Automatic signal range selector for metering devices Patent

Voltage range selection apparatus for sensing and applying voltages to electronic instruments without loading signal sourc

Real-time Measurement of Stress and Damage Evolution During Initial Lithiation of Crystalline Silicon

Crystalline to amorphous phase transformation during initial lithiation in (100) silicon-wafers is studied in an electrochemical cell with lithium metal as the counter and reference electrode. It is demonstrated that severe stress jumps across the phase boundary lead to fracture and damage, which is an essential consideration in designing silicon based anodes for lithium ion batteries. During initial lithiation, a moving phase boundary advances into the wafer starting from the surface facing the lithium electrode, transforming crystalline silicon into amorphous LixSi. The resulting biaxial compressive stress in the amorphous layer is measured in situ and it was observed to be ca. 0.5 GPa. HRTEM images reveal that the crystalline-amorphous phase boundary is very sharp, with a thickness of ~ 1 nm. Upon delithiation, the stress rapidly reverses, becomes tensile and the amorphous layer begins to deform plastically at around 0.5 GPa. With continued delithiation, the yield stress increases in magnitude, culminating in sudden fracture of the amorphous layer into micro-fragments and the cracks extend into the underlying crystalline silicon.Comment: 12 pages, 5 figure

Adaptive multigrid algorithm for the lattice Wilson-Dirac operator

We present an adaptive multigrid solver for application to the non-Hermitian Wilson-Dirac system of QCD. The key components leading to the success of our proposed algorithm are the use of an adaptive projection onto coarse grids that preserves the near null space of the system matrix together with a simplified form of the correction based on the so-called gamma_5-Hermitian symmetry of the Dirac operator. We demonstrate that the algorithm nearly eliminates critical slowing down in the chiral limit and that it has weak dependence on the lattice volume

Natural Cycles, Gases

The major gaseous components of the exhaust of stratospheric aircraft are expected to be the products of combustion (CO2 and H2O), odd nitrogen (NO, NO2 HNO3), and products indicating combustion inefficiencies (CO and total unburned hydrocarbons). The species distributions are produced by a balance of photochemical and transport processes. A necessary element in evaluating the impact of aircraft exhaust on the lower stratospheric composition is to place the aircraft emissions in perspective within the natural cycles of stratospheric species. Following are a description of mass transport in the lower stratosphere and a discussion of the natural behavior of the major gaseous components of the stratospheric aircraft exhaust

Silicon materials task of the low cost solar array project. Phase 3: Effect of impurities and processing on silicon solar cells

The 13th quarterly report of a study entitled an Investigation of the Effects of Impurities and Processing on Silicon Solar Cells is given. The objective of the program is to define the effects of impurities, various thermochemical processes and any impurity-process interactions on the performance of terrestrial silicon solar cells. The Phase 3 program effort falls in five areas: (1) cell processing studies; (2) completion of the data base and impurity-performance modeling for n-base cells; (3) extension of p-base studies to include contaminants likely to be introduced during silicon production, refining or crystal growth; (4) anisotropy effects; and (5) a preliminary study of the permanence of impurity effects in silicon solar cells. The quarterly activities for this report focus on tasks (1), (3) and (4)

Stability of Filters for the Navier-Stokes Equation

Data assimilation methodologies are designed to incorporate noisy observations of a physical system into an underlying model in order to infer the properties of the state of the system. Filters refer to a class of data assimilation algorithms designed to update the estimation of the state in a on-line fashion, as data is acquired sequentially. For linear problems subject to Gaussian noise filtering can be performed exactly using the Kalman filter. For nonlinear systems it can be approximated in a systematic way by particle filters. However in high dimensions these particle filtering methods can break down. Hence, for the large nonlinear systems arising in applications such as weather forecasting, various ad hoc filters are used, mostly based on making Gaussian approximations. The purpose of this work is to study the properties of these ad hoc filters, working in the context of the 2D incompressible Navier-Stokes equation. By working in this infinite dimensional setting we provide an analysis which is useful for understanding high dimensional filtering, and is robust to mesh-refinement. We describe theoretical results showing that, in the small observational noise limit, the filters can be tuned to accurately track the signal itself (filter stability), provided the system is observed in a sufficiently large low dimensional space; roughly speaking this space should be large enough to contain the unstable modes of the linearized dynamics. Numerical results are given which illustrate the theory. In a simplified scenario we also derive, and study numerically, a stochastic PDE which determines filter stability in the limit of frequent observations, subject to large observational noise. The positive results herein concerning filter stability complement recent numerical studies which demonstrate that the ad hoc filters perform poorly in reproducing statistical variation about the true signal