The course will review some basic concepts in semiconductor devices and introduce the challenges and limitations of current CMOS nano devices. The focus will then move to thin film devices (i.e. MOSFETs, sensors) and circuits. The second part of the cours

The goal is to provide an overview of two emerging fields of electronics. The course will try to illustrate the basic physical mechanisms of the devices and highlight their limitations and technological challenges. The main objective is not to treat the topics in a comprehensive manner but rather to stimulate the interests of the students and researchers.

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Initially, the course will review some basic concepts in semiconductor devices and introduce the challenges and limitations of current CMOS nano devices. The focus will then move to thin film devices (i.e. MOSFETs, sensors) and circuits. These are some of the topics that will be discussed:
- micro and nanomaterials (CNTs, graphene and 2D materials, inorganic thin film) for flexible electronics;
- microfabrication of the devices: conventional microfabrication and additive manufacturing;
- challenge and limitations;
- examples of application: flexible displays, flexible sensors for brain monitoring and recording, epidermal circuits, degradable implants.
The second part of the course will focus on neuromorphic computing. Today, neural networks and machine learning algorithms are widely used to solve problems in data mining, vision recognition and language processing. These algorithms require high computational capabilities and are usually run on GPU (graphical processing unit). However, the computation on such machines is highly inefficient. New computer architectures that emulate the firing behaviour of the brain would be necessary to decrease power consumption and latency.

Here, some of the topics discussed in the course:
- computers Vs brain: Von Neuman (digital, clocked) and in-memory computing (analog, event-based)
- electrical model of the synapsis and its realization in CMOS technology;
- new devices and architecture for in-memory computing: resistive, phase change and ferroelectric memory;
- examples of application: computation, prosthetics, autonomous robots.

- S.M. Sze, Kwok K. Ng, “Physics of semiconductor devices”, John Wiley & Sons,
- slides and additional readings will be provided during the course.

PowerPoint presentations, blackboard and printed material (when needed). Video conference might also be possible (if needed).

A final (oral) exam, where every student will also deliver a short presentation about a topic discussed during the course