Publications

Dugger, Michael T.; Dirk, Shawn M.; Celina, Mathias C.; Ohlhausen, J.A.; Szarka, Sara L.; Garcia, Ernest J.

Abstract not provided.

Ohlhausen, J.A.

Abstract not provided.

Ohlhausen, J.A.; Keenan, Michael R.

Abstract not provided.

Dugger, Michael T.; Ohlhausen, J.A.

Abstract not provided.

Dugger, Michael T.; Ohlhausen, J.A.

Abstract not provided.

Ohlhausen, J.A.

Abstract not provided.

Dugger, Michael T.; Ohlhausen, J.A.

Abstract not provided.

Analytical Chemistry

Smentkowski, V.S.; Ostrowski, S.G.; Braunstein, E.; Keenan, M.R.; Ohlhausen, J.A.; Kotula, Paul G.

Three-spatial-dimension (3D) time-of-flight-secondary ion mass spectrometry (TOF-SIMS) analysis can be performed if an X-Y image is saved at each depth of a depth profile. In this paper, we will show how images reconstructed from specified depths, depth profiles generated from specific X-Y coordinates, as well as three-spatial-dimensional rendering provide for a better understanding of the sample than traditional depth profiling where only a single spectrum is collected at each depth. We will also demonstrate, for the first time, that multivariate statistical analysis (MVSA) tools can be used to perform a rapid, unbiased analysis of the entire 3D data set. In the example shown here, retrospective analysis and MVSA revealed a more complete picture of the 3D chemical distribution of the sample than did the as-measured depth profiling alone. Color overlays of the MVSA components as well as animated movies allowing for visualization (in 3D) from various angles will be provided. © 2007 American Chemical Society.

Zavadil, Kevin R.; Kotula, Paul G.; Ohlhausen, J.A.

Abstract not provided.

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

Abstract not provided.

Ohlhausen, J.A.; Celina, Mathias C.; Keenan, Michael R.

Abstract not provided.

Dugger, Michael T.; Ohlhausen, J.A.

Abstract not provided.

Dugger, Michael T.; Ohlhausen, J.A.

Abstract not provided.

Keenan, Michael R.; Ohlhausen, J.A.

Abstract not provided.

Surface and Interface Analysis

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

Abstract not provided.

Analytical Chemistry

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

Abstract not provided.

Sandia journal manuscript; Not yet accepted for publication

Ohlhausen, J.A.; Kotula, Paul G.; Michael, Joseph R.

Spectrum imaging combined with multivariate statistics is an approach to microanalysis that makes the maximum use of the large amount of data potentially collected in forensics analysis. Here, this study examines the efficacy of using spectrum imaging-enabled microscopies to identify chemical signatures in simulated bioagent materials. This approach allowed for the ready discrimination between all samples in the test. In particular, the spectrum imaging approach allowed for the identification of particles with trace elements that would have been missed with a more traditional approach to forensic microanalysis. Finally, the importance of combining signals from multiple length scales and analytical sensitivities is discussed.

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

Abstract not provided.

Nature

Dugger, Michael T.; Ohlhausen, J.A.

Abstract not provided.

Ohlhausen, J.A.; Keenan, Michael R.

Abstract not provided.

Proposed for publication in Science.

Dugger, Michael T.; Ohlhausen, J.A.

As the size of mechanical systems shrinks from macro- to nanoscales, surface phenomena such as adhesion, friction, and wear become increasingly significant. This paper demonstrates the use of alcohol adsorption as a means of continuously replenishing the lubricating layer on the working device surfaces and elucidates the tribochemical reaction products formed in the sliding contact region. Friction and wear of native silicon oxide were studied over a wide range of length scales from macro- to nanoscales using a ball-on-flat tribometer (millimeter scale), sidewall microelectromechanical system (MEMS) tribometer (micrometer scale), and atomic force microscopy (nanometer scale). In all cases, the alcohol vapor adsorption successfully lubricated and prevented wear. Imaging time-of-flight secondary ion mass spectrometry analysis of the sliding contact region revealed that high molecular weight oligomeric species were formed via tribochemical reactions of the adsorbed linear alcohol molecules. These tribochemical products seemed to enhance the lubrication and wear prevention. In the case of sidewall MEMS tests, the lifetime of the MEMS device was radically increased via vapor-phase lubrication with alcohol.

Kotula, Paul G.; Ohlhausen, J.A.

Abstract not provided.

Grant, Richard P.; Michael, Joseph R.; Ohlhausen, J.A.

Abstract not provided.

Walraven, J.A.; Cox, James C.; Skousen, Troy J.; Ohlhausen, J.A.; Jenkins, Mark W.; Jokiel, Bernhard J.; Parson, Ted B.; Tang, Michelle D.

Qualification of microsystems for weapon applications is critically dependent on our ability to build confidence in their performance, by predicting the evolution of their behavior over time in the stockpile. The objective of this work was to accelerate aging mechanisms operative in surface micromachined silicon microelectromechanical systems (MEMS) with contacting surfaces that are stored for many years prior to use, to determine the effects of aging on reliability, and relate those effects to changes in the behavior of interfaces. Hence the main focus was on 'dormant' storage effects on the reliability of devices having mechanical contacts, the first time they must move. A large number ({approx}1000) of modules containing prototype devices and diagnostic structures were packaged using the best available processes for simple electromechanical devices. The packaging processes evolved during the project to better protect surfaces from exposure to contaminants and water vapor. Packages were subjected to accelerated aging and stress tests to explore dormancy and operational environment effects on reliability and performance. Functional tests and quantitative measurements of adhesion and friction demonstrated that the main failure mechanism during dormant storage is change in adhesion and friction, precipitated by loss of the fluorinated monolayer applied after fabrication. The data indicate that damage to the monolayer can occur at water vapor concentrations as low as 500 ppm inside the package. The most common type of failure was attributed to surfaces that were in direct contact during aging. The application of quantitative methods for monolayer lubricant analysis showed that even though the coverage of vapor-deposited monolayers is generally very uniform, even on hidden surfaces, locations of intimate contact can be significantly depleted in initial concentration of lubricating molecules. These areas represent defects in the film prone to adsorption of water or contaminants that can cause movable structures to adhere. These analysis methods also indicated significant variability in the coverage of lubricating molecules from one coating process to another, even for identical processing conditions. The variability was due to residual molecules left in the deposition chamber after incomplete cleaning. The coating process was modified to result in improved uniformity and total coverage. Still, a direct correlation was found between the resulting static friction behavior of MEMS interfaces, and the absolute monolayer coverage. While experimental results indicated that many devices would fail to start after aging, the modeling approach used here predicted that all the devices should start. Adhesion modeling based upon values of adhesion energy from cantilever beams is therefore inadequate. Material deposition that bridged gaps was observed in some devices, and potentially inhibits start-up more than the adhesion model indicates. Advances were made in our ability to model MEMS devices, but additional combined experimental-modeling studies will be needed to advance the work to a point of providing predictive capability. The methodology developed here should prove useful in future assessments of device aging, however. Namely, it consisted of measuring interface properties, determining how they change with time, developing a model of device behavior incorporating interface behavior, and then using the age-aware interface behavior model to predict device function.

Ohlhausen, J.A.

Abstract not provided.