Applying Artificial Intelligence to Advanced Sustainable Energy Technologies

CONTEXT

Challenge: Global energy demand is steadily rising, putting a strain on traditional energy sources. Fossil fuels, the dominant energy source today, contribute significantly to greenhouse gas emissions, accelerating climate change.
Urgency: There is an urgent need to transition towards cleaner, more sustainable energy solutions. Renewable energy sources like solar, wind, and hydropower offer a promising alternative, but require significant advancements in efficiency, storage, and grid management.
Opportunity: Artificial intelligence (AI) has emerged as a powerful tool with the potential to revolutionize the sustainable energy sector.

OBJECTIVES

Utilize AI to accelerate the discovery and development of next-generation sustainable energy technologies.

METHODOLOGY & APPLICATION

Scientific discovery through the scientific method requires more than just data-driven machine learning.
A combination of various AI techniques is essential: learning, reasoning, and planning.

The integration also involves human-computer interaction.
This collective approach allows for the incorporation of multiple knowledge sources.

DELIVERABLES

Development of AI-driven materials discovery pipelines: Automate the process of identifying, synthesizing, and characterizing promising inorganic materials for sustainable energy.
Discovery of novel high-performance materials: Accelerate the development of next-generation sustainable energy technologies with improved efficiency and functionality.
Publications and presentations: Disseminate research findings to the scientific community and industry stakeholders.
Collaboration: Foster partnerships with AI researchers and computational scientists to further advance the integration of AI in materials science.