Summer and Winter Research Programs for Undergraduates

Metals for the global energy transition – an analysis of site-level ESG disclosures

7 weeks duration, 35 hours per week. The applicant will need to be on-site at St Lucia Campus for the project, although work from home may be possible one day per week.

Low-carbon energy technologies and infrastructure require an enormous quantity and diversity of metals, which cannot be sourced from recycling only. We therefore need mining to mitigate climate change, which is problematic since mining activities have historically caused adverse impacts including environmental degradation, population displacement, violent conflicts, and human rights violations.
 
This research project undertakes a qualitative analysis of global mining data to identify mining locations where significant pressures on mining communities and environments are emerging. It involves sorting and categorising corporate disclosures and news articles, particularly targeting mine site level information. This project will contribute to building an atlas of geolocated ESG (environmental, social, governance) events across the global mining sector.

The effect of fire on soil physio-chemical properties of Temperate Highland Peat Swamps on Sandstone

This project will contribute to a large SMI research project called “Fire resilience of Temperate Highland Peat Swamps on Sandstone (THPSS)”. One of the objectives of that project is to develop understanding of the effect of fire and its severity on THPSS soil, hydrology and the post fire recovery process of these swamps.

THPSS typically have a high resilience to fire at wet conditions, due to their usually high soil moisture, and ability to support rapid vegetation re-growth. However, THPSS of Sydney Basin overlie underground coal mining area that may affect hydrology of swamps due to an increase in swamp drainage. THPSS of Sydney Basin was severely affected by wildfires during the fire season 2019-2020. Most burnt swamps lost their surface organic matter layers (fibrous or spongy organic-rich detritus). In the most severely burnt swamps (very high or high burn severity burn class), the upper portion of the peat layers (called the alternating organic sands layer) also incinerated. Fires can alter soil physio-chemical properties. However, the effect of bushfires on THPSS that have been undermined is not understood. 

The successful applicant will work on the physical, chemical and hydrological analysis of pre- and post-fire soil samples collected from these swamps and develop an understanding of the effect of fire and its severity on THPSS soil and hydrology. 

The candidate will benefit from this project by being exposed to high-quality applied research in the mining context, and by potentially becoming a co-author in a manuscript to be published in an international journal.

This project can be the start of a larger research project, such as Honours or PhD.

This project is open to students with an interest in soil physics, with strong laboratory skills and the ability and enthusiasm to learn and apply new equipment and tools. Ideal candidates would be Masters, 3rd or 4th year students of Soil, Environmental, Earth or Agricultural Sciences, or Civil/Environmental Engineering.

Unpicking Juukan Gorge: Applying the Linear-Landscape-Layered modelling framework for identifying new questions for cultural disaster prevention

10 weeks duration, between 30-36 hours per week.

COVID-19 considerations: This project can be completed remotely. Presence on site at the Sustainable Minerals Institute (either St Lucia or Indooroopilly Mine Site) is encouraged, however other plans can be made via negotiation with the supervisory team.

In 2020, the mining company Rio Tinto blew up a 46,000 year old cave of significant indigenous cultural heritage in Juukan Gorge, WA. Previous to the disaster, the state government had given approval to Rio Tinto to progress with the expansion of their mining activities under WA legislation. This expansion led to the destruction of the cave, a sacred site for the traditional owners, Puutu Kunti Kurrama and Pinikura (Binigura) peoples. A quote from Rio Tinto's website about the event:

"In allowing the destruction of the Juuka Gorge rock shelters to occur, we fell far short of our values as a company and breached the trust placed in us by the Traditional Owners of the lands on which we operate. It is our collective responsibility to ensure that the destruction of a site of such exceptional cultural significance never happens again, to earn back the trust that has been lost, and to re-establish our leadership in communities and social performance."

Much analysis has already been performed on this terrible and complex scenario, examining how this could come to pass. In such cases as these, though, it is common to return to the data gathered about what happened, for a deeper investigation through various analytical lenses, perspectives and methods. This is so that as much as possible can be learnt about the situation so that similar disasters can be prevented from happening elsewhere. This project seeks to do that that: to look again at what happened in Juukan Gorge through the lense of a recently develped modelling framework with the intention of expanding the range and type of questions that could, or should, be asked to maximise what we as a society can learn about preventing such cultural disasters.

