The goal of this project was to develop non-destructive, minimally disruptive eddy sensors to inspect small diameter stainless steel metal tubes. Modifications to Sandia's Emphasis/EIGER code allowed for the modeling of eddy current bobbin sensors near or around 1/8-inch outer diameter stainless steel tubing. Modeling results indicated that an eddy sensor based on a single axial coil could effectively detect changes in the inner diameter of a stainless steel tubing. Based on the modeling results, sensor coils capable of detecting small changes in the inner diameter of a stainless steel tube were designed, built and tested. The observed sensor response agreed with the results of the modeling and with eddy sensor theory. A separate limited distribution SAND report is being issued demonstrating the application of this sensor.
The integration of block-copolymers (BCPs) and nanoimprint lithography (NIL) presents a novel and cost-effective approach to achieving nanoscale patterning capabilities. The authors demonstrate the fabrication of a surface-enhanced Raman scattering device using templates created by the BCP-NIL integrated method. The method utilizes a poly(styrene-block-methyl methacrylate) cylindrical-forming diblock-copolymer as a masking material to create a Si template, which is then used to perform a thermal imprint of a poly(methyl methacrylate) (PMMA) layer on a Si substrate. Au with a Cr adhesion layer was evaporated onto the patterned PMMA and the subsequent lift-off resulted in an array of nanodots. Raman spectra collected for samples of R6G on Si substrates with and without patterned nanodots showed enhancement of peak intensities due to the presence of the nanodot array. The demonstrated BCP-NIL fabrication method shows promise for cost-effective nanoscale fabrication of plasmonic and nanoelectronic devices.
We will describe how novel nanoporous framework materials (NFM) such as metal-organic frameworks (MOFs) can be interfaced with common mechanical sensors, such as surface acoustic wave (SAW), microcantilever array, and quartz crystal microbalance (QCM) devices, and subsequently be used to provide selectivity and sensitivity to a broad range of analytes including explosives, nerve agents, and volatile organic compounds (VOCs). NFM are highly ordered, crystalline materials with considerable synthetic flexibility resulting from the presence of both organic and inorganic components within their structure. Chemical detection using micro-electro-mechanical-systems (MEMS) devices (i.e. SAWs, microcantilevers) requires the use of recognition layers to impart selectivity. Unlike traditional organic polymers, which are dense, the nanoporosity and ultrahigh surface areas of NFM allow for greater analyte uptake and enhance transport into and out of the sensing layer. This enhancement over traditional coatings leads to improved response times and greater sensitivity, while their ordered structure allows chemical tuning to impart selectivity. We describe here experiments and modeling aimed at creating NFM layers tailored to the detection of water vapor, explosives, CWMD, and volatile organic compound (VOCs), and their integration with the surfaces of MEMS devices. Molecular simulation shows that a high degree of chemical selectivity is feasible. For example, a suite of MOFs can select for strongly interacting organics (explosives, CWMD) vs. lighter volatile organics at trace concentrations. At higher gas pressures, the CWMD are deselected in favor of the volatile organics. We will also demonstrate the integration of various NFM on the surface of microcantiliver arrays, QCM crystals, and SAW devices, and describe new synthetic methods developed to improve the quality of NFM coatings. Finally, MOF-coated MEMS devices show how temperature changes can be tuned to improve response times, selectivity, and sensitivity.
The effect of critical dimension (CD) variation and metallization ratio on the efficiency of energy conversion of a surface acoustic wave (SAW) correlator is examined. We find that a 10% variation in the width of finger electrodes predicts only a 1% decrease in the efficiency of energy conversion. Furthermore, our model predicts that a metallization ratio of 0.74 represents an optimum value for energy extraction from the SAW by the interdigitated transducer (IDT).