Materials for Quantum and Photonic Technologies

Due to the aggressive miniaturisation of electronic devices, modern technologies are based on nanometer-sized devices and hence termed as "Nanotechnology". At this ultra-small scale, the primary focus is to harness the power of quantum nature of materials for the design and optimisation of next generation devices such as super-fast quantum computers, spin-based quantum sensors, high-efficiency photovoltaics, low-loss photonic devices, imaging of individual molecules, and nano-particle drug delivery systems, among many others.       
Our team studies quantum physics to enable innovative nanotechnologies through advanced atomistic simulations of nano-materials and nano-structures. We develop multi-scale computational tools based on tight-binding and DFT theories to enable quantitative understanding of new and emergent quantum materials in close collaboration with experimentalists. Based on our state-of-the-art simulation framework, we also predict not-yet-fabricated devices with optimised functionalities by exploring uncharted territories and provide guidance for new measurements to be carried out. 
Above all, the pursuit of understanding physical phenomena at nanometer scale is an absolutely fascinating journey, as it unravels the complexity of nature underpinning everything around us! 

Broad Areas of Interest:

Nanoelectronics, Quantum Physics, Machine Learning, High Performance Computing, Materials Science


Quantum Computing, Spin Qubits, Optoelectronic/Photonic Devices, Materials Discovery.

Few key questions which motivate our work are:

  • How can we benefit from the available noisy intermediate-scale quantum (NISQ) devices for implementation and testing of quantum concepts?

  • How to exploit the very long coherence time of SiP spin qubits for designing a scalable and universal quantum computing architecture?

  • Can we engineer the wavelength and polarisation properties of III-V QDs for photonic and photovoltaic devices with optimised functionalities? 

  • Can we design low-loss photonic devices from novel bismide materials such as GaBiAs and GaBiNAs with tailored wavelengths? 

  • Audio/Video available online at and Youtube: 

    [Video] Quantum Computing: Fundamentals and Applications
     @ IEEE University of Melbourne Talk, 2020.

    [Video] World's first pinpointing of qubits for quantum computers @ CQC2T, University of Melbourne, and University of New South Wales, Australia

    [Video] Quantum Dot based Photonic Devices @ Physics Department, Dartmouth College, New Hampshire, USA 

    [Audio] Multi-layer QD Stacks for SOAs @ 3rd International Workshop on Epitaxial Growth and Fundamental Properties of Semiconductor Nanostructures, Austria 

    [Audio] Excited State Spectroscopy of a Bilayer QD Molecule @ Electrical & Computer Engineering Department, University of Iowa, Iowa, USA 

    [Audio] Theory of Bismide Alloys @ 2nd International Workshop on Bismuth containing Semiconductors, Surrey University, UK 

    [Audio] Why QD Simulations Must Contain Multi-Million Atoms?   

    [PDF] PhD Research Summary @ Purdue University, Indiana, USA 

    [PDF] Theory of Self-Assembled Quantum Dots - My Ph.D. Thesis @ Purdue University, Indiana, USA 

    Summary of Research Methods:

    The theory and modeling work is based on the following methods:

  • Strain relaxation of atoms in a quantum heterostructure based on atomistic valence force field (VFF) method.

  • Electronic structure calculations based on sp3d5s* tight-binding theory, k.p model, DFT, or some hybrid of these methods.

  • Inter-band optical transition strengths and optical gain from Fermi's Golden rule.

  • Linear and quadratic piezoelectric potentials by solving the Poisson's equation.

  • Multi-particle excitonic spectra from Heitler-London and full configuration interaction (FCI).

  • STM wave function images by coupling Bardeen's tunnelling theory, Chen's derivate rule, and Slater orbitals with tight-binding theory

  • Further details about these methods are presented here: Modeling Methodologies

    Compute Resources:

    Simulations with realistic dimensions of devices ranging from 10-100 nm include several hundred thousands to a few million atoms in the simulation domain and therefore require high-performance super-computing machines. Our work is supported by computational resources provided by the following super-computers:
    • Magnus @ Pawsey Supercomputing Centre through NCMAS Allocation (2016-current)
    • Raijin @ National Computing Infrastructure through NCMAS Allocation (2016-current)
    • Spartan @ the University of Melbourne (2014-current)
    • RCAC @ Purdue University through NCN/Nanohub (2005-15)

    (1) Are you an experimentalist and interested in our theory? Please feel free to send an email. 

    (2) Are you a student and want to be a part of our team? Please feel free to send an email. 
        For admission and scholarship information, please visit: 

    Selected Articles
    Small 2021

    Long-range molecule-molecule interactions 
    npj Computational Materials 2020

    Machine learning to scale up the quantum computer 
    Nanoscale 2019

    Million-atom simulations propose optimal GaBiAs/GaAs core-shell nanowire structures for telecom-wavelength photonics. 
    Nanoscale 2017

    Visualisation of central-cell-effects in STM images for high-precision donor physics. 
    Nature Nanotechnology 2016

    World's first pinpointing of atoms for quantum computers. (Article Here)

    Nanoscale 2015

    Electric field breaks the strong coupling of quantum dot molecules. (Article Here)

    JPCM (Invited Article) 2015

    Si:As Donor Wave function - Fixing the central-cell corrections in the tight-binding theory. (Article Here)

    PRB Rapid Comm. 2014

    An InAs/GaAs QD stack tilted to offer unique optoelectronic properties. (Article Here

    PRBs 2011 & 2013,  Invited Feature Article 2013

    An elemental change to laser design. (Article Here)

    Nanotechnology 2011, Editor Highlight

    Supercomputers model real-world quantum dot devices atom-by-atom (Article Here)