As governments and the innovation sector intensify efforts to develop solutions for the transition to a clean energy future, AI is emerging as a key driver of progress. Quantitative AI along with quantum mechanics-based algorithms are at the forefront of these efforts. Large Quantitative Models (LQM’s) can unlock new possibilities in energy storage, sustainable materials design, and the elimination of harmful chemicals like PFAS, making it an essential tool in addressing global environmental challenges and driving the move to cleantech solutions.
The recent surge in generative AI applications has mostly focused on content creation and customer service, driven by large language models (LLMs) that excel at tasks like text generation and virtual assistance. However, this is just one facet of AI. A transformative new wave of AI innovation is reshaping how we solve complex physical challenges. AI simulation using LQMs enables researchers to model intricate real-world systems at the molecular and atomic levels, creating digital twins that can simulate chemical reactions, material properties, and energy processes with unprecedented precision. These simulations bypass time-consuming physical experiments, accelerating discovery and innovation.
At the core of this revolution is the development of LQMs. Unlike traditional machine learning models that rely on vast datasets of historical observations, LQMs are powered by first-principles physics. These models leverage quantum mechanics-based algorithms and are trained on data generated from billions of in silico simulations—virtual experiments that predict molecular interactions and the behaviors of new compounds. This shift from data-driven to physics-driven AI allows for real-time prediction and optimization of materials and chemical processes, accelerating solutions for some of the most pressing global challenges.
As the world scales to renewable energy sources and electric vehicles (EVs), energy storage is critical. Lithium-ion batteries are the current standard for storing energy from wind, solar, and other renewable sources, as well as powering EVs. Coupled with the ever-growing number of digital devices, the demand for lithium-ion batteries has skyrocketed in recent years. Additional challenges in capacity, cost, and environmental impact risk curbing the transition to a sustainable energy future.
As the auto industry moves towards an electric future, manufacturers require lighter, more durable, more powerful, and longer-lasting batteries. Developing new battery chemistries and designs typically takes years of testing before they can be put into production. However, using AI, researchers can reduce the testing period to months and deliver new data and insights that will further advance future battery development. This approach accelerates the development of batteries with higher energy densities, longer lifespans, and lower costs, facilitating the widespread adoption of renewable energy and electric vehicles while reducing environmental impact.
Another major environmental challenge is the proliferation of harmful chemicals in manufacturing and everyday products. Per- and polyfluoroalkyl substances (PFAS), commonly known as "forever chemicals," have become a significant concern due to their persistence in the environment and potential health risks. PFAS are widely used in products such as non-stick cookware, firefighting foam, and water-repellent clothing, but they do not break down naturally, leading to contamination of water sources and ecosystems.
By modeling the molecular structure of alternative compounds, researchers can design chemicals that maintain the desired properties of PFAS—such as water resistance—without the associated environmental risks. These simulations predict how new compounds will behave in real-world applications, reducing reliance on trial-and-error methods and speeding up the discovery of safer, biodegradable alternatives.
The importance of this work cannot be overstated. PFAS have been linked to serious health issues such as cancer and liver damage, and have been found in the blood of 97% of Americans. Similar studies in Europe show widespread PFAS contamination of air, water and land resources as well.
By using quantitative AI to eliminate these toxic substances, we can make significant strides in protecting both human health and the environment.
AI simulation is also driving breakthroughs in materials science—a field that has far-reaching implications for industries ranging from construction to aerospace. The global construction industry is a major contributor to greenhouse gas emissions, accounting for approximately 21% of total CO2 emissions globally, according to the United Nations Environment Programme (UNEP). The development of sustainable materials that are lighter, stronger, and less energy-intensive to produce is critical to reducing the environmental impact of construction and manufacturing.
For example, innovative companies are exploring the creation of "green steel", a type of steel produced using hydrogen instead of coal as a reducing agent, which significantly lowers carbon emissions. According to the World Steel Association, the steel industry alone accounts for 7-9% of global CO2 emissions, making innovations in this area essential for meeting climate targets.
New materials can impact other high-emissions sectors such as transportation. Developing lighter, stronger, more durable materials with improved strength-to-weight ratio could make automobiles and airplanes more fuel-efficient while retaining or improving their current safety standards. These next-generation materials could also lead to innovative new designs that are not currently possible due to the limitations of existing materials or more energy-efficient and eco-friendly manufacturing processes.
As outlined in the Quantum Economy Blueprint, fully realizing the potential of frontier technologies such as quantum and AI will require deep collaboration between academia, public and private sectors, and nation-states. Cross-sector partnerships, such as the Clean Energy Ministerial and the AI for Climate initiative, showcase how collective efforts can invest in these technologies and ensure their resulting innovations are scalable and globally accessible.
While AI simulation is currently running on advanced classical hardware like GPUs, the future lies in the increasing potential of quantum computers. As quantum computing technology advances, its ability to solve intricate molecular and material challenges will unlock even more powerful capabilities for AI simulation. However, to reach this future, coordinated efforts across sectors will be essential to build the necessary infrastructure and regulatory frameworks that support these advancements.
Beyond technological progress, the success of frontier technologies in powering climate innovation will depend on upskilling the global workforce. Engineers, scientists, and policymakers must be equipped with the knowledge and tools to harness the power of AI and quantum in their efforts to limit climate change. Integrating AI and quantum education into academic curricula and professional development programs will be key to empowering the next generation of climate innovators.
As the world faces the dual challenges of mitigating climate change and ensuring sustainable development, AI is emerging as a critical tool for unlocking breakthroughs across industries. From accelerating the development of clean energy solutions to revolutionizing materials design and chemical processes, AI simulation is enabling researchers to solve some of the most pressing environmental challenges. By investing in these technologies and fostering cross-sector collaboration, we can realize AI’s full potential to build a sustainable future.
Jack Hidary leads SandboxAQ, which focuses on enterprise SaaS solutions at the convergence of AI and Quantum tech. A serial entrepreneur, he co-founded several tech companies, including EarthWeb/Dice (NYSE: DHX), which he led from its founding through IPO, and Vista Research which was acquired by S&P/ McGraw-Hill. He is also a trustee of the X Prize Foundation and has been a board member of Trickle Up, to support entrepreneurs and small business growth.