Computational Materials Design at The Dow Chemical Company

J. Moore
The Dow Chemical Company, US

Keywords: modeling, simulation, nanoscale

Summary:

Many of the most basic human welfare needs – needs like water purification, health and nutrition, personal care, packaging, architectural coatings, building materials and insulation, etc. - are commonly addressed by soft materials (polymer matrix composites from amorphous and semi-crystalline polymers, gels, foams, colloids, etc.) that have relatively ill-defined and complex structure (molecular weight distributions, distributions of chemical composition, particle size distributions, complex interactions between a myriad of chemical components in multiple phases). The need to simultaneously consider multiple components, phases, length and time scales, and/or properties makes the design and realization of such materials a highly complex and challenging endeavor. The problem is further exacerbated as pressures to reduce costs and development time become more and more intense. In response to these difficulties, leading chemicals and materials firms had been developing and exploiting capabilities in high throughput research (HTR) to accelerate R&D in a variety of application areas during that last one to two decades. Early on it was clear that “materials informatics” (i.e. “data handling, data mining, design-of-experiments and modeling”) must be an indispensable element of the HTR paradigm in order to maximize the benefit of materials HTR. As an integral component of the Materials Genome Initiative for Global Competitiveness (MGI), materials informatics has taken on an even higher profile as “the use of computational capabilities, data management, and an integrated approach to materials science and engineering” are seen as critical to accelerating the pace of discovery and deployment of the advanced materials necessary to address challenges in areas like clean energy, national security, and human welfare. This talk will highlight several examples of computational materials design for soft materials with applications in fields such as architectural coatings, building materials, food/pharma, and electronics. As such, they provide examples of the benefits of computational materials design in an industrial setting and the types of problems where the modeling of soft matter can speed the development of innovative materials solutions. They also strengthen the case for making the various modeling approaches more routine and high throughput and for integrating them with experiment in such a way that the impact is synergistic and revolutionary rather than disjointed and incremental as it often is today.