Developing a Microstructural Fingerprint for Mining Process-Microstructure

The Henry Royce Institute is the UK’s national institute for advanced materials research and innovation. With its Hub at The University of Manchester, the Royce is a partnership of nine leading institutions – the universities of Cambridge, Imperial College London, Liverpool, Leeds, Oxford, Sheffield, the National Nuclear Laboratory, and UKAEA. The Institute’s aims are to undertake world-class research in materials science, to accelerate the commercialisation of materials research for economic and societal benefit and to train the next generation of materials scientists and engineers to tackle some of our most pressing global challenges.

Henry Royce Institute

A seminar presenting work in Machine Learning for Materials Science in alignment with Materials 4.0.

Royce Hub Building

As part of our commitment to Materials 4.0 we are running a series of webinars to showcase and demystify research towards Materials 4.0.The seminar is also hosted in-person at the Royce Hub BuildingThe event will feature a 30-minute talk by one of our Royce Researchers followed by a 20-minute Q&amp;A portion.Guests are welcome to submit questions in advance of the event.AbstractFinding efficient means of quantitatively describing material microstructure is a critical step towards harnessing data-centric machine learning approaches to understanding and predicting processing-microstructure-property relationships. Common quantitative descriptors of microstructure tend to consider only specific, narrow features such as grain size or phase fractions, but these metrics discard vast amounts of information. Since the gain in traction of machine learning and computer vision, more abstract methods for describing image data in a concise and quantitative manner have become available but have yet to be fully exploited within materials science. Here, we explore some of these methods as tools for constructing compressed representations of microstructural image data, referred to as “microstructural fingerprints”, and investigate their potential for mining correlations between fingerprints.SpeakerMike White is a PhD student at the University of Manchester, working on machine learning-based tools for materials applications, with Chris Race and Phil Withers, in the Department of Materials.This event will be recorded and posted online. By attending you consent to some of your actions being recorded. Video for attendees will be turned off.

Our {communityGuidelinesLink} describe the sort of content we prohibit on Eventbrite. If you suspect an event may be in violation, you can report it to us so we can investigate.

To report other categories of prohibited or illegal content, submit {link}

Developing a Microstructural Fingerprint for Mining Process-Microstructure

More events from Henry Royce Institute

Discover more events from Henry Royce Institute, from Science & Tech to other experiences you might love.

Developing a Microstructural Fingerprint for Mining Process-Microstructure

More events from Henry Royce Institute

Discover more events from Henry Royce Institute, from Science & Tech to other experiences you might love.

You might also like...

Browse more events with different dates, prices, and formats to find your next great experience.