The Citrination platform is the world’s most-used cloud-based materials and chemical data infrastructure, with millions of records and multi-user deployments at national laboratories and Global 1000 manufacturing companies. Our platform continually ingests and understands large-scale data from countless sources, such as research papers, characterization tools, simulations, and existing databases, and uses state-of-the-art machine learning to anticipate the behavior of all materials and products under any relevant conditions. Citrine is backed by top-tier Silicon Valley venture capital firms, including Eric Schmidt’s fund Innovation Endeavors, Data Collective, Prelude Ventures, AME Cloud Ventures, Morado Ventures, and XSeed Capital.

 
 

Data Catalogue

  • Citrine’s public Open Citrination platform has ingested over 17 million property-structure-process relationships available to all Citrine customers and users; this is the world’s largest materials database
  • The Open Citrination user community is constantly contributing new data that become available to users and our learning algorithms
  • Citrine provides an ever-growing set of commercial data modules available at additional cost
 

Materials Data Infrastructure

  • Store and search experimental and computational data about physical systems, ranging from atomistic data on materials to device- or part-scale performance, with Citrine’s open Physical Information File JSON-based data format
  • Integrate diverse data from existing databases and infrastructures into a single repository
  • Support for highly structured datasets and unstructured documents
  • Data accessible for read/write via graphical web interface and Citrine API (both python and java clients available)
  • Citrine and our user community are developing a constantly-growing set of data importers for a variety of tools and simulations
    • Example: DFT codes such as VASP and Quantum Espresso
    • Example: CALPHAD tools such as Computherm and Thermocalc
 

Artificial Intelligence Engines

  • Citrine’s platform trains predictive models on ingested materials, device, and product datasets and exposes the resulting models to users with detailed accuracy statistics via a graphical interface
  • Inverse design capability, wherein users supply any number of design targets and Citrine suggests novel materials or processes likely to meet these targets
  • Citrine’s developer program allows third-party research groups to integrate analysis software within our platform