AI Data Science White Papers for R&D

AI and Business Strategy

White Paper – How Not To Fail at AI – Notes from the field

In this paper we will draw on the experience of two experts who have been involved in hundreds of AI projects in chemical companies and learn lessons about what works and what doesn’t.

White Paper – Building AI Demands Action

This white paper focuses on the building of the value, in this case the ability to conceive, evaluate, create, and deliver new materials that meet your business’s goals, meet or exceed the sustainability targets, and differentiate your solutions in the global market.

White Paper – Leading Requires Action

Learn about AI and the new toolset for digital innovation in materials, and how executives can create the strategy and define the value early to leverage technology in product R&D.

White Paper – 3 Ways AI Supports Your Sustainability Goals

How AI supports materials and chemicals companies in their efforts to source sustainably, make processes more efficient and develop sustainable products.

eBook – Digital Transformation and Materials Informatics

Digital transformation is a key business initiative of most of the world's large chemicals and materials companies. This paper identifies critical success factors for digitalization in materials and chemicals and how the Citrine Platform supports them.

Return on investment for artificial intelligence project in materials

White Paper – How an AI-Enabled Data Infrastructure Impacts the Bottom Line

Learn how materials informatics can systematically improve return on investment (ROI) for new product development, with a platform that becomes more powerful with each new project.

White Paper – Amplify the impact of your data science team

Paper discussing how implementing a 3rd party Materials Informatics platform frees up the time of your data science team to do what they are good at.

AI for Different Markets

White Paper – No Data No Problem: How to get started with AI in Adhesives and Sealants

This paper will outline what value Adhesives and Sealants companies are already gaining from AI and give practical tips on how to get started and what to look for in an AI provider.

White Paper – No Data No Problem: How to get started with AI in Paints and Coatings

This paper will outline what value Paints and Coatings companies are already gaining from AI and give practical tips on how to get started and what to look for in an AI provider.

White Paper – The Value of AI in Polymers

Leaders across the Polymers value chain have adopted AI as part of their product development and optimization processes, and with good reason - it works!

White Paper – How Beauty and Personal Care Companies Extract Value from AI

Consumer Packaged Goods (CPG) companies have been adopting AI as part of their product development process, and with good reason - it works! Learn how the Citrine Platform is delivering ROI for 2 of the 5 top global CPG companies worldwide.

White Paper – Agile Recycled Plastics Formulation Using AI

Recycling polymers is important. Customers are specifying sustainability criteria, and legislation is now in place in major markets to forcibly increase recycling efforts. Motivation is high to work out how we can recycle plastics into new high-quality plastics in a consistent and efficient way.

White Paper – Materials Informatics for Coatings Formulations

To meet ever-shifting market, customer and supply demands, leaders in the coatings industry have adopted materials informatics (MI) to accelerate formulation development.

White Paper – Challenges in Machine Learning for Formulations

Formulations development has unique challenges associated with the vast spectrum of possible ingredient combinations and the complex rules that govern their mixing. Learn how we address these challenges with formulations-specific AI and data management approaches.

White Paper – AI and Catalysis

This paper explains and gives examples of how AI can be used to efficiently explore the highly multi-dimensional challenge of developing new catalysts and how hierarchical, graphical AI models can be used to model complex interactions and compensate for scarce data through transfer learning.

Ebook – AI for AM

This paper explores how AI can be used to accelerate developments in additive manufacturing materials, and how AI can help optimize processing parameters.

Battery cross section showing the components of a battery system that can be optimized with AI.

Ebook – Better Battery Design Using AI

Better batteries with with higher energy density and the ability to charge quickly are needed to enable the energy transition. This paper explores how AI can be used to reach ambitious battery property targets quickly, through material development, battery configuration optimization and improved battery testing.

Concepts

White Paper – Leveraging Physics-Based Models and AI for New Material Development

Physics-based models (PBMs) are used extensively in materials research, primarily as a proxy for more time and cost intensive experimental material production and characterization.

White Paper – Challenges in Machine Learning for Materials

Learn how Machine Learning for Materials and typical AI applications are different. See how Citrine has overcome these difficulties and why off-the-shelf open source AI will require a lot of tailoring to make it work in this space.

White Paper – Domain Knowledge Integration

Learn how the Citrine Platform integrates domain knowledge to accelerate development and increase knowledge sharing across a materials or chemicals business.

Data Management

White Paper – Data Management on the Citrine Platform

Understand the data landscape and get tips on data management best practices. Learn how to upload your data to the Citrine Platform and how to prioritize data digitization.

White Paper – Advanced Data Preparation Services

Short overview of the data preparation services we offer and how they add value to customers.

White Paper – Integration with the Citrine Platform

Overview of how the Citrine Platform fits in to your wider data ecosystem.

Security

White Paper – Generative AI and LLM Security Levels

Most people have heard the stories of LLMs like ChatGPT hallucinating. But that is not the only risk to using a large language model (LLM). These models learn and process data in different ways, and employees must take great care with them to ensure the model's stated security policies...