NANOTECHNOLOGY

NANOTECHNOLOGY
1 YEAR II semester  6 CFU
Antonio Agresti (3cfu)

Francesca De Rossi (3cfu)

A.Y. 2021-22
Antonio Agresti (3cfu)

Fabio Matteocci (3cfu)

A.Y. 2022-23

A.Y. 2023-24

Antonio Agresti A.Y. 2024-25
Code:
SSD: ING-INF/01

LEARNING OBJECTIVES AND EXPECTED LEARNING OUTCOMES:

LEARNING OUTCOMES:
The first part of the Nanotechnology course introduces thin film depositions using both physical and chemical vapour depositions. The main objective is the knowledge of the potential and limits of the different thin film depositions in the nanotechnology field. Particular attention is destinated to the deposition technique used in micro and nanoelectronics based on semiconductors using top-down and bottom-up approaches. The interaction of both approaches has been discussed with the student in order to share the importance of multidisciplinary knowledge (physics, chemistry and engineering) where the nanotechnology field is based. The final part of module 1 is destinated to the introduction of the case study of the course about the thin film fabrication of an emergent photovoltaic technology: the perovskite solar cells. In particular, the study of the optoelectronic properties of the materials and the fabrication of several device architectures is important to understand the important role of the manufacturing design in thin film photovoltaic technologies destinated at the industrial level.

KNOWLEDGE AND UNDERSTANDING:
Regarding the first module, at the end of the course, the student will have a clear overview of the main deposition technique studied and applied in nanotechnology for different application fields.
Regarding the second module, at the end of the course, the student will know the main characterization techniques for nanostructured materials and electronic and optoelectronic devices till nanometric size.

APPLYING KNOWLEDGE AND UNDERSTANDING:
The student will be able to recognize the applicability areas for the various characterization and realization techniques at nanometric scales. She/He will also be able to apply the knowledge and understanding developed during the course to study and understand recent literature.

MAKING JUDGEMENTS:
The transversal preparation provided by the course implies
1) the student’s capability to integrate knowledge and manage complexity
2) the student’s ability to deal with new and emerging areas in nanotechnology application to energy and nanoelectronics.

COMMUNICATION SKILLS:
The student will be able to clearly and unequivocally communicate the course content to specialized interlocutors. He will also be able to communicate the main physico-chemical characteristics of nanostructured materials and to indicate the most appropriate deposition/processing technique of these materials to technical interlocutors (example: other engineers, physicists, chemists) but not specialists in the field of electronics or devices. The student will also have a sufficient background to undertake a thesis/research work in modern nanotechnology laboratories.

LEARNING SKILLS:
The structure of the course contents, characterized by various topics apparently separated but connected by an interdisciplinary and modular vision, will contribute to developing a systemic learning capacity that will allow the student to approach in a self-directed or autonomous way to other frontier problems on nanotechnology application to energy and nanoelectronics. Furthermore, the student will be able to read and understand recent scientific literature.

 

SYLLABUS

 

First Module: 1 Prof. Antonio Agresti (3 cfu)

1) Quantum Mechanics and p-n junction

2 )Solar Cells: main electrical characterization techniques

3) Absorbance and Fluorescence Spectroscopy

4) Electron scanning microscopy (SEM)

5) Electron transmission microscopy (TEM)

6) Scanning tunneling microscopy (STM)

7) Atomic force microscopy (AFM)

8) Kelvin Probe Microscopy (KPFM)

9) Raman spectroscopy

10) Bi-Dimensional Materials

 

Second module – Prof. Fabio Matteocci (3cfu)

 

