Lab Partnering Service Discovery
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Computer engineers have developed a new design to support construction of large computer systems that perform closer to their theoretical peak. This approach emphasizes scalable throughput rather than attempting to tailor systems around the highest performing accelerators, and allows selection of individual components that maximize performance against energy draw or cost. The design makes use of commodity components that are modest in computing power and energy consumption.
Most supercomputer applications require some non-local communication. As a result, the relatively high-latency and low-bandwidth interconnection network becomes a limiting factor on the machine’s efficiency. In addition, designers are extending the peak performance of supercomputers by adding multi-core accelerators such as Cell processors or Graphics Processing Units (GPUs). This introduces another high-latency and low-bandwidth bottleneck, at the point where data moves into and out of the accelerator, as well as another dimension of complexity in software.
These factors limit the kinds of applications that can run effectively on supercomputers, and increase the cost of developing or porting those applications. Algorithms that require intercommunication result in underutilized components, wasting energy and the potential of the machine. Furthermore, there appear to be some problems which perform poorly on these architectures, regardless of optimization.
Los Alamos National Laboratory (LANL) researchers have developed a new design to support construction of large machines, allowing the machines to perform closer to their theoretical peak. This approach emphasizes scalable throughput rather than attempting to tailor machines around the highest performing accelerators, and allows selection of individual components that maximize performance against energy draw or cost. The design makes use of commodity components that are modest in computing power and energy consumption.
The LANL hardware is being co-designed along with a powerful and expressive high-level programming language, adapted from a well-studied body of research languages. It is expected that applications written in this language will require no other system-level or low-level programming in order to run efficiently, but diagnostic feedback could allow selection of more efficient idioms.
LANL’s design supports the data-intensive applications currently encountered in scientific computing, while opening the door to new levels of capability for communication-intensive and throughput-intensive applications such as molecular dynamics and signal correlation. In addition, researchers expect the LANL design can support transparent fail-over, allowing failed nodes to be replaced on-the-fly without stopping ongoing computations.
The scientists developing this capability welcome the opportunity to unite with industry and advance its potential.
Cost is a critical issue limiting widespread adoption of photovoltaic (PV) technology. Consequently, organic semiconductors represent an attractive direction for PV development, as they can be made into devices at very low cost by means of continuous processes such as solution printing and roll processing. In addition, organic semiconductors have unique attributes distinct from inorganic semiconductors such as strong infrared absorption with visible transparency, low weight, and weak intrinsic radiation interactions. However, the comparatively low efficiency and reliability of existing organic photovoltaic (OPV) technologies precludes their use as a surrogate for more expensive inorganic alternatives in a variety of applications.
For over a decade, Los Alamos National Laboratory (LANL) has worked with organic electronic materials and devices such as organic light-emitting diodes (OLEDs) using a theory-fabrication-measurement approach. LANL’s research produced a better understanding of how organic light emitting diodes work, particularly with regard to the processes controlling charge injection and transport; these same capabilities are now being applied to OPVs.
LANL researchers recognize the obstacles to high OPV efficiency and are focused on developing a fundamental understanding of organic semiconductor device physics with regard to interface, band structure, charge transport, and exciton diffusion in order to increase the effectiveness and reliability of OPVs. The ultimate objective is to optimize OPV device design across a number of key areas while preserving the low-cost fabrication schemes that make them an economically practicable alternative to inorganic photovoltaic devices.
To support this effort, the Laboratory has a number of unique capabilities designed specifically to meet the needs of current organic semiconductor research, development, processing, and fabrication:
- Argon glove boxes (~1 ppm 02, H2O) with integrated deposition chambers of various types (e.g., sputtering, e-beam, thermal, and Radak evaporators)
- SEM, EDX, XRD, XRF, and optical microscopy
- I-V, C-V, impedance, electroabsorption, EL, PL, spectroscopic ellipsometry
- General cw and time resolved (ns) optoelectronic measurements
- Sample cryostats from liquid He to ~500 C
Plasmonically-active surfaces developed by this group could potentially increase optical absorption and photocurrent generation over a broad range of visible wavelengths in photovoltaic devices, thereby increasing energy conversion efficiency. When integrated with traditional photovoltaic cell designs, these enhanced surfaces have the potential to reduce manufacturing costs by enabling the use of thinner PV materials. In addition, reducing the required thickness of PV materials will expand the number of materials that are suitable for photovoltaic devices. LANL is seeking partnership opportunities to utilize these capabilities and further advance this technology area.
An important component on the path to reducing the cost of photovoltaic (PV) cells is to improve energy efficiency with less photoactive material. An attractive possibility in this respect would be to use surface plasmons for initial light capture. Surface plasmons are oscillations of conducting electrons that trap optical waves near their surface. Los Alamos National Laboratory (LANL) investigators aim to integrate traditional PV designs with novel surfaces designed to create plasmonic activity at the PN junction of the cell. Plasmonically-enhanced photovoltaic cells have the potential to enhance optical absorption and enable the use of thinner materials for lower-cost manufacturing of solar panels.
