Computational Design of Electrocatalysts for Oxygen Evolution and Reduction Reactions

Xin Mao

PhD Student, Aijun Du Group, QUT

Abstract: Supported single-atom catalysts (SAC) have attracted enormous attention due to their high selectivity, activity and efficiency, compared to conventional nanoparticles and metal bulk catalysts. However, all of these unique merits rely on the stability of the SAC, as concerned by many investigators. To avoid aggregation of single metal atoms and maintain the high performance of SAC, various substrates have been attempted to support them, particularly on graphene nanosheets. A spontaneous interface phenomenon between graphene and Co (and Ni) substrate is discovered in this part is that the holes in graphene layer can stimulate metal atoms to pop up from a metal substrate and fill the double vacancy in graphene (DV-G) and stabilize on the graphene surface. The unique structure of the lifted metal atom is expected to be useful for bifunctional SAC for electrocatalytic OER and ORR. Our first-principle calculations indicate that the DV-G on Co (0001) surface can serve as an excellent bi-functional OER/ORR catalyst with extremely low overpotentials of 0.39 V for OER, and only 0.36 V for ORR processes, respectively, even lower than previously reported bi-functional catalysts. We believe the catalytic activity stems from the coupling effect between the graphene layer and metal substrate as well as the charge redistribution in the graphitic sheet.

Bio: Xin MAO received his Bachelor’s and Master's degree in Chemistry at Anhui Normal University (China). Then, he joined Prof. Aijun Du’s group at Queensland University of Technology as a PhD student from February 2018. His current research is mainly focused on the theoretical discovery of some novel materials for electrochemical processes, such as OER, ORR, CO2 reduction and N2 fixation.

Local Transport properties of Inhomogeneous Fluids

Mirella Simões Santos

Post-doc, Bernhardt Group, AIBN, UQ

Abstract: Inhomogeneous fluids, such as those confined in narrow pores, can be found in many different systems, e.g., living cells, clathrate hydrates, micelles, oil and gas reservoirs, and they are especially relevant in micro and nanofluidics. The properties of such fluids differ largely from those observed in bulk conditions. Furthermore, they are not a constant but rather a function of the distance to the walls of the system. Here, we explore different methodologies to calculate local transport properties of inhomogeneous fluids using molecular dynamics simulations. This is one important step towards the main goal of this project which is, through computational approaches, understand the mechanisms of charge and discharge of supercapacitors.  Such knowledge will allow us to contribute to the optimization of the performance of supercapacitors.

Bio: Dr. Santos has received her Doctor of Science degree in Chemical Engineering from the Federal University of Rio de Janeiro (UFRJ), Brazil, where in her thesis she modelled and simulated electrolyte systems. During her doctoral studies she also spent a year at the Massachusetts Institute of Technology (MIT) where she worked on the description of the behaviour of room temperature ionic liquids using mean field theory. Between 2017 and 2019, she was a postdoctoral researcher and visiting lecturer at Texas A&M University at Qatar where she focused on using molecular simulations to describe the behaviour of confined fluids. In June of this year she joined the Bernhardt group at AIBN, where she is working on molecular simulations of supercapacitors. 

Investigating the mechanism of Drug Resistance in Patients with Metastatic Breast Cancer Using Single-Cell RNA-seq Data

Huiwen Zheng

PhD Student, Mar Group, AIBN, UQ

Abstract: A major obstacle for efficient breast cancer treatments is the development of drug resistance. For example, Fulvestrant is one of the most widely used drugs for treating hormone receptor-positive metastatic breast cancer, as well as locally advanced unresectable disease in postmenopausal women. However, resistance to Fulvestrant is difficult to detect during the patient’s chemotherapy progression as the tumours are extremely heterogeneous. With the development of single-cell RNA-sequencing technology, we are now able to identify cancer cell heterogeneity under treatment at the single-cell level. This allows us to profile the cohort of individual cancer cell profiles in an effort to understand how drug-resistance mechanisms may be controlled.

My project aims to investigate the heterogeneity of these single cancer cells by quantifying the gene-expression variability between drug-responsive and -resistant cancer cells. This will be carried out in both homogenous cell line data and heterogeneous patients’ data. The model is constructed from the cell line data then applied to patients’ data, enabling us to trace and quantify the progression of drug resistance by identifying the molecular drivers of this process and evaluating the changing patterns of the dysregulated genes and pathways. Through this model, we can track and make predictions to decelerate patient’s levels of resistance during the chemotherapy progression, and reduce therapy failures in the future.

Bio: Huiwen Zheng received her bachelor’s degree in Marine Pharmacy at China Pharmaceutical University (China) and her Master of Bioinformatics degree from the University of Queensland. She is currently undertaking her PhD with Associate Professor Jessica Mar in Computational Biology and Biostatistics at the Australian Institute for Bioengineering and Nanotechnology (AIBN). Her research is mainly focused on analysing large-scale single-cell transcriptomic data to understand the gene-expression heterogeneity within cancer cell populations.

Thursday, 15 August 2019

9.30 – 10.30am

AIBN Seminar Room, Level 1 (Bldg 75, UQ)



Upcoming CTCMS seminars: 19 Sep, 17 Oct, 21 Nov



Level 1 (Bldg 75, UQ)
AIBN Seminar Room