Measuring the ice nucleation activity of particles in the ambient atmosphere can help develop better representations for use in climate models.

PNNL contributes to 30 years of data on clouds, radiation, and other climate-making factors as part of field campaigns and analysis conducted by DOE's Atmospheric Radiation Measurement user facility.

Parallel graph neural networks identify protein-ligand 3-D structural interactions to aid in protein function prediction and drug discovery.

Researchers use machine learning to speed up the analysis of aerosol datasets from mass spectrometry.

PNNL researchers have uncovered a plant-derived process that leads to the formation of aerosol particles over the Amazon rainforest and potentially other forested parts of the world. 

Combining aircraft measurements and regional modeling allowed researchers to identify the role of in-plant biochemistry in secondary organic aerosol formation.

Using unique laboratory single-particle measurements to understand some of the most uncertain processes affecting secondary organic aerosol formation.

Moving toward a deeper understanding of the influence of large marine biogenic particles on cloud ice formation by combining modeling and observational data.

IDREAM researchers use fast force mapping to provide insights into the boehmite interfacial solution structure.

The rapid growth of urban nanoparticles via the condensation of organic vapors substantially alters shallow cloud formation and suppresses precipitation.

Vanda Glezakou and Laboratory Fellow Roger Rousseau collaborated with other experts to write an American Chemical Society book chapter.

A hybrid computing approach for solving quantum chemical problems offers a practical bridge between classical and quantum computing.

Researchers achieved the complete assignment of the infrared spectrum of a hydronium-water “magic number” cluster reported in Science in 2004.

A team of researchers developed a simulation approach to identify how atomic structures can affect the phonon transport of energy and information in quantum systems near absolute zero temperatures.

Simulations show a strong correlation between the water content and the viscosity of organic aerosol over the Amazon rainforest.

Theoretical work shows that an important natural iron source can be described as a nanoscale composite of different, but experimentally indistinguishable, structures.

Fundamental research conducted at the $90-million research facility will help the nation meet its clean energy goals.

PNNL researchers are studying catalysts that are key to dealing with waste and producing sustainable energy.

Creating films with atomic precision allows researchers moving to the Energy Sciences Center to identify small, but important changes in the materials.

PNNL data scientists are refining their artificial intelligence tools with COVID-19 data to advance therapeutics and treatments for a future pandemic.