This modelling framework is called the Linear-Landscape-Layered approach intended to be used to help observers decide how to interact with a 'system of interest' in order to drive that system towards a desirable end-state. e.g. if the system of interest were the socio-technical system of a mining company relating to a local indigenous community and a state government with reference to a piece of land and the end-state were sacred sites left intact, all desired ore extracted from the area, all laws complied with then the question becomes how best should each of those stakeholders interact with each other and the landform to achieve the desired end-state? The Linear-Landscape-Layered approach supports decision-making for this type of problem by uniting the following concepts:

• Nature of an 'event' in a causal scenario, such as what played out in the Juukan Gorge crisis.
• Causal relationships between evens in describing a causal network of events, typically a description of linear causality.
• Seeing this causal network as a coarse-grained description of a more fundamental continuous causal landscape.
• Relating the linear and landscape descriptions of event causation to a layered systems model.
• The hierarchical systems model describes how parts of a system are connected, how function arises from interactions of parts across layers of the system to drive the system state. This also incorporates concepts such as emergence and downwards causation.

The activities of this project include:

1. Selecting a defined set of sources that describe what happened in the Juukan Gorge scenario. This can be, e.g. official reports, journal articles, relevant media articles and testimonials from local communities. The literature should include previous analyses of the scenario.
2. Fitting the data about what events occurred in the juukan Gorge scenario into the Linear-Landscape-Layered framework, and linking them to the parts of the layered systems model. This is to investigate what functions of the system of interest were activated to drive the outcome where the cave was destroyed.
3. Using the formal structure of the Linear-Landscape-Layered framework, explore what other reasonable events, system parts of functions could have been relevant for progressing the scenario, that may not have been identified by previous analyses.
4. From the results of step 3, generate a set of questions tht could be asked of the situation to understand it more deeply. Compare this list with recommendations from previous analyses and discuss the similarities and differences.

The goal of the project is to explore whether the Linear-Landscape-Layered modelling framework, applied in this way, can help generate new insights about the Juukan Gorge scenario.

Students can expect to learn about:

• Collecting diverse data froma variety of sources about the Juukan Gorge scenario
• The details of the Linear-Landscape-Layered (L³) modelling approach, and how to integrate and fit data into it to make inferences
• Causal network analysis (basis in graph theory)
• Systems theory and emergence of function for understanding state changes.

This project would be suited to 3^rd or 4^th year students, however an excellent 2nd year will be considered.

The student can be from any of the following disciplines (non-exhaustive):

• Social Science and related fields
• Business Management / Organisational dynamics and related fields
• Project Management
• Economics
• Engineering - e.g. mining, chemical
• Science - especially mathematics or physics
• Environmental Science

Other disciplines will be considered.

Enhancing mine site rehabilitation risk analysis through model combination: integrating Bayesian Networks, Causal Networks and Ecosystem Trajectory Models

10 weeks duration, between 30-36 hours per week.

COVID-19 considerations: This project can be completed remotely. Presence on site at the Sustainable Minerals Institute (either St Lucia or Indooroopilly Mine Site) is encouraged, however other plans can be made via negotiation with the supervisory team.

Mine closure and rehabilitation is a complex process. There are many technical, environmental, social and economic considerations that must be made and managed together in order to successfully rehabilitate the mine site.

Being a multi-faceted problem, this means that rehabilitation has many different but interconnected risks - i.e. the uncertainties associated with the process of rehabilitation which can threaten its success. Exploring the depth to which these diverse risks are causally interconnected is an open area of research, but critically imortant for the environment and society in the vicinity of a closed mine to thrive.

Ranger is a uranium mine in the Northern Territory that is a few years away from the end of its mine-life. there is ongoing collaboration between the Supervising Scientist of the Northern Territory (NT government department) in conjunction with the Sustainable Minerals Institute at UQ to help support and enable the rehabilitation journey for Ranger post-closure. Previous work performed to undertand the risks to rehabilitation for Ranger has been two-fold:

1. The development of a Bayesian Network-based model of the rehabilitation outcomes across a diverse set of possible environmental conditions. This was done by the Supervising Scientist of NT aid post-closure decision making in terms of knowing what risks contribute to successful rehabilitation, and what risks undermine this.
2. Ongoing research into a framework for ecosystem trajectory model development, tailored to Ranger. Ecosystem trajectory models describe the states an ecosystem traverses on its journey from immediately after the mine is closed to the final rehabilitated state. These models help in the identification of risks to rehabilitation success across time, highlighting when these risks drive the state of the ecosystem away from the desired path.

This project explores enhancements that could be gained in mine rehabilitation risk management by combining both of the above modelling approaches, Bayesian Networks (BNs) and ecosystem trajectory models (ETM), together by means of a third kind of causal model: Causal Network Topology Analysis (CaNeTA). CaNeTA is a very flexible approach that can be used to convert data about risk events from a wide variety of sources, and embed causally connected risk events in space-time.

