Sandia National Laboratories

About: Sandia National Laboratories is a facility organization based out in Livermore, California, United States. It is known for research contribution in the topics: Laser & Combustion. The organization has 21501 authors who have published 46724 publications receiving 1484388 citations. The organization is also known as: SNL & Sandia National Labs.

The fall, recovery, orbit, and composition of the Tagish Lake meteorite: a new type of carbonaceous chondrite.

Abstract: The preatmospheric mass of the Tagish Lake meteoroid was about 200,000 kilograms. Its calculated orbit indicates affinity to the Apollo asteroids with a semimajor axis in the middle of the asteroid belt, consistent with a linkage to low-albedo C, D, and P type asteroids. The mineralogy, oxygen isotope, and bulk chemical composition of recovered samples of the Tagish Lake meteorite are intermediate between CM and CI meteorites. These data suggest that the Tagish Lake meteorite may be one of the most primitive solar system materials yet studied.

Cellular automata method for phase unwrapping

Abstract: Research into two-dimensional phase unwrapping has uncovered interesting and troublesome inconsistencies that cause path-dependent results. Cellular automata, which are simple, discrete mathematical systems, offered promise of computation in a nondirectional, parallel manner. A cellular automaton was discovered that can unwrap consistent phase data in n dimensions in a path-independent manner and can automatically accommodate noise-induced (pointlike) inconsistencies and arbitrary boundary conditions (region partitioning). For data with regional (nonpointlike) inconsistencies, no phase-unwrapping algorithm will converge, including the cellular-automata approach. However, the automata method permits more simple visualization of the regional inconsistencies. Examples of its behavior on one- and two-dimensional data are presented.

Three-dimensional direct numerical simulation of a turbulent lifted hydrogen jet flame in heated coflow: a chemical explosive mode analysis

Abstract: A chemical explosive mode analysis (CEMA) was developed as a new diagnostic to identify flame and ignition structure in complex flows. CEMA was then used to analyse the near-field structure of the stabilization region of a turbulent lifted hydrogen–air slot jet flame in a heated air coflow computed with three-dimensional direct numerical simulation. The simulation was performed with a detailed hydrogen–air mechanism and mixture-averaged transport properties at a jet Reynolds number of 11000 with over 900 million grid points. Explosive chemical modes and their characteristic time scales, as well as the species involved, were identified from the Jacobian matrix of the chemical source terms for species and temperature. An explosion index was defined for explosive modes, indicating the contribution of species and temperature in the explosion process. Radical and thermal runaway can consequently be distinguished. CEMA of the lifted flame shows the existence of two premixed flame fronts, which are difficult to detect with conventional methods. The upstream fork preceding the two flame fronts thereby identifies the stabilization point. A Damkohler number was defined based on the time scale of the chemical explosive mode and the local instantaneous scalar dissipation rate to highlight the role of auto-ignition in affecting the stabilization points in the lifted jet flame.

All‐Solid‐State Synaptic Transistor with Ultralow Conductance for Neuromorphic Computing

Abstract: Electronic synaptic devices are important building blocks for neuromorphic computational systems that can go beyond the constraints of von Neumann architecture. Although two-terminal memristive devices are demonstrated to be possible candidates, they suffer from several shortcomings related to the filament formation mechanism including nonlinear switching, write noise, and high device conductance, all of which limit the accuracy and energy efficiency. Electrochemical three-terminal transistors, in which the channel conductance can be tuned without filament formation provide an alternative platform for synaptic electronics. Here, an all-solid-state electrochemical transistor made with Li ion–based solid dielectric and 2D α-phase molybdenum oxide (α-MoO3) nanosheets as the channel is demonstrated. These devices achieve nonvolatile conductance modulation in an ultralow conductance regime (<75 nS) by reversible intercalation of Li ions into the α-MoO3 lattice. Based on this operating mechanism, the essential functionalities of synapses, such as shortand long-term synaptic plasticity and bidirectional near-linear analog weight update are demonstrated. Simulations using the handwritten digit data sets demonstrate high recognition accuracy (94.1%) of the synaptic transistor arrays. These results provide an insight into the application of 2D oxides for large-scale, energy-efficient neuromorphic computing networks.