1) Introduction to nanotechnology and thin film properties;
2) Thin Film Deposition: the importance of vacuum and plasma;
3) Thermal Evaporation: Working mechanism, material properties, deposition parameters and applications;
4) DC and RF Sputtering: Working mechanism, material properties, deposition parameters and applications;
5) Pulsed Laser Deposition: Working mechanism, material properties, deposition parameters and applications;
6) Chemical Vapour Deposition: Working mechanism, material properties, deposition parameters and applications;
7) Atomic Layer Deposition: Working mechanism, material properties, deposition parameters and applications;
8) Solution Processing: Spin coating, Screen Printing, Blade Coating, Slot die coating;
9) Patterning Procedures: Photolithography and Laser Ablation;
10) Introduction to Perovskite Solar Cell: Working mechanism, material properties, deposition techniques, up-scaling process and applications;
11) Building Integration Photovoltaics;

VLSI CIRCUIT AND SYSTEM DESIGN

VLSI
1 YEAR II semester  9 CFU
Luca DI NUNZIO A.Y. 2021-22
Luca DI NUNZIO (5 cfu)

Vittorio MELINI (2 cfu)

Sergio SPANO’ (2 cfu)

since A.Y. 2022-23
Code:
SSD: ING-INF/01

PREREQUISITES:

It is strictly suggested to take the “Digital Electronics” exam before attending this course. You can contact Prof. Luca DI NUNZIO for any doubts regarding the topic.

LEARNING OUTCOMES:

The VLSI CIRCUIT AND SYSTEM DESIGN course aims to teach the basics of combinational and sequential circuits that represent the basic blocks of any modern digital system. In addition, the course will provide the basic concepts of the VHDL language

KNOWLEDGE AND UNDERSTANDING:

At the end of the course, the student will learn the basic concepts of combinational and sequential circuits that are the basis of any system and the basic concepts of the VHDL language useful for the design of digital systems

APPLYING KNOWLEDGE AND UNDERSTANDING:

Ability to analyze the characteristics of digital circuits with particular emphasis on timing and power consumption.

MAKING JUDGEMENTS:

The student will understand the acquired knowledge independently and critically to be able to connect and integrate the various aspects related to the design of digital systems

COMMUNICATION SKILLS:

The student must be able to communicate their knowledge acquired during the course in clear, correct, and technical language.

LEARNING SKILLS:

Ability to critically approach a digital circuit design problem, know how to manage it, and find implementation solutions using the VHDL language

SYLLABUS:

(L. DI NUNZIO)

Digital electronics basic concepts
Floating-point and fixed-point numeric representation formats
Combinatorial circuits: encoders, decoders, multiplexers
Sequential circuits: flip flops, latch registers, counters, memories
Introduction to VHDL: entity and architecture, levels of abstraction, HDL design flow, combinatorial and sequential processes, objects in VHDL test bench
Practical activities of circuit design in VHDL

(S. SPANO’)

Central unit
ALU
System registers
Address logic
System buses
Scheduler
Branching of instructions
Interrupts
Bus synchronization
RAM memories
ROM memories
Flash memories
CAM memories

 

Feedback Control Systems (block B)

Feedback Control Systems (block B)
1 YEAR II semester  6 CFU
Cristiano M. VERRELLI A.Y. 2021-22
A.Y. 2022-23
Code:
SSD: ING-INF/04

FORMATIVE OBJECTIVES

LEARNING OUTCOMES:

The theory of differential equations is successfully used to gain profound insight into the fundamental mathematical control design techniques for linear and nonlinear dynamical systems.

KNOWLEDGE AND UNDERSTANDING:

Students should be able to deeply understand (and be able to use) the theory of differential equations and of systems theory, along with related mathematical control techniques.

APPLYING KNOWLEDGE AND UNDERSTANDING:

Students should be able to design feedback controllers for linear (and even nonlinear) dynamical systems.

MAKING JUDGEMENTS:

Students should be able to identify the specific design scenario and to apply the most suitable techniques. Students should be able to compare the effectiveness of different controls while analyzing theoretical/experimental advantages and drawbacks.

COMMUNICATION SKILLS: Students are expected to be able to read and capture the main results of a technical paper concerning the topics of the course, as well as to effectively communicate in a precise and clear way the content of the course. Tutor-guided individual projects (including Maple and Matlab-Simulink computer simulations as well as visits to labs) invite intensive participation and ideas exchange.

