Platform 2.3 – Multiscale models of exciton transport

Platform Leader: Jared Cole
Deputy Platform Leader: Salvy Russo


International Collaborations

Exciton Science Research Groups

Exciton dynamics in materials and across hybrid interfaces are highly complex and are dependent on nanoscale morphology, spin polarisation and vibrational properties. The aim of this platform is to develop computational modelling techniques to understand the exciton dynamics in single molecules or organic-inorganic hybrid systems.

In this platform, we employ a combination of different theoretical approaches to examine the interplay between electronic coupling, spin and structure on exciton diffusion and delocalisation in disordered organic and hybrid materials on scales ranging from the atomistic to the device level. To this end, this platform will develop multiscale computational methods that can help interpret and predict exciton behaviour from the nanoscale to the device level.


Chief Investigators

Name Node
Salvy Russo RMIT
Alison Funston Monash
Jared Cole RMIT
Paul Mulvaney UoM
Trevor Smith UoM
Girish Lakhwani USyd
Dane McCamey UNSW
Asaph Widmer-Cooper USyd

Associate Investigators

Name Node
Kavan Modi Monash
Ivan Kassal USyd

Postdoctoral Research Fellows

Name Node
Mykhailo Klymenko RMIT
Igor Lyskov RMIT
Robert Shaw RMIT
Nastaran Meftahi RMIT
Francesco Campaioli RMIT
Yawei Liu USyd
Stefano Bernardi USyd
Martin Cyster RMIT
Jesse Collis UoM
Jesse Vaitkus RMIT

Postgraduate students

This platform is primarily concerned with method development, which is led by postdoctoral researchers. The postgraduate students using these methods are reported under the other platforms, which focus on the applications of the methods developed within this platform.

Progress towards Project Scope

As this is a central fundamental theme, exciton transport insights and multiscale modelling provides guidance across all platforms and capabilities, most particularly within Theme 1 and 2. The first three years involved a large amount of expertise and capability development. We are now applying these techniques to open problems of interest to the Centre, which should see an increase in cross-nodal projects and publications.

Progress update in 2020

New grant:

RMIT/UNSW (Cole, Russo, Schmidt) has been successful in obtaining funding of a standard proposal #6508, "Ab initio study of hybrid inorganic-organic semiconductor interfaces for photovoltaic applications", through the Molecular Foundry. The proposal plans to study the interface between Silicon (Si) and a singlet fission material like tetracene using advanced quantum chemistry techniques recently developed at the Molecular Foundry. Progress to date is steady and we have been invited to submit a continuation request in the March/April 2021 round.

New capabilities:

A key benefit of the Molecular Foundry proposal is training in the use of the BerkeleyGW code which was developed at Lawrence Berkeley National Laboratory (LBNL), which complements our existing expertise (Russo) in VASP+GW. These techniques allow accurate calculation of the excited state properties of materials which is essential for computing exciton levels and binding energies. We have also made good progress in matching quantum chemistry techniques with open-quantum systems techniques to study the movement of excitons in both polymer and crystalline materials.

Progress to date:

Results published in 2020 which demonstrate or take advantage of our multiscale modelling capabilities include:

  • The release of our new atomistic transport code (NanoNET) This codebase provides a python framework for constructing tight-binding models from atomic structures and using these models to compute electron transport properties.
  • Electron transport through ultra-thin dielectric barriers. This method uses atomic coordinates obtained from abinitio or empirical methods to compute the effective barrier seen by carriers. The I-V characteristics are then computed using a non-equilibrium Greens function approach. This method is generally applicable to charge transport in nanoscale dielectric barriers and coatings. This work is also part of a collaboration with the ARC Centre FLEET on charge transport in nanoscale devices.
  • Molecular dynamics simulations of aluminium oxidation for the formation of ultra-thin dielectric barriers. This method provides a computational approach to optimising the formation of ultra-thin dielectric layers. In doing so we can save considerable time in fabrication by exploring the full parameter space before selecting the experimental conditions. This approach has also recently been used to interpret neutron scattering studies of aluminium nanoparticles performed at the ANSTO nuclear reactor.
  • A software tool is being developed (Russo) to interrogate Data Tables of Material Properties and material performance (obtained using Material Databases software tool) and produce (via machine learning algorithms) metrics to predict material performance in similar systems. Several key modules have been written and tested: 1) API created which can interrogate the web databases Materials Project and AFLOW, download data based on search query parameters and format data for machine learning, 2) A module which calculates bandgaps of new materials based on a Machine Learning Algorithms, 3) A module which automatically calculates electron and hole effective mass parameters for semiconductor materials (including perovskite based solar cell materials), 4) A module which allows us to calculate the radiative and non-radiative (internal conversion) rates of light-harvesting molecules. The website is in beta test phase ( and a publication is under review.
  • Organic photovoltaic (OPV) materials are promising candidates for cheap, printable solar cells. However, there are a very large number of potential donors and acceptors, making selection of the best materials difficult. We have shown that machine-learning approaches can leverage computationally expensive DFT calculations to estimate important OPV materials properties quickly and accurately. We generate quantitative relationships between simple and interpretable chemical signature and one-hot descriptors and OPV power conversion efficiency (PCE), open circuit potential (Voc), short circuit density (Jsc), highest occupied molecular orbital (HOMO) energy, lowest unoccupied molecular orbital (LUMO) energy, and the HOMO–LUMO gap. This model is useful for pre-screening potential donor and acceptor materials for OPV applications, accelerating design of these devices for green energy applications.
  • We developed a computationally efficient technique based on semiconductor Bloch equations (SBEs) augmented with GW calculations, to compute the optical response of metal halides (Russo and Cole). As an example, we applied this approach to BiSBr and found excellent agreement with the experimental optical gap, and close agreement with the excitonic stabilisation energy and the absorption spectrum computed using the far more computationally demanding ab initio Bethe-Salpeter approach. The SBE method is a good candidate for theoretical spectroscopy on large or low dimensional systems which are too computationally expensive for an ab initio treatment.
  • Using a combination of quantum chemistry and molecular dynamics methods, the aggregation-induced excitonic quenching mechanisms for perylene diimide chromophores were explored (Russo). This is another example of multi-scale techniques being used to clarify the role of structure and packing in excitonic response.
  • To better understand exciton transfer in molecules, the UoM (Smith, Wong) and RMIT (Cole, Russo) groups are studying Bilirubin analogues. We have recently completed a quantum chemistry analysis of several examples using DFT/MR-CI. The next step is to perform detailed transient spectroscopy of these molecules (much of which has already been completed) and compare the exciton dynamics to master equation models based on the energy levels and couplings determined through MR-CI (collaboration with P2.1).
  • We developed an analytical framework to study the influence of a weakly intercoupled in-plane spherical metal nanoparticle (MNP) assembly on a coherently illuminated quantum emitter (QE). We reduce the analytical expressions derived for the aforementioned generic planar setup into simple and concise expressions representing a QE mediated by a symmetric MNP constellation, by exploiting the symmetry. We use generalised nonlocal optical response (GNOR) theory that has successfully explained plasmonic experiments to model the MNPs, coupled to a master equation approach to describe the dynamics of the quantum emitter. Due to the use of GNOR theory, and our analytical approach, the procedure we suggest is extremely computationally efficient. Using the derived model, we analysed the absorption rate, resultant Rabi frequency, effective excitonic energy shift, and dephasing rate shift spectra of an exciton bearing QE at the Centre of a symmetric MNP setup. This approach is now being applied to model experimental studies of pairs and clusters of quantum dots and metal nanoparticles (collaboration with P2.2).

Other important results and progress in 2020 include:

  • Based on the proposal for using silicon nanowires as detectors of exciton and charge transfer, an experimental project has commenced to demonstrate this approach. ‘Micro’wires have been fabricated (Mulvaney group) and are being measured at UNSW (McCamey). The initial experiments will focus on measurements of spatially and temporally resolved photoconductance. Later the focus will be on measuring response of organic films coated onto the wires, both large scale (McCamey) and with scanning near-field optical microscopy (SNOM) (Funston).
  • Initial computational work on Si/Tetracene interface using Berkley-GW is being drafted (Cole), focusing on the formation of dipole layers and the dependence on crystal phase, alignment and orientation.
  • A general code base is being developed to calculate Radiative and Non-Radiative Decay Rates in Chromophore molecules (Russo). This uses a combination of time-dependent density functional theory (TDDFT) and DFT coupled multi reference configuration interaction.
  • The USyd group (Widmer-Cooper) have developed a versatile model and simulation method for studying phase behaviour and dynamics in colloidal nanorod suspensions. Two papers on this were published last year, in collaboration with the Monash node (Bach) and CSIRO/RMIT (Gomez). Following on from the development of the simulation model for phase behaviour and dynamics in colloidal nanorod suspensions, this model is being used to study the formation of binary nanorod assemblies, which may reduce loss mechanisms in LSCs. In addition, the model has been used to explain the origin of rod alignment in electrophoretic assembly experiments, in collaboration with UoM (Mulvaney), and to explain the origin of chiral gels formed via helical assembly of molecular chromophores, in collaboration with USyd (Lakhwani) - reported in P2.2/3.1.
  • The USyd group (Lakhwani) have been working on a 1D drift-diffusion model to investigate the origin of reduced bimolecular recombination, when compared to that predicted by coarse grain macroscopic Langevin methods. They have identified reduced BR to depend on the ratio between rate of charge transfer (CT) exciton dissociation to free charges and rate of intersystem crossing between singlet and triplet CT states, hence, has linked it to nanoscale donor-acceptor interfacial CT states.
  • Extending the previous computational work on crystalline PPV, a new general model of exciton transport in amorphous PPV is being developed (Cole). This will allow us to study the role of confirmational changes, impurities, trapping states and diffusion rates in amorphous phases of organic semiconductors.
Schematic diagram of the Materials Discovery Software Toolkit, which enables data curation from International Materials Science Databases and Machine Learning Prediction of data.

Schematic diagram of the Materials Discovery Software Toolkit, which enables data curation from International Materials Science Databases and Machine Learning Prediction of data.

Schematic diagram of a quantum dot surrounded by metallic nanoparticles. When applying a laser field to the quantum dot, the nanoparticles dramatically modify the optical response of the dot.

Schematic diagram of a quantum dot surrounded by metallic nanoparticles. When applying a laser field to the quantum dot, the nanoparticles dramatically modify the optical response of the dot.

International Collaboration

Dr Liang Tan, Molecular Foundry, Lawrence Berkeley National Laboratory, USA

Collaboration with Mike Klymenko et al. on applying GW methods to exciton stability and energy levels at organic/inorganic interfaces (Si/Tc).

Risk and Mitigation

Staffing: Recruitment has been difficult over the last few years due to a shortage of qualified applicants and relatively inflexible University regulations. In late 2019 we were finally able to offer all the necessary appointments. Unfortunately, two of these appointments were for internationals requiring visas. These visas were then swept up in the COVID related visa freeze. Based on the delay, the University has rescinded the offers. However, there is no plan to re-advertise as the current team has the required skill set and therefore the funding will be invested in contract extensions beyond the original two or three-year contracts.

Device Modelling: In previous ISAC and internal reviews, a weakness was identified in both device modelling and transport modelling at micron to millimetre scales. This year, a “joint postdoc” appointment has been made between RMIT (Russo) and Monash (Jasieniak) to focus on device models for current and future planned experiments at Monash.

Outlook to 2021

In 2021, a range of modelling techniques will continue to be explored and benchmarked. In addition, there are an increasing number of projects underway using existing techniques to model experimental systems within the Centre and with collaborators.

Areas of interest within the platform moving forward:

  • Develop charge and exciton transport models for organic crystals to predict their photoconductance properties.
  • Develop charge and exciton transport models which can be used to study transport across the organic/inorganic interface.
  • Understand mathematical models of Boltzmann transport in metals.
  • Find a particle-based Gauss-Hermite method for solving the Boltzmann equation.
  • Develop a materials design toolkit which can predict properties of new and existing PV molecules and crystalline structures, using a combination of machine learning and ab-initio modelling techniques.
  • Understand the photophysical properties of conjugated materials and the nature of intermolecular interactions.
  • Apply simulation models for the self-assembly of colloidal nanoparticle suspensions to applications of interest to the Centre.
  • Develop and benchmark atomistic models for the formation of ultra-thin films.