A new technology has been developed by Draslovka Mining Process Solutions to extract metals from ores using glycine as the main lixiviant (i.e. extracting ligand). This technology is very innovative for a variety of reasons, including its ability to selectively leach precious- and base-metals within complex environments all while yielding substantive cost and sustainability benefits (through using non-toxic, fully recoverable/recyclable, and cheap lixiviants) when compared to industry-standard extraction processes.
The structure, stability and composition of the metal-organic complexes that form during glycine-leaching-technology based processes are mostly unexplored. Because it is new chemistry, and due to the complexity of the reaction environment, the atomic details underpinning the formation of these complexes is non-trivial to investigate with experimental techniques. Computational methods based on machine learning approaches, classical and quantum mechanical methods can support research in this field through providing such information. The challenge here is to develop a theoretical framework that is realistic and accurate, while being computationally affordable. Typically, methods that are accurate require substantial computing time. A balanced approach that will allow realistic predictions of large system-sizes (solvated metal-organic complexes) will be developed.
This research will contribute to understand and to optimise glycine leaching technologies so that the derived knowledge may be utilised to design similar processes to extract a variety of metals, and/or to provide a computational framework that can be used more broadly to address similar problems.
The student will have a unique opportunity to work closely with the multi-disciplinary and international team at Draslovka. They will gain transferable skill sets (including supercomputing, data science, molecular modelling), knowledge of hydrometallurgy/mining processes, experiences in applying modelling tools to address industrial problems, which will help building long-term career capability in chemical research. The collaboration across Curtin University and Draslovka will help the student to grow as an effective and independent researcher in this field.
Aim
Provide atomistic-level information on metal-lixiviant complexes to understand the chemistry underpinning the glycine leaching technologies so these processes can be further optimised.
Objectives
Develop a computational framework to model with high accuracy metal-lixiviant complexes in extractive fluids.
Identify the structure, stability, and formation mechanisms of metal-lixiviant complexes involved in existing glycine leaching technologies.
Significance
This project will look at the recently developed glycine leaching technologies from a new perspective and will make use of innovative methodological approaches with regards to what is traditionally used in this field: a combination of ab initio, semi-empirical and classical computational methods will be adopted to provide an atomistic-scale picture of these chemical processes, and a new computational framework will be developed to allow for a realistic description of these complex systems. This project will provide for a unique opportunity to show how very fundamental research can bring significant outputs to an end-user problem.
The project is closely aligned with Curtin’s strategic Planet and Partnership priorities, and with Draslovka’s priority of understanding and improving their glycine leaching technologies. This is extremely important as it relies on the development of more environmentally friendly and sustainable extraction processes of in-demand metals within the mining industry. The modelling results will be used to interpret experimental data and provide predictions that will be used to optimise the process and to eventually design new ones.
Ideal Candidate
We are looking for a motivated PhD candidate with a collaborative mindset and good communication skills. The project is suitable to students with a strong background in Chemistry and/or Physics. An aptitude for Mathematics and Computer Science is highly desirable, including knowledge of Unix and of programming/scripting languages, as well as previous experience with molecular modelling, though this is not essential provided there is a willingness to learn. Additionally, the applicants should meet the eligibility criteria for entry into a PhD program at Curtin University.
This project is open to International and Domestic applicants.
Scholarship
If you are identified as the preferred candidate for this project, you may be considered for an RTP scholarship. Additionally, support is available for eligible candidates through the Trailblazer program (Project PRO700725). The scholarship includes:
- Total scholarship value: AUD $35,000
- AUD $10,000 annual stipend
- AUD $5,000 travel allowance per year
Enquires and How to Apply
For enquires about this opportunity contact Associate Professor Raffaella Demichelis at Raffaella.Demichelis@curtin.edu.au
To formally apply submit an Expression of Interest to Associate Professor Raffaella Demichelis during the Central Scholarship round (July 1st – July 31st 2026)