LANL researchers are leveraging the following unique Laboratory capabilities to develop enhanced surfaces and advanced nanoparticle architectures to produce surface plasmons in photovoltaic devices:
- Robust plasmonic testing platforms
- Modeling and testing of plasmonic enhancement at surface versus interface
- Fabrication-free plasmonic substrates through polymer-directed electroless deposition
- Seed-mediated reduction of gold nanoshells
- Field-assisted particle assembly
- Acid-directed synthesis of silver particles
- Laser-structured silicon surfaces
The scientists developing this capability welcome the opportunity to unite with industry and advance its potential.
As the solar industry works to build the infrastructure necessary to make electricity from photovoltaic (PV) technologies cost-competitive with grid electricity by 2015, many technical challenges emerge along the way. Los Alamos National Laboratory (LANL) researchers are working to anticipate and solve these challenges by modeling multi-scale, light-harvesting processes in nanomaterials.
The design of efficient PV cells necessitates an optimization of the device’s energy band structure to the solar spectrum; this, in turn, calls for the engineering of materials with controlled energy band structures. The energy band structure of a PV device can be determined by a myriad of aspects including the composition, surface chemistry, and lattice strain effects of the material itself. To support this effort, LANL researchers are using theoretical modeling to study a variety of effects including:
- Modeling of new materials for PV applications
- Impacts of amorphous optically-active conjugated polymers on light-harvesting properties
- Effects of ligands on semiconductor quantum dot (QD) functionality
- Contributions of direct photogeneration and population relaxation on the total quantum efficiency of carrier multiplication in lead selenide QDs
- Effects of plasmonically-enhanced nanoparticles on energy transport
- Impact of carrier transport phenomena on photovoltaic efficiency
- Effects of conformational disorder in bulk polymeric materials on electronic transport
The ultimate goal of this research is to determine the optimal composition of semiconductor structures in order to engineer materials with the electronic and optical properties necessary to increase power-conversion efficiency in solar cells.
Laser-Weave is a new, high-tech approach to synthesizing strong, flexible, highly-functionalized inorganic fibers in arbitrarily complex patterns. The technology provides a simple, low-cost route to synthesizing fine, refractory-metal fibers and their compounds, as well as improving their underlying fiber strength, elasticity, and toughness. Laser
Laser-Weave is a new, high-tech approach to synthesizing strong, flexible, highly-functionalized inorganic fibers in arbitrarily complex patterns. Laser-Weave provides a simple, low-cost route to synthesizing fine, refractory-metal fibers and their compounds, as well as improving their underlying fiber strength, elasticity, and toughness. Laser-Weave uses lasers with chemical vapor deposition to grow inorganic fibers currently exceeding 13 cm/s. Laser-Weave combines all the advantages of a rapid prototyping technology with advanced metallurgy and textile production methods.
Laser-Weave is the first process that can produce flexible, multifunctional refractory materials in a one-step process. Using lasers to grow inorganic fibers, Laser-Weave can assemble fibers in any configuration needed. Laser-Weave provides manufacturers with the ability to grow fibers in three dimensions and braid these refractory and normally brittle fibers into ropes or cords or weave them into cloth for use in fire protection. The fibers are grown:
- Into their nominal shapes within the cable or cloth structures, rather than bent to fit within a braided or woven shape;
- As fully dense materials, without defects, voids, or cracks that can compromise the entire structure;
- With lower temperatures;
- Without the need to separate elements in the alloys;
- Rapidly and with complete flexibility of braiding and weaving patterns;
- With a process that permits junctions to be formed between fibers;
- Using the hardest refractory compounds and without the use of seed wires or fibers; and
- Into very fine fibers down to submicron dimensions.
Metal aminoboranes of the formula M(NH.sub.2BH.sub.3).sub.n have been synthesized. Metal aminoboranes are hydrogen storage materials. Metal aminoboranes are also precursors for synthesizing other metal aminoboranes. Metal aminoboranes can be dehydrogenated to form hydrogen and a reaction product. The reaction product can react with hydrogen to form a hydrogen storage material. Metal aminoboranes can be included in a kit.
A template article including a base substrate including: (i) a base material selected from the group consisting of polycrystalline substrates and amorphous substrates, and (ii) at least one layer of a differing material upon the surface of the base material; and, a buffer material layer upon the base substrate, the buffer material layer characterized by: (a) low chemical reactivity with the base substrate, (b) stability at temperatures up to at least about 800.degree. C. under low vacuum conditions, and (c) a lattice crystal structure adapted for subsequent deposition of a semiconductor material; is provided, together with a semiconductor article including a base substrate including: (i) a base material selected from the group consisting of polycrystalline substrates and amorphous substrates, and (ii) at least one layer of a differing material upon the surface of the base material; and, a buffer material layer upon the base substrate, the buffer material layer characterized by: (a) low chemical reactivity with the base substrate, (b) stability at temperatures up to at least about 800.degree. C. under low vacuum conditions, and (c) a lattice crystal structure adapted for subsequent deposition of a semiconductor material, and, a top-layer of semiconductor material upon the buffer material layer.
