy) in order to interpret correctly.
- Data mining or high‐throughput use may require institutional infrastructure (APIs, storage) and familiarity with the dataset’s structure and codes.
Discover Data, Discover Abstracts, Field Specific Search, Data Analysis, Multidisciplinary Search, Bibliography Options
