Block D

MACHINE LEARNING METHODS FOR PHYSICS (D)

Simona Ranieri 2nd year, 8 CFU, Block D, II semester, Subjects , ,
Mathematical-Methods
2 YEAR (Block D)
 2 semester 8 CFU
(from Physics LM-17 )
Prof. Michele BUZZICOTTI A.Y. 2025-26
Code: 8067607
SSD: FIS/01
https://www.master-mass.eu/

 

  • PREREQUISITES: Basic concepts of Linear Algebra, Mathematical Analysis and Python Programming
  • OBJECTIVE: The lectures are thought to give a solid knowledge of the theoretical Machine Learning (ML) background. A special focus is given to the ML application for data analysis of physical systems. The students will also learn how to implement a typical ML model using the standard libraries in a Python environment.

 

Block D – Computational Methods

Simona Ranieri Block D
Block D

—> This block is conceived for eager students of Mechatronics Engineering coming from Engineering Sciences or Systems Engineering who are willing to complete their knowledge by acquiring advanced mathematical skills and computing capabilities.

Besides a first advanced course in mathematical analysis addressing complements of complex variable theory and elements of distribution theory, the block provides a second course introducing the Python exosystem for scientific computing along with a third course on data analysis and signal processing techniques for model fitting and parametric estimates or non-linear solving of inverse problems (such as image denoising, source separation, and PSF decomposition).

The fourth course will finally provide a solid knowledge of the theoretical background behind the main Machine Learning (ML) algorithms from Neural Networks to Reinforcement Learning, along with their application (by using the standard libraries in a Python environment) to open physical problems.

Block D aims to prepare professionals who can deal with complex design and managing problems using advanced mathematical tools, yet with an engineering attitude.

Professional opportunities involve R&D divisions in manufacturing or engineering companies that deal with complex computational problems or need advanced mathematical tools.

Year sem

SPECIFIC SUBJECTS – Block D

 CFU SSD class hours
1 I MATHEMATICAL METHODS FOR PHYSICS 8 FIS/02 80
1 I NUMERICAL METHODS FOR ASTROPHYSICS 6 FIS/05 60
2 I LABORATORY – CALCULUS 4 INF/01 40
2 II MACHINE LEARNING METHODS FOR PHYSICS 6 FIS/01 60
    TOTAL ECTS
 24    

1st Year – I sem – II sem

2nd Year  – I sem – II sem (since A.Y. 2025-26)

 

ELECTRONICS OF IOT AND EMBEDDED SYSTEMS

Simona Ranieri 12 CFU, 2nd year, a.a. 2023-2024, a.a. 2024-25, a.a. 2025-26, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, Block C1, Block C2, Block D, Block E, I sem, Subjects ,
ELECTRONICS OF IOT AND EMBEDDED SYSTEMS
2 YEAR 1 semester 12 CFU
Patrick LONGHI (3cfu)
Giancarlo ORENGO (3cfu)
Gian Carlo CARDARILLI (4cfu)
Luca DI NUNZIO (2cfu)		 since A.Y. 2019-20
M-5519 – ELECTRONICS OF IOT (6cfu)
M-5520 – DESIGN OF EMBEDDED SYSTEMS FOR MECHATRONICS (6cfu)
Code: 8039795
SSD: ING-INF/01

EDUCATIONAL OBJECTIVES:
The objectives of the course are:
1) to provide the tools to carry out a radio link assessment in a real application context.
2) learn the fundamental parameters of the antennas used in IoT applications
3) provide the tools to interpret the electrical diagram of the RF front end of a typical trans receiver.

KNOWLEDGE AND UNDERSTANDING:
Provide the fundamental tools to understand the most advanced and updated content from publications, magazines, forums, blogs, etc., to always be updated on the state of the art.

ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING:
Practical radio link budget, electronic noise evaluation on receiver behavior, installation effects of the antennas, understanding of key parameters of commonly used antennas in the targeted scenario, analysis of an RF transceiver block diagram

AUTONOMY OF JUDGMENT:
With the enormous amount of information that is available today to developers of IoT applications, the course seeks to develop the ability of the student to select the highest quality and most validated content.

