HLD-NAC in RheoCube

During the development of new end-products in the chemical industry, many ingredients are currently screened and selected based on a trial-and-error approach. This is a process in which specialized laboratory personnel assemble new combinations and perform a series of physical experiments on various formulations. The goal is to find the formulation that best matches the desired properties and often includes preferred (renewable or better) ingredients. This formulation method is quite inefficient. It consumes a lot of cost and time, taking weeks, months, and often even years, for a new product development project. The chemical industry is desperately seeking digital equivalents to accelerate and modernize these processes. Electric Ant Lab (EAL) has developed RheoCube, a simulation tool that virtually reproduces micro-level ingredient interactions in simulation models. With RheoCube, validated simulation models of real physical systems are created. This allows R&D professionals to virtually simulate experiments to study, predict and optimize the behavioral phenomena of complex matter structures. The resulting benefits in terms of saving time and resources are substantial. Researchers can transfer up to 80% of their physical experiments to the virtual environment, resulting in a 60-90% cost reduction in terms of laboratory and human resources. In addition, researchers can gain new insights, which are not easily accessible through physical experimentation, leading to further long-term improvements to their R&D process. Van Loon Chemical Innovations (VLCI) is applying the predictive formulation science HLD-NAC for their R&D services, which is an effective method for selecting the right surfactant for a (micro-)emulsion. Surfactants are widely used in the formulation industry (e.g. personal care, coatings, food, oil recovery) as they help to create emulsions and foams and can stabilize suspensions. Selecting the right surfactant for a formulation is a constant challenge due to their complex behavior and an overwhelmingly long list of options. The efficient implementation of surfactants is a demanding area. This is especially so as more and more customers are requesting faster, cheaper methods of developing emulsions, which are not based on trial-and-error. The HLD-NAC approach gives a predictive and rational selection of surfactants to develop an emulsion, allowing to address this request. Innovative companies, EAL and VLCI will collaborate on this joint R&D project to co-develop RheoCube simulation models using the HLD-NAC methodology. Both parties see strong potential in creating a joint value chain where customers in the formulation industry can use this approach to benefit from a ‘one-stop-shop’ setup. This will enable them to create more reliable formulations, faster at a fraction of the current costs. When successful, the result is a fully automated workflow from sample to simulation model, which can provide valuable predictive information on the desired physical emulsion. By merging their unique knowledge and expertise, both companies are building a sustainable innovation with a strong competitive edge. This innovation has the capacity to eliminate costly trial-and-error experiments, which are rendered un-necessary for surfactant selection in the emulsion industry. The combination of HLD-NAC surfactant selection in RheoCube simulation models is highly applicable, resulting in substantial economic returns for both companies, the HTSM ICT sector, and the Dutch economy. To service existing clients and a growing number of requests, EAL and VLCI will first focus on the personal care and home care markets, which have estimated global values of US$ 175 billion (6.6% CAGR) and US$ 155 billion (2% CAGR), respectively. The size and positive trend of these markets ensure a very positive economic outlook for the HLD-NAC application in RheoCube. EAL and VLCI are both at a pivotal scale-up stage, where they are outgrowing their business. As part of becoming mature, established companies, they must keep innovating. This project is essential in that regard. While extremely promising from a commercial perspective, the project is still in an early, fundamental phase and there-fore entails multiple technical risks. It’s never possible to guarantee that a project will be able to pay for itself. The total financial risk of this project can be mitigated how-ever via co-financing of the project costs. This, alongside a subsidy will empower both parties to participate in the project and continue innovating.