PNNL's accomplishments in FY 2024 help address the remaining challenges the wind industry faces.

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.

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.

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

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

In a new approach, quantum flow algorithms are used to simulate many-body systems on quantum computers and effectively describe chemical processes.

There are many ways that researchers at PNNL bring unique perspectives to the field of distributed wind. One is the fact that PNNL's distributed wind projects are all led by women.

PNNL will lead support to one of six community teams chosen today by the U.S. Department of Energy to receive a total of up to $25 million.

The Distributed Wind Market Report provides market statistics and analysis, along with insights into market trends and characteristics of wind technologies used as distributed energy resources.

Through collaboration with the Department of Homeland Security Soft Target Engineering to Neutralize the Threat Reality Center of Excellence, PNNL is advancing research and development of tools and methodologies to protect crowded places.

PNNL’s ARENA test bed analyzes how electrical cables degrade in extreme environments and how nondestructive examination inspection technologies can detect and locate damage.

A combined experimental and theoretical study identified multiple interactions that affect the performance of redox-active metal oxides for potential electrochemical separation and quantum computing applications.

A new approach broadens the reach of quantum computers to previously challenging systems.

An evaluation of models and prediction tools for distributed wind turbines has unearthed data that can help potential users make the most informed decisions on upfront investments.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

New research shows that compressing quantum circuits decreases noise and increases the accuracy of quantum calculations.

PNNL wind energy experts have published the Distributed Wind Market Report: 2022 Edition, supplying key findings that can help businesses, communities, and homeowners make informed decisions.

New research from PNNL results in faster and more accurate variational quantum algorithm training.

PNNL researchers developed a hybrid quantum-classical approach for coupled-cluster Green’s function theory that maintains accuracy while cutting computational costs.