Dr Carla Verdi

ARC DECRA Fellow

Physics
Faculty of Science
c.verdi@uq.edu.au
+61 7 336 52473

Overview

Dr Verdi's research is in the field of computational materials physics. Her work employs first-principles or ab initio methods, complemented by machine learning techniques, to predict and understand physical properties of materials without relying on empirical models.

She received her doctorate in Materials from the University of Oxford in 2017. After working at the University of Oxford and the University of Vienna, Dr Verdi moved to the University of Sydney in 2023 as an ARC DECRA Fellow. In the same year she then joined UQ as a Lecturer in Condensed Matter Physics.

Her current research focuses on understanding the structural, optical and thermodynamic properties of atomic defects for applications in quantum technologies. She is also interested in studying the influence of atomic vibrations, defects, temperature and disorder on the intrinsic properties of various functional materials that can be exploited for novel technologies. Feel free to reach out to Dr Verdi if you are interested in simulating materials properties from first principles using supercomputers and exploring how this can help develop better materials.

Qualifications

  • Doctor of Philosophy of Materials, University of Oxford
  • Masters (Research) of Physics, Università degli Studi di Padova
  • Bachelor of Physics, Università degli Studi di Padova

Publications

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Grants

View all Grants

Supervision

  • Doctor Philosophy

  • Doctor Philosophy

View all Supervision

Available Projects

  • Atomic defects in solids are one of the most promising single-photon sources or 'quantum emitters', an important building block for many quantum technologies. In order to design and engineer better quantum emitters, a fundamental understanding of their optical and electronic properties, as well as defect formation and migration, is essential. In this project, first-principles quantum mechanical calculations combined with machine-learning techniques are used in order to uncover key properties such as defect dynamics, formation mechanisms, free energies and stabilities at room and elevated temperatures. The theoretical insights gained in the project aim to inform the design of atomic defects systems for tailored applications as quantum emitters. The student will gain experience with high-performance computing and materials simulation methods, in particular first-principles methods and machine-learned potentials.

  • Density functional theory (DFT) is a prominent tool that enables the simulation of materials and molecules at the atomic scale 'from first principles', i.e., without relying on empirical data. To underscore its importance in modern materials physics and beyond, it should suffice to mention that 12 papers on the top-100 list of the most-cited papers of all time, including 2 of the top 10, are all related to DFT. In this project, first-principles DFT calculations will be used to investigate and characterise the structural and electronic properties of 2D structures and solid surfaces. These properties can be directly compared to experimental data, such as scanning tunneling microscopy (STM) experiments conducted in SMP. Target systems include solvated molecules on alkali halide structures, perovskite materials for next-gen solar cells, and oxide structures on metal superconductors.

    The student will gain experience with widely used first-principles materials modelling software and high-performance computing.

View all Available Projects

Publications

Book Chapter

Journal Article

Grants (Administered at UQ)

PhD and MPhil Supervision

Current Supervision

  • Doctor Philosophy — Principal Advisor

    Other advisors:

  • Doctor Philosophy — Associate Advisor

    Other advisors:

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • Atomic defects in solids are one of the most promising single-photon sources or 'quantum emitters', an important building block for many quantum technologies. In order to design and engineer better quantum emitters, a fundamental understanding of their optical and electronic properties, as well as defect formation and migration, is essential. In this project, first-principles quantum mechanical calculations combined with machine-learning techniques are used in order to uncover key properties such as defect dynamics, formation mechanisms, free energies and stabilities at room and elevated temperatures. The theoretical insights gained in the project aim to inform the design of atomic defects systems for tailored applications as quantum emitters. The student will gain experience with high-performance computing and materials simulation methods, in particular first-principles methods and machine-learned potentials.

  • Density functional theory (DFT) is a prominent tool that enables the simulation of materials and molecules at the atomic scale 'from first principles', i.e., without relying on empirical data. To underscore its importance in modern materials physics and beyond, it should suffice to mention that 12 papers on the top-100 list of the most-cited papers of all time, including 2 of the top 10, are all related to DFT. In this project, first-principles DFT calculations will be used to investigate and characterise the structural and electronic properties of 2D structures and solid surfaces. These properties can be directly compared to experimental data, such as scanning tunneling microscopy (STM) experiments conducted in SMP. Target systems include solvated molecules on alkali halide structures, perovskite materials for next-gen solar cells, and oxide structures on metal superconductors.

    The student will gain experience with widely used first-principles materials modelling software and high-performance computing.