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A centrality measure based on the time of first returns rather than the number of steps is developed and applied to finding proton traps and access points to proton highways in the doped perovskite oxides: AZr 0.875 D 0.125 O 3 , where A is Ba or Sr and the dopant D is Y or Al. The high centrality region near the dopant is wider in the SrZrO 3 systems than the BaZrO 3 systems. In the aluminum-doped systems, a region of intermediate centrality (secondary region) is found in a plane away from the dopant. Kinetic Monte Carlo (kMC) trajectories show that this secondary region is an entry to fast conduction planes in the aluminum-doped systems in contrast to the highest centrality area near the dopant trap. The yttrium-doped systems do not show this secondary region because the fast conduction routes are in the same plane as the dopant and hence already in the high centrality trapped area. This centrality measure complements kMC by highlighting key areas in trajectories. The limiting activation barriers found via kMC are in very good agreement with experiments and related to the barriers to escape dopant traps. C 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License. [http://dx

Multivariate optical computing (MOC) is an instrumentation design concept for optically demultiplexing the spectroscopic signals in radiometric measurements. The advantages of optically demultiplexing are improved precision, optical throughput, improved reliability, and reduced cost of instrumentation. Conceptually, the instrument implements a multivariate regression vector whose dot product with the spectrum yields a single value related to a spectroscopically active physical property of interest. Instrumentation designs for implementing MOC are diverse, and there has been no systematic comparison of the performance of these designs. This report develops a general expression for comparing the precision of the different instrumentation designs of MOC. Additionally, an expression is given for the transition from low- to high-signal-limited performance of MOC instrumentation. These two general expressions are applied to the traditional multivariate analysis and five examples of MOC.

A new algorithm for the design of optical computing filters for chemical analysis, otherwise known as multivariate optical elements (MOEs), is described. The approach is based on the nonlinear optimization of the MOE layer thicknesses to minimize the standard error in sample prediction for the chemical species of interest using a modified version of the Gauss–Newton nonlinear optimization algorithm. The design algorithm can either be initialized with random layer thicknesses or with layer thicknesses derived from spectral matching of a multivariate principal component regression (PCR) vector for the constituent of interest. The algorithm has been successfully tested by using it to design various MOEs for the determination of Bismarck Brown dye in a binary mixture of Crystal Violet and Bismarck Brown.

Proton conduction is an important property for fuel cell electrolytes. The search for molecular details on proton transport is an ongoing quest. Here, we show that in hydrated yttrium doped barium zirconate using X-ray and neutron diffraction that protons tend to localize near the dopant yttrium as a conjugated superstructure. The proton jump time measured using quasi-elastic neutron scattering follows the Holstein-Samgin polaron model, revealing that proton hopping is weakly coupled to the high-frequency O-H stretching motion, but strongly coupled to low-frequency lattice phonons. The ratio of the proton polaron effective mass, m*, and the proton mass is m*/m = 2, when coupled to the Zr-O stretching mode, giving experimental evidence of proton pairing in perovskites, as a result of proton-phonon coupling. Possible pathways of a proton pair are provided through Nudge Elastic Band calculations. The pairing of protons, when jumping, is discussed in context of a cooperative protonic charge transport process.

An automated method for producing multivariate optical element (MOE) interference filters that are robust to errors in the reactive magnetron sputtering process is described. Reactive magnetron sputtering produces films of excellent thickness and uniformity. However, small changes in the thickness of individual layers can have severe adverse effects on the predictive ability of the MOE. Adaptive reoptimization of the filter design during the deposition process can maintain the predictive ability of the final filter by changing the thickness of the undeposited layers to compensate for the errors in deposition. The merit function used, the standard error of calibration, is fundamentally different from the standard spectrum matching. This new merit function allows large changes in the transmission spectrum of the filter to maintain performance.

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Marker compounds are needed to determine dietary compliance in free-living human study populations participating in dietary intervention trials for cancer research. Nine organosulfur marker compounds were detected and identified in an aged garlic extract. A convenient method that involves solvent extraction and gas chromatographic/mass spectrometric analysis was developed to quantify the organosulfur compounds in the garlic extract. Although the garlic extract proved to be unstable and the concentration of the organosulfur compounds varied with time, one analysis of the extract gave the following results: methyl disulfide (0.607 pglg), methyl trisulfide (0.181 pglg), allyl sulfide (2.02 pglg), allyl disulfide (0.784 pg/g), allyl trisuifide (0.795 pg/g), allyl methyl sulfide (1.64 pg/g), allyl methyl disulfide (0.411 pglg), allyl methyl trisulfide (0.695 pg/g), and ethyl 2-propenesulfinate (11.4 pglg).