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BackgroundRecent breakthroughs in molecular biology and next generation sequencing technologies have led to the expenential growh of the sequence databases. Researchrs use BLAST for processing these sequences. However traditional software parallelization techniques (threads, message passing interface) applied in newer versios of BLAST are not adequate for processing these sequences in timely manner.MethodsA new method for array job parallelization has been developed which offers O(T) theoretical speed-up in comparison to multi-threading and MPI techniques. Here T is the number of array job tasks. (The number of CPUs that will be used to complete the job equals the product of T multiplied by the number of CPUs used by a single task.) The approach is based on segmentation of both input datasets to the BLAST process, combining partial solutions published earlier (Dhanker and Gupta, Int J Comput Sci Inf Technol_5:4818-4820, 2014), (Grant et al., Bioinformatics_18:765-766, 2002), (Mathog, Bioinformatics_19:1865-1866, 2003). It is accordingly referred to as a “dual segmentation” method. In order to implement the new method, the BLAST source code was modified to allow the researcher to pass to the program the number of records (effective number of sequences) in the original database. The team also developed methods to manage and consolidate the large number of partial results that get produced. Dual segmentation allows for massive parallelization, which lifts the scaling ceiling in exciting ways.ResultsBLAST jobs that hitherto failed or slogged inefficiently to completion now finish with speeds that characteristically reduce wallclock time from 27 days on 40 CPUs to a single day using 4104 tasks, each task utilizing eight CPUs and taking less than 7 minutes to complete.ConclusionsThe massive increase in the number of tasks when running an analysis job with dual segmentation reduces the size, scope and execution time of each task. Besides significant speed of completion, additional benefits include fine-grained checkpointing and increased flexibility of job submission. “Trickling in” a swarm of individual small tasks tempers competition for CPU time in the shared HPC environment, and jobs submitted during quiet periods can complete in extraordinarily short time frames. The smaller task size also allows the use of older and less powerful hardware. The CDRH workhorse cluster was commissioned in 2010, yet its eight-core CPUs with only 24GB RAM work well in 2017 for these dual segmentation jobs. Finally, these techniques are excitingly friendly to budget conscious scientific research organizations where probabilistic algorithms such as BLAST might discourage attempts at greater certainty because single runs represent a major resource drain. If a job that used to take 24 days can now be completed in less than an hour or on a space available basis (which is the case at CDRH), repeated runs for more exhaustive analyses can be usefully contemplated.

This effort demonstrates the development of a novel, graphene oxide nanoscale thermite composite with thermally tunable microwave ignitability. A model thermite system containing nanoscale aluminum and nanoscale iron(II) oxide in a stoichiometric ratio (30/70 wt %) was combined with sheets of graphene oxide (GO) or reduced graphene oxide (rGO) using an immiscible two-fluid sonication and tape casting process. The samples were microwave irradiated within a singlemode resonant microwave cavity to determine the microwave ignition delay. Neat thermites were found to ignite after 4.34 s of microwave illumination, whereas 30 wt % rGO thermite composite ignition delay was an order of magnitude shorter (0.43 s). For most samples (4 of 6 trials), it was found that application of a 30 wt % GO coating inhibits microwave ignition of the thermite. Thermal treatment of the GO thermite composite led to switching of thermites from unignitable to ignitable with microwave field application as short as 0.24 s due to GO reduction. Optimum heat treatment time and GO content are explored with SEM, DSC/TGA-MS, Raman, and XPS deconvolution. This effort demonstrates the use of GO and rGO addition to achieve thermally switchable microwave ignitability to electromagnetically shield or enhance nanoscale energetic ignition by microwave energy.

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Alkali metals are prevalent in coal combustion, biomass thermal conversion to fuels, and energetic material combustion, and have applications as dopants for combustion diagnostics and plasma-based combustion control. Recently, the dynamic control of propellant burning rate and pyrotechnic luminosity have been demonstrated through combined microwave field radiation and incorporation of alkali dopants. Understanding of the alkali distribution within the flame is essential to predicting field–flame interaction. However, the multiphase propellant combustion environment exhibits significant particle scattering, broadband emission background, and high optical density, which complicate optical measurements. Here, multiple two-photon laser-induced fluorescence (LIF) schemes for atomic sodium were compared in gas-phase flames and sodium-doped solid propellant combustion. For the two-photon Na LIF scheme, a rate equation model incorporating fluorescence, amplified spontaneous emission, and ionization shows good agreement with experimental characterization in a gas-phase flame. The technique was then extended to sodium-doped solid propellant flames, a multiphase combustion environment characterized by strong particle scattering. The 3s–3d two-photon excitation LIF achieved a better signal-to-noise ratio of ∼ 100 in the propellant flame and allowed imaging of gradients in the gas-phase sodium distribution at the burning surface.

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