Mass spectral similarity mapping applied to fentanyl analogs.

This manuscript outlines a straight-forward procedure for generating a map of similarity between spectra of a set. When applied to a reference set of spectra for Type I fentanyl analogs (molecules differing from fentanyl by a single modification), the map illuminates clustering that is applicable to automated structure assignment of unidentified molecules. An open-source software implementation that generates mass spectral similarity mappings of unknowns against a library of Type I fentanyl analog spectra is available at http://github.com/asm3-nist/FentanylClassifier.

Numerical optimization of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry: application to synthetic polymer molecular mass distribution measurement.

A novel approach is described for the selection of optimal instrument parameters that yield a mass spectrum which best replicates the molecular mass distribution of a synthetic polymer. The application of implicit filtering algorithms is shown to be a viable method to find the best instrument settings while simultaneously minimizing the total number of experiments that need to be performed. This includes considerations of when to halt the iterative optimization process at a point when statistically-significant gains can no longer be expected. An algorithm to determine the confidence intervals for each parameter is also given. Details on sample preparation and data analysis that ensure stability of the measurement over the time scale of the optimization experiments are provided. This work represents part of an effort to develop an absolute molecular mass distribution polymer Standard Reference Material.

Flow Control Through the Use of Topography.

In this work, optimal shaft shapes for flow in the annular space between a rotating shaft with axially-periodic radius and a fixed coaxial outer circular cylinder, are investigated. Axisymmetric steady flows in this geometry are determined by solving the full Navier-Stokes equations in the actual domain. A measure of the flow field, a weighted convex combination of the volume averaged square of the L 2-norm of the velocity and vorticity vectors, is employed. It has been demonstrated that boundary shape can be used to influence the characteristics of the flow field, such as its velocity component distribution, kinetic energy, or even vorticity. This ability to influence flow fields through boundary shape may be employed to improve microfluidic mixing or, possibly, to minimize shear in biological applications.

Simulation of an Austenite-Twinned-Martensite Interface.

Developing numerical methods for predicting microstructure in materials is a large and important research area. Two examples of material microstructures are Austenite and Martensite. Austenite is a microscopic phase with simple crystallographic structure while Martensite is one with a more complex structure. One important task in materials science is the development of numerical procedures which accurately predict microstructures in Martensite. In this paper we present a method for simulating material microstructure close to an Austenite-Martensite interface. The method combines a quasi-Newton optimization algorithm and a nonconforming finite element scheme that successfully minimizes an approximation to the total stored energy near the interface of interest. Preliminary results suggest that the minimizers of this energy functional located by the developed numerical algorithm appear to display the desired characteristics.

Global and Local Optimization Algorithms for Optimal Signal Set Design.

The problem of choosing an optimal signal set for non-Gaussian detection was reduced to a smooth inequality constrained mini-max nonlinear programming problem by Gockenbach and Kearsley. Here we consider the application of several optimization algorithms, both global and local, to this problem. The most promising results are obtained when special-purpose sequential quadratic programming (SQP) algorithms are embedded into stochastic global algorithms.