ProfessorDaniel Holland

Traditional process design has been limited by the fact that most instruments only measure what enters and exits a system. Very little information is available about what happens inside a chemical process. New imaging and analytical technologies now allow us to observe internal behaviour in real time. My research develops and applies these methods—particularly magnetic resonance imaging (MRI), X‑ray tomography, and nuclear magnetic resonance (NMR) spectroscopy—to gain new insight into chemical systems. I use these tools to study a range of problems, with a particular focus on granular and particulate flows, as well as the performance and optimisation of heat exchangers.

One area of particular interest at present is in the development of novel structures for heat transfer that exploit recent developments in additive manufacturing ("3D-printing").  These new manufacturing paradigms permit entirely new ways of constructing chemical engineering systems, and make the construction of almost any physical structure possible. The challenge now is to determine what those structures should be. 

I also work with emerging benchtop NMR systems and investigate how they can deliver rapid, robust analysis of complex chemical mixtures under industrially relevant conditions. One current project explores the potential of these systems to help reduce harm associated with the use of illicit drugs, by enabling fast and accurate chemical identification.

Key words:

magnetic resonance imaging, nuclear magnetic resonance spectroscopy, granular flow, heat exchangers, chemical analysis, machine learning, data science