The Department of Energy’s Pacific Northwest National Laboratory (PNNL) and Microsoft are collaborating to use high-performance computing and advanced artificial intelligence (AI) to accelerate scientific discovery. The partnership will focus on chemistry and materials science, fields crucial to addressing global energy challenges. Microsoft’s Azure Quantum Elements platform, which uses advanced AI models, is being tested by PNNL researchers to identify new materials for energy applications. The collaboration aims to leverage AI to discover unconventional solutions worth investigating. The partnership will initially focus on computational chemistry and material science.
“We are at the dawn of a new era of scientific discovery that can transform our world for the better. With novel AI and hyperscale capabilities, we can speed up research and unlock the discovery of new molecules that can address some of the most pressing issues of our time, from clean energy to eliminating toxic chemicals and beyond. We are honored to work with world-class scientific institutions like Pacific Northwest National Laboratory. Our breakthrough in using AQE to find new battery materials is just one of the many examples of how our innovative approach to materials research can improve our daily lives,”
Jason Zander, Executive Vice President of Strategic Missions and Technologies at Microsoft.
PNNL and Microsoft’s Energy Storage and Scientific Discovery Collaboration
The Department of Energy’s Pacific Northwest National Laboratory (PNNL) and Microsoft have initiated a multi-year collaboration to accelerate scientific discovery using high-performance computing in the cloud and advanced artificial intelligence (AI). The partnership aims to expedite the application of energy solutions to meet global clean energy goals. The initial focus is on chemistry and materials science, which are crucial to addressing global energy challenges.
PNNL’s Deputy Director for Science and Technology, Tony Peurrung, emphasized the potential of AI in accelerating scientific results. The collaboration aims to make AI accessible to scientists and explore unconventional materials or approaches worth investigating. The partnership is a significant step towards accelerating the pace of scientific discovery.
AI + Quantum Development
The collaboration between PNNL and Microsoft is centered on leveraging AI’s ability to synthesize billions of information bits and quickly present conclusions based on its analysis. Microsoft’s Azure Quantum Elements platform uses advanced AI models specifically designed to aid scientific discovery. PNNL researchers are currently testing its ability to identify promising new materials for energy applications. The collaboration is committed to leveraging advanced AI models to find viable new materials and chemistries that can provide energy-on-demand while preserving Earth’s resources for future generations.
Jason Zander, Executive Vice President of Strategic Missions and Technologies at Microsoft, highlighted the potential of AI and hyperscale capabilities to speed up research and unlock the discovery of new molecules that can address pressing issues such as clean energy and the elimination of toxic chemicals.
Energy Storage as a Test Case
The agreement between PNNL and Microsoft formalizes the next phase of their ongoing relationship. Over the next several years, the partnership aims to pioneer breakthroughs in scientific discovery and sustainable energy by leveraging cutting-edge computing and AI technologies. The initial emphasis will be on computational chemistry and material science.
Materials scientist Vijay Murugesan and his team at PNNL are studying new battery electrolyte materials identified through the collaboration with Microsoft. The entire process, from receiving the simulated candidates to producing a functioning battery, took less than nine months, significantly faster than traditional methods.
The Role of AI and High-Performance Computing in Scientific Discovery
The collaboration between Microsoft and PNNL demonstrates how the combination of advanced AI and next-generation cloud computing can accelerate the pace of scientific discovery. Scientists at PNNL are testing a new battery material that was found in a matter of weeks, not years, as part of the collaboration with Microsoft. This collaboration uses advanced AI and high-performance computing (HPC), a type of cloud-based computing that combines large numbers of computers to solve complex scientific and mathematical tasks.
“The new battery results are just one example—a proof point if you will,” said PNNL’s Chief Digital Officer Brian Abrahamson.
The Future of Scientific Discovery
The collaboration between PNNL and Microsoft is a testament to the dawn of a new era of scientific discovery. The use of novel AI and hyper scale capabilities can speed up research and unlock the discovery of new molecules that can address some of the most pressing issues of our time. The breakthrough in using Azure Quantum Elements to find new battery materials is just one example of how innovative approaches to materials research can improve our daily lives.
The collaboration between PNNL and Microsoft is a significant step towards accelerating scientific discovery and addressing global energy challenges. By leveraging advanced AI and high-performance computing, the partnership aims to identify promising new materials and chemistries that can provide energy-on-demand while preserving Earth’s resources. The initial focus of the collaboration is on chemistry and materials science, with an emphasis on computational chemistry and material science in the future. The partnership is a testament to the potential of AI in accelerating scientific results and the dawn of a new era of scientific discovery.
“The intersection of AI, cloud and high-performance computing, along with human scientists, we believe is key to accelerating the path to meaningful scientific results,”
PNNL’s Deputy Director for Science and Technology Tony Peurrung.
Quick Summary
The Department of Energy’s Pacific Northwest National Laboratory and Microsoft are collaborating to use high-performance computing and advanced artificial intelligence to accelerate scientific discovery, with an initial focus on chemistry and materials science. The partnership aims to identify new materials for energy applications, potentially speeding up the development of solutions to global energy challenges.
“With Microsoft and PNNL, this is an enduring collaboration to accelerate scientific discovery, bringing the power of these computational paradigm shifts to bear, with the chemistry and material science that are a hallmark strength of the Pacific Northwest National Laboratory,”
Brian Abrahamson, the chief digital officer at PNNL.
- The Department of Energy’s Pacific Northwest National Laboratory (PNNL) and Microsoft have partnered to use high-performance computing and advanced artificial intelligence (AI) to accelerate scientific discovery.
- The collaboration aims to speed up the application of energy solutions, with an initial focus on chemistry and materials science.
- Microsoft’s Azure Quantum Elements platform, which uses advanced AI models, is being tested by PNNL researchers for its ability to identify new materials for energy applications.
- The partnership aims to find new materials and chemistries that can provide energy-on-demand while preserving Earth’s resources.
- The collaboration has already resulted in the identification of a new battery material in a matter of weeks, not years.
- The Microsoft Quantum team used AI to identify around 500,000 stable materials in a few days.
- The new battery material was identified from 32 million potential inorganic materials, and narrowed down to 18 promising candidates in just 80 hours.
- The partnership between PNNL and Microsoft is expected to continue over the next several years, with a focus on computational chemistry and material science.
- The collaboration has the potential to speed up solutions for urgent sustainability, pharmaceutical, and other challenges, and provides a glimpse of the advances that will become possible with quantum computing.
