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project is to overcome these limitations through the design of a flexible, quantum sensing foil based on an atomically-thin two-dimensional (2D) material. Our approach consists in using optically-active
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, neuromorphic electronics based on spiking neural networks (SNNs) and the compute-in-memory (CIM) paradigm is emerging as the most promising path. While the research community has so far favored resistive Compute
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staff of around 120, including 66 permanent staff. It has a strong experimental component, with numerous prototype set-ups supported by both standard equipment and high-tech instrumentation
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the development of the optical strategy and its integration with the electrochemical one. Besides optimizing a sensitive quantitative phase imaging setup for analysis of thin surface layers in reflection mode, it