See Attached Patent
Scientists at Los Alamos National Laboratory (LANL) have developed an electrochemical carbon monoxide (CO) sensor that is more reliable and reproducible than any other CO sensor on the market today. The patented method for producing the sensor ensures reproducibility and reduces the need for calibration of every sensor coming off the production line.
Inaccurate CO sensors on the market today result in alarms failing to go off, or alarms going off when CO is not present. Both can result in substantial costs to a company. LANL’s CO sensor offers a solution to this problem by providing a reliable CO sensor.
Scientists at Los Alamos National Laboratory (LANL) have developed an innovative method for gas sensor manufacturing using a thin film deposition. The thin film requires very little material and can be applied in high throughput applications.
The gas sensor market is highly competitive. LANL’s thin film deposition method for manufacturing gas sensors decreases manufacturing time and costs, while increasing consistency and quality. With the use of thin film deposition, gas sensor manufacturers can offer a higher quality product at a very competitive price.
Researchers at the Los Alamos National Laboratory Intelligent Wind Turbine Program are developing a multi-physics modeling approach for the analysis of wind turbines in the presence of realistic wind loading.
Researchers at the Los Alamos National Laboratory (LANL) Intelligent Wind Turbine Program are developing a multi-physics modeling approach for the analysis of wind turbines in the presence of realistic wind loading. This first-of-a-kind simulation tool will decipher connections between wind events and compromising/damaging load configurations, providing a synthetic environment for preliminary evaluation of changes in operating loads and for testing control algorithms. This work is expected to provide key design and operational guidance for defining turbine design criteria and to enhance wind farm energy production.
This capability is being developed to fill the wind industry’s need for a fast and reliable approach to optimize wind turbine operations in real world conditions. Wind turbines operate with too many variables to explore that may, and probably do, affect wind turbine performance in the short and long term. The potential cost is manifested in many ways, including 1) extensive R&D to understand how to increase performance and mitigate turbine damage in the field and 2) maintenance miscalculations that compromise optimal energy production in multiple operational scenarios due to lack of on-location guidance.
This new technology will integrate multi-scale monitoring of both local and global conditions with a validated, predictive simulation capability, advanced diagnostics, and data extraction and interrogation, with the goal of both creating system state awareness for production enhancement and damage mitigation in the field and accelerating the pace of significant discoveries to optimize current design parameters in multiple field scenarios.
Successful implementation of this multi-scale monitoring will result in a system capable of predicting the behavior of damaged components in wind turbines and its consequences on system performance. Developing a validated, predictive capability to support the design and analysis of intelligent wind turbines will require integration on an unprecedented scale (See HIGRAD/WindBlade and Wind Turbine Structural Health Monitoring). Elements to be integrated include simulations, finite element models, adjoint optimization, resulting data products, and uncertainty inherent in field experiments. The decision-making framework will articulate a strategy to manage these simulations, experiments, and results via a combination of prognostics and exploratory and explanatory visual analysis.
Polymer-Assisted Deposition (PAD) works with a wide range of metal-oxide and metal nitride films. Simply put, “problematic” metal oxides and metal nitrides are not a problem for PAD. PAD can be used for the high-quality deposition of metal oxides and metal nitrides for the successful production of both simple and complex metal-oxide films such as TiO2, ITO, SrTiO3, TiN, AlN, and GaN. In addition, nitrides, sulfides, and carbides could potentially be deposited using this process.
Metal-oxide and metal-nitride films are essential parts of semiconductors. These types of films can also have benefits as coatings that are resistant to a number of environmental effects. Unfortunately, growing metal-oxide and metal-nitride films requires large, expensive equipment. Capital costs for a single metal-oxide or metal-nitride film deposition machine can run from $500,000 to $3.5 million, and only very small films can be grown using traditional methods. We have developed a simple process for using polymers to grow large quantities of high-quality metal-oxide and metal-nitride films. Rather than spray a precise amount of material in a high vacuum (which requires the expensive equipment), we solubilize the metal oxides and metal nitrides in inexpensive polymers, then bake off the polymer, leaving a uniform thin film of metal oxide deposited on
the substrate. Our process is equivalent in quality to industry-standard chemical vapor deposition, yet much cheaper. Polymer-assisted deposition (PAD) is cost effective and can be used to cover much larger areas of substrates with metal-oxides and metal nitrides. PAD is also superior to sol-gel methods because PAD can be used with many more metal oxides and metal nitrides; the thin film is uniform and not susceptible to cracking; and because the metal oxide stoichiometry can be precisely controlled. Currently, the semiconductor industry spends $990 million annually on vacuum-based thin-film deposition machines. Another $260 million are spent for thin-film deposition machines outside the semiconductor industry. Thus, the total addressable market is roughly $1.25 billion. PAD could form the core of a business based on either a pure licensing model or a direct-sales-to-industry model.