Projects


These below are examples of projects our group can offer to Master and Bachelor students

Bachelor Projects

Several of the master projects listed above and described below can be adapted to be a bachelor project. Even more so, a solid background in math/physics/programming is required - please email your request to the relevant project proposer, mentioning your grades in all classes relevant.

Master thesis projects

The master projects that we offer require a solid background in maths, physics, and programming. Therefore, anyone interested should first follow the course on Quantum Simulations of Materials (MSE468, spring semester, taught either by Prof. Nicola Marzari or Dr. Giovanni Pizzi). If interested, please contact the responsible for the organisation of the projects Nicephore Bonnet at least two weeks before the EPFL registration deadline, with a copy of your transcripts and a short description of your competences and interests. The projects listed below are also suitable for EPFL master students who will take the course “Research project in materials I” (10 credits) [https://edu.epfl.ch/studyplan/en/master/materials-science-and-engineering/coursebook/research-project-in-materials-i-MSE-490]. Be aware that all the master students are required to attend all the group meetings and recommended seminars, remote supervision is guaranteed in case of absence of places in the laboratory.

Accelerating structure optimizations using perturbative post-processing

High-throughput studies, where thousands to tens of thousands of materials are simulated, are a powerful tool for broadening our knowledge of materials properties and discovering new and interesting functional materials. A key step in many of these studies is structure optimization, in which an approximate arrangement of atoms in a crystal is optimized to the most stable configuration.

Since each iterative step of the associated with this optimization is roughly as expensive as a single-point calculation of ground state energy, atomic structure optimization accounts for a substantial amount of computational time in high-throughput workflows. Additionally, the obtained minimal-energy geometry can be highly dependent on the chosen numerical parameters for the calculation, such as the basis set cutoff. Therefore, a good compromise between the error of a too small cutoff and a too slow (but accurate) structure optimization needs to be found.

Along this direction, mathematical research has provided a number of new tools in the past years to (a) estimate the numerical error due to basis set discretizations and (b) correct for this error using post-processing techniques. For the force as the key quantity of interest in structure optimizations, a promising perturbative approach has emerged recently [1]. A preliminary implementation of this force-refinement strategy is already available in the density-functional toolkit (DFTK, [2]), a Julia-based code which enables joint research of both mathematicians and scientists performing first-principle materials simulations.

Here at THEOS, we develop AiiDA [3], a software framework written in python which simplifies and automates workflows for high-throughput studies. By integrating DFTK with AiiDA, we want to both test the force refinement approach on a broader range of systems and unlock this cheaper route to structure optimizations for broader use.

Requirements: Strong programming skills in particular python; knowledge of Julia programming is a bonus, but can also be acquired as we go along; interest in learning about the numerical and mathematical underpinnings of first-principle based materials simulations.

Contact: Michael Herbst or Austin Zadoks

[1] E. Cancès, G. Dusson, G. Kemlin and A. Levitt. SIAM J. Sci. Comp. 44 (2022). ArXiv 2111.01470v1

[2] M. Herbst, A. Levitt and E. Cancès Proc. JuliaCon Conf. 3, 69 (2021). https://dftk.org

[3] S. Huber, et al. Scientific Data. 7, 300 (2020). https://www.aiida.net/

Phonon-mediated heat transport in graphene and hexagonal boron nitride

Two-dimensional materials have received growing interests owing to their unique physical properties, which are the promising candidates for next-generation efficient and reliable energy harvesting. In particular, graphene and hexagonal boron nitride (h-BN) which are excellent heat conductors with superior thermal properties have been demonstrated to provide high-performance thermal management of electronic devices and power batteries [1,2]. Because of the reduced dimensionality, the emergence of quadratic flexural vibrational modes in low dimensions dominates heat transport and play a vital role in exhibiting a non-Fourier conduction regime such as hydrodynamic phonon flow [3].

In this project, we will utilize the state-of-the-art classical molecular dynamics with our recently implemented internal-coordinate potential (ICP) [4] in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) to investigate the heat transport in graphene and h-BN. This interatomic potential allows to simulate the large physical system at the micro-/meso-scale with ab initio accuracy. The student will learn how to perform equilibrium molecular dynamics via the Green-Kubo linear response theory and nonequilibrium molecular dynamics via the Fourier’s law to calculate thermal conductivity, and carry out normal mode analysis to extract mode-dependent phonon properties such as lifetime [5]. Besides, transient laser heating can be further performed with molecular dynamics to probe the time evolution of temperature field which signatures the wave-like heat propagation (second sound).

Requirements: Prior to this project, the candidate must have completed the two courses MSE-423 and MSE-468.

Contact: Changpeng Lin

[1] Balandin, A. A. Thermal properties of graphene and nanostructured carbon materials. Nature materials, 2011, 10(8): 569.

[2] Song, H. et al. Two-dimensional materials for thermal management applications. Joule, 2018, 2(3): 442.

[3] Cepellotti, A. et al. Phonon hydrodynamics in two-dimensional materials. Nature communications, 2015, 6(1): 1.

[4] Libbi, F., Bonini, N. and Marzari, N. Thermomechanical properties of honeycomb lattices from internal-coordinates potentials: the case of graphene and hexagonal boron nitride. 2D Materials, 2020, 8(1): 015026.

[5] Lin, C., Chen, X. and Zou, X. Phonon–grain-boundary-interaction-mediated thermal transport in two-dimensional polycrystalline MoS2. ACS Applied Materials & Interfaces, 2019, 11(28): 25547.