LEARNING SKILLS:

Being enough skilled in the specific field to undertake the following studies characterized by a high degree of autonomy.

SYLLABUS:

The matrix exponential; the variation of constants formula.

Computation of the matrix exponential via eigenvalues and eigenvectors and via residual matrices. Necessary and sufficient conditions for exponential stability: Routh-Hurwitz criterion. Invariant subspaces.

Impulse responses, step responses and steady state responses to sinusoidal inputs. Transient behaviours. Modal analysis: mode excitation by initial conditions and by impulsive inputs; modal observability from output measurements; modes which are both excitable and observable. Popov conditions for modal excitability and observability. Autoregressive moving average (ARMA) models and transfer functions.

Kalman reachability conditions, gramian reachability matrices and the computation of input signals to drive the system between two given states. Kalman observability conditions, gramian observability matrices and the computation of initial conditions given input and output signals. Equivalence between Kalman and Popov conditions.

Kalman decomposition for non-reachable and non-observable systems.

Eigenvalues assignment by state feedback for reachable systems. Design of asymptotic observers and Kalman filters for state estimation of observable systems. Design of dynamic compensators to stabilize any reachable and observable system. Design of regulators to reject disturbances generated by linear exosystems.

Bode plots. Static gain, system gain and high-frequency gain.

Zero-pole cancellation.

STATISTICS:

A.Y.  Mechatronics students Other courses Students Mechatronics average Other courses average
2019/2020 10 62 24 23
2020/2021 19 25 23 24
2021/2022 13 44 21 22

POWER ELECTRONICS AND ELECTRICAL DRIVES

POWER ELECTRONICS AND ELECTRICAL DRIVES
2 YEAR 2 semester 9 CFU
Stefano Bifaretti
A.Y. 2021-22
Stefano Bifaretti (7cfu)

Cristina Terlizzi (2cfu)

A.Y. 2022-23 1st Year I semester

A.Y. 2023-24  (NOT HELD)

A.Y. 2024-25

Code: 8039781
SSD: ING-INF/01

LEARNING OUTCOMES:
The Power Electronics and Electrical Drives course aims to provide a basic understanding of the power semiconductors of the main electronic circuits used for the static conversion of electrical energy as well as the electrical drives. The student will acquire the ability to analyse and perform an initial sizing of power electronic converters operating in either direct or alternating current.

KNOWLEDGE AND UNDERSTANDING:
The student will be gradually guided to the knowledge of the functional characteristics and behavior of the main static power converters used, in particular, in industrial applications, in Distributed Generation Systems and in power trains of electical vehicles. In order to improve the topics understanding, the use of Matlab-Simulink specific packages for the simulation of electronic power converters is illustrated.

APPLYING KNOWLEDGE AND UNDERSTANDING:
The knowledge acquired during the course allows the student to select the topology and size of the power converter in relation to the final design.
Different application examples, in particular devoted to distributed energy generation plants, uninterruptible power supplies and electric mobility will allow the student to improve his ability to apply the acquired knowledge.

MAKING JUDGEMENTS:
The student will be able to collect and process specialized technical information on power converters and verify their validity.

COMMUNICATION SKILLS:
The student will be able to relate with power electronics specialists in order to request the technical information necessary for the development of a project activity.

LEARNING SKILLS:
The skills acquired during the course will allow the student to undertake, with a high degree of autonomy, subsequent studies or apply for technical roles in companies working in the field.

 

SYLLABUS:

POWER SEMICONDUCTORS

Power Semiconductors employed in Power Electronics converters: Diodes, BJT, MOSFET, IGBT, Thyristors, Wide Bandgap Semiconductors).

Static and dynamic behavior. Thermal behavior. Conduction and switching losses.

Technical specifications provided by manufacturers’ datasheets. Driving circuits.

POWER CONVERTER TOPOLOGIES

Behavioral characteristics: unidirectional and bidirectional energy transfer, controlled voltage sources. Analysis method of power converters.

