Skip to content
  • Webinars
  • Careers
  • Contact
  • Request a Demo ›
Citrine Informatics logo

Citrine Informatics

  • Product
    • Overview
    • The Citrine Platform
    • Adding Business Value
    • AI at Scale
    • Adoption
  • Solutions
  • Success
    • Case Studies
    • White Papers
    • Newsletters
    • Podcasts
    • Blog
    • Webinars
  • What is Materials Informatics?
  • Research
    • Overview
    • Technology Differentiation
    • Publications
    • How To Work With Us
    • Education and Training
  • About
    • Overview
    • Team
    • Media
      • News
      • Press Releases
    • Careers
      • Overview
      • Current Openings
    • Contact
    • Product
      • Overview
      • The Citrine Platform
      • Adding Business Value
      • AI at Scale
      • Adoption
    • Solutions
    • Success
      • Case Studies
      • White Papers
      • Newsletters
      • Podcasts
      • Blog
      • Webinars
    • What is Materials Informatics?
    • Research
      • Overview
      • Technology Differentiation
      • Publications
      • How To Work With Us
      • Education and Training
    • About
      • Overview
      • Team
      • Media
        • News
        • Press Releases
      • Careers
        • Overview
        • Current Openings
      • Contact
    • Webinars
    • Careers
    • Contact
    • Request a Demo ›
Home / Research / Publications

Publications

Scaling data-driven materials development in industry

Presented 9 Nov 2020 @ High Throughput Research: Accelerating Materials Discovery, Design, Development and Deployment, organized by the National Academy of Engineering, Division on Engineering and Physical Sciences, National Materials and Manufacturing Board

Conference Presentations
An Industrial Perspective on FAIR Data and Machine Learning for Materials

Presented 3-5 June 2020 @ FAIR Data Infrastructure and Materials Genomics, organized by FAIR Data Infrastructure for Physics, Chemistry, Materials Science, and Astronomy e.V.

Conference Presentations
Design space visualization for guiding investments in biodegradable and sustainably sourced materials

In many materials development projects, scientists and research heads make decisions to guide the project direction. For example, scientists may decide which processing steps to use, what elements to include in their material selection, or from what suppliers to source their materials. Research heads may decide whether to invest development effort in reducing the environmental […]

Papers By Citrine
Assessing the Frontier: Active Learning, Model Accuracy, and Multi objective Materials Discovery and Optimization

Discovering novel materials can be greatly accelerated by iterative machine learning-informed proposal of candidates—active learning. However, standard global error metrics for model quality are not predictive of discovery performance, and can be misleading. We introduce the notion of Pareto shell error to help judge the suitability of a model for proposing material candidates. Further, through […]

Papers By Citrine
Machine-learned metrics for predicting the likelihood of success in materials discovery

Materials discovery is often compared to the challenge of finding a needle in a haystack. While much work has focused on accurately predicting the properties of candidate materials with machine learning (ML), which amounts to evaluating whether a given candidate is a piece of straw or a needle, less attention has been paid to a […]

Papers By Citrine
The 2019 Materials by Design Roadmap

Advances in renewable and sustainable energy technologies critically depend on our ability to design and realize materials with optimal properties. Materials discovery and design efforts ideally involve close coupling between materials prediction, synthesis and characterization. Increased use of computational tools, the generation of materials databases, and advances in experimental methods have substantially accelerated these activities. […]

Papers By Citrine
Strategies for accelerating the adoption of materials informatics

Ongoing, rapid innovations in fields ranging from microelectronics, aerospace, and automotive to defense, energy, and health demand new advanced materials at even greater rates and lower costs. Traditional materials R&D methods offer few paths to achieve both outcomes simultaneously. Materials informatics, while a nascent field, offers such a promise through screening, growing databases of materials […]

Papers By Citrine
Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery

Traditional machine learning (ML) metrics overestimate model performance for materials discovery. We introduce (1) leave-one-cluster-out cross-validation (LOCO CV) and (2) a simple nearest-neighbor benchmark to show that model performance in discovery applications strongly depends on the problem, data sampling, and extrapolation. Our results suggest that ML-guided iterative experimentation may outperform standard high-throughput screening for discovering […]

Papers By Citrine
Materials Data Infrastructure and Materials Informatics

Data-driven materials research requires two key supporting components: data infrastructure and informatics. In this chapter, we review the state of the art in materials data infrastructure, focusing in detail on four infrastructure projects spanning academia, government, and industry. We also discuss data standards as an enabling step on the path to community-scale materials data infrastructure. […]

Papers By Citrine
Building Data-driven Models with Microstructural Images: Generalization and Interpretability

As data-driven methods rise in popularity in materials science applications, a key question is how these machine learning models can be used to understand microstructure. Given the importance of process–structure–property relations throughout materials science, it seems logical that models that can leverage microstructural data would be more capable of predicting property information. While there have […]

Papers By Citrine

Research Categories

  • Papers by Citrine
  • Papers Mentioning Citrine
  • Conference Presentations

Learn More

  • Publications
  • Blog
  • Newsletters
  • Webinars
  • Case Studies
  • White Papers
  • Podcasts
1 2 3 4 5
Citrine Informatics
  • Product
  • Solutions
  • Success
  • What is Materials Informatics?
  • Research
  • About
  • Careers
  • Contact
  • Request a Demo

2023 © Copyright Citrine Informatics Privacy

We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept”, you consent to the use of ALL the cookies.
Cookie settingsACCEPT
Manage consent

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary
Always Enabled
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Non-necessary
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.
SAVE & ACCEPT