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