Self-learning labs to transform American Discovery
The Orchestrated Platform for Autonomous Laboratories (OPAL) is a multi-laboratory project led by the U.S. Department of Energy (DOE) to turn biological discovery into a self-driving process. By combining artificial intelligence (AI), robotics, and automated experimentation, OPAL seeks to create a network of autonomous laboratories that can learn, adapt, and accelerate breakthroughs across biology, biotechnology, and energy science.
A National Collaboration
Four DOE national laboratories are joining forces to make autonomous science a reality, building a federated network of intelligent, interconnected research platforms that can collaborate and share data in real time, reducing the time from discovery to real-world application. From designing new microbial proteins and pathways to helping plants pull critical minerals from the soil, these teams are focusing on the discoveries that will power America’s future.
Accelerating Discovery: Self-learning labs conduct experiments around the clock, reducing the time from idea to impact.
Empowering Innovation: AI-guided biodesign opens new frontiers in energy, critical materials, and manufacturing.
Streamlining Collaboration: Integrated systems enable data sharing between laboratories for real-time collaboration.
Transforming Protein Engineering Through Intelligent Automation
At Argonne National Laboratory, scientists are pioneering a transformative approach to protein design by integrating AI with advanced robotics. By coordinating design, build, test, and learn cycles these robotic agents will optimize proteins for critical applications such as bioleaching enzymes for rare earth element extraction. This innovative system will bridge the gap between computational design and experimental validation.
Harnessing Microbial Functions for Bio-Based Manufacturing
At Lawrence Berkeley National Laboratory and Pacific Northwest National Laboratory, scientists are drawing on their microbial engineering expertise to develop a distributed platform that will allow them to map the molecular determinants of microbial functions back to genomes, accelerating scalable predictive biodesign approaches. Leveraging the Anaerobic Microbial Phenotyping Platform, a fully automated laboratory at the Environmental Molecular Sciences Laboratory, a DOE Office of Science National User Facility located at PNNL, the team will evaluate how AI-driven agentic workflows, integrated with multi-modal data (omics, imaging, physiology, and genomics), can enable scalable and predictive microbial bioprocess design. The multi-modal foundation models from this project will have broad application, from critical minerals to high-performance materials and fuels, helping to transform industrial processes through accelerated biotechnology advances.
Accelerating AI-Driven Biodesign for U.S. Critical Minerals Supply
At Oak Ridge National Laboratory, OPAL leverages the unique capabilities of one of the world’s most advanced automated plant research facilities: the Advanced Plant Phenotyping Laboratory (APPL). APPL integrates high-resolution imaging, robotics, and AI-powered analytics to link genetic variation to phenotypic traits, enabling rapid, data-driven plant characterization. Scientists are using this unique facility to develop plants that can “mine” rare earth elements critical for energy technologies.