DC-DC Converters. Buck, Boost, Buck-Boost. Switching losses reduction. Average Model. Modulation techniques (PWM, PFM, PRM). Output voltage open-loop control. Closed-loop control. Current control.Half and Full Bridge DC-DC converters.

DC-AC Converters (Inverters). Half and Full Bridge DC-AC single-phase converters based on static switches. Three-phase converters. Modulation techniques. Selective Harmonic Elimination (SHE). Sinusoidal Pulse Width Modulation (SPWM).

Rectifiers: Single-phase and three-phase diode rectifiers. Single-phase and three-phase force-commutated PWM rectifiers: topologies, voltage and current controls. Power Factor Corrector (PFC). Effects on grid side of power converters. Generalized power factor. Compliance with grid codes.
Isolated DC-DC converter.

ELECTRICAL DRIVES
Introduction to Electrical Drives. DC, Permanent Magnet Synchronous Motors and Induction Motors. DC motors model.

Power Electronics Applications

Power Converters simulation using Matlab-Simulink/Simpowersystem.
Photovoltaic Conversion Systems.
Power trains for electrical vehicles. Battery chargers.

 

ROBOT MECHANICS

ROBOT MECHANICS

 

1 YEAR (Blocks B|C)
2 YEAR (Blocks A)
1 semester 9 CFU
Marco Ceccarelli (6/9 cfu)

Matteo Russo (3/6 cfu)

A.Y. 2021-22

A.Y. 2022-23

Matteo Russo A. Y. 2023-24
A.Y. 2024-25
Code: 8039785
SSD: ING-IND/13

LEARNING OUTCOMES:

 The aims of the course are related to explaining the modeling and algorithms for the analysis and design of the functioning of robot mechanisms in terms of mechanical performance. The students will learn how to handle the mechanics of robot by acquiring skills in analyzing and design robots for manipulation tasks in industrial and service applications.

KNOWLEDGE AND UNDERSTANDING:

during the course, problems and characteristics of robotic systems structures and operations are presented to increase students’ knowledge and to allow them to understand problems and solutions in the specific area of ​​robotics

APPLYING KNOWLEDGE AND UNDERSTANDING:

Students are required to apply the characteristics and algorithms for the analysis of manipulations and robotizations of specific robotic systems for merit assessments and demonstrate specific presentation and discussion skills of robotics issues.

MAKING JUDGEMENTS:

Students are involved in the presentation of the modeling and in the discussion of the problems to learn to examine in an autonomous and critical way the problems of analysis of robotic systems.

COMMUNICATION SKILLS:

During the course, the students take part in the discussion of the presented topics and at the end of the course present a report of manipulation and robotization analysis of their choice.

LEARNING SKILLS:

During the course, the students are involved in the discussion for a continuous stimulus to verify the learning and presentation of robot mechanics. the learning achieved is also verified in the presentation of the elaboration of manipulation and robotization analysis of their choice

SYLLABUS:

types of robots and industrial and service applications; components, technical characteristics, and evaluation; analysis and evaluation of manipulative movements; types of manipulators; Denavit-Hartenberg’s notation; fundamentals of direct kinematics; workspace analysis, trajectory planning; fundamentals of statics and dynamics: modeling, actions, equilibrium conditions; equation of motion; fundamentals of the regulation and control of the motion; types and functionality of grippers; grasp mechanics: modeling, actions, equilibrium conditions; mobile service robots: structures and operation; parallel architecture robots; service robots for medical applications: structures and operation; preparation of performance analysis reports of a robot.

INTEGRATED SENSORS

INTEGRATED SENSORS
1 YEAR (Block A|C|D|E)
2 YEAR (Block B)
1 semester 9 CFU
Corrado Di Natale A.Y. 2019-20 (new name, ex Electronic Devices and Sensors )

A.Y. 2021-22

Alexandro Catini (6cfu)

Corrado  Di Natale (3cfu)

A.Y. 2022-23

A.Y. 2023-24

Alexandro Catini A.Y. 2024-25
Code: 8039927
SSD: ING-INF/01

LEARNING OUTCOMES:

To introduce the student to modern sensor technologies and their major applications.

