A webinar introducing how advanced machine learning technology can be used to make materials, plastics, and chemical processes more sustainable.
A data-driven route to more sustainable materials, processes and polymers
How can we best incorporate recycled feedstock into our material? Can we make plastics more sustainable? How do we modify processes to comply with regulations protecting the environment or human health? These are common challenges for scientists and engineers. They must use all available data to respond, optimising materials and processes, while minimising costly trial-and-error experiments. But this data is often sparse or noisy, limiting the value of conventional data analysis or machine learning methods. In this webinar, we will show how Alchemite™ deep learning software solves these problems, with examples of metals, formulated products, and a feature demonstration based on polymers.
Our mission is to help clients accelerate innovation by using our unique deep learning solutions to extract valuable information from existing processes and data.
Our technology originated from the work of Dr Gareth Conduit and collaborators at the Cavendish Laboratory, University of Cambridge. At Intellegens, we have further developed this work to build a unique Artificial Intelligence (AI) toolset that can train deep neural networks from sparse or noisy data.