Welcome to the Computational Modeling of Nanosystems course by Mario Barbatti.

Table of Contents

    Course presentation

    Welcome to the enchanting world of Computational Modeling of Nanosystems! Get ready for a mind-blowing journey into the tiniest wonders of life! I’m your guide on this thrilling adventure, where you’ll become a molecular architect, crafting 3D models of the building blocks that make up everything around us.

    In this Master’s level course, we’ll unlock the door to groundbreaking discoveries and innovation. From designing new drugs to predicting photochemical behavior, the possibilities are endless.

    Sure, it won’t be a walk in the park, but we’ll take it step by step, and you’ll have a blast. Masterclasses, tutorials, and practical works were designed to drive you through the mathematics, physics, and chemistry we need in this endeavor.

    So, aspiring molecular wizards, get ready to turn complex concepts into a playground of learning and growth. The adventure begins now. Are you ready? Let’s do this! 🚀

    – Mario Barbatti


    Course program

    Our Computational Modeling of Nanosystems course is composed of three parts:

    • Quantum mechanics
    • Classical mechanics
    • Statistical mechanics

    Each part has four masterclasses followed by a few tutorials and practical work sections.

    I will be in charge of the masterclasses. The practical work will count on the help of my colleague Vijay Chilkuri. Members of the Light & Molecules team will teach the tutorials.


    Evaluation

    The evaluation will be based on three tasks assigned to practical works (TP):

    • A short literature review that you should write (TP2) (25%)
    • A molecular dynamics program that you should code (TP3, TP4, and TP5) (50%)
    • A seminar you should deliver (TP6) (25%)

    The literature review and the seminar can be on the same topic. See TP2 below for instructions about how to choose a topic.

    Although these tasks are scheduled to specific TPs, you can start working on them from day one after assigning your research topic.

    You can discuss and work with colleagues, but the MD program and literature review are individual works you must do yourself.

    For researching, writing, illustrating, coding, and any other tasks, you can (and must!) use generative AI (ChatGPT, BingAI, Bard, Midjourney, …) to help. However, you are the author. Any mistake, omission, or false information is not a machine’s fault; it’s yours!

    Also, plagiarism is a deadly sin.


    Course Schedule

    DateMorningAfternoon
    Part I
    18-SepLecture QM1Practical work TP1
    25-SepLecture QM2Tutorial TD1
    02-OctLecture QM3Tutorial TD2
    09-OctLecture QM4Practical work TP2
    Part II
    16-OctLecture CM1Tutorial TD3
    23-OctLecture CM2Practical work TP3
    06-NovLecture CM3Tutorial TD4
    13-NovLecture CM4Practical work TP4
    Part III
    20-NovLecture SM1Tutorial TD5
    27-NovLecture SM2Practical work TP5
    04-DecLecture SM3Tutorial TD6
    11-DecLecture SM4Tutorial TD7
    08-JanPractical work TP6

    Program of the Masterclasses

    I – QUANTUM MECHANICS
    QM1 – Intro to QM & Born-Oppenheimer approximation
    Wave functions and the Schrodinger Equation
    BO approximation: potential energy surfaces
    A math reminder
    The BO approximation in detail
    QM2 – Quantum chemistry
    BO approximation: TD perspective
    A note about molecular time
    Introduction to quantum chemistry
    QM3- Beyond BO approximation
    A bit of history: Born & Oppenheimer
    Nonadiabatic couplings and conical intersections
    Nonadiabatic dynamics
    QM4 – QM in context
    From quantum to classical nuclear motions
    Wave function decoherence and collapse
    Framing molecules in the Core theory
    II – CLASSICAL MECHANICS
    CM1 – Newton’s laws
    Mechanics of a particle
    Mechanics of a system of particles
    Reference frames (toward special relativity)
    EOM integration
    CM2 – Molecular mechanics: normal modes
    Harmonic approximation
    Normal modes
    Continuous medium
    Spin-Boson PES
    QM of normal modes
    Using the normal modes
    CM3 – Molecular mechanics: dynamics
    BO MD
    Fitted PES
    Model Hamiltonian
    Force fields
    QM/MM
    Continuum model
    Adiabatic x diabatic PES
    Photophysics in active environments
    CM4 – Hamilton and Lagrange formulations & MQCD
    Mixed-quantum classical methods
    Newton-X
    The cost of dynamics
    Lagrange’s equations
    Car-Parrinello MD
    Hamilton’s equations
    III – STATISTICAL MECHANICS
    SM1 – Principles of SM
    The Boltzmann picture
    Maxwell-Boltzmann statistics
    Particle distributions
    The Gibbs picture
    Thermostats
    SM2 – Monte Carlo algorithms, sampling techniques, and rates
    Monte Carlo & Metropolis
    Rate theory: Fermi, Marcus, emission
    SM3 – Fourier transform and spectrum simulations
    Statistical errors in MD
    Spectrum simulations
    Pyrene as case study
    SM4 – Machine learning
    Supervised ML: Dynamics simulations
    Unsupervised ML: Dynamics analysis

    Content of the Tutorials

    Tutorials
    TD1 – Best practices for research (Rafael Mattos)
    TD2 – Mathematics review (Mario Barbatti)
    TD3 – Python basics (Rafael Mattos)
    TD4 – Molecular dynamics and QM/MM Tutorial (Josene Toldo)
    TD5 – DFT & TDDFT Tutorial (Saikat Mukherjee)
    TD6 – Nuclear ensemble and surface hopping Tutorial (Saikat Mukherjee)
    TD7 – Machine learning Tutorial (Matheus Bispo)

    Info about the Practical Works

    Practical worksDelivery date
    TP1 – Software installation
    TP2 – Topic review writingBefore 20/12
    TP3 – PES codingBefore 30/10
    TP4 – MD codingBefore 20/11
    TP5 – Thermostat codingBefore 08/12
    TP6 – Seminars08/01

    TP1 – Software installation

    We will need several programs during the Molecular Modeling course. In TP1, we will install them on our laptops.

