The scanning tunneling microscopy (STM) is one of the most useful local probe methods for studying physical and chemical phenomena at surfaces of various materials in atomic resolution by using tunneling electrons. STM can not only image but also manipulate surface structures with atomic precision. The development of the STM, awarded by the Nobel prize in Physics in 1986, contributed to the emergence of nanotechnology as we know today.
Materials with reduced dimensions are known to have different properties compared to their bulk counterparts. Two-dimensional (2D) materials, like graphene among many others, and layered heterostructures show intriguing properties that are promising for using them as building elements of devices in a variety of future technologies in the wide fields ranging from sensorics to catalysis, solar cells, molecular electronics/spintronics, nano-biomedicine, etc. Computational methods, for instance multiscale modeling employing density functional theory (DFT), Monte Carlo methods, and STM simulations are ultimately useful for understanding the physical and chemical properties of such new materials and material combinations.
The proposed theoretical PhD research covers analytical, programming, and numerical tasks in the fields of materials research and STM simulations. The main goal is to characterize 2D materials, oxide surfaces/interfaces, ultrathin oxide films and metal-organic frameworks by DFT+STM calculations in collaboration with international research groups. Another goal is to develop theoretical tools in STM and scanning tunneling spectroscopy (STS), and solve emerging technologically relevant problems with the newly developed computational methods. The above outlined theoretical research activities, partly in close combination with experiments, will contribute to an in-depth atomic level understanding of structural, stability, electronic, adsorption and catalytic properties of a variety of novel 2D material surfaces, which lays the basis for future technological exploitations.
During the PhD training, the successful applicant will gain considerable research skills in multiscale materials modeling, from first principles DFT to electron transport methods. Moreover, soft skills in programming, problem solving, analytical thinking, teamwork, and international collaborations will be developed. The work involves close collaborations with a number of internationally leading research groups from Canada, China, Germany, Korea, and Poland, and includes regular visits at foreign partners and at international conferences.
More details on the supervisor: http://www.phy.bme.hu/~palotas/index.html
Motivation for theoretical and computational work, programming skills, good communication skills, open personality, knowledge of solid state physics and/or chemistry