COMMUNICATION SKILLS:
The final test is based on an oral exam in which the student illustrates a part of the module

LEARNING ABILITY:
The course aims to develop in the student the ability to independently learn new and constantly updated content because the knowledge acquired today soon becomes obsolete.

SYLLABUS:

(Longhi):

Introduction to radiating elements and their key parameters.
Ideal and practical link budget.
The effect of noise in electronic receivers, figures of merit and mathematical modelling. Receiver G/T.
Practical aspects of IoT RF systems
RFID
Radiating elements key parameters, gain, directivity, HPBW, nulls, radiation pattern, polarization, and input impedance. Some practical cases: the mono/di-pole family, microstrip antennas, parabolic reflector, wearables
Introduction to RF transceiver systems and key-components (switches, HPA, LNA, mixers, frequency generators).

(G.Orengo):

Summary of Digital Electronics: digital encoding of information, binary (fixed and floating point), hexadecimal and ASCII; operators and main logic circuits, registers and memories, programmable devices. Prototyping boards for IoT (Arduino, Rasberry), Systems on Chip (SoC), architecture of a microcontroller, description of the Arduino Uno board. Programming languages ​​(assembly, compiled, interpreted), structure of an Arduino sketch (libraries, setups, loops, functions, interrupts), programming elements in C (variables, math and logical operations, cycles, conditional statements). Use of digital and analog I/O ports (A/D conversion, PWM output). Synchronous and asynchronous serial communication modes, wired (USB) and wireless with Bluetooth, RF and WiFi modules. Remote control of electronic modules (sensors, dc stepper and servo motors, LED/LCD displays etc.) from portable devices (Windows, IoS), through applications developed in Processing and Python, and mobile (Android), through Apps developed with the MIT App Inventor platform. Internet protocols for device local/remote control through WiFi modules connected as access points/clients to web platforms or public/private cloud servers controlled by laptops and/or mobile devices.

(G.Cardarilli):

– Introduction to the Internet of Things (IoT) and embedded systems
– Wireless and mobile communications
– The Sensors
– Low power processing
– IoT and machine learning applications
– Future developments in the field of IoT and embedded systems

 

CONTROL OF MECHANICAL SYSTEMS

Simona Ranieri 2nd year, 9 CFU, a.a. 2023-2024, a.a. 2024-25, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, Block C1, Block C2, Block D, Block E, I sem, Subjects ,
CONTROL OF MECHANICAL SYSTEMS
2 YEAR
 1 semester 9 CFU
Riccardo MARINO Since 2019-20
Code: 8039823
SSD: ING-INF/04

LEARNING OUTCOMES:

Ability to understand scientific papers on the control of mechanical systems

KNOWLEDGE AND UNDERSTANDING:

Knowledge of dynamic modeling of mechanical systems. Knowledge of basic feedback control techniques for single input single output systems and of decoupling techniques for multi input multi output nonlinear systems

APPLYING KNOWLEDGE AND UNDERSTANDING:

Ability to simulate using Matlab Simulink complex controlled mechanical systems

MAKING JUDGEMENTS:

Ability to evaluate stability, robustness, and performance of a control system

COMMUNICATION SKILLS: Ability to present and discuss an autonomous design project

LEARNING SKILLS: Ability to fully understand a scientific paper on the control of mechanical systems

SYLLABUS:

BASIC CONTROL TOOLS
Bounded- input bounded- output linear systems. Pole placement theorem for controllable and observable linear systems. Luenberger observers for observable systems. Design of dynamic compensators for linear systems. Integral feedback control to reject constant disturbances. PID control. System inverses for minimum phase linear systems. The combination of feedback and feedforward control actions.
ADVANCED CONTROL TOOLS
Linear approximations of nonlinear control systems about operating conditions. The definition of region of attraction for an operating condition. Output feedback compensators with integral actions to control nonlinear systems about a given operating condition. Liapunov matrix equations to determine quadratic Liapunov functions and assess the region of attraction. The definition of the sensitivity transfer function and its properties. The gang of four: sensitivity, complementary sensitivity, load sensitivity and noise sensitivity functions. How to determine the robustness of a control loop using the gang of four functions. Bode’s integral formula and the limitations imposed by unstable open loop poles. Youla parametrization to design stable compensation. Kalman filters, Riccati equations and robust control design.

