Computational modeling of nanosystems

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

Table of Contents

Course presentation

Welcome to the world of Computational Modeling of Nanosystems! I’m your guide on this thrilling adventure into molecular sciences, where you’ll understand the scientific basis that makes up everything around us.

In this Master’ s-level course, we’ll explore quantum, classical, and statistical mechanics to unlock the door to groundbreaking discoveries and innovation.

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, 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. My colleague Vijay Chilkuri will help with the practical work.

Evaluation

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

A short literature review that you should write (TP2) (12.5%): You should prepare a manuscript on a topic related to chemical nano engineer, reviewing the state of the art of that field. We will evaluate the quality of research, insights, writing, and presentation.
A seminar you should deliver on the same topic of the review (TP6) (12.5%): You should give a 15-minute seminar for their colleagues about the topic of the short literature review. We will evaluate the clarity of the message, the answers to questions, the quality of slides, and time management.
A molecular dynamics program that you should code (TP3, TP4, and TP5) (25%): You should 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. We will evaluate the quality of the coding, notebook documentation, and insight delivered by analyzing the data.
Final exam (50%): This is a conventional written exam about the course topics, focused on assessing the student’s understanding of the main concepts discussed in class.

The literature review and the seminar can be on the same topic. See TP2 below for instructions about choosing 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

Date	Morning	Afternoon
Part I
16/9	Lecture QM1	Practical work TP1
23/9	Lecture QM2	Tutorial TD1
30/9	Lecture QM3	Tutorial TD2
7/10	Lecture QM4	Practical work TP2
Part II
8/10	Lecture CM1	Tutorial TD3
21/10	Lecture CM2	Practical work TP3
4/11	Lecture CM3	Tutorial TD4
18/11	Lecture CM4	Practical work TP4
Part III
25/11	Lecture SM1	Tutorial TD5
2/12	Lecture SM2	Practical work TP5
9/12	Lecture SM3	Tutorial TD6
16/12	Lecture SM4	Tutorial TD7
6/1		Practical work TP6
20/1	Examen

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 + QM review

TD2 – Mathematics review

TD3 – Python basics

TD4 – DFT Tutorial

TD5 – TDDFT Tutorial

TD6 – Nuclear ensemble and surface hopping Tutorial

TD7 – Machine learning Tutorial

Info about the Practical Works

Practical works	Delivery date
TP1 – Software installation + Python
TP2 – Topic review writing	16/12
TP3 – PES coding	4/11
TP4 – MD coding	25/11
TP5 – Thermostat coding	9/12
TP6 – Seminars	6/1

TP1 – Software installation

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

Program	Function	Website	Do I need it?
Anaconda	Python management + Jupyter	https://docs.anaconda.com/free/anaconda/install/	Recommended
MobaXTerm	SSH (Only for Windows laptops)	https://mobaxterm.mobatek.net/download.html	Needed
JMOL	Molecular visualization	https://jmol.sourceforge.net/download/	Needed
MS Office	Text, worksheets, presenttations (Maybe it’s already installed?)	https://login.microsoftonline.com/login.srf?wa=wsignin1.0&whr=univ-amu.fr	Needed
Zotero	Literature management (Only for Windows)	https://www.zotero.org/download/	Recommended
Grammarly	Writing assistant	https://www.grammarly.com/desktop	Recommended
Chrome	Browser (Likely it’s already there)	https://www.google.com/chrome/	Needed
Lean library	Journal access (Only after installing Chrome!)	https://download.leanlibrary.com/aix-marseille-universite	Needed

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.

Topic	Student
Green nanotechnology	ZYCH GONZALEZ ALBO, C.
Biologically inspired nano-assembly: DNA origami	ZHUMANIYAZOV, K.
Design and Synthesis of Nanoporous Materials for Adsorption	VITHANAGE, A. S.
Thermally activated delayed fluorescence	VILLEGAS, E.
Nano-Engineered Photocatalysts for Water Treatment	SULEIMAN, S.
Biocompatible materials for medical applications	SANCHEZ, J. D.
Nanocomposite Membranes for Advanced Filtration	SAEED, M.
Artificial intelligence for nanoengineering	RYAN, J.
Nanotechnology for carbon capture	PEREZ SIGUENZA, J.
Inorganic photovoltaics	MUIGAI, S.
New developments in high-temperature supercondutivity	MRKONJIC, M.
Nanomaterials for electrocatalytic water splitting for hydrogen generation	MOUSA, A.
Oxygen Evolution Reaction (OER) Catalysts in Zn-air Batteries	LAI, P. M.
Metal and Metal Oxide Nanoparticles in Water Purification	KARAGODA GAMAGE, D.
Mechanical and Thermal Properties of Graphene-Reinforced Aluminum Alloy Nanocomposites	JUMAMYRATOV, A.
Applications of Nanoporous Materials in Gas and Liquid Adsorption	IBRAHIMOVA, F.
Chromophore development for sunscreen	GUZMÁN, J.
Cellulose nanomaterials	FIZZA, F.
Oxygen Reduction Reaction (ORR) Catalysts in Zn-air Batteries	FATIMA, L.
Carbon-Based Nanomaterials for Water Treatment	CHERUKUNNATH PAPPINISSERI, V.
Quantum dots	ANSARI, N.
Graphene oxide	AKIK, R.
Synthesis and Fabrication of Graphene-Reinforced Aluminum Alloy Nanocomposites	ABAD, N.
Supercapacitors: perspective to energy storage
Green synthesis of quantum dots
Organic photovoltaics
Atmospheric photochemistry
Quantum computing: algorithms
Quantum computing: hardware
Machine learning for predicting molecular properties
Large language models applied to material science
Exciton propagation
Polaritronics
Quantum decoherence and quantum to classical transition
Superradiance
Materials for space exploration
Advanced nuclear fuels
Density functional theory
Classical force fields and molecular mechanics

The review should focus on molecular or material 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:

manuscript_template_single-author Download

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.)

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