Webinars

Hear from leading steel and technology provider voestalpine as they explain how they have applied machine learning (ML) in additive manufacturing (AM) applications.

Learn about simple-to-use software to save experimental time and cost and find optimal formulations.  With applications from dairy products to aerospace coatings, pharmaceuticals to paint, plastics to perfume.

See how machine learning is powering innovative 3D printing technology to enable an autonomous manufacturing process. In partnership with Photocentric.

See how machine learning-led DOE can be applied in just a few button-clicks, cutting experimental workloads by 50-80%.

Through a case study of an oligonucleotide project, learn how machine learning can improve the productivity of life science research and help to optimise manufacturing processes. With guest speaker CPI.

Learn how machine learning can design new formulations and chemicals, reduce experimental workloads by 50-80%, and enable response to regulatory constraints.  Domino Printing Sciences give a case study presentation on their use of machine learning to develop ink formulations.

In this webinar, we demonstrate ML for materials design and development and hear a case study presentation from Welding Alloys Group. This details a project in which ML found an improved, cost-effective, and more environmentally-friendly hardfacing material.

Physics and chemistry simulation and analytical methods are now standard tools in the development of improved materials and formulations, and the use of machine learning (ML) is increasing. Each of these classes of method has advantages and drawbacks. In this webinar, we shared the results of a project that developed a framework allowing such methods to be combined, including case studies of studying different phases in an alloy and of predicting surfactant properties.

Alchemite™ is a novel machine learning method originally developed in the group of Dr Gareth Conduit at the University of Cambridge. The new Alchemite™ Academic Programme makes access to Alchemite™ affordable and easy for academic researchers. In this webinar, with live Q&A, Gareth Conduit introduces the method and provides examples of its application to academic research in materials science, chemistry, battery research, and life sciences.

Guest speaker: Lukas Kuerten, CPI

Machine learning methods generate insights from data to accelerate innovation in areas including drug discovery, translational medicine, formulation, and manufacturing processes. In this webinar, we explored the potential and some of the challenges of applying this technology. We heard a case study from Lukas Kuerten of CPI on using machine learning to predict viability of biopharmaceuticals early in development.

Guest speaker: Claire Hatfield, Johnson Matthey

Designing and developing new and improved products at pace is challenging when responding to rising costs, supply chain and regulatory constraints and the need to meet sustainability targets. Johnson Matthey presents case studies of the use of machine learning in designing catalyst formulations for clean air and life science applications. Benefits include increased process yields and reductions in experimental time and cost.

Guest speaker: Gabe Guss, Lawrence Livermore National Laboratory

In this webinar, we heard how machine learning can be applied to predict and optimise print parameters for additively-manufactured parts and in the development of materials for AM processes.

Guest speaker: Matthias Eisner, Yili

This webinar demonstrates the use of machine learning for formulation development, including a case study presentation from leading global food producer, Yili.

Optimising the chemistry, blending, and formulation of polymers can have profound impacts on the performance, economics, and sustainability of an array of products and industrial processes. Find out how innovative machine learning can enable a data-driven approach.

Join Intellegens and battery experts Deregallera as we discuss how machine learning can supercharge battery development. We will look at three key applications: (1) New battery materials and formulations; (2) Design of battery packs; (3) Battery management. We’ll discuss the challenges of applying machine learning to these problems and how these challenges are being overcome to improve charging capacity and energy density, lower development times and costs, and enable more efficient operation.

Guest speaker: Dr Richard Padbury, Lucideon

Find out how materials technology experts Lucideon are applying machine learning to research applications including controlled release drug delivery, battery technology, ceramics, polymers, and complex formulations. We discuss how machine learning might transform the future of material and process development and see a demonstration of the Alchemite™ deep learning technology.

Development organisations in engineering, manufacturing, and materials need to design new and improved materials and components and to wring every drop of performance from existing systems. In this webinar, we hear about a project to validate and apply Alchemite™ machine learning in pursuit of these goals at NASA Glenn Research Center.

Find out how machine learning methods are being applied to solve key problems in the design, characterization, and processing of metal alloys and other advanced materials. With guest speaker from the Advanced Manufacturing Research Centre, discussing a joint project between the AMRC, Intellegens, and Boeing.