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Citrine Informatics

AI for Product Development, Production, and Sales in Materials and Chemicals

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Home / Content Library

Content Library

The citrine content library includes scientific papers featuring citrine technology written by our own team and distinguished academics.

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Applying AI to Paints and Coatings R&D
This webinar will showcase the benefits of combining AI with physics-based simulations at different length scales, from atomic and molecular simulation to microstructural modelling tools and FEA.
Plastics, Webinars, All Webinars
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The Business and Scientific Value of Artificial Intelligence in R&D of New Materials
This webinar summarizes how AI is impacting materials companies through faster speeds to market, increased responsiveness to customer and market needs and greater knowledge retention and new hire onboarding.
Webinars, Business Case & Concepts, All Webinars
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DataLab Webinar: The Intersection of Sustainability and Digitalization
An executive discussion between the founders of Citrine Informatics and Zymergen on the intersection of sustainability and digitalization. They discuss how Zymergen has developed sustainable products in record time...
Webinars, Hear From Industry, All Webinars
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The importance of purposeful work
The best missions don’t just provide lip service to pipe dreams, they add purpose to the work employees are pushing toward on a daily basis.
Life at Citrine
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Five High-Impact Research Areas in Machine Learning for Materials Science
Over the past several years, the field of materials informatics has grown dramatically. Applications of machine learning (ML) and artificial intelligence (AI) to materials science are now commonplace. As...
Papers By Citrine
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Reproducibility in high-throughput density functional theory: a comparison of AFLOW, Materials Project, and OQMD
A central challenge in high throughput density functional theory (HT-DFT) calculations is selecting a combination of input parameters and post-processing techniques that can be used across all materials classes,...
Papers By Citrine
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Single-Crystal Automated Refinement (SCAR): A Data-Driven Method for Determining Inorganic Structures
Single-crystal diffraction is one of the most common experimental techniques in chemistry for determining a crystal structure. However, the process of crystal structure determination and refinement is not always...
Papers By Citrine
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Data‐driven glass/ceramic science research: Insights from the glass and ceramic and data science/informatics communities
Data‐driven science and technology have helped achieve meaningful technological advancements in areas such as materials/drug discovery and health care, but efforts to apply high‐end data science algorithms to the...
Papers By Citrine
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Machine Learning in Materials Discovery: Confirmed Predictions and Their Underlying Approaches
The rapidly growing interest in machine learning (ML) for materials discovery has resulted in a large body of published work. However, only a small fraction of these publications includes...
Papers By Citrine
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Machine-Learning Guided Quantum Chemical and Molecular Dynamics Calculations to Design Novel Hole-Conducting Organic Materials
Materials exhibiting higher mobilities than conventional organic semiconducting materials such as fullerenes and fused thiophenes are in high demand for applications such as printed electronics, organic solar cells, and...
Papers By Citrine
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Citrine Informatics

Citrine Informatics is an enterprise SaaS platform company that leverages generative artificial intelligence (AI) and materials science to help customers to improve materials and chemicals development.

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Redwood City, CA 94063
info@citrine.io

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