Can big data, AI and chemical footprinting help the renewable energy sector avoid a toxic waste legacy? – GreenBiz

The launch of the digital economy has brought with it an expansion of disruptive technologies such as predictive analytics, artificial intelligence (AI) and robotics that are readily being used to transform the marketplace. But can we also use these breakthrough technologies to accelerate the development of safer, more sustainable materials for the renewable energy sector? 

Starting with one of the fastest-growing clean energy sectors, solar technology, this is the fundamental question that a unique collaboratory is asking itself.

Three years ago, the Department of Materials Design and Innovation at the University at Buffalo, Clean Production Action (CPA) and Niagara Share created the Collaboratory for a Regenerative Economy (CoRE). CoRE recognizes the critical societal importance of scaling clean energy technologies such as solar to address the climate crisis. But to do this sustainably, we need to collectively scale solutions to reduce the use of toxic chemicals and scarce, unrecyclable materials that impede circular economies. 

Issues such as toxicity and environmental impact are often an afterthought in the design phase, which is predominantly focused on improving the technical functions and efficiencies of materials. With more than 78 million tons of contaminated waste related to solar panels expected to hit landfills by 2050, this trend needs to be reversed.

To improve the life-cycle footprint of solar panels, big data tools can help manufacturers embed human health and environmental criteria into the front end of the design phase of materials and products.

We need to collectively scale solutions to reduce the use of toxic chemicals and scarce, unrecyclable materials that impede circular economies.

In a recently released report, “Elements of Change: Moving forward together towards a cleaner safer future,” CoRE outlines strategies for renewable energy companies to:

  • Reduce chemical footprints of products, supply chains and manufacturing;
  • Apply machine learning to design techniques for lead-free panels; and 
  • Use big data tools to rapidly characterize chemicals and identify safer solvents.

Safely meet demand for renewable energy technologies

Solar energy, along with other clean energy technologies, depends on hazardous chemicals and novel materials to reduce costs and optimize efficiencies. Some of these chemistries are unsafe for the environment and human health.

For example, solar energy technologies rely on toxic materials such as lead in solar cells and hydrofluoric acid used in manufacturing processes. This is especially harmful for workers exposed to hazardous chemicals throughout the life cycle of renewable energy technologies from production to disposal.

The solar energy sector is not alone with this major challenge. More than 2,780,000 workers die globally annually from unsafe and unhealthy work conditions, according to the International Labor Organization. The United Nations Human Rights Commission estimated that a worker dies at least every 30 seconds from exposure to toxic industrial chemicals, pesticides, dust, radiation and other hazardous substances. 

CPA’s work with the electronics sector to driver safer chemical is applicable to the solar sector and all clean energy technologies. For example, HP, Inc is a leader in its work to reduce its chemical footprint, documented by its participation in the annual Chemical Footprint Survey. This survey measures a company’s chemical footprint against best practices. It is modeled on the Carbon Disclosure Project, and is open and transparent, providing solar companies with a roadmap to safer chemical use.

Apple uses CPA’s GreenScreen to provide guidance to its suppliers on safer substitution of hazardous chemicals used as cleaners and degreasers in its supply chain. GreenScreen is a leading hazard assessment tool that benchmarks chemicals based on performance across 18 human health and environmental end points. Solar companies can use this tool to identify safer solutions to problematic materials such as hydrofluoric acid. 

These leading electronic companies even have teamed up with nonprofits such as CPA and academics to form the Clean Electronic Production Network (CEPN), which aims to eliminate exposure to toxic substances in the workplace.

This is a massive undertaking related to the manufacturing of computers, electronics and other information technologies. Solar manufacturers work off a similar manufacturing platform that stands to benefit from the tools and resources that CEPN is creating to do full chemical inventories and safer substitution with suppliers.

Solar companies today can adapt CEPN tools and strategies, proven effective by electronic companies, and make meaningful progress towards safer chemical use. But there remains a major challenge for all these companies, notably solar — the time it takes to discover new materials relative to their growth projections. This is where CoRE believes AI, machine learning and predictive analytics can play a role in accelerating the process of material discovery to the benefit of human health and the environment as well as optimized technical performance. 

Using big data and AI to accelerate material discovery 

The development of high-performance materials typically takes decades, sometimes up to 30 years to commercialize a new material. Big data tools can organize the large volumes of disaggregated information companies need to improve the technical, environmental and social performance of materials. Solar companies that participate annually in the CPA Chemical Footprint Survey to measure their chemical footprint and track their performance against best practices, can leverage these tools to map patterns and impacts necessary for decisionmaking and prioritization.

For example, the use of lead in solar panels is problematic in the production and disposal of these products. Electronics companies have shown it is possible to design lead-free electronic products, but solar companies are still very dependent on lead-based technologies. This is true even with the next generation of solar panels — for example, perovskite-based solar panels show the potential to increase the efficiency of panels, but their chemistry is dependent on lead.

Rational design is a process that bypasses trial-and-error approaches and creates new materials based on a predictive understanding of the fundamental science governing materials performance.

CoRE has demonstrated that “data fingerprints” can provide a powerful representation of the characteristics of perovskite crystal chemistry. This is key to overcoming the barriers to safer substitution for toxic elements such as lead. 

Data-driven screening tools and machine learning methods can help navigate the complexity of information associated with new and emerging chemicals used in the manufacture of solar devices. This includes harnessing advanced materials modeling and informatics techniques to identify pathways for the rational design of new materials chemistries for renewable technologies (solar energy) that minimize adverse environmental and human health impacts without compromising functionality.

Rational design is a process that bypasses trial-and-error approaches and creates new materials based on a predictive understanding of the fundamental science governing materials performance. Searching for the proper chemistry of materials that meet multiple functionality metrics of minimal hazard and enhanced engineering performance requires us to explore a chemical search space that is prohibitively too large to explore and make critical discoveries within a reasonable time frame using traditional methods.

CoRE seeks to address this challenge by applying materials informatics and physics-based modeling to fill the gaps in scientific knowledge, which then guides accelerated materials discovery and design for solar technologies. At CoRE, our goal is to gain a greater understanding of how atomic-scale changes in chemistry have a multiscale influence on materials manufacturing, performance and sustainability of solar cells. 

The European Commission recently announced a new chemical strategy for its Green New Deal that promises a non-toxic future for its citizens and a plan for zero pollution. The plan includes new investments for green and safer material innovation. This policy will stimulate demand for greener, safer products; putting pressure on renewable energy companies to think more holistically about their lifecycle impacts.

By building on best practices established widely in the electronics sector and leveraging the untapped benefits of AI and big data, solar companies can lead the way for the renewable energy sector in transforming their chemical footprints and accelerating the adoption of safer materials.  

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