High-throughput screening of high thermal conductivity materials for efficient thermal management

Engineering materials with superior thermal properties is fundamental to electronic industry for realizing high-performance devices and reliable thermal management. The traditional procedure to discover new materials which relies on in-lab synthesis, characterization and measurements is slow, impeding the rapid economic and societal developments. Thanks to the advances in computational power nowadays, instead the high-throughput calculations can be performed to accelerate the discovery of novel materials, providing an initial screening of promising candidates for subsequent experiment verification.

The goal of this project is to identify high thermal conductivity materials from the recently built database for two-dimensional materials (MC2D) [1], for efficient heat dissipation. The first assessment of more than 1000 candidates based on elastic properties (e.g. elastic moduli, sound velocity and Debye temperature) has been carried out to select materials with potentially high thermal conductivity [2]. The student will play with the Boltzmann transport equation to calculate thermal conductivity from first principles [3] and develop the AiiDA [4] workflow for the automated calculations of thermal transport properties.

Requirements: Prior to this project, the candidate must have completed the two courses MSE-423 and MSE-468.

Contact: Changpeng Lin

[1] Mounet, N. et al. Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds. Nature nanotechnology, 2018, 13(3): 246.

[2] Lin, C., Poncé, S. and Marzari, N., in preparation, 2022.

[3] Shindé, S. L. and Srivastava, G. P. Length-scale dependent phonon interactions, Springer, 2014.

[4] Huber, S. P. et al. AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance. Scientific data, 2020, 7(1): 1.

Theoretical and computational study of cathode materials for eco-friendly rechargeable batteries

Requirements: Prior to this project, the candidate must follow the two courses MSE-423 and MSE-468.

Description of the project:

Our society is currently making a big effort to undergo a transition to the climate-friendly ecosystem. Constant growing of the population is accompanied by needs in larger amounts of energy [1], which is currently being produced mainly by using oil, coal, natural gas, which are sources of huge CO2 emissions which lead to the global warming. This cannot be continued like that further because the consequences for our planet and for the humanity will be disastrous. In fact, many governments announced roadmaps for achieving carbon-free ecosystem by 2050 (Swiss Energy Strategy 2050, EU's Battery2030+ flagship). Therefore, all the traditional energy sources must be replaced by the renewable energy sources (solar, wind, hydro, etc.), but these are not stable, and hence we need efficient and eco-friendly ("green") battery technologies for storing large amounts of energy and use it later when there are large demands. This semester project is focused on the theoretical and computational investigation of batteries, more precisely of the positive electrodes ("cathodes") [2].

Cathode materials contain transition-metal compounds (TMCs) (see figure below, which is the crystal structure of LiFePO4 [3]), and from the theoretical point of view modelling of TMCs is very challenging due to the presence of strongly localized and partially filled d-type electrons. In this project the student will use Hubbard-corrected density-functional theory [4,5,6], which has proven to be successful for accurate modelling of TMCs. All calculations will be done using the Quantum ESPRESSO package, which is the most widely used open-source electronic-structure software for materials modelling at the atomistic scale [7,8]. For more information see this page.

figure1

[1] D. Larcher and J.-M. Tarascon, Nature Chem. 7, 19 (2014).

[2] L. Monconduit, L. Croguennec, R. Dedryvere, Book "Electrodes for Li-ion Batteries: Materials, Mechanics, and Performance", vol. 2, Wiley (2015).

[3] M. Cococcioni and N. Marzari, Phys. Rev. Materials 3, 033801 (2019).

[4] V.L. Campo Jr. and M. Cococcioni, J. Phys.: Condens. Matter 22, 055602 (2010).

[5] I. Timrov, N. Marzari and M. Cococcioni, Phys. Rev. B 98, 085127 (2018).

[6] I. Timrov, N. Marzari and M. Cococcioni, Phys. Rev. B 103, 045141 (2021).

[7] P. Giannozzi et al., J. Phys.: Condens. Matter 29, 465901 (2017).

[8] P. Giannozzi et al., J. Chem. Phys. 152, 154105 (2020).

This project requires the following skills:

  • Good knowledge of quantum mechanics, density-functional theory
  • Basic knowledge of Linux and bash scripting

Contact: Iurii Timrov

Visualization plugins for the Materials Cloud platform

Our group has been developing AiiDA (www.aiida.net), a platform to automate simulation of materials, store results in a database, analyse the results and share them. Moreover, we develop Materials Cloud (www.materialscloud.org), a rich web interface to expose the AiiDA database and show research results, as well as to provide simulation tools to researchers. These projects require that the student is already expert with python, including its object-oriented programming features.

Option 1: There is room for the students to choose a project to extend the functionalities to support researchers in the use of AiiDA via web interfaces, or to improve the web interface tools of Materials Cloud.

These projects require experience with JavaScript, HTML, CSS.

A non-exhaustive list of examples:

  • New visualizer plugins of data in the database, or of specific physical properties: see e.g. http://materialscloud.org/tools/seekpath/ for crystal structures and Brillouin zones
  • graph browsing, or Graphical Query Builder to look into the database
  • advanced python tools to analyse calculation results

Option 2:

These project requires experience with python and jupyter.

Task: create interactive visualisations in python notebooks and/or as Materials Cloud tools (https://www.materialscloud.org/work/tools/options).

On possible example is the realisation of a tool that, given the Hamilonian parameters as obtained from a Wannier-Function calculation, can compute the interpolated band structure on the fly, and when zooming recalculates the band structure on the selected region, giving the illusion of an infinite-zoom capability. This project would help students in better understanding band structures, dealing with the interpolation of them from DFT calculations on denser grids using Wannier functions, and to put this knowledge together in a useful and advanced web tool.

Contact: Kristjan Eimre, Giovanni Pizzi