Tutorial ES13—Data-Driven Design of Sustainable Materials with Artificial Intelligence, Machine Learning and Assessment

Materials are critical enablers for reducing the resource intensity of society's industrial, commercial and energy systems. But materials themselves also require resources and can negatively impact humans and the environment, thereby compromising the sustainability of our world. To promote materials development for a more sustainable world, it is essential that the material footprint be better understood and improved for all products and processes. Fundamental research is required that addresses the creation and sharing of sustainability-related data, metrics and assessments of materials, processes and performance; use of this knowledge to inform sustainability-focused decision making; improved decision-making tools to enable product and process designers and engineers to incorporate sustainability metrics at the earliest stages of the design phase; and establish better defined sustainability metrics for policymakers. This tutorial brings together leading experts in sustainability who are using machine learning and data-driven design of materials and processes to focus equally on the economic, performance and societal dimensions of sustainability.

This tutorial will introduce approaches and tools for quantifying not only the technological performance impacts of selecting specific materials and processes, but also their economic, environmental, societal and human health impacts.  This approach puts design tools in the hands of materials researchers for creating materials and processes that meet the needs of humanity, not just for today but for future generations.

1:30 pm—Using AI for Sustainable Materials: New Approaches, New Challenges
Elsa Olivetti, Massachusetts Institute of Technology

This tutorial will present case examples of the role that AI might play in materials development with an eye toward improving environmental and economic sustainability. These examples will be drawn from academic research as well as industrial cases. Particular focus will be on accounting for the context in which a material operates to understand the appropriateness of particular mitigation strategies. Participants should gain insight into methods to quantify environmental impacts of materials choice on all aspects of the life cycle considering the context in which the material operates and the role that data analytics might play.

2:30 pm—BREAK

3:00 pm—Tools for Techno-Economic, Life-Cycle and Logistics Analyses for Creating Sustainable Materials, Processes and Circular Economies
Hongyue Jin, The University of Arizona

This tutorial will show the power of using techno-economic, life-cycle and logistics analysis in assessing the opportunity for early-stage technologies to provide sustainable solutions.  Techno-economic analysis (TEA) aims to identify, quantify and ultimately surmount the technical and financial barriers that hinder the commercialization of new technologies, products and processes. Life-cycle analysis (LCA) identifies the environmental hotspots and pinpoints improvement opportunities that influence consumers, companies and policymakers in their purchasing behaviors, product design and policy development decisions. Since the data required for LCA are often a subset of the data required for TEA (or vice versa), an integrated study of TEA and LCA is beneficial as it maximizes the knowledge gained from a given set of information. With TEA and LCA, a better knowledge may be obtained from multiple perspectives. For example, TEA informs us of the potential profit structure of a business, which helps formulate a strategy to maximize the financial gain. By combining the knowledge from TEA and LCA, a problem may be formulated for maximizing the overall economic and environmental benefits. One example of such an integrated approach is demonstrated by the optimization of reverse logistics. Operations research techniques are applied to develop mathematical models and derive practical solutions. In the tutorial, several examples will be demonstrated for value recovery of rare-earth-containing products, using TEA, LCA and optimization techniques described above.

4:00 pm—Quantitative Tools to Advance the Use of Safer Chemicals and Sustainable Materials
Mark S. Rossi, Clean Production Action

This tutorial will present two tools–GreenScreen for Safer Chemicals and the Chemical Footprint Project–and examples of their application for measuring the chemical footprint of products and organizations. Chemical footprinting is the process of measuring chemicals of high concern in products and supply chains. GreenScreen provides a framework for both identifying chemicals of high concern and safer chemicals. The Chemical Footprint Project specifies how to aggregate chemicals of high concern data from products to the organizational level. The tutorial will detail examples of how companies and standards use GreenScreen to identify chemicals of high concern and safer chemicals, and how companies use the Chemical Footprint Project to calculate their chemical footprint, quantify their baseline use of chemicals and report reductions in their chemical footprint.