UniDataPro/materials-platform-for-data-science
Materials Platform for data science Dataset includes 405,100 publications, 139,005 phase diagrams, 409,771 crystalline nanostructures, 1,075,676 physical property sets, and 189,682 material phases. It integrates decades of scientific research on inorganic materials, enabling computational materials design, machine learning applications, and materials informatics studies across industry and academia. Built on data extracted from about half a million peer-reviewed scientific… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/materials-platform-for-data-science.
Materials Platform for data science
Dataset includes 405,100 publications, 139,005 phase diagrams, 409,771 crystalline nanostructures, 1,075,676 physical property sets, and 189,682 material phases. It integrates decades of scientific research on inorganic materials, enabling computational materials design, machine learning applications, and materials informatics studies across industry and academia.
Built on data extracted from about half a million peer-reviewed scientific publications, it offers standardized data, detailed chemical structures, crystal structures, and extensive metadata on various materials. - [Get the data](https://unidata.pro/datasets/materials-platform-for-data-science/?utm_source=huggingface&utm_medium=referral&utm_campaign=materials-platform-for-data-science)
The dataset helps researchers and engineers advance scientific discovery, predicting materials behavior, and accelerating materials innovation through data-driven research.
Frequently Asked Questions
What research areas can benefit from this materials dataset?
The dataset is useful for researchers in materials science, chemistry, physics, engineering, and AI-driven scientific discovery. It can support projects involving material property prediction, computational materials research, optimization of new materials, and development of machine learning models for scientific applications.
What types of material information are available?
The dataset includes information about inorganic materials, including phase diagrams, crystalline nanostructures, and physical property measurements. It connects different material characteristics such as chemical elements, formulas, crystal systems, symmetry information, and other scientific attributes for advanced analysis.
What makes this materials dataset different from general scientific datasets?
This dataset is built from more than 30 years of expert-curated scientific information rather than automatically collected web data. The records were manually reviewed and structured by materials science specialists, providing researchers with reliable information for machine learning, materials discovery, and industrial research applications."
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It allows researchers and engineers to explore computational chemistry, develop machine learning models for predicting materials behaviors. By combining raw data, experimental records, and computational analyses, MPDS helps scientists and materials experts design new compounds, identify similar materials, and optimize materials properties for engineering applications.