KNOWLEDGE AND UNDERSTANDING:

To make the student condition to analyze the sensor performance and to design simple sensors’ interface circuit.

APPLYING KNOWLEDGE AND UNDERSTANDING:

Capability to select sensors for each specific application MAKING JUDGEMENTS:
Evaluate in the different contexts which are the most suitable sensors and evaluate the performance using a standardized parameters set.

COMMUNICATION SKILLS:

Capability to write synthetic reports about the working principles of sensors

LEARNING SKILLS:

To learn how to solve sensors’ circuits to determine their performance and to optimally design sensor systems.

SYLLABUS:

Electronic properties of materials: semiconductors.

General properties of sensors;

Sensitivity and resolution.

Temperature sensors: thermistors, integrated sensors, thermocouples;
Mechanic sensors: Strain gauges: Introduction to MEMS: accelerometer, gyroscope, pressure and flow sensors;

Magnetic sensors;

Optical sensors: photodiodes and image sensors;

infrared sensors; interface circuits for resistive and capacitive sensors

Innovative Materials with Laboratory (blocks B-C)

Innovative Materials with Laboratory (blocks B-C)
1 YEAR 1 semester 6 CFU
TATA MARIA ELISA (1cfu)
COSTANZA GIROLAMO (1cfu)
VARONE ALESSANDRA (4cfu)
A.Y. 2021-22

A.Y. 2022-23

A.Y. 2023-24 (MS TEAMS)

Code: 8039786
SSD: ING-IND/21

LEARNING OUTCOMES:
The aim of the course is to provide an overview of novel materials recently developed and investigated for applications in mechanics, electronics, and mechatronics. Different types of materials are considered and described with particular attention on the preparation route, specific characteristics, and applications. Some of them are of basic importance for new technologies gaining increasing attention in industrial practice. The knowledge of innovative materials is strictly connected to the possibility and capability of designing new products.

KNOWLEDGE AND UNDERSTANDING:
Deep knowledge of the metallic structure and their mechanical behavior; in particular knowledge of innovative materials for mechatronics applications; selection of conventional material or not as a function of application, structure and properties.

APPLYING KNOWLEDGE AND UNDERSTANDING:
Ability to define materials properties and the most suitable production technologies for the components realization; Ability to perform tests in laboratory; Ability to define appropriate treatments in order to obtain the suitable mechanical properties as a function of service conditions. Ability to select innovative materials; ability to evaluate innovative materials properties.

MAKING JUDGEMENTS:
Ability to investigate, select and choose metallic materials as a function of the application.

COMMUNICATION SKILLS:
Clear and correct expression, in English language, skills on the topics covered in the course.

LEARNING SKILLS:

Ability to face a new problem, know how to manage it and find functional and correct solutions. learning ability will be evaluated by exam tests and laboratory activities.

SYLLABUS:

Amorphous alloys: production and applications of metallic glasses as mechatronic devices. Alloys with mixed structure (nanocrystalline and amorphous).

Ultrafine grained (UFG) materials: microstructural features and production routes.

Nanoporous and mesoporous materials: structural characterization and properties. Their applications for energy and gas storage.

Porous materials: metal foams, Open and closed porosity (micro and macro). Classification according to size and shape of the pores.

Properties (sound, energy and vibration absorption, crash behavior) and production methods. Functional and structural applications: lightweight construction, automotive. Metal sandwich structures.

Functional and Smart Materials. Property change as a response of external stimulus: shape memory alloy (one-way and two-way shape memory), thermochromic, photomechanical. Energy conversion:

piezoelectric, thermoelectric. Phase change materials. Applications: mechatronic, energy. Functionally graded materials.

Additive Manufacturing Technologies.

Advanced composite materials: properties, applications, and their production routes.