All of these types are useful models in their own domain, and are (can be) all used to study a closure process. The hypothesis is that being able to switch between or use each of these models in an integrated way for a specific closure scenario will help improve the overall certainty in the actions to take to drive the ecosystem to where you want it to be, compared to only using them separately. This is because it is thought that combining all three approaches would yield a method that helps identify:

• what the risks are, their causes and consequences
• when the risks impact on the ecosystem trajectory across time, and;
• where interventions could optimally be made to ensure rehabilitation success.

The key activities of this project will be:

1. Literature review: understand how the BN, ETM and CaNeTA methods operate; understand the key steps in mine site rehabilitation.
2. Develop a method of switching between BN models, ETMs and CaNeTA models of mine rehabilitation risks.
3. Apply the approach developed in step 2 to compare effectiveness of risk management decision making with the models combined and separately in a case study related to the closure of Ranger.

The student will gain skills in:

• Understanding the process of mine site rehabilitation.
• Developing and using Bayesian Networks, Ecosystem Trajectory Models and Causal Networks. These represent three different but complementary modelling approaches that can be applied in many settings outside of the mine closure scenarios.
• Performing and evaluating risk management decision making.
• The outputs of this project will be collated into a final report, which could be further converted into a journal or conference paper, depending on the final quality and quantity of work delivered.
• Throughout the project, the student will be asked to present their interim findings in both informal and formal settings, for developing presentation skills.

This project would be suited to 3^rd or 4^th year students, however an excellent 2nd year will be considered.

The student can be from any of the following disciplines (non-exhaustive):

• Engineering
• Environmental Science (or equivalent)
• Science
• Mathematics

Students from any degree are welcome to apply, but they are required to be comfortable with the following content in the project:

• Probability theory, graph theory, state space representations and ecosystem models
• Mine site rehabilitation processes
• Risk management processes
• Learning how to use previously unfamiliar (but simple) software to perform the required analyses.

IMPORTANT:  You do NOT have to know the above content to be considered. We will teach you what you need to know, but we are looking for someone willing to learn.

Dr Ben Seligmann (Sustainable Minerals Institute)

Co-supervision will be delivered by Professor Peter Erskine (Sustainable Minerals Institute), in association with Katherine Harries (PhD student, Sustainable Minerals Institute)

Mineralogical and geochemical characterisation of Rare Earth Element (REE) deportment

This project forms part of the Rare Earth Element (REE) Processing Project which is a collaboration between the Sustainable Minerals Institute and the Queensland Government Department of Resources. The project aims to identify new resources of REE across Queensland and develop new and novel methods for extraction and processing of these critical elements. REEs include Ce and Nd used extensively in the high-technology/manufacturing sectors for specialised magnets, electronics and advanced engineering applications. Whilst the main REE bearing minerals include allanite and apatite, REEs may also occur in a range of trace minerals including monazite and titanite. The broader project focusses on developing novel methods to extract REEs from a range of samples using novel extraction methods.

The specific aim of this project is to characterise the geological occurrence of REE-bearing phases in a range of samples from sites across Queensland to develop a detailed mineralogical and geochemical understanding of REE deportment. This work has significant implications developing new REE extraction and beneficiation processes.

The work program will involve:

• Systematic sample preparation at the JKMRC Pilot Plant
• Detailed mineralogical and geochemical analysis including X-ray diffraction and automated mineralogy (e.g., SEM)
• Data compilation and analysis

The student will have the opportunity to be exposed to a range of research groups involved in the broader collaborative project including UQ’s hydrometallurgy group and the geomicrobiology group at SEES.

This project presents the opportunity to develop insights into the growing field of critical metals in Australia, focussing on rare earth elements (REEs). Through this project, the candidate will develop skills in systematic sampling and sample preparation methods, mineralogical analysis tools and to gain insights into the significance of mineralogy on beneficiation and extraction processes.

The research outcomes will be included in quarterly reports to the Queensland Department of Resources with opportunities to contribute to publications based on the results.

The candidate will contribute to written reports and may provide a short oral presentation of results at regular meetings of the REE Processing Project working group .  

This project would be suited to 3^rd or 4^th year students with a background in mineralogy, geochemistry or science, looking to gain applied experience in characterisation for mineral processing applications.

