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Details of Grant 

EPSRC Reference: EP/N025318/1
Title: Predictive formulation of high-solid-content complex dispersions
Principal Investigator: Sun, Dr J
Other Investigators:
Poon, Professor W
Researcher Co-Investigators:
Project Partners:
AKZO Nobel Centre for Process Innovation Limited DuPont (Global)
Johnson Matthey Schlumberger The Chemours Company
Department: Sch of Engineering
Organisation: University of Edinburgh
Scheme: Standard Research
Starts: 01 September 2016 Ends: 31 August 2019 Value (£): 989,150
EPSRC Research Topic Classifications:
EPSRC Industrial Sector Classifications:
Manufacturing Chemicals
Related Grants:
EP/N024982/1
Panel History:
Panel DatePanel NameOutcome
19 Feb 2016 Future Formulation FULL Announced
Summary on Grant Application Form
High-solid-content dispersions of solid particles of size about 1-50 microns in a liquid phase (HSCDs) occur ubiquitously in industrial applications, from cement and ceramic pastes to catalyst washcoats, paints, foods and drilling fluids. The reliable and efficient processing and manufacture of these diverse products presents 'grand challenges' to formulation technology because at high solids volume fraction process flow and product behaviour become increasingly unstable and unpredictable. But achieving high volume fraction is often desirable in many applications: in generic process flow, to maintain throughput and cut energy/materials costs; in ceramics manufacture, higher volume fraction green bodies sinter to mechanically stronger products; increasing volume fraction of a slurry for spray drying reduces drying time; higher volume fraction drilling fluids reduce problems of fluid and gas influx and collapse in bore holes. Conversely, unstable flow at large viscosity is sometimes actually desirable, as long as it is predictable, e.g., in breaking aggregates to disperse catalytic converter washcoats or pigments in a mixer.



In all these applications and many others the ability to control and predict rheology for a given formulation--to 'dial up' required behaviour--would transform formulation science and practice with HSCDs. However, experience repeatedly shows that as volume fraction increases, the flow and stress become increasingly unstable, and characterization, measurement, control and prediction increasingly challenging and unreliable. Conventional rheological characterization of HSCDs is often poorly reproducible and also fails to predict correct flow behaviour in the complex, non-rheometric geometries encountered in applications. Notoriously, small changes beyond the manufacturer's control, e.g. due to unforeseen variations in processing conditions or a change in supplier, can have catastrophic effects (e.g. a normally flowable formulation can suddenly fracture rather than flow). On top of this, industrial applications span many length scales, from < 100-particle-diameter extrusion mouldings and printed films to kilometre-deep bore holes so that predicting and characterizing HSCD flow faces the simultaneous requirements of scale up and scale down. Faced with these ubiquitous challenges, and because the basic science of flow at high volume fraction is not understood and predictive engineering tools are not established, formulators often resort to accumulated experience and informal procedures such as 'finger rheology' (rubbing samples between fingers!) to guide their work. Thus, existing formulations are often sub-optimal, and problems arising from these formulations are solved mostly by trial and error, while the risk associated with formulation innovation severely limits development of new products and processes.

Our vision, inspired by recent major scientific advances by members of the project team, is to transform practice in the formulation of HSCDs through a tight collaboration of researchers and major multi-sector industry partners. Our new scientific understanding will provide new methodology of characterization, measurement, prediction and control, leading to reliable process and manufacture of HSCD-based products. The project will enable manufacturers to formulate their products according to rational design principles, using parameters deduced from well-characterised reproducible flow measurements. This approach will yield step changes in control and predictability over multiple length scales and multiple application sectors.

Key Findings
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