Intellegens delivers speaker paper on using AI to design advanced materials

Using artificial intelligence (AI) and harnessing the power of deep learning to guide the design of new advanced materials, is the topic of a speaker paper that will be delivered at Engineering Materials Live later this week in Duxford.

On Thursday 20 September, Dr Gareth Conduit, Chief Technology Officer at Intellegens, and a Royal Society Research Fellow, will deliver a paper entitled The Modern Day Blacksmith. The presentation will explain how Intellegens used AI to help a commercial client develop a new nickel-based alloy for direct laser deposition.

 Using a revolutionary deep learning technique, Intellegens helped the company in question identify the best material combinations for an alloy that would deliver excellent results in terms of process-ability, cost, density, phase stability, creep resistance, oxidation and resistance to thermal stress. Intellegens created an artificial neural network, trained from pre-existing materials data, that was able to accurately predict individual material properties both as a function of composition and heat treatment. The system made it quicker and easier to search for material combinations with the properties most like to exceed the company’s target criteria. The result was the development of a new and improved material, that helped the company in question lower its costs and reduce the length of its development cycle.

Dr Gareth Conduit will deliver his presentation at 1:15pm at Engineering Materials Live on Thursday 20 September at the Imperial War Musuem, Duxford, Cambridge.

For more information about the use of AI in materials science, or to find out more about Intellegens go to: or email

About Intellegens

Intellegens is a spin-out from the University of Cambridge with a unique Artificial Intelligence (AI) toolset that can train deep neural networks from sparse or noisy data. The technique, created at the Cavendish Laboratory, is encapsulated in Intellegens’ first commercial product, AlchemiteTM. The innovative deep learning algorithms that AlchemiteTM is based on can see correlations between all available parameters, both inputs and outputs, in fragmented, unstructured, corrupt or even dirty datasets. The result is accurate models that can predict missing values, find errors and optimise target properties. Capable of working with data that is as little as 0.05% complete, AlchemiteTMcan unravel data problems that are not accessible to traditional deep learning approaches. Suitable for deployment across any kind of numeric dataset, AlchemiteTM is delivering ground breaking solutions in drug discovery, advanced materials, patient analytics and predictive maintenance – enabling organisations to break through data analysis bottlenecks, reduce the amount of time and money spent on research, and support better, faster decision-making.

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