Existing theories for particulate flow lack the robustness, predictability and flexibility required to handle the totality of phenomena that such flow may exhibit. Some unwanted industrial issues (such as particle agglomeration) and their management still remain an "art". Current practice is based mainly on ad-hoc models for each specific flow. I propose a novel approach, based on the combination of physical evidence and mathematical methods (statistical mechanics) that will lead to the formulation of a reliable theory applicable to industrial and natural phenomena. A successful theory will create a paradigm shift in the way particulate flow is modelled and will produce a tool that can be employed to substitute ad hoc models, hence avoiding a priori judgements of the flow conditions before selecting the appropriate model. The work proposed aims at bridging the gap between particle technology and rheology. It will result in devising a robust theory able to describe the meso-scale phenomena and link them to particle interactions. The theory will strongly rely on implementing accurate rheological measurement to validate the theory at the meso-scale and to assure a meaningful scale-up to the reactor scale. It will produce fundamental as well as user orientated research by developing a novel predictor which has the potential to significantly reduce production costs and improve the product quality in three areas important to the UK economy, namely pharmaceuticals, paints and detergents, valued at £200B per year