Developing new products in the personal care, pharmaceutical, and chemical process industries involves a linked set of processes (the so-called “value chain”), beginning with early-stage discovery of new chemistries and materials, to engineering and eventually to manufacturing. A key challenge in commercializing new materials is the transition from early-stage laboratory discovery to scaling up in engineering and production. Computational methods can help develop and screen thousands of new chemical formulations for new materials, but the scale-up experiments on the most promising handful of formulations is much slower, leading to bottlenecks. In addition, developing new chemistries means that companies may not have data from the past to calibrate artificial intelligence-based development and screening methods.
Register to watch this on-demand webinar where featured speaker Professor Dr. ir. Johannes (Hans) Fraaije presents computational solutions to these problems, including several new algorithms:
Get an in-depth overview of methods and capabilities of the Simcenter CULGI suite of solutions and the importance of increasing the speed of value chains.
Are you faced with the challenge of determining the thermodynamic properties of new materials? With changing requirements for new formulations (e.g., moving away from petrochemical-based materials), this webinar presents novel algorithms, such as coarse-graining, for predicting the thermodynamic characteristics of soft materials. This allows you to gain insight into the material’s behavior and whether your product or process is stable enough to survive the manufacturing process.
Does phase behavior of mixtures or the rheological properties of a complex formulation puzzle you? Computational materials discovery should also include rheology when screening materials. One of the most important aspects in scaling up these formulations is understanding this type of behavior, as the more insight obtained in the early stages will help to increase the speed at which you move along the value chain. Learn about a new method for microrheology--Stokesian Particle Dynamics--and how it can reduce trial and error and create higher confidence during the scale-up stage.
Modeling with multiscale computational chemistry allows for the design and screening of novel materials early in development. Learn how these methods and tools can ease the pain of transitioning from early-stage discovery to the scale-up stage and hear about cases where significant time & cost savings have been realized through reduced trial and error and higher confidence during the scale-up stage.
The following use cases are discussed in more detail:
Register now to learn why materials discovery is critical in the 21st century and how manufacturers can speed up the value chain with integration and digitalization.