Research

We, the MAVENs, are a computational physics group focused on exploring, understanding, and predicting the fundamental and utilitarian properties of diverse materials such as MXenes, Heusler alloys, and 2D materials. Utilising advanced techniques like Density Functional Theory (DFT), Monte Carlo methods, and machine learning (ML), we explore electronic structures and uncover the governing principles to engineer materials for various applications. Our integration of ML enhances material discovery, enabling us to optimise properties and accelerate innovation. Through this interdisciplinary approach, we contribute to the development of advanced materials with transformative potential for cutting-edge technologies, positioning our research at the forefront of computational materials science.

Discover more about the paths we take to achieve our goal below:

Disordered Materials

Disordered systems stand apart due to their lack of long-range atomic order, which often enhances their mechanical, magnetic, and electronic properties. In HEAs, a multi-component, near-equimolar composition creates high configurational entropy, resulting in properties like exceptional strength, corrosion resistance, and thermal stability.

Materials Informatics

The discovery of novel functional materials underpins the modern technological revolution, yet identifying materials with specific properties within an immense chemical composition space remains a formidable challenge. The complex structure-property relationships in materials make this search inherently difficult.

Single Magnetic Molecules

Single magnetic molecules, such as organometallic systems, and 2D materials offer immense potential as molecular magnets and qubits for quantum information processing and spintronic devices. Their tunable electronic states and intrinsic magnetic properties make them ideal candidates for such applications.