Tensile Properties of Amorphous Diamond Films

The strength and modulus of amorphous diamond, a new material for surface micromachined MEMS and sensors, was tested in uniaxial tension by pulling laterally with a flat tipped diamond in a nanoindenter. Several sample designs were attempted. Of those, only the single layer specimen with a 1 by 2 {micro}m gage cross section and a fixed end rigidly attached to the substrate was successful. Tensile load was calculated by resolving the measured lateral and normal forces into the applied tensile force and frictional losses. Displacement was corrected for machine compliance using the differential stiffness method. Post-mortem examination of the samples was performed to document the failure mode. The load-displacement data from those samples that failed in the gage section was converted to stress-strain curves using carefully measured gage cross section dimensions. Mean fracture strength was found to be 8.5 {+-} 1.4 GPa and the modulus was 831 {+-} 94 GPa. Tensile results are compared to hardness and modulus measurements made using a nanoindenter

Laboratory studies of water transport in rock salt

The transport of water through rock salt as a result of heating is examined experimentally and a new model proposed to explain the data. The experiment consists of the measurement of water loss rate as a function of time for three 1 kg blocks of Southeastern New Mexico rock salt. Each block was heated for approximately three days with maximum temperatures ranging from 165 to 250/sup 0/C. The resulting data is qualitatively explained by a continuum model of Darcian flow of water vapor from a receding evaporation front. The model includes the prediction of thermal stresses which are calculated to crack the specimens during heater shutdown giving an anomalously high water loss spike in agreement with the data

Tensile properties of amorphous diamond films

The strength and modulus of amorphous diamond, a new material for surface micromachined MEMS and sensors, was tested in uniaxial tension by pulling laterally with a flat tipped diamond in a nanoindenter. Several sample designs were attempted. Of those, only the single layer specimen with a 1 by 2 {micro}m gage cross section and a fixed end rigidly attached to the substrate was successful. Tensile load was calculated by resolving the measured lateral and normal forces into the applied tensile force and frictional losses. Displacement was corrected for machine compliance using the differential stiffness method. Post-mortem examination of the samples was performed to document the failure mode. The load-displacement data from those samples that failed in the gage section was converted to stress-strain curves using carefully measured gage cross section dimensions. Mean fracture strength was found to be 8.5 {+-} 1.4 GPa and the modulus was 831 {+-} 94 GPa. Tensile results are compared to hardness and modulus measurements made using a nanoindenter

Characterization and error analysis of an N×N unfolding procedure applied to filtered, photoelectric x-ray detector arrays. II. Error analysis and generalization

A five-channel, filtered-x-ray-detector (XRD) array has been used to measure time-dependent, soft-x-ray flux emitted by z-pinch plasmas at the Z pulsed-power accelerator (Sandia National Laboratories, Albuquerque, New Mexico, USA). The preceding, companion paper [D. L. Fehl et al., Phys. Rev. ST Accel. Beams 13, 120402 (2010)PRABFM1098-4402] describes an algorithm for spectral reconstructions (unfolds) and spectrally integrated flux estimates from data obtained by this instrument. The unfolded spectrum S_{unfold}(E,t) is based on (N=5) first-order B-splines (histograms) in contiguous unfold bins j=1,…,N; the recovered x-ray flux F_{unfold}(t) is estimated as ∫S_{unfold}(E,t)dE, where E is x-ray energy and t is time. This paper adds two major improvements to the preceding unfold analysis: (a) Error analysis.—Both data noise and response-function uncertainties are propagated into S_{unfold}(E,t) and F_{unfold}(t). Noise factors ν are derived from simulations to quantify algorithm-induced changes in the noise-to-signal ratio (NSR) for S_{unfold} in each unfold bin j and for F_{unfold} (ν≡NSR_{output}/NSR_{input}): for S_{unfold}, 1≲ν_{j}≲30, an outcome that is strongly spectrally dependent; for F_{unfold}, 0.6≲ν_{F}≲1, a result that is less spectrally sensitive and corroborated independently. For nominal z-pinch experiments, the combined uncertainty (noise and calibrations) in F_{unfold}(t) at peak is estimated to be ∼15%. (b) Generalization of the unfold method.—Spectral sensitivities (called here passband functions) are constructed for S_{unfold} and F_{unfold}. Predicting how the unfold algorithm reconstructs arbitrary spectra is thereby reduced to quadratures. These tools allow one to understand and quantitatively predict algorithmic distortions (including negative artifacts), to identify potentially troublesome spectra, and to design more useful response functions

Characterization and error analysis of an N×N unfolding procedure applied to filtered, photoelectric x-ray detector arrays. I. Formulation and testing

An algorithm for spectral reconstructions (unfolds) and spectrally integrated flux estimates from data obtained by a five-channel, filtered x-ray-detector array (XRD) is described in detail and characterized. This diagnostic is a broad-channel spectrometer, used primarily to measure time-dependent soft x-ray flux emitted by z-pinch plasmas at the Z pulsed-power accelerator (Sandia National Laboratories, Albuquerque, New Mexico, USA), and serves as both a plasma probe and a gauge of accelerator performance. The unfold method, suitable for online analysis, arises naturally from general assumptions about the x-ray source and spectral properties of the channel responses; a priori constraints control the ill-posed nature of the inversion. The unfolded spectrum is not assumed to be Planckian. This study is divided into two consecutive papers. This paper considers three major issues: (a) Formulation of the unfold method.—The mathematical background, assumptions, and procedures leading to the algorithm are described: the spectral reconstruction S_{unfold}(E,t)—five histogram x-ray bins j over the x-ray interval, 137≤E≤2300  eV at each time step t—depends on the shape and overlap of the calibrated channel responses and on the maximum electrical power delivered to the plasma. The x-ray flux F_{unfold} is estimated as ∫S_{unfold}(E,t)dE. (b) Validation with simulations.—Tests of the unfold algorithm with known static and time-varying spectra are described. These spectra included—but were not limited to—Planckian spectra S_{bb}(E,T) (25≤T≤250  eV), from which noise-free channel data were simulated and unfolded. For Planckian simulations with 125≤T≤250  eV and typical responses, the binwise unfold values S_{j} and the corresponding binwise averages ⟨S_{bb}⟩_{j} agreed to ∼20%, except where S_{bb}≪max⁡{S_{bb}}. Occasionally, unfold values S_{j}≲0 (artifacts) were encountered. The algorithm recovered ≳90% of the x-ray flux over the wider range, 75≤T≤250  eV. For lower T, the test and unfolded spectra increasingly diverged as larger fractions of S_{bb}(E,T) fell below the detection threshold (∼137  eV) of the diagnostic. (c) Comparison with other analyses and diagnostics.—The results of the histogram algorithm are compared with other analyses, including a test with data acquired by the DANTE filtered-XRD array at the NOVA laser facility. Overall, the histogram algorithm is found to be most useful for x-ray flux estimates, as opposed to spectral details. The following companion paper [D. L. Fehl et al., Phys. Rev. ST Accel. Beams 13, 120403 (2010)PRABFM1098-4402] considers (a) uncertainties in S_{unfold} and F_{unfold} induced by both data noise and calibrational errors in the response functions; and (b) generalization of the algorithm to arbitrary spectra. These techniques apply to other diagnostics with analogous channel responses and supported by unfold algorithms of invertible matrix form