CONTROL DESIGN FOR MULTIVARIABLE NONLINEAR SYSTEMS
Relative degree for a single input single output nonlinear system. State feedback control design for input-output linearization. State feedback linearization when the relative degree is equal to the state space dimension. The definition of nonlinear inverse systems. Relative degrees or decoupling indices for multivariable (multi-input, multi-output) nonlinear systems. The definition of the decoupling matrix. State feedback control design for input-output linearization when the decoupling matrix is full rank using the Penrose pseudoinverse. State feedback linearization when the sum of relative degrees is equal to the state space dimension and the decoupling matrix is full rank.

CASE STUDIES OF NONLINEAR MECHANICAL CONTROL SYSTEMS
Control of bycicles, robots, vehicles and aircrafts

POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY (ex Internal Combustion Engines)

Simona Ranieri 1st year, 2nd year, 9 CFU, a.a. 2023-2024, a.a. 2024-25, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, Block C1, Block C2, Block D, Block E, II semester, Subjects , , , ,
POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY (ex Internal Combustion Engines)
1 YEAR (Block C)

2 YEAR (Blocks A|B|D|E)

 II semester  9 CFU
Stefano CORDINER (6/9 cfu)
Lorenzo BARTOLUCCI (3/9 cfu)
 A.Y. 2021-22

Internal Combustion Engines
Since A.Y. 2022-23

POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY
Code: 80300079

80300077 M-6264
SSD: ING/IND/08
(by Mechanical Engineering)

PREREQUISITES: Technical Physics, Fluid Machinery

FORMATIVE OBJECTIVES

LEARNING OUTCOMES:

The course aims to provide students with in-depth scientific training to correctly address the problems of designing, choosing and managing new propulsion systems for sustainable mobility starting from current solutions with internal combustion engines as well as creating the conditions for the development of innovative and low environmental impact solutions. To this end, students will develop in-depth knowledge of the operating principles of propulsion systems for transport and will learn simulation procedures for their verification and sizing. Finally, particular attention is dedicated to the most recent technological development of internal combustion engine technology aimed at overcoming current limits in terms of emissions and efficiency and defining innovative scenarios for sustainable mobility.

KNOWLEDGE AND UNDERSTANDING:
Course aim is to provide the students with tools for the analysis of the performances and the evaluation of proper design solution for internal combustion engines and their core components. At the end of the course, the student will be able to independently understand the functional link between design variables and the performance of internal combustion engines also in case of innovative design,

APPLYING KNOWLEDGE AND UNDERSTANDING:
The course, through the analysis of specific problems and quantitative data, is aimed at providing the tools for analysis and evaluation of the effects of different design choices. The theme of energy efficiency and pollution reduction are at the heart of the teaching organization. The student will be able to interpret and propose design solutions, even innovative ones, adapted to the specificity of the problems that are presented to him.

MAKING JUDGEMENTS:
By studying theoretical and practical aspects of engine design and critically assessing the influence of different design variables, the student will be able to improve his judgment and proposal in relation to design. and the management of internal combustion engines.

COMMUNICATION SKILLS:
The presentation of the theoretical and application profiles underlying the operation of internal combustion engines will be carried out to allow the knowledge of the technical language of the appropriate specialist terminology; The development of communication skills, both oral and written will also be stimulated through classroom discussion, participation in seminary activities and through final tests.

LEARNING SKILLS:
The learning capacity, even individual, will be stimulated through numerical exercises, the drafting of papers on specialized topics, the discussion in the classroom, also aimed at verifying the actual understanding of the topics treated. The learning capacity will also be stimulated by integrative educational aids (journal articles and economic newspapers) in order to develop autonomous application capabilities.

