We present a dynamic laboratory spontaneous imbibition test and interpretation method, demonstrated on volcanic tuff samples from the Nevada National Security Site. The method includes numerical inverse modeling to quantify uncertainty of estimated two-phase fluid flow properties. As opposed to other approaches requiring multiple different laboratory instruments, the dynamic imbibition method simultaneously estimates capillary pressure and relative permeability from one test apparatus.
High density interconnects are required for increased input/output for microelectronics applications, incentivizing the development of Cu electrochemical deposition (ECD) processes for high aspect ratio through-silicon vias (TSVs). This work outlines Cu ECD processes for 62.5 μm diameter TSVs, etched into a 625 μm thick silicon substrate, a 10:1 aspect ratio. Cu ECD in high aspect ratio features relies on a delicate balance of electrolyte composition, solution replenishment, and applied voltage. Implementing a CuSO4-H2SO4 electrolyte, which contains suppressor and a low chloride concentration, allows for a tunable relationship between applied voltage and localized deposition in the vias. A stepped potential waveform was applied to move the Cu growth front from the bottom of the via to the top. Sample characterization was performed through mechanical cross-sections and X-ray computed tomography (CT) scans. The CT scans revealed small seam voids in the Cu electrodeposit, and process parameters were tuned accordingly to produce void-free Cu features. During the voltage-controlled experiments, measured current data showed a characteristic current minimum, which was identified as an endpoint detection method for Cu deposition in these vias. We believe this is the first report of this novel endpoint detection method for TSV filling.
Natural and induced fractures are potential preferential pathways for migration of radioactive gases to earths surface from underground nuclear explosions (UNEs). This report documents X-ray computed tomography (XRCT) imaging on 26 samples of rock core that was collected to support the Underground Nuclear Explosion Signatures Experiment (UNESE) program. The XRCT datasets are intended to help fill a data gap on the three-dimensional (3D) characteristics of natural and/or induced fractures at the centimeter and smaller scale, which may strongly influence multiphase fluid flow and transport properties of preferential flow paths and interaction with the matrix of the surrounding host rock. Pre- and post-UNE rock samples were carefully chosen to enable comparison of fractures as a function of lithologic and petrophysical properties, as well as distance to the past UNEs. This report serves as documentation for the data, including an introduction with the research motivation, a methods and materials section, descriptions of the XRCT datasets without post-processing, and recommendations for 3D quantification via image analysis and digital rock physics.
Quantifying in-situ subsurface stresses and predicting fracture development are critical to reducing risks of induced seismicity and improving modern energy activities in the subsurface. In this work, we developed a novel integration of controlled mechanical failure experiments coupled with microCT imaging, acoustic sensing, modeling of fracture initiation and propagation, and machine learning for event detections and waveform characterization. Through additive manufacturing (3D printing), we were able to produce bassanite-gypsum rock samples with repeatable physical, geochemical and structural properties. With these "geoarchitected" rock, we provided the role of mineral texture orientation on fracture surface roughness. The impact of poroelastic coupling on induced seismicity has been systematically investigated to improve mechanistic understanding of post shut-in surge of induced seismicity. This research will set the groundwork for characterizing seismic waveforms by using multiphysics and machine learning approaches and improve the detection of low-magnitude seismic events leading to the discovery of hidden fault/fracture systems.