The Royal Society | Data-driven materials discovery | The Royal Society @royalsociety | Uploaded 1 year ago | Updated 1 hour ago
Join us for the Clifford Paterson Lecture 2020 given by Professor Jacqui Cole.
#crystallography #chemistry #energy #materials #ai
Join the discussion: https://app.sli.do/event/ovdxfNLv5bS1gHViyN9P14
StreamText offers a full page of captions and you can personalise the display adjusting the font, the font size and background. You can also open the link in a separate webpage, adjust the size of the page and place it at the top/bottom of the screen on which you are viewing the event if you would like to view the event and captions on one page. It needs to be opened/copied into a web browser on a phone, tablet or laptop. The link is set to go live at 19:00.
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Professor Jacqueline Cole was awarded the Clifford Paterson Medal and Lecture 2020 for the development of photo-crystallography and the discovery of novel high-performance nonlinear optical materials and light-harvesting dyes using molecular design rules. After 2 years of delays due to the global pandemic, Professor Cole now has the opportunity to deliver the Prize Lecture.
Professor Cole will describe how one can combine the predictive power of artificial intelligence with data science and algorithms to discover new materials for the energy sector. A ‘design-to-device’ pipeline for materials discovery will be demonstrated. Thereby, large-scale data-mining workflows are fashioned to predict successfully new chemicals that possess a targeted functionality.
The success of such a data-driven materials discovery approach is nonetheless contingent upon having the right data source to mine. It also requires algorithms that suitably encode structure-function relationships into data-mining workflows that progressively short list data toward the prediction of a lead material for experimental validation. The talk shows how suitable data are sourced, algorithms are designed and fed into predictions, and how these predictions are borne out by experiments.
The Royal Society is a Fellowship of many of the world's most eminent scientists and is the oldest scientific academy in continuous existence.
▶royalsociety.org
🔔Subscribe to our channel for exciting science videos and live events, many hosted by Brian Cox, our Professor for Public Engagement: bit.ly/3fQIFXB
We’re also on Twitter ▶ twitter.com/royalsociety
Facebook ▶ facebook.com/theroyalsociety
Instagram ▶ instagram.com/theroyalsociety
And LinkedIn ▶ linkedin.com/company/the-royal-society
Join us for the Clifford Paterson Lecture 2020 given by Professor Jacqui Cole.
#crystallography #chemistry #energy #materials #ai
Join the discussion: https://app.sli.do/event/ovdxfNLv5bS1gHViyN9P14
StreamText offers a full page of captions and you can personalise the display adjusting the font, the font size and background. You can also open the link in a separate webpage, adjust the size of the page and place it at the top/bottom of the screen on which you are viewing the event if you would like to view the event and captions on one page. It needs to be opened/copied into a web browser on a phone, tablet or laptop. The link is set to go live at 19:00.
streamtext.net/player?event=RoyalSociety
Professor Jacqueline Cole was awarded the Clifford Paterson Medal and Lecture 2020 for the development of photo-crystallography and the discovery of novel high-performance nonlinear optical materials and light-harvesting dyes using molecular design rules. After 2 years of delays due to the global pandemic, Professor Cole now has the opportunity to deliver the Prize Lecture.
Professor Cole will describe how one can combine the predictive power of artificial intelligence with data science and algorithms to discover new materials for the energy sector. A ‘design-to-device’ pipeline for materials discovery will be demonstrated. Thereby, large-scale data-mining workflows are fashioned to predict successfully new chemicals that possess a targeted functionality.
The success of such a data-driven materials discovery approach is nonetheless contingent upon having the right data source to mine. It also requires algorithms that suitably encode structure-function relationships into data-mining workflows that progressively short list data toward the prediction of a lead material for experimental validation. The talk shows how suitable data are sourced, algorithms are designed and fed into predictions, and how these predictions are borne out by experiments.
The Royal Society is a Fellowship of many of the world's most eminent scientists and is the oldest scientific academy in continuous existence.
▶royalsociety.org
🔔Subscribe to our channel for exciting science videos and live events, many hosted by Brian Cox, our Professor for Public Engagement: bit.ly/3fQIFXB
We’re also on Twitter ▶ twitter.com/royalsociety
Facebook ▶ facebook.com/theroyalsociety
Instagram ▶ instagram.com/theroyalsociety
And LinkedIn ▶ linkedin.com/company/the-royal-society
