Publications

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Sandia Materials Science Investment Area contributed to the SARS-CoV-2 virus and COVID-19 disease which represent the most significant pandemic threat in over 100 years. We completed a series of 7, short duration projects to provide innovative materials science research and development in analytical techniques to aid the neutralization of COVID-19 on multiple surfaces, approaches to rapidly decontaminate personal protective equipment, and pareto assessment of construction materials for manufacturing personal protective equipment. The developed capabilities and processes through this research can help US medical personnel, government installations and assets, first responders, state and local governments, and multiple federal agencies address the COVID-19 Pandemic.

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We have developed and characterized novel in-situ corrosion sensors to monitor and quantify the corrosive potential and history of localized environments. Embedded corrosion sensors can provide information to aid health assessments of internal electrical components including connectors, microelectronics, wires, and other susceptible parts. When combined with other data (e.g. temperature and humidity), theory, and computational simulation, the reliability of monitored systems can be predicted with higher fidelity.

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Three balance of systems (BOS) connector designs common to industry were investigated as a means of assessing reliability from the perspective of arc fault risk. These connectors were aged in field and laboratory environments and performance data captured for future development of a reliability model. Comparison of connector resistance measured during damp heat, mixed flowing gas and field exposure in a light industrial environment indicated disparities in performance across the three designs. Performance was, in part, linked to materials of construction. A procedure was developed to evaluate new and aged connectors for arc fault risk and tested for one of the designs. Those connectors exposed to mixed flowing gas corrosion exhibited considerable Joule heating that may enhance arcing behavior, suggesting temperature monitoring as a potential method for arc fault prognostics. These findings, together with further characterization of connector aging, can provide operators of photovoltaic installations the information necessary to develop a data-driven approach to BOS connector maintenance as well as opportunities for arc fault prognostics.

The continued exponential growth of photovoltaic technologies paves a path to a solar-powered world, but requires continued progress toward low-cost, high-reliability, high-performance photovoltaic (PV) systems. High reliability is an essential element in achieving low-cost solar electricity by reducing operation and maintenance (O&M) costs and extending system lifetime and availability, but these attributes are difficult to verify at the time of installation. Utilities, financiers, homeowners, and planners are demanding this information in order to evaluate their financial risk as a prerequisite to large investments. Reliability research and development (R&D) is needed to build market confidence by improving product reliability and by improving predictions of system availability, O&M cost, and lifetime. This project is focused on understanding, predicting, and improving the reliability of PV systems. The two areas being pursued include PV arc-fault and ground fault issues, and inverter reliability.

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Tomographic spectral imaging is a powerful technique for the 3D analysis of materials. The present work describes the application of this technique to the analysis of localized corrosion of a connector pin. Implemented via serial sectioning in a focused ion-beam/scanning electron microscope, electron-excited x-ray spectra were acquired from each voxel in a 3D array. The resultant tomographic spectral image was analyzed in its entirety with Sandia's Automated eXpert Spectral Image Analysis multivariate statistical analysis software. The result of the analysis is a small number of chemical components which describe the 3D phase distribution in the volume of material sampled. © 2012 IEEE.

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A reliability and availability model has been developed for a portion of the 4.6 megawatt (MWdc) photovoltaic system operated by Tucson Electric Power (TEP) at Springerville, Arizona using a commercially available software tool, GoldSim{trademark}. This reliability model has been populated with life distributions and repair distributions derived from data accumulated during five years of operation of this system. This reliability and availability model was incorporated into another model that simulated daily and seasonal solar irradiance and photovoltaic module performance. The resulting combined model allows prediction of kilowatt hour (kWh) energy output of the system based on availability of components of the system, solar irradiance, and module and inverter performance. This model was then used to study the sensitivity of energy output as a function of photovoltaic (PV) module degradation at different rates and the effect of location (solar irradiance). Plots of cumulative energy output versus time for a 30 year period are provided for each of these cases.

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A series of thin electrodeposited Cu foils and Cu foil/Kapton flex circuits were tested in bending fatigue according to ASTM E796 and IPC-TM-650. The fatigue behavior was analyzed in terms of strain vs. number of cycles to failure, using a Coffin-Manson approach. The effects of Cu foil thickness and Cu trace width are discussed. The Cu foils performed as expected and the Cu foil/Kapton® (E.I. du Pont de Nemours and Company, Wilmington, DE) composites showed significant improvement in fatigue lifetime due to the composite strengthening effect of the Kapton layers. However, the flex circuits showed more scatter in fatigue life based on electrical continuity. The effect of the Kapton layers manifests itself by significantly more widespread microcracking in the Cu traces and the extent of microcracking depended on the strain level. *Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. © 2008 MS&T'08 ®.

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The goal of this study is to model the electrical response of gold plated copper electrical contacts exposed to a mixed flowing gas stream consisting of air containing 10 ppb H{sub 2}S at 30 C and a relative humidity of 70%. This environment accelerates the attack normally observed in a light industrial environment (essentially a simplified version of the Battelle Class 2 environment). Corrosion rates were quantified by measuring the corrosion site density, size distribution, and the macroscopic electrical resistance of the aged surface as a function of exposure time. A pore corrosion numerical model was used to predict both the growth of copper sulfide corrosion product which blooms through defects in the gold layer and the resulting electrical contact resistance of the aged surface. Assumptions about the distribution of defects in the noble metal plating and the mechanism for how corrosion blooms affect electrical contact resistance were needed to complete the numerical model. Comparisons are made to the experimentally observed number density of corrosion sites, the size distribution of corrosion product blooms, and the cumulative probability distribution of the electrical contact resistance. Experimentally, the bloom site density increases as a function of time, whereas the bloom size distribution remains relatively independent of time. These two effects are included in the numerical model by adding a corrosion initiation probability proportional to the surface area along with a probability for bloom-growth extinction proportional to the corrosion product bloom volume. The cumulative probability distribution of electrical resistance becomes skewed as exposure time increases. While the electrical contact resistance increases as a function of time for a fraction of the bloom population, the median value remains relatively unchanged. In order to model this behavior, the resistance calculated for large blooms has been weighted more heavily.

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