| 17 Sept. | 14:00 - 15:30 | |||
| ROOM 25 | |||||||
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| ADVANCED MATERIALS | |||||||
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| 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 |
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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. |
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| The symposium is part of WS.I |
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| 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 |
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| 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 |
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| 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 |
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| TT.III.D.4 WS.I.3.4 |
Enzo ROTUNNO - CV CNR-NANO Towards Autonomous Electron Microscopy Characterisation: Automation, Data Management, and AI Analysis |
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| Back to Fields & Topics | Back to Plan 17 September | ||





