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Materials Platform for Data Science (MPDS) Dataset

Materials Platform for Data Science Dataset (Project Pauling Files) is a highly curated inorganic materials dataset with a 30-year track record, based on about half a million peer-reviewed scientific publications and powering several successful commercial products from the world's leading publishers. It integrates materials data from 405,100 publications, linking 139,005 phase diagrams, 409,771 crystalline nanostructures, and 1,075,676 physical property sets into 189,682 materials phases within a large-scale materials graph of ~5 million nodes and ~150 million edges, making it a comprehensive materials platform for data science and a cornerstone among modern material science datasets and materials project database resources.

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  • Publications
    405,100
  • Phase diagrams
    139,005
  • Crystalline nanostructures
    409,771
  • Property sets
    1,075,676
  • Material phases
    189,682
  • Materials Science
  • Chemistry
  • Physics
  • Data Science
  • Machine Learning

Materials Platform for Data Science Dataset (Project Pauling Files) is a highly curated inorganic materials dataset with a 30-year track record, based on about half a million peer-reviewed scientific publications and powering several successful commercial products from the world's leading publishers. It integrates materials data from 405,100 publications, linking 139,005 phase diagrams, 409,771 crystalline nanostructures, and 1,075,676 physical property sets into 189,682 materials phases within a large-scale materials graph of ~5 million nodes and ~150 million edges, making it a comprehensive materials platform for data science and a cornerstone among modern material science datasets and materials project database resources.

Get in touch Download sample
  • Materials Science
  • Chemistry
  • Physics
  • Data Science
  • Machine Learning
  • Publications
    405,100
  • Phase diagrams
    139,005
  • Crystalline nanostructures
    409,771
  • Property sets
    1,075,676
  • Material phases
    189,682

Dataset Info

Characteristic Data
Description Inorganic materials with a 30-year history, powering academic research and commercial applications
Data types Relational SQL database, JSON export
Tasks Academic and industrial R&D, materials discovery, ML modeling
Labeling 100+ categories: elements, formulas, properties, symmetry, etc.
Language Controlled scientific English
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Technical
Characteristics

Characteristic Data
Format JSON, schema
Searchable fields Physical properties, chemical elements, material classes, crystal system, formula, space group, etc.
Source and collection methodology: Data were collected by a partner of Unidata (Manually curated by experts over 30 years)

Dataset Use Cases

  • Materials Science & Academic Research

    Unified Knowledge Base for Fundamental Studies

    The materials platform for data science supports fundamental materials science by linking phase diagrams, crystal structures, and physical properties into a single materials dataset. Researchers use this materials project database to analyze inorganic materials, compare similar materials, and validate hypotheses using standardized data drawn from peer-reviewed scientific research.

  • Computational Materials Engineering

    Data-Driven Materials Design and Simulation

    Engineers apply MPDS as a materials dataset for computational materials workflows, where materials data feeds modeling, simulation, and property prediction tasks. The platform enables materials informatics studies by combining chemical structures, crystalline materials, and metadata, helping teams design new compounds and assess performance trends before physical experiments.

  • Machine Learning & Materials Informatics

    Training Predictive Models on Materials Data

    MPDS is widely used for machine learning in materials science, providing high-quality datasets for training models that predict materials properties and stability. Its graph-scale structure and consistent data quality make it suitable for learning models, large-scale analytics platforms, and research projects focused on discovering patterns across vast materials databases.

  • Industrial R&D and Applied Innovation

    Accelerating Industrial Materials Development

    Industrial teams rely on this materials platform for data science to shorten development cycles in chemistry, energy, and advanced manufacturing. By accessing curated materials data and published research in one repository, companies improve data management, reduce duplication, and support materials innovation with reliable inputs for engineering and product design.

FAQs

What is included in Materials Platform for Data Science dataset?
The dataset includes inorganic materials data linked to phase diagrams, crystal structures, and physical property records. It connects over 189,000 materials phases derived from hundreds of thousands of scientific research publications.
Can I request a sample of the MPDS dataset before purchasing?
Yes. Free samples are available so researchers can review data quality, schema structure, and searchable material properties. This allows evaluation of compatibility with analytics platforms, learning models, and scientific research workflows.
What types of annotations and metadata are provided?
The dataset contains over 100 standardized metadata categories, including elements, formulas, symmetry, space groups, and physical properties. These annotations enable structured querying, materials informatics analysis, and model training.
What data formats are available in the MPDS dataset?
Data is available as a relational SQL database with JSON exports and a defined schema.
How was the data collected and curated?
Data has been manually curated by domain experts from peer-reviewed publications for over 30 years. This expert-driven process ensures high data quality, consistency, and reliability for scientific research and engineering applications.
How are Unidata datasets licensed?
Unidata follows a dual-licensing model. Free samples are provided for testing and evaluation, while full datasets are available exclusively through purchase.
Do Unidata datasets comply with GDPR and data privacy regulations?
Yes. All datasets are curated in compliance with GDPR and applicable data protection laws. Data is sourced from legally permissible and ethical scientific publications.
How are Unidata datasets stored and managed?
All datasets are securely stored on AWS cloud infrastructure and managed according to ISO 27001 and ISO 27701 standards. This ensures secure access, scalability, and long-term reliability of materials databases.
Still have questions about using Unidata datasets? Read our user-guides

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