At present, there are different projects ranging from PhD projects, at the Master level as well for Bachelor thesis.
Project: Machine Learning Room Temperature Superconductors
The field of superconducting hydrides has witnessed the first room-temperature superconductor. Recently, an unknown system formed by C-S-H had been reported with a maximum temperature of superconductivity close to 15-degree celsius. The crystalline structure and exact composition are still debated. Further progress in computational techniques is highly desirable to speed up the discovery of other high-Tc materials. Help could come from advanced methodologies such as machine learning models, fingerprints and neural networks that are robust and well tested in other fields. During the development of this project, you will be brought up top-speed into the state of the art material simulation methods: we will build a machine learning model and test its accuracy versus a curated database. Succeeding in this task, and you will be able to predict the superconducting values of Tc, at a relatively small fraction of the large computational overhead. Only a handful subset of materials from hundreds that have been proposed have been measured. Considering a large number of systems that contain hydrogen and the vast space of thermodynamic conditions yet to be explored, there is plenty of room for discovering your new high-Tc material!
Project: Complex Phase Transformation in 2D materials
Two-dimensional materials are substances with a thickness of a few nanometres or less. Electrons in these materials are free to move in the two-dimensional plane, but their restricted motion in the third direction is governed by quantum mechanics. Prominent examples include quantum wells and graphene. Other systems of interest are materials that easily exfoliate or are fabricated from 3D counterparts. We will focus on intermetallic compounds that, in their bulk, have been extensively studied for the purpose of thermoelectricity, superconductivity and as hard materials. Here, we revive a subset of materials overlooked by generations and understand the process that leads to a specific transformation from 3D to 2D. The transformation is not merely peeling like in graphite (which leads to graphene), it involves re-arranged of bonds and is driven by energetic reactions. Your aim is to understand further the transformation by mapping the lattice vibrations. Aiming to connect the results to an experimental observable (spectroscopy, Raman, IR, etc.). Succeeding in this task, and you will be able to unmask novel quantum materials.
Project: Computational Evaluation of Prospective High-Performance p-Type Transparent Conductors
Transparent electronic and photonic devices have been a long-coveted technological advancement that would enable the creation of many futuristic applications, allowing us to turn windows into power generators (solar panels). At the centre of this technological advancement are unique materials –transparent to visible light, yet capable of sustaining an electric current. Such materials, known as transparent conductors (TCs), are typically formed from wide bandgap semiconductors, where the mobile charge carriers are introduced by heavy doping. The electrons (n-type) or holes (p-type) are generated through point defect incorporation. Though such point defects, as the name implies, create structural imperfections in the host crystalline lattice, their presence is key to the performance of TC materials. High-throughput studies are gaining increasing popularity as a tool for predicting p-type transparent conductors. However, the lack of appropriate descriptors makes the efficient screening of materials for this purpose challenge. Yet, to identify and validate novel descriptors, more robust data on non-oxide p-type transparent conductors is needed. During this project, you will focus on point-defect (native and impurity) calculations in a variety of wide bandgap materials. We suggest an in-depth investigation of the p-type propensity of all recently speculated, but not experimentally verified, p-type TC materials through an exhaustive study of native defects. Succeeding in this goal will open possibilities to advance the field of transparent conductors and bring futuristic applications at hand.