Add BrightSurf on Google Email

DOE/Argonne National Laboratory


Extracting a clean fuel from water

A low-cost catalyst developed by Argonne National Laboratory can produce clean hydrogen from water at a lower cost, making it an ideal choice for replacing fossil fuels and reducing greenhouse gas emissions. The new catalyst uses cobalt instead of expensive iridium, significantly reducing the cost and increasing efficiency.

Argonne’s self-driving lab accelerates the discovery process for materials with multiple applications

Researchers at Argonne National Laboratory have developed a self-driving laboratory called Polybot, which automates electronic polymer research and frees scientists' time to work on tasks only humans can accomplish. The tool combines AI and robotics to streamline experimental processes and accelerate discovery.

SourceDOE/Argonne National Laboratory·JournalChemistry of Materials·DateApr 25, 2023

Argonne drops data on the question of efficient drone use for e-commerce deliveries

A new Argonne study compares drone energy usage to diesel trucks and electric vehicles, finding that drones consume as much energy as either on average windy days. The models are based on regional energy consumption and facility costs of direct delivery drones under various wind speed scenarios.

SourceDOE/Argonne National Laboratory·JournalTransportation Research Record Journal of the Transportation Research Board·DateMar 1, 2023

Biofuel on the road to energy, cost savings

Researchers at Argonne National Laboratory have identified promising new biofuels that can reduce greenhouse gas emissions by up to 60% while improving fuel efficiency or reducing tailpipe emissions. The biofuels, developed using advanced engine design, can be blended with conventional fuels to improve engine performance and meet more ...

SourceDOE/Argonne National Laboratory·JournalACS Sustainable Chemistry & Engineering·DateNov 10, 2022

Through thick and thin: X-rays track the behavior of soft materials

Scientists explore the dynamics of soft materials like toothpaste and hair gel using X-ray photon correlation spectroscopy (XPCS). The technique reveals microscopic dynamics and helps understand properties like viscosity and elasticity. Insights gained can aid in designing consumer products, nanotechnologies, and drug delivery systems.

SourceDOE/Argonne National Laboratory·JournalProceedings of the National Academy of Sciences·DateOct 10, 2022

Future-proofing the Great Lakes region through climate research: Improved regional climate models will help the Great Lakes Region become more informed, ready and resilient

A new study uses high-resolution regional model experiments to explore how lake surface temperatures may affect the climate of the Great Lakes region. Small differences in lake surface temperatures can have a significant impact on summer climate and fuel extreme weather events.

SourceDOE/Argonne National Laboratory·JournalJournal of Geophysical Research Atmospheres·DateAug 3, 2022

Researchers now able to predict battery lifetimes with machine learning

Scientists have developed a machine learning algorithm that can accurately predict the lifetimes of different battery chemistries using as little as a single cycle of experimental data. The technique could reduce costs and accelerate the development of new battery materials, enabling researchers to quickly evaluate and test multiple ma...

SourceDOE/Argonne National Laboratory·JournalJournal of Power Sources·DateMay 5, 2022

The quest for an ideal quantum bit

A team of scientists at Argonne National Laboratory has developed a new qubit platform formed by freezing neon gas into a solid and trapping an electron there. The platform shows great promise in achieving ideal building blocks for future quantum computers, with promising coherence times competitive with state-of-the-art qubits.