Exploring for new economy metals: circular economy of mine waste

Background: In Australia, much like the rest of the world, the circular economy is growing with a target set by the Australian Government for it to generate at least AUD $26 billion by 2025. Whilst industries like plastics, food and fashion are making significant changes to meet this target, the mining industry has been considerably slower to adapt. Further, there is an international drive for countries to transition to low-carbon economies. New technologies are required to support this including electric vehicles and products for the medical and defence sectors. To manufacture these products new resources, here termed ‘new economy metals’ which include cobalt, tungsten, rare earth elements, indium, gallium and germanium, are required. In many downstream markets globally, these metals are increasingly required to have green credentials (e.g., Rio Tinto’s green aluminium; the EU’s battery passport). Traditionally, these metals are by-products of base metal and precious metal mining operations, and therefore have been disposed of in waste dumps and tailings storage facilities. These sites can contain reactive wastes (e.g. causing the generation of acid and metalliferous drainage or AMD), and therefore require effective rehabilitation.

This project will focus on secondary prospectivity. This is defined as the examination of previously unconsidered mining opportunities in existing and abandoned mines, with this pursuit in keeping with circular economy principles. This collaborative project between the Geological Survey of Queensland (GSQ), within the Department of Resources, and the Sustainable Minerals Institute (SMI), within The University of Queensland ,will examine mine waste at several sites across the state (operational and abandoned) to determine their new economy mineral endowment and will also investigate the mining technologies and techniques required to recover these metals as part of an economic rehabilitation approach.

Project Aim/Objectives: This program focusses on performing routine mineralogical and chemical investigations at operational and abandoned mine sites across the state to quickly assess the new economy metal fertility and reprocessing potential of mine waste. This will be achieved through robust sampling (in the upper 5m of the sediment package in the case of tailings or spent heap leach materials, otherwise with representative samples of the major mine waste types selected).

Approach: In this project, mine waste samples from select mine sites across Queensland are to be sampled and subjected to chemical assay, mineralogical analysis and mineral chemistry analysis using a range of techniques including bulk XRD, MLA, pXRF, LA-ICPMS and micro-XRF to quantify the critical metal content and identify their host minerals. The student working in this project will have the opportunity to get involved in one or more of the following project tasks (for a select site):

1. Mine waste sampling
2. Mine waste characterisation through microanalytical techniques
3. Geochemical and mineralogical data processing and visualisation
4. Performing a secondary prospectivity assessment on a site

A key outcome of this research will be the provision of data to build a secondary prospectivity map of Queensland informing future brownfields exploration in the state.

Students may gain skills in geochemical and mineralogical data collection, and be involved in data handling and visualisation softwares (e.g. IOGas, Leapfrog, Geoscience Analyst).

The outcomes of this project will feed into the Queensland Government’s New Economy Metals Initiative (https://www.resources.qld.gov.au/mining-resources/initiatives/new-economy-minerals). From this, the student will have an opportunity to contribute towards publications. 

Students may also be asked to produce a report or oral presentation at the end of their project, to both the SMI and the Geological Survey of Queensland.  

This project would be suited to 3^rd or 4^th year geology or environmental science students with a background in mineralogy or exploration geochemistry.

Using machine learning to assess acid mine drainage potential

Background: Sulphide minerals contained in mine waste (e.g. tailings, waste rock) can undergo oxidation and produce acid mine drainage (AMD). However, by understanding the degree of oxidation of the sulphide minerals responsible for generating AMD, predictions can be made regarding likelihood of formation and indeed, longevity. This project is focused on developing a computer algorithm for rapid assessment of sulphide minerals using the sulphide alteration index or SAI (Blowes and Jambor, 1990). The SAI is a ranking scheme to assess the degree of sulphide oxidation and focusses on examining the formation of secondary oxidation products as rims, and the relationship between different sulphide minerals, as these will govern the rate of AMD formation.   

Aim: Collected automated mineralogy data to feed into the development of an algorithm to rapidly perform the sulphide alteration index.   

Approach: 1) Selection of a range of mounted mine waste materials (tailings, waste rock) containing sulphide minerals (from existed data); 2) Collection of reflected light images from these grain mounts on an automated microscope; 3) Manual SAI assessment of the sulphide grains; 4) Using machine learning platforms, development of a code for computer-based performance of the SAI.

Students will gain skills in reflected light microscopy, and an understanding of mine waste mineralogy and coding.

The student will have an opportunity to contribute this data to publications arising from this research project.  Students may also be asked to produce a report or oral presentation at the SMI Researchers Forum, at the end of their project.

This project is open to applications from students with a background in geology (skills in reflected-light microscopy are advantageous) with computation science skills beneficial and would suit those with an interest in mining and environmental geosciences.