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Epsilon to Omega. The Frontiers of Clean Energy

  • Book

  • August 2026
  • Elsevier Science and Technology
  • ID: 6250455
Epsilon to Omega: The Frontiers of Clean Energy illuminates the transformative impact of artificial intelligence (AI) on the journey toward sustainable energy. In a world facing urgent environmental challenges, this book explores how AI, energy innovation, and decarbonization are converging to redefine the future of power generation and consumption. Through detailed case studies, the text provides technical insights and forward-looking perspectives, empowering engineers, entrepreneurs, policymakers, and researchers to drive meaningful change. Each of the seven chapters unveils a unique domain within the AI-driven energy revolution, guiding readers through a landscape of pioneering technologies and real-world applications.

In addition, the book investigates the rise of smart machines, the next generation of AI engineers, and the latest advancements in AI-powered scientific discovery. Readers encounter visionary concepts, such as intelligent agents for zero-carbon strategies and breakthroughs in achieving carbon negativity, as well as practical guidance for leveraging AI in energy solutions. The work stands out for its wealth of actionable insights, making it an indispensable resource for those seeking to turn innovative ideas into impactful, sustainable energy initiatives. Ultimately, it inspires stakeholders to shape a cleaner, more resilient future.

Table of Contents

1. The Swarm of Smart Machines
2. AI Engineers of Tomorrow
3. AI Trailblazers: Shaping the Future of Science
4. Machine Intelligence Fueling the Infinite-Energy Future
5. Intelligent Agents Paving the way to a Zero-Carbon Planet
6. Going Beyond Zero to the Frontiers of Carbon Negativity
7. Energy Unleashed: A Sustainable Future

Authors

Siddharth Misra Associate Professor, Harold Vance Department of Petroleum Engineering and the Department of Geology and Geophysics, Texas A&M University, USA. Siddharth Misra is currently associate professor at the Harold Vance Department of Petroleum Engineering, Texas A&M University, College Station, Texas. His research work is in the area of data-driven predictive models, machine learning, geosensors, and subsurface characterization. He earned a PhD in petroleum engineering from the University of Texas and a bachelor of technology in electrical engineering from the Indian Institute of Technology in Bombay. He received the Department of Energy Early Career Award in 2018 to promote geoscience research.