RemPlex provides a global forum committed to fostering technical leadership, collaborative research, and professional development that facilitates the cost-effective remediation of complex sites.
The Data-Model Convergence (DMC) Initiative is a multidisciplinary effort to create the next generation of scientific computing capability through a software and hardware co-design methodology.
PNNL’s integrated software systems (FRAMES, MEPAS, MetView, APGEMS, CAPP) allow users to assess the environmental fate and transport of contaminants—and the potential impacts on humans and the environment—in a systematic, holistic approach.
PNNL is a leader in the integration of aberration-corrected electron microscopy, in-situ techniques, and atom probe tomography to address challenges in nuclear materials, environmental remediation, energy storage, and national security.
PNNL’s ESMI is a Laboratory-funded research and development (R&D) program focused on transforming and accelerating materials development processes for next-generation energy storage technologies.
PNNL partners with agencies and industry to identify and engage historically disadvantaged populations in regulatory decision-making, environmental assessment, and impact estimation of the consequences of complex polices and projects.
The Isotope Program at PNNL supports scientific advances in the production and use of radioisotopes for research, medicine, and industrial applications.
PNNL data scientists and engineers will be presenting at NeurIPS, the Thirty Fourth Conference on Neural Information Processing Systems, and the co-located Women in Machine Learning workshop, WiML.
The Pacific Northwest National Laboratory is developing a Port Electrification Handbook—a reference to aid maritime ports nationwide in their clean energy transition.
PREPARES demonstrates linkages between climate or weather conditions and human domain systems by combining quantitative geophysical data with qualitative data.
The user-friendly Project Schedule Visualizer software developed at PNNL helps users readily identify and understand the impacts of updates to the schedule, budget, and risks associated with large, complex projects that cross departments.