- Arash is a PhD candidate in the Department of the Chemical Engineering at The University of Melbourne. His PhD project title is “Energy-Efficient Liquid Sorbent for Carbon Dioxide Separation” under the supervision of A/Prof. Kathryn Mumford. Negative emission technologies (NETs) play an increasingly essential role in the route to net zero emissions by 2050, and among them, direct air capture (DAC) is placed in a critical position, with considerable potential to influence climate change mitigation. However, due to the high costs associated with these systems, the widespread implementation is still lagging.
- One of the primary factors to this high cost is the heat/power requirement of the chemical solvent regeneration process, which is a critical for chemical absorption-desorption systems. Hence it is necessary to introduce new energy-efficient technologies. Catalytic solvent regeneration is a novel pathway for energy-efficient DAC. Engineered water-dispersible nanocatalysts exhibit high efficiency and activity to reduce the temperature required for the regeneration processes due to their unique physical and chemical properties. Since catalytic solvent regeneration is an emerging and growing technology, further studies are greatly needed in this area to enhance the performance, efficiency, and stability in an absorption-desorption system. This is particularly crucial in the new developing systems such as DAC to reduce the energy input, which this study aims to achieve. Reducing the energy input and cost is one of the key research challenges of DAC, which is aligned with the CarbonLock FSP goals.
Ibrahim Baris “Barry” Orhan
- Ibrahim Baris “Barry” Orhan is a candidate for a PhD in Applied Chemistry in RMIT University’s School of Science. He obtained his bachelor’s in mechanical engineering from Northeastern University (Boston, MA) in 2018, along with a minor in industrial engineering. He went on to complete his master’s degree in Sustainable Energy through RMIT University (Melbourne, VIC) in 2020. His undergraduate capstone project involved intensive computational modelling to build a material properties’ test device for synthetic cartilage material, and his master’s thesis utilised machine learning and heuristic optimisation methods to predict properties of organic solar cell materials.
- His current PhD project is titled “Accelerated Material Discovery Through Machine Learning for Gas Adsorption and Storage ” and is supervised by Dr Aaron Thornton (CSIRO), Dr Ravichandar Babarao (RMIT), Dr Tu Le (RMIT). The project involves the development of machine learning models and novel methods of numerically describing the candidate materials. Presently, the project is focused on the capture of CO2 through metal organic frameworks and significant work has been done to predict the capture of this gas at low partial pressures.
- The focus of my PhD project is to investigate the influence of ocean alkalinity enhancement (OAE) on phytoplankton species composition, and to determine the underlying mechanisms driving these changes. Specifically, my research question is “How will changes in the carbonate chemistry of seawater associated with OAE influence the composition of phytoplankton communities?”
- To answer this question, I will conduct a series of experiments, including 1) a microcosm study to monitor changes in a coastal phytoplankton community and associated biogeochemical parameters during a spring bloom, 2) a mesocosm study in Norway assessing the influence of simulated mineral-based OAE on diatom silicification, and 3) a laboratory-based experiment investigating the relationship between changes in carbonate chemistry and diatom growth, silicification, and photophysiology. The outcomes of this research will contribute to our understanding of how phytoplankton and the larger marine ecosystem may respond to changes in carbonate chemistry resulting from the implementation of OAE.
- Bojun Yin received his bachelor’s degree in exploration engineering of mineral resources from China University of Geosciences in 2020. He then carried out his master’s research in 2020-2023, focusing on the recognition and fusion of ore-forming information that include two aspects: anomaly detection of geochemical exploration data and mineral prospectivity mapping with the aid of geographic information system (GIS) and machine learning algorithms.
- The focus of his PhD project at Murdoch University is to investigate mineral carbonation processes under the supervision of A/Prof. Fang Xia, Dr. Hans Oskierski, and Dr. Yuan Mei (CSIRO). The rise of CO2 level in the atmosphere has resulted in global warming and an increase of extreme weather events, causing serious and persistent effect on human society. Mineral carbonation is one of the most promising next-generation carbon dioxide removal techniques that has the potential to lock enormous amounts of CO2 safely and permanently in minerals. However, this technology is still not economically feasible for industrial application due to challenges especially like slow reaction rates and high cost. This PhD project aims to study the mechanism and kinetics of mineral carbonation reactions to assist the development of cost-effective, fast, and scalable mineral carbonation technologies.