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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.

Polarization drift in quantum networks is a major issue. Fiber transforms a transmitted signal’s polarization differently depending on its environment.

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.

ORNL contributes to developing the concept of passive CO2 DAC by designing and testing a hybrid sorption system. This design aims to leverage the advantages of CO2 solubility and selectivity offered by materials with selective sorption of adsorbents.

Electrochemistry synthesis and characterization testing  typically occurs manually at a research facility.

Atmospheric carbon dioxide is captured with an aqueous solution containing a guanidine photobase and a small peptide, using a UV-light stimulus, and subsequently released when the light stimulus is removed.