A suite of new modeling methods gives researchers better tools to predict molecular behavior inside cavities.

PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.

A recent article highlighted a PNNL report focused on post-quantum cryptography and electric vehicle charging infrastructure.

Darío Gil, DOE's Undersecretary for Science, makes his inaugural visit to PNNL.

An approach combining multiple theories increases the accuracy of quantum-based simulations without increasing computational demands.

PNNL researchers developed a new computational workflow to study day-to-night gene expression dynamics of cyanobacterium in real time.

PNNL researchers have found yet another way to turn trash into treasure: using algal biochar, a waste production from hydrothermal liquefaction, as a supplementary material for cement.

Neural networks techniques enable the efficient capture of electron correlation effects in reduced-dimensionality spaces.

In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.

Developing a new scheme to more efficiently solve quantum chemistry problems.

PNNL chemical engineer Mariefel Olarte shares passion for mentoring students and the next-generation workforce.

RemPlex and IAEA convene international leaders to tackle recruitment and retention in complex environmental cleanup efforts.

Pacific Northwest National Laboratory researchers developed a new theoretical method for studying highly correlated systems.

Nineteen PNNL-affiliated researchers have been named to Clarivate’s 2024 list of the world's most highly cited researchers.

Francesca Pierobon holds a joint appointment with UW and WSU to advance low-carbon technologies.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

Researchers found that in a future where the Great Plains are 4 to 6 degrees Celsius (°C) warmer as projected in a high-emission scenario, these storms could bring three times more intense rainfall.

A recent study suggests a higher global mean precipitation increase and narrows the uncertainty range.

A new approach validates quantum algorithms for low-energy nuclear physics applications

A new quantum algorithm speeds up simulations of coupled oscillator dynamics.