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Direct Laser Sintering of Metals
The use of a directed laser bealn source to selectively sinter multiple layers of
binderless metal powder for the purposes of rapid prototyping is described. The
work in this paper is restricted to -325 mesh iron powder, which was sintered
using a C\V 50 W Nd:YAG laser to approximately 3.5% density. A subsequent
post-treatlnent was perfornled to achieve a fully dense saulple. It is envisioned
that such a system can be used to manufacture functional metallic prototypes
directly from CAD without part-specific tooling.Mechanical Engineerin
Automated Array Assembly Task In-depth Study of Silicon Wafer Surface Texturizing
Several aspects of silicon wafer surface texturizing were studied. A low cost cleaning method that utilizes recycled Freon in an ultrasonic vapor degreaser to remove organic and inorganic contaminants from the surface of silicon wafers as received from silicon suppliers was investigated. The use of clean dry air and high throughout wafer batch drying techniques was shown to lower the cost of wafer drying. A two stage texturizing process was examined for suitability in large scale production. Also, an in-depth gettering study with the two stage texturizing process was performed for the enhancement of solar cell efficiency, minimization of current versus voltage curve dispersion, and improvement in process reproducibility. The 10% efficiency improvement goal was exceeded for the near term implementation of flat plate photovoltaic cost reduction
Study of Resistive Micromegas in a Mixed Neutron and Photon Radiation Field
The Muon ATLAS Micromegas Activity (MAMMA) focuses on the development and
testing of large-area muon detectors based on the bulk-Micromegas technology.
These detectors are candidates for the upgrade of the ATLAS Muon System in view
of the luminosity upgrade of Large Hadron Collider at CERN (sLHC). They will
combine trigger and precision measurement capability in a single device. A
novel protection scheme using resistive strips above the readout electrode has
been developed. The response and sparking properties of resistive Micromegas
detectors were successfully tested in a mixed (neutron and gamma) high
radiation field supplied by the Tandem accelerator, at the N.C.S.R. Demokritos
in Athens. Monte-Carlo studies have been employed to study the effect of 5.5
MeV neutrons impinging on Micromegas detectors. The response of the Micromegas
detectors on the photons originating from the inevitable neutron inelastic
scattering on the surrounding materials of the experimental facility was also
studied
Chaotic quantum ratchets and filters with cold atoms in optical lattices: properties of Floquet states
Recently, cesium atoms in optical lattices subjected to cycles of
unequally-spaced pulses have been found to show interesting behavior: they
represent the first experimental demonstration of a Hamiltonian ratchet
mechanism, and they show strong variability of the Dynamical Localization
lengths as a function of initial momentum. The behavior differs qualitatively
from corresponding atomic systems pulsed with equal periods, which are a
textbook implementation of a well-studied quantum chaos paradigm, the quantum
delta-kicked particle (delta-QKP). We investigate here the properties of the
corresponding eigenstates (Floquet states) in the parameter regime of the new
experiments and compare them with those of the eigenstates of the delta-QKP at
similar kicking strengths. We show that, with the properties of the Floquet
states, we can shed light on the form of the observed ratchet current as well
as variations in the Dynamical Localization length.Comment: 9 pages, 9 figure
Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints
The inapplicability of amino acid covariation methods to small protein
families has limited their use for structural annotation of whole genomes.
Recently, deep learning has shown promise in allowing accurate residue-residue
contact prediction even for shallow sequence alignments. Here we introduce
DMPfold, which uses deep learning to predict inter-atomic distance bounds, the
main chain hydrogen bond network, and torsion angles, which it uses to build
models in an iterative fashion. DMPfold produces more accurate models than two
popular methods for a test set of CASP12 domains, and works just as well for
transmembrane proteins. Applied to all Pfam domains without known structures,
confident models for 25% of these so-called dark families were produced in
under a week on a small 200 core cluster. DMPfold provides models for 16% of
human proteome UniProt entries without structures, generates accurate models
with fewer than 100 sequences in some cases, and is freely available.Comment: JGG and SMK contributed equally to the wor
Constrained LQR Using Online Decomposition Techniques
This paper presents an algorithm to solve the infinite horizon constrained
linear quadratic regulator (CLQR) problem using operator splitting methods.
First, the CLQR problem is reformulated as a (finite-time) model predictive
control (MPC) problem without terminal constraints. Second, the MPC problem is
decomposed into smaller subproblems of fixed dimension independent of the
horizon length. Third, using the fast alternating minimization algorithm to
solve the subproblems, the horizon length is estimated online, by adding or
removing subproblems based on a periodic check on the state of the last
subproblem to determine whether it belongs to a given control invariant set. We
show that the estimated horizon length is bounded and that the control sequence
computed using the proposed algorithm is an optimal solution of the CLQR
problem. Compared to state-of-the-art algorithms proposed to solve the CLQR
problem, our design solves at each iteration only unconstrained least-squares
problems and simple gradient calculations. Furthermore, our technique allows
the horizon length to decrease online (a useful feature if the initial guess on
the horizon is too conservative). Numerical results on a planar system show the
potential of our algorithm.Comment: This technical report is an extended version of the paper titled
"Constrained LQR Using Online Decomposition Techniques" submitted to the 2016
Conference on Decision and Contro
Migration of latent fingermarks on non-porous surfaces:observation technique and nanoscale variations
Latent fingermark morphology was examined over a period of approximately two months. Variation in topography was observed with atomic force microscopy and the expansion of the fingermark occurred in the form of the development of an intermediate area surrounding the main fingermark ridge. On an example area of a fingermark on silicon, the intermediate region exists as a uniform 4nm thick deposit; on day 1 after deposition this region extends approximately 2µm from the edge of the main ridge deposit and expands to a maximum of ~ 4µm by day 23. Simultaneously the region breaks up, the integrity is compromised by day 16, and by day 61 the area resembles a series of interconnected islands, with coverage of approximately 60%. Observation of a similar immediate area and growth with time on surfaces such as Formica was possible by monitoring the mechanical characteristics of the fingermark and surfaces though phase contrast in tapping mode AFM. The presence of this area may affect fingermark development, for example affecting the gold distribution in vacuum metal deposition. Further study of time dependence and variation with donor may enable assessment of this area to be used to evaluate the age of fingermarks
Enhanced Cloud Disruption by Magnetic Field Interaction
We present results from the first three-dimensional numerical simulations of
moderately supersonic cloud motion through a tenuous, magnetized medium. We
show that the interaction of the cloud with a magnetic field perpendicular to
its motion has a great dynamical impact on the development of instabilities at
the cloud surface. Even for initially spherical clouds, magnetic field lines
become trapped in surface deformations and undergo stretching. The consequent
field amplification that occurs there and particularly its variation across the
cloud face then dramatically enhance the growth rate of Rayleigh-Taylor
unstable modes, hastening the cloud disruption.Comment: 4 pages, 2 figures, ApJ (Letter) in press. High resolution postscript
figures available at http://www.msi.umn.edu/Projects/twj/mhd3d
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