SYLLABUS:

Legislation evolution on Internal Combustin Engines. Definition of the performance of the propulsion systems and their operating characteristics in relation to the mission, driving cycles. Generalities on reciprocating internal combustion engines: Characteristics and classification, thermodynamic and performance analysis of reciprocating internal combustion engines.
Air supply for 4-stroke engines: volumetric efficiency and its evaluation; Design elements of intake systems: quasi-stationary effects; valve sizing; influence of other engine parameters; Variable Valve Actuation systems. 2-stroke engines: construction schemes; Non-stationary phenomena in intake and exhaust ducts: inertia and wave propagation; variable geometry systems; calculation models; Supercharging.
In cylinder charge Motion: Turbulence; swirl, squish, tumble; stratified charge engines.
Traditional and alternative fuels; Properties of motor fuels. Generalities: combustibles; stoichiometric air; calorific value Gaseous fuels: natural gas, hydrogen and mixtures. bio-ethanol, bio-diesel and DME. Characteristics and their use in engines: technical solutions, performance and emissions.
Fuel supply Premixed combustion engines; Non-pre-mixed combustion engines.
Combustion : Analytical elements of combustion; thermodynamics of combustion processes; calculation of the chemical composition and of the adiabatic equilibrium temperature ; transport phenomena ; chemical kinetics.
Pollutant emissions and abatement systems; Emissions: formation mechanisms, effects on health and the environment, measurement of emissions; influence of engine parameters; Innovative combustion solutions, Advanced Thermodynamic Cycles. Sustainable mobility. Operating principles of hybrid vehicles: series and parallel solution; motors a.c. and electrical employees; regenerative braking; lithium batteries, performance and prospects. Plug-in hybrid vehicles, i.c. engines “range extender”. Innovative control logics for optimal powersplitting between the different energy sources. Electric vehicles, characteristics and prospects. Numerical simulation tools will be presented for all course topics

ATTENDANCE

Course attendance is strongly recommended. During the course, students are invited to interact with the Professor during the class or office hours for any clarification or insight in specific topics related to the program.

NANOTECHNOLOGY

Simona Ranieri 1st year, 6 CFU, a.a. 2023-2024, a.a. 2024-25, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, Block C1, Block C2, Block D, Block E, II semester, Subjects ,
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 (6cfu) A.Y. 2024-25
Code: 8039791
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

 

I part: Physics and Engineering of cutting-edge nanotechnologies (tot. 3 CFU)

1) Quantum Mechanics and physiscs of semiconductors.
2) Quantum structures and nanodevices: quantum wires, quantum dots, quantum well.
3) p-n junction and diodes.
4) Devices based on quantum mechanics: Working principles and design guidelines for photodiodes, solar cells, light emitting diode (LED), laser.
5) New frontiers of the nanotechnology applications: innovative nanomaterials (2D materials) and organic electronics.

II part) Characterization techniques for nanomaterials and nanodevices (tot. 2 CFU)

1) Absorbance and Fluorescence Spectroscopy
2) Transient Absorption Spectroscopy
3) Raman Spectroscopy
4) Electron Scanning Microscopy (SEM)
5) Tansmission Electron Microscopy (TEM)
6) Scanning Tunneling Microscopy (STM)
7) Atomic Force Microscopy (AFM)
8) Kelvin Probe Microscopy (KPFM)

III part: Lab Experiences on characterization and engineering of nanomaterials and nanodevices (tot. 1 CFU)

 

VLSI CIRCUIT AND SYSTEM DESIGN

Simona Ranieri 1st year, 9 CFU, a.a. 2023-2024, a.a. 2024-25, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, Block C1, Block C2, Block D, Block E, II semester, Subjects ,
VLSI
1 YEAR II semester  9 CFU
Luca DI NUNZIO (9 cfu) A.Y. 2021-22
Luca DI NUNZIO (5 cfu)

Vittorio MELINI (2 cfu)

Sergio SPANO’ (2 cfu)

 since A.Y. 2022-23
Code: 8039166
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