Engineering topics

Larson, Steven R.

Publications and source records attributed to Larson, Steven R..

3 records

DOE OSTI2024

Characterization of MoS 2 films via simultaneous grazing incidence X-ray diffraction and grazing incidence X-ray fluorescence (GIXRD/GIXRF)

Physical vapor deposited (PVD) molybdenum disulfide (nominal composition MoS 2 ) is employed as a thin film solid lubricant for extreme environments where liquid lubricants are not viable. The tribological properties of MoS 2 are highly dependent on morphological attributes such as film thickness, orientation, crystallinity, film density, and stoichiometry. These structural characteristics are controlled by tuning the PVD process parameters, yet undesirable alterations in the structure often occur due to process variations between deposition runs. Nondestructive film diagnostics can enable improved yield and serve as a means of tuning a deposition process, thus enabling quality control and materials exploration. Grazing incidence X-ray diffraction (GIXRD) for MoS 2 film characterization provides valuable information about film density and grain orientation (texture). However, the determination of film stoichiometry can only be indirectly inferred via GIXRD. The combination of density and microstructure via GIXRD with chemical composition via grazing incidence X-ray fluorescence (GIXRF) enables the isolation and decoupling of film density, composition, and microstructure and their ultimate impact on film layer thickness, thereby improving coating thickness predictions via X-ray fluorescence. We have augmented an existing GIXRD instrument with an additional X-ray detector for the simultaneous measurement of energy-dispersive X-ray fluorescence spectra during the GIXRD analysis. This combined GIXRD/GIXRF analysis has proven synergetic for correlating chemical composition to the structural aspects of MoS 2 films provided by GIXRD. We present the usefulness of the combined diagnostic technique via exemplar MoS 2 film samples and provide a discussion regarding data extraction techniques of grazing angle series measurements.

MoS2↗

DOE OSTI2024

Electrodeposited Mo x S y O z /Ni Tribological Coatings

Deposition of molybdenum disulfide (MoS 2 ) coatings using physical vapor deposition (PVD) and mechanical burnishing has been widely assessed for solid lubricants in space applications but still suffers from line-of-sight constraints on complex geometries. Here, we highlight one of the first demonstrations of electrodeposited Mo x S y O z and Mo x S y O z /Ni thin-film coatings from aqueous solutions of ammonium tetrathiomolybdate for solid lubricant applications and their remarkable ability to provide low coefficients of friction and high wear resistance. Characterization of the coating morphology shows amorphous microstructures with a high oxygen content and cracking upon drying. Even so, electrodeposited Mo x S y O z can achieve low steady-state coefficients of friction (μ ∼ 0.05–0.06) and wear rates (2.6 × 10 –7 mm 3 /(N m)) approaching those of physical vapor deposited coatings (2.3 × 10 –7 mm 3 /(N m)). Additionally, we show that adding dopants such as nickel increased the wear rate (7.5 × 10 –7 mm 3 /(N m)) and initial coefficient of friction (μ i = 0.23) due to compositional modifications such as dramatic sub-stoichiometry (S/Mo ∼ 1) and expression of a NiO x surface layer, although doping did reduce the degree of cracking upon drying.

Babuska, Tomas F.↗

DOE OSTI2021

Towards Predictive Plasma Science and Engineering through Revolutionary Multi-Scale Algorithms and Models (Final Report)

This report describes the high-level accomplishments from the Plasma Science and Engineering Grand Challenge LDRD at Sandia National Laboratories. The Laboratory has a need to demonstrate predictive capabilities to model plasma phenomena in order to rapidly accelerate engineering development in several mission areas. The purpose of this Grand Challenge LDRD was to advance the fundamental models, methods, and algorithms along with supporting electrode science foundation to enable a revolutionary shift towards predictive plasma engineering design principles. This project integrated the SNL knowledge base in computer science, plasma physics, materials science, applied mathematics, and relevant application engineering to establish new cross-laboratory collaborations on these topics. As an initial exemplar, this project focused efforts on improving multi-scale modeling capabilities that are utilized to predict the electrical power delivery on large-scale pulsed power accelerators. Specifically, this LDRD was structured into three primary research thrusts that, when integrated, enable complex simulations of these devices: (1) the exploration of multi-scale models describing the desorption of contaminants from pulsed power electrodes, (2) the development of improved algorithms and code technologies to treat the multi-physics phenomena required to predict device performance, and (3) the creation of a rigorous verification and validation infrastructure to evaluate the codes and models across a range of challenge problems. These components were integrated into initial demonstrations of the largest simulations of multi-level vacuum power flow completed to-date, executed on the leading HPC computing machines available in the NNSA complex today. These preliminary studies indicate relevant pulsed power engineering design simulations can now be completed in (of order) several days, a significant improvement over pre-LDRD levels of performance.

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