(268b) How Molecular Modeling, AI, and a Better Assessment Process can Speed the Energy Transition

In 2015 essentially all the nations of the world decided to stabilize the climate within the next few decades. To accomplish this important societal goal, low-greenhouse alternatives will need to be developed to replace most of today’s energy and fuel system, and also many chemicals/materials manufacturing processes. In some cases completely new products should be developed to replace products with large environmental impacts. Society is counting on the chemical engineering community to develop most of these new processes and products, and to provide accurate information on which proposed new processes and products merit societal investment or policy support. Because of the number and scale of the products and processes that will need to be replaced, and the relatively short timeline, this is a huge challenge.

Fortunately, computer modeling methods have been developed that can significantly speed the development of new processes and products by reducing the number of experiments required. In some cases high-throughput experiments can further reduce the time required. In this talk I will discuss some of the computer modeling methods, and highlight cases where various combinations of computational chemistry, machine learning, high-throughput experiments, and process models have drastically reduced the time required to identify a promising new product or process.

However, there are many steps between identification of a promising green product or process, and its real-world deployment at a scale which would materially affect the global climate. First, investors need to be confident the new product/process will be successful before they risk the billions of dollars needed for large scale deployment. Often there is not a compelling economic case for rapidly deploying a new product or process to replace an established technology, and sometimes existing regulations make deployment impossible. So usually some policy changes are needed to allow and support the deployment of the new technology. Policy changes can reduce the investment risk, making it much more likely that investors will provide the funds needed. Both the government and the investors look to the engineering community to provide clear assessments of the climate impact and economics of each proposed process or product, to inform their policy and investment decisions. Some ideas for how the chemical engineering community could cooperate to provide the needed reliable clear assessments will be discussed.