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In Situ and Operando Characterization of Materials: Techniques and AI-Driven Data Interpretation

     
   17 Sept. clessidra che gira 14:00 - 15:30
ROOM 25
Advanced Materials 01
ADVANCED MATERIALS
ARTIFICIAL INTELLIGENCE AND NANOTECHNOLOGY
ARTIFICIAL INTELLIGENCE AND NANOTECHNOLOGY 
TT.III - Technical Parallel Track Sessions
In Situ and Operando Characterization of Materials: Techniques and AI-Driven Data Interpretation
Co-organized with Polytechnic University of Turin
Chair: Marco FONTANA, Polytechnic University of Turin

In situ / operando characterization techniques are attracting considerable interest from the research community and industry, since they provide insight into the dynamical evolution of physical-chemical properties of functional materials under relevant, realistic conditions. During such advanced characterization experiments, an external stimulus is applied, while the properties of interest are monitored over time and space. Significant examples are: temperature control, variable pressure, electrochemical stimulation in conditions relevant for the applications. The data collected during in situ / operando experiments are essential for the development and validation of digital twins of the functional material, building a more accurate representation under working conditions. This predictive capability of the digital twin can guide new experiments, which then provide fresh in situ / operando data, forming a closed loop, resulting in accelerated design of advanced functional materials.

The symposium is part of WS.I
TT.III.D.1
WS.I.3.1
Silvia NAPPINI - CV
CNR-IOM
In-Situ and Operando Soft X-Ray Spectroscopy of Liquid/Solid Interfaces for Digital Twin Development in Energy and Environmental Applications
NAPPINI Silvia  
TT.III.D.2
WS.I.3.2
Katarzyna BEJTKA - CV
Politecnico di Torino
Real-time electrochemical characterization of catalysts using in situ / operando TEM and complementary Raman techniques
BEJTKA Katarzyna  
TT.III.D.3
WS.I.3.3
Rocco CALIANDRO - CV
CNR-IC
In situ/operando characterization of materials by X-ray diffraction: from theory to applications
CALIANDRO Rocco  
TT.III.D.4
WS.I.3.4
Enzo ROTUNNO - CV
CNR-NANO
Towards Autonomous Electron Microscopy Characterisation: Automation, Data Management, and AI Analysis
ROTUNNO Enzo  
 

 

 
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