From global issues such as melting permafrost and the creation of alternate biofuels to matters affecting microbiomes and micro-sized life, PNNL research is featured in news publications worldwide.

HydroWIRES initiative helps water stakeholders reap the full benefit of hydropower’s superpower: versatility

PNNL is heavily engaged in the development and use of mass spectrometry technology across its science, energy, and security missions, from fundamental research through mature operational capabilities.

Physics Informed Machine Learning (PIML) is a modeling approach that harnesses the power of machine learning and big data to improve the understanding of coupled, dynamic systems.

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.

PNNL's Subsurface Biogeochemical Research Scientific Focus Area works to transform understanding of spatial and temporal dynamics in river corridor hydrobiogeochemical functions from molecular reaction to watershed and basin scales.

The Salish Sea Model (SSM) is a predictive coastal ocean model for estuarine research, restoration planning, water-quality management, and climate change response assessment.

Advancing our understanding of how soil microbial communities respond to--and affect--changing environmental conditions

PNNL researchers developed and manage the online database Tethys to actively collects and curates information on the environmental effects of wind and marine energy.

The Triton Initiative was created to help the marine energy industry better understand the environmental impacts of marine energy devices.

PNNL water quality research and tools help inform hydropower decisions and operations.

PNNL develops training, exercises, and assessments to prepare and equip border security officers to detect, identify, and interdict the illicit movements of materials, commodities, and components associated with WMD.