Engineering topics
Fiedler, Kevin R.
Publications and source records attributed to Fiedler, Kevin R..
Optical Evidence of Compositional Fractioning between Plasma‐Condensed and Melt Pool Matter
Control of multicomponent alloys during welding is challenging because it lacks a real‐time understanding of composition. The optical emissions of plasma formed during laser‐induced metal welding correlate with the composition of particles ejected from the melt pool. Plasma emissions observed in this study contain large iron, manganese, chrome, and copper signatures, which match the composition of emitted particles. Particles recovered closest to the melt pool exhibit a core–shell morphology that is composed of iron‐manganese‐chrome intermetallic cores within copper shells. Particles collected farther from the melt pool, do not share this core–shell morphology, though similar elemental compositions are observed. The correlation between plasma optical emissions and particle composition can be used to predict the composition of the melt pool, allowing for real‐time welding and sintering control.
Correlations between Molecular Structure, Solvation Topology, and Transport Properties of Aqueous Organic Flow Battery Electrolyte Solutions
Aqueous organic redox flow batteries (AORFBs) are considered promising technologies for storing energy generated from renewable resources. However, designing organic electrolyte molecules is limited by gaps between fundamental understanding of coupling between solvation structure and dynamics, and macroscopic transport properties like viscosity. Herein, we used molecular dynamics simulations to understand correlations between ionic molecular structures, ion clustering, and transport properties in 2,3-dihydrophenazine (2,3-DHP), a promising AORFB anolyte. We show that experimentally measured viscosity can be reproduced from simulations at relevant concentrations and that the asymmetric structure of 2,3-DHP leads to unique inhomogeneity in the solvation topology. However, order parameters and metrics need to be developed for better correlations over spatiotemporal scales, with careful consideration of the inhomogeneity of organic anolyte molecules. In conclusion, we show that the increased size and asymmetry of the anolyte leads to breakdown of assumptions within methods for determining ion transport mechanisms previously developed for Li-ion batteries.
TiltEM User Manual
The ability to automate the scanning transmission electron microscope (S/TEM) is tantamount to addressing next generation artificial intelligence, machine learning, and materials modeling capabilities. Constant utilization of these high-end capital equipment purchases also serves the requirements of the Department of Energy (DOE) to be fiscally responsible to the public. The development of an automated multi-modal tilt series algorithm for dark field/bright field S/TEM imaging plus chemical identification with energy dispersive x-ray spectroscopy has been achieved at PNNL. A tilt series workflow has now been generated which allows for autonomous collection of imaging and compositional information simultaneously. This advancement is due in large part to a transition from the rigid and microscope specific JEOL hardware environment, to the more adaptable GMS environment. This has thereby led to a greater degree of flexibility in the application of this method across platforms in addition to substantial time savings to the user.