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The ORNL invention addresses the challenge of poor mechanical properties of dry processed electrodes, improves their electrical properties, while improving their electrochemical performance.
A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.
The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.
Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.
Simulation cloning is a technique in which dynamically cloned simulations’ state spaces differ from their parent simulation due to intervening events.
The QVis Quantum Device Circuit Optimization Module gives users the ability to map a circuit to a specific quantum devices based on the device specifications.
QVis is a visual analytics tool that helps uncover temporal and multivariate variations in noise properties of quantum devices.
We have developed an aerosol sampling technique to enable collection of trace materials such as actinides in the atmosphere.
ORNL has developed a new hydrothermal synthesis route to generate high quality battery cathode precursors. The new route offers excellent compositional control, homogenous spherical morphologies, and an ammonia-free co-precipitation process.
Sodium-ion batteries are a promising candidate to replace lithium-ion batteries for large-scale energy storage system because of their cost and safety benefits.