    ProgramFunctionWebsite
    AnacondaPython management + Jupyterhttps://docs.anaconda.com/free/anaconda/install/
    VScodeProgramming editorhttps://code.visualstudio.com/download
    WSLLinux for Windows
    (Only for Windows laptops)
    https://learn.microsoft.com/en-us/windows/wsl/install
    MobaXTermSSH
    (Only for Windows laptops)
    https://mobaxterm.mobatek.net/download.html
    JMOLMolecular visualizationhttps://jmol.sourceforge.net/download/
    MS OfficeText, worksheets, presenttations
    (Maybe it’s already installed?)
    https://login.microsoftonline.com/login.srf?wa=wsignin1.0&whr=univ-amu.fr
    ZoteroLiterature management
    (Only for Windows)
    https://www.zotero.org/download/
    LabPlotGraphicshttps://labplot.kde.org/download/
    GrammarlyWriting assistanthttps://www.grammarly.com/desktop
    ChromeBrowser
    (Likely it’s already there)
    https://www.google.com/chrome/
    Lean libraryJournal access (Only after installing Chrome!)https://download.leanlibrary.com/aix-marseille-universite

    After installing Chrome, go to Settings > Privacy and Security> Security Change DNS to “Google (Public DNS).”


    TP2 – Topic review writing

    You will write a literature review and give a seminar (TP6) on a specific topic. The topic assignment is provided below.

    TopicStudent
    Graphene oxideM. Belay
    Supercapacitors: perspective to energy storageA. Diima
    Cellulose nanomaterialsW. Perera
    Nanoporous materials: applications in adsorptionJ. Attupuram Joychan
    Green nanotechnologyK. Duerme
    Nanomaterials for electrocatalytic water splitting for hydrogen generationL. Shaju
    Quantum dotsR. Ahmad
    Green synthesis of quantum dotsB. De La Toba Acevedo
    Biologically inspired nano-assembly: 2D DNA origamiM. Ahmed
    Nanotechnology for water and water waste treatmentM. Mohamed
    Organic photovoltaicsE. Ali
    Inorganic photovoltaicsM. Tahir Hafeez
    Electrocatalysis in Zn-air BatteryN. Moustafa
    Atmospheric photochemistryC. Crîmpiță
    Quantum computingS. Mburu
    Nanotechnology for carbon captureZ. Farzizada
    Graphene-Reinforced Aluminum Alloy NanocompositesA. Marterior
    New developments in high-temperature supercondutivityI. Islam
    Chromophore development for sunscreen L. Younes
    Machine learning for predicting molecular propertiesM. Karasek

    The review should focus on molecular aspects and, when pertinent, on molecular modelization features.

    In terms of format, the review should:

    • Be in a standard paper format (Abstract, Introduction, Middle sections, Conclusions)
    • Be fully referenced and illustrated
    • Have about 2000 to 3000 words
    • Emphasize recent research (after 2020)
    • Survey at least 15 references

    You can discuss and share notes with a colleague writing on a similar topic, but the review is individual.

    Your paper should:

    • Introduce the topic and tell why it is relevant
    • Briefly explain it
    • Review the latest findings and developments
    • Draw (and even speculate about) perspectives for the future.

    We will evaluate:

    • Quality of research (pertinence of the works surveyed)
    • Quality of insights (your perspective on the topic)
    • Quality of writing (we expect publication-level English. Grammarly is your friend, Use it!)
    • Quality of formatting (the document should be beautiful, structured, and clean)

    I suggest you use this template:

    If you are uncomfortable writing in English, I strongly recommend Pinker’s The Sense of Style.


    TP3, TP4, and TP5 – Molecular dynamics coding

    We will code an analytical potential energy surface in Python and run microcanonical and canonical dynamics on it. This will be done in a Jupyter or Google Colab Notebook, which will be used in TP3, TP4, and TP5.

    Your notebook should:

    • Fully documented, clear, and understandable by someone else
    • Run smoothly

    You can work with other colleagues, but each must have their own notebooks, which must not be identical.

    We will evaluate:

    • Quality of coding
    • Quality of the notebook documentation
    • Quality of the insight delivered analyzing the data

    If your programming skills are not up-to-date, take a look at the following materials:

    For the evaluation, you should share your Jupyter notebook with the teacher responsible for the TP (it can be Dr. Vijay Chilkuri or myself). You can directly send us your .jpynb file. If you use Google Colab, it is enough to send us the link, but do not forget to make it available for anyone with the ink. (If you want to know more about sharing with Google Colab, check this video.)

    The tasks and theory needed for these TPs are described in this document.


    TP6 – Seminars

    Now it’s your turn to teach. You should give a 15-minute seminar for your colleagues about the topic of your short review (TP2).

    Your presentation should be about 10 min, with 5 minutes for questions.

    We will evaluate:

    • The clarity of your message
    • Your answers to questions
    • Quality of your slides
    • Time management

    Literature and textbooks

    The course does not follow a single source, but it references many books, papers, and internet materials like essays and videos. The references are given during the lectures. Most of them can be downloaded from the link below (the password will be given in the first lecture).

    https://amubox.univ-amu.fr/s/xXAiMZrDPb9RMRX

    CNE Class of 2023

    CNE Class of 2023 with tutors and teachers.