Molecularscale surface analytics Giovanni Costantini Department of Chemistry

  • Slides: 7
Download presentation
Molecular-scale surface analytics Giovanni Costantini Department of Chemistry, University of Warwick, UK

Molecular-scale surface analytics Giovanni Costantini Department of Chemistry, University of Warwick, UK

Our instruments • 4 STM instruments LT-UHV Createc VT-UHV Specs RT-UHV Omicron ambient •

Our instruments • 4 STM instruments LT-UHV Createc VT-UHV Specs RT-UHV Omicron ambient • 2 ESI-deposition setups O’Spray SEISMIC • XPS-UPS Warwick Interdepartmental Photoemission Facility • Synchrotron (NIXSW in particular, IO 9 @ Diamond) 2

Polymer Analytics A B 2 nm B A A BB 1 nm A B

Polymer Analytics A B 2 nm B A A BB 1 nm A B A D. A. Warr, et al. , Sci. Adv. 4, eaas 9543 (2018) 3

Ultrahigh Resolution Molecular Imaging for Chemical Structure Determination © IBM Zürich The central idea

Ultrahigh Resolution Molecular Imaging for Chemical Structure Determination © IBM Zürich The central idea of this project is to exploit the unparalleled spatial resolution of UHVSPM to solve a fundamental analytical problem: determining the exact chemical structure of an unknown molecule. Our proposed solution is extremely simple but, at the same time, potentially transformative: adsorb the molecule onto a surface and just take a picture of it. A. Mistry, et al. , hem. : Eur. J 21, 2011 (2015) 4

“It would be very easy to make an analysis of any complicated chemical substance;

“It would be very easy to make an analysis of any complicated chemical substance; all one would have to do would be to look at it and see where the atoms are”. (There's Plenty of Room at the Bottom, 1959) 5

Automating scanning probe microscopy Necessary condition to make SPM into a “real” and useful

Automating scanning probe microscopy Necessary condition to make SPM into a “real” and useful analytical technique. (towards a “push button” technique) Main objectives: • Tip preparation • Image recognition (chemical structure determination) 6

Machine Learning collaborations Andrea Cavallaro Professor of Multimedia Signal Processing, QMUL Director of the

Machine Learning collaborations Andrea Cavallaro Professor of Multimedia Signal Processing, QMUL Director of the Centre for Intelligent Sensing. QMUL 20+ years of research (well before the hype!) in ML applied to automated vision, image recognition, audio detection Current research interests: Robotic perception, Camera networks, Multimodal information fusion, Underwater imaging, Privacy-by-design. 7