1 - 10 of 13 Results
Dual-GP addresses limitations in traditional GPBO-driven autonomous experimentation by incorporating an additional surrogate observer and allowing human oversight, this technique improves optimization efficiency via data quality assessment and adaptability to unanticipated exp
High-gradient magnetic filtration (HGMF) is a non-destructive separation technique that captures magnetic constituents from a matrix containing other non-magnetic species. One characteristic that actinide metals share across much of the group is that they are magnetic.
The invention introduces a novel, customizable method to create, manipulate, and erase polar topological structures in ferroelectric materials using atomic force microscopy.
Sintering additives to improve densification and microstructure control of UN provides a facile approach to producing high quality nuclear fuels.
Scanning transmission electron microscopes are useful for a variety of applications. Atomic defects in materials are critical for areas such as quantum photonics, magnetic storage, and catalysis.
A human-in-the-loop machine learning (hML) technology potentially enhances experimental workflows by integrating human expertise with AI automation.
The scanning transmission electron microscope (STEM) provides unprecedented spatial resolution and is critical for many applications, primarily for imaging matter at the atomic and nanoscales and obtaining spectroscopic information at similar length scales.
The use of Fluidized Bed Chemical Vapor Deposition to coat particles or fibers is inherently slow and capital intensive, as it requires constant modifications to the equipment to account for changes in the characteristics of the substrates to be coated.
Real-time tracking and monitoring of radioactive/nuclear materials during transportation is a critical need to ensure safety and security. Current technologies rely on simple tagging, using sensors attached to transport containers, but they have limitations.
In scientific research and industrial applications, selecting the most accurate model to describe a relationship between input parameters and target characteristics of experiments is crucial.