Complex metal alloys enter a new era of predictive design for aerospace and other high-temperature applications.

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

Scientists stop the motion of atoms to watch electrons move in liquid water.

The convergence of artificial intelligence, cloud, and high-performance computing to accelerate scientific discovery is the focus of a multi-year collaboration between Microsoft and PNNL.

PNNL has created the Center for AI @PNNL to coordinate the pioneering research of hundreds of scientists working on a range of projects in artificial intelligence.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

The diversity and function of organic matter in rivers at a large scale are influenced by factors, such as the types of vegetation covering the land, the energy characteristics, and the breakdown potential of the molecules.

Scientists have developed a better way to recognize denial-of-service internet attacks, improving detection by 90 percent.

Research from PNNL and the University of Washington demonstrates the extension of the MBE for periodic systems and its use to decompose the lattice energies of different ice polymorphs.

Researchers have knitted together three large databases of information to help cybersecurity experts detect and prevent attacks.

Irradiated boehmite nanoplatelets form smaller aggregates and have a rougher surface than non-irradiated platelets.

Hydrogen bonding and proton transfer control the identity and reactivity of molecules in highly concentrated and alkaline aluminate solutions.

A new method to convert waste plastic to fuel and raw materials promises to help close the carbon cycle at mild temperature and with high yield.

Scientists have taken a key step toward harnessing a form of AI known as deep reinforcement learning to protect computer networks.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

Researchers identified a new intermediate phase that forms during the crystallization of hydrated aluminum-containing salts.

The amount of radiation in a system influences how fast aggregated boehmite particles dissolve.

Simulations show that pH influences boehmite nanoparticle structure and sorption ability.

The size and concentration of ions influences the aggregation behavior of solutions of boehmite.

A new longer-lasting sodium-ion battery design is much more durable and reliable in lab tests. After 300 charging cycles, it retained 90 percent of its charging capacity.