Magnetic Resonance Imaging (MRI) found its first applications in medical physics and is now routinely used in hospitals to image the internal structure of the human body and the blood flow within it. The real power of MRI is that it provides images of processes occurring within optically opaque objects – the human body being the obvious example. Over the past 20-30 years, there has been increasing effort in translating this imaging technology across to the non-medical sector and, in particular, to research challenges in physical sciences and engineering. Our particular interest has been in applying MRI to reaction engineering, hydrocarbon recovery and controlled pharmaceutical release. It is the first of these and, in particular, how MRI methods can be used in GLS reaction engineering research that is the topic of this lecture.

This lecture does not assume any prior knowledge of magnetic resonance methods; neither will it be a lecture on the physics underlying these measurements! Further, whilst examples will be taken from MRI, discussion of the new data acquisition methods and consideration of how we use imaging (or tomographic) data are generic to many fields of metrology in reaction engineering.

Three themes will be addressed:

What information can MRI provide? Capabilities of any measurement method are best understood through examples – these will include:

1. direct measurement of catalyst wetting
2. hydrodynamic transitions and bubble formation during two-phase flow in a fixed bed
3. characterization of bubble-size distributions in two-phase gas-liquid bubbly flows
4. mapping of the formation of gas and liquid species, and their mobility, within a fixed bed during an heterogeneous catalytic conversion – the case study taken with be ethene oligomerization occurring at 29 bar and 100 °C.

New frontiers in dynamic magnetic resonance measurements. The advent of under-sampling techniques, such as compressed sensing, in data acquisition and signal processing are making a significant impact in many areas of physical sciences and engineering. Alongside these methods, Bayesian methods are also of increasing interest. The examples presented will include studies of gas-liquid dynamics, and the imaging of gas and liquid flow fields in fixed beds.

How do we use imaging data in numerical simulation? Imaging/tomographic data are used in a number of ways. The most commonly used approach is to compare directly the output of a numerical simulation with two- or three-dimensional imaging data. However, many of these measurements also offer the opportunity to improve the predictive ability of our numerical simulation tools either by, for example, critically evaluating the assumptions embedded within the code, providing more accurate input data to the simulation or giving insights to improved implementations of the simulation. Examples from our MRI work include single- and two-phase flow in fixed beds, period operation of fixed beds, and granular dynamics in gas-solid fluidized beds.