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Sandia Academic Alliance Program Collaboration Report: 2020-2021 Accomplishments

Peebles, Diane E.; Horton, Rebecca D.; Claudet, Andre C.; Miner, Nadine E.; Patel, Kamlesh P.; Windsor, Matthew W.; Stites, Mallory C.; Treece, Amy T.

University partnerships play an essential role in sustaining Sandia’s vitality as a national laboratory. The SAA is an element of Sandia’s broader University Partnerships program, which facilitates recruiting and research collaborations with dozens of universities annually. The SAA program has two three-year goals. SAA aims to realize a step increase in hiring results, by growing the total annual inexperienced hires from each out-of-state SAA university. SAA also strives to establish and sustain strategic research partnerships by establishing several federally sponsored collaborations and multi-institutional consortiums in science & technology (S&T) priorities such as autonomy, advanced computing, hypersonics, quantum information science, and data science. The SAA program facilitates access to talent, ideas, and Research & Development facilities through strong university partnerships. Earlier this year, the SAA program and campus executives hosted John Myers, Sandia’s former Senior Director of Human Resources (HR) and Communications, and senior-level staff at Georgia Tech, U of Illinois, Purdue, UNM, and UT Austin. These campus visits provided an opportunity to share the history of the partnerships from the university leadership, tours of research facilities, and discussions of ongoing technical work and potential recruiting opportunities. These visits also provided valuable feedback to HR management that will help Sandia realize a step increase in hiring from SAA schools. The 2020-2021 Collaboration Report is a compilation of accomplishments in 2020 and 2021 from SAA and Sandia’s valued SAA university partners.

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The 2017 Nonlinear Mechanics and Dynamics Research Institute

Kuether, Robert J.; Allensworth, Brooke M.; Peebles, Diane E.

The 2017 Nonlinear Mechanics and Dynamics (NOMAD) Research Institute was successfully held from June 19 to July 28, 2017. NOMAD seeks to bring together participants with diverse technical backgrounds to work in small teams to utilize an interactive approach to cultivate new ideas and approaches in engineering . NOMAD provides an opportunity for researchers - especially early career researchers - to develop lasting collaborations that go beyond what can be established from the limited interactions at their institutions or at annual conferences. A total of 17 students from around the world came to Albuquerque, New Mexico to participate in the six - week long program held at the University of New Mexico campus. The students collaborated on one of six research projects that were developed by various mentors from Sandia National Laboratories, academia, and other government laboratories. In addition to the research activities, the students attended weekly technical seminars, toured the National Museum of Nuclear Science & History, and socialized at various off - hour events including an Albuquerque Isotopes baseball game. At the end of the summer, the students gave a final technical presentation o n their research findings that was broadcast via Skype. Many of the research discoveries made at NOMAD are published as proceedings at technical conference s and have direct alignment with the critical mission work performed at Sandia.

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The 2014 Sandia Nonlinear Mechanics and Dynamics Summer Research Institute

Brake, Matthew R.; Reuss, Pascal R.; Schwingshackl, Christoph W.; Salles, Loic S.; Negus, Michaela N.; Peebles, Diane E.; Mayes, R.L.; Bilbao-Ludena, Juan-Carlos B.; Bonney, Matthew S.; Catalfamo, Simone C.; Gastaldi, Chiara G.; Gross, Johann G.; Lacayo, Robert M.; Robertson, Brett A.; Smith, Scott S.; Swacek, Christian S.; Tiedemann, Merten T.

A collaborative research institute was organized and held at Sandia Albuquerque for a period of six weeks. This research institute brought together researchers from around the world to work collaboratively on a set of research projects. These research projects included: developing experimental guidelines for studying variability and repeatability of nonlinear structures; decoupling aleatoric and epistemic uncertainty in measurements to improve dynamic predictions; a numerical round robin to assess the performance of five different numerical codes for modeling systems with strong nonlinearities; and an assessment of experimentally derived and numerically derived reduced order models. In addition to the technical collaborations, the institute also included a series of seminars given by both Sandians and external experts, as well as a series of tours and field trips to local places of scientific and engineering importance. This report details both the technical research and the programmatic organization of the 2014 Sandia Nonlinear Mechanics and Dynamics Summer Research Institute.

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Phonon engineering for nanostructures

Friedmann, Thomas A.; Piekos, Edward S.; Sullivan, John P.; Peebles, Diane E.

Understanding the physics of phonon transport at small length scales is increasingly important for basic research in nanoelectronics, optoelectronics, nanomechanics, and thermoelectrics. We conducted several studies to develop an understanding of phonon behavior in very small structures. This report describes the modeling, experimental, and fabrication activities used to explore phonon transport across and along material interfaces and through nanopatterned structures. Toward the understanding of phonon transport across interfaces, we computed the Kapitza conductance for {Sigma}29(001) and {Sigma}3(111) interfaces in silicon, fabricated the interfaces in single-crystal silicon substrates, and used picosecond laser pulses to image the thermal waves crossing the interfaces. Toward the understanding of phonon transport along interfaces, we designed and fabricated a unique differential test structure that can measure the proportion of specular to diffuse thermal phonon scattering from silicon surfaces. Phonon-scale simulation of the test ligaments, as well as continuum scale modeling of the complete experiment, confirmed its sensitivity to surface scattering. To further our understanding of phonon transport through nanostructures, we fabricated microscale-patterned structures in diamond thin films.

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Multivariate statistical analysis of time-of-flight secondary ion mass spectrometry images using AXSIA

Applied Surface Science

Ohlhausen, J.A.; Keenan, Michael R.; Kotula, Paul G.; Peebles, Diane E.

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) by its parallel nature, generates complex and very large datasets quickly and easily. An example of such a large dataset is a spectral image where a complete spectrum is collected for each pixel. Unfortunately, the large size of the data matrix involved makes it difficult to extract the chemical information from the data using traditional techniques. Because time constraints prevent an analysis of every peak, prior knowledge is used to select the most probable and significant peaks for evaluation. However, this approach may lead to a misinterpretation of the system under analysis. Ideally, the complete spectral image would be used to provide a comprehensive, unbiased materials characterization based on full spectral signatures. Automated eXpert spectral image analysis (AXSIA) software developed at Sandia National Laboratories implements a multivariate curve resolution technique that was originally developed for energy dispersive X-ray spectroscopy (EDS) [Microsci. Microanal. 9 (2003) 1]. This paper will demonstrate the application of the method to TOF-SIMS. AXSIA distills complex and very large spectral image datasets into a limited number of physically realizable and easily interpretable chemical components, including both spectra and concentrations. The number of components derived during the analysis represents the minimum number of components needed to completely describe the chemical information in the original dataset. Since full spectral signatures are used to determine each component, an enhanced signal-to-noise is realized. The efficient statistical aggregation of chemical information enables small and unexpected features to be automatically found without user intervention. © 2004 Elsevier B.V. All rights reserved.

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14 Results
14 Results