78740Rheality - COVID-19 ChallengeClosedCollaborative R&DInnovate UKRheality Ltd was incorporated on 14th January 2020 and is a spin-out from the University of Birmingham. The company's innovation is based on the technology arising from the work of Dr Federico Alberini, in the School of Chemical Engineering at the University of Birmingham. Rheality aims to demonstrate, in a relevant environment, a cost-effective, real-time, in-line rheology/liquid fingerprint measurement device to monitor state of materials flowing through pipelines at large volumes even at high speeds improving quality & process control. The technology and its process has been patented. Rheality has secured an exclusive option from the University of Birmingham to exclusive licence of the Intellectual Property, upon receiving IUK funds. Last March the company was awarded £300,000 by IUK as part of the ICURe programme. We are confident that Rheality's technology meets an urgent market need. Fluid state knowledge represents a major challenge and significant cost to a variety of industries, including but not limited to FMCG, Chemicals, Oil&Gas and Pharmaceutical. The measurement of intermediate and/or final product state is fundamental to process & quality control as the performance of a finished product is directly linked to its product state during processing. Moreover a tight control of the process will enable a drastic reduction in waste and a fast integration, in existing plants, of new formulations. This is, currently, a key challenge for industry which needs to control the consistency of their product in-line after the introduction of greener chemicals in the existing formulations. This is not possible without a technology that enables the direct monitoring of the process like Rheality does. Rheology provides direct measurements of product state and it's the ideal gold standard to ensure the desired product performance/quality. The technology is enabled through a novel passive acoustic approach which reliably and robustly predicts rheological properties of fluids. Our novel approach utilises an external piezo-sensor to measure passive signals within the fluid to create an acoustic fingerprint. Machine-learning algorithms then extrapolate the rheology based on a correlation between the observed frequency spectra and those stored in a database for fluids of known rheology. The key innovation of this technology is through the provision of a minimally invasive sensor system on a proprietary pipe segment to measure the real-time rheological properties of all types of fluids in a format compatible with large-scale manufacturing. We use passive acoustic emission sensors that until now have only been used for structural surveillance, but not to monitor fluid flows. We have developed unique software to interpret acoustic spectra with rapid de-noising and feature selection elements using machine learning algorithms that can be programmed into a basic data processing unit. To our knowledge there is nothing similar to our technology in development and we are driving innovation in this area. The initial target customers are FMCG manufacturers (batch/continuous processing), however with this specific project we want to expand into the Petrochemical sector, in particular in paints and catalyst slurry manufacture.