The other, since 1952, is Lawrence Livermore National Laboratory. LANL is a United States Department of Energy (DOE) national laboratory, managed and operated by Los Alamos National Security (LANS), located in Los Alamos, New Mexico. The laboratory is one of the largest science and technology institutions in the world. It conducts multidisciplinary research in fields such as national security, space exploration, renewable energy, medicine, nanotechnology, and supercomputing.
LANL is the largest institution and the largest employer in northern New Mexico, with approximately 9,000 direct employees and around 650 contractor personnel.
Additionally, there are roughly 120 DOE employees stationed at the laboratory to provide federal oversight of LANL’s work and operations. Approximately one-third of the laboratory’s technical staff members are physicists, one quarter are engineers, one-sixth are chemists and materials scientists, and the remainder work in mathematics and computational science, biology, geoscience, and other disciplines.
Professional scientists and students also come to Los Alamos as visitors to participate in scientific projects. The staff collaborates with universities and industry in both basic and applied research to develop resources for the future. The annual budget is approximately US$2.2 billion.
Los Alamos National Laboratory research articles from Innovation Toronto
- Biosurveillance Gateway Supports Centralized Global Disease Response – January 30, 2015
- Secure computing for the ‘Everyman’ – September 6, 2014
- Photovoltaic solar-panel windows could be next for your house – April 15, 2014
- Significant progress toward creating ‘benchtop human’ reported
- Los Alamos catalyst could jumpstart e-cars, green energy
- Nanoscale optical switch breaks miniaturization barrier
- Your next fridge could keep cold more efficiently using magnets | refrigeration technology using magnets
- Fusion, Anyone?
- Quantum cryptography put to work for electric grid security
- Researchers test novel power system for space travel
- How to detect smuggled uranium and plutonium using muons
- Hydrogen Storage Gets New Hope
- New transparent, light-harvesting material could lead to power generating windows
- New materials for renewable energy
- Safer Nuclear Reactors With Self-Healing Nanocrystalline Materials
- Defusing the Methane Greenhouse Time Bomb
A Los Alamos National Laboratory research team demonstrates an important step in taking quantum dot, solar-powered windows from the laboratory to the construction site.
In a paper this week for the journal Nature Energy, a Los Alamos National Laboratory research team demonstrates an important step in taking quantum dot, solar-powered windows from the laboratory to the construction site by proving that the technology can be scaled up from palm-sized demonstration models to windows large enough to put in and power a building.
“We are developing solar concentrators that will harvest sunlight from building windows and turn it into electricity, using quantum-dot based luminescent solar concentrators,” said lead scientist Victor Klimov. Klimov leads the Los Alamos Center for Advanced Solar Photophysics (CASP).
Luminescent solar concentrators (LSCs) are light-management devices that can serve as large-area sunlight collectors for photovoltaic cells. An LSC consists of a slab of transparent glass or plastic impregnated or coated with highly emissive fluorophores. After absorbing solar light shining onto a larger-area face of the slab, LSC fluorophores re-emit photons at a lower energy and these photons are guided by total internal reflection to the device edges where they are collected by photovoltaic cells.
At Los Alamos, researchers expand the options for energy production while minimizing the impact on the environment, supporting the Laboratory mission to strengthen energy security for the nation.
In the Nature Energy paper, the team reports on large LSC windows created using the “doctor-blade” technique for depositing thin layers of a dot/polymer composite on top of commercial large-area glass slabs. The “doctor-blade” technique comes from the world of printing and uses a blade to wipe excess liquid material such as ink from a surface, leaving a thin, highly uniform film behind. “The quantum dots used in LSC devices have been specially designed for the optimal performance as LSC fluorophores and to exhibit good compatibility with the polymer material that holds them on the surface of the window,” Klimov noted.
LSCs use colloidal quantum dots to collect light because they have properties such as widely tunable absorption and emission spectra, nearly 100 percent emission efficiencies, and high photostability (they don’t break down in sunlight).
If the cost of an LSC is much lower than that of a photovoltaic cell of comparable surface area and the LSC efficiency is sufficiently high, then it is possible to considerably reduce the cost of producing solar electricity, Klimov said. “Semitransparent LSCs can also enable new types of devices such as solar or photovoltaic windows that could turn presently passive building facades into power generation units.”
The quantum dots used in this study are semiconductor spheres with a core of one material and a shell of another. Their absorption and emission spectra can be tuned almost independently by varying the size and/or composition of the core and the shell. This allows the emission spectrum to be tuned by the parameters of the dot’s core to below the onset of strong optical absorption, which is itself tuned by the parameters of the dot’s shell. As a result, loss of light due to self-absorption is greatly reduced. “This tunability is the key property of these specially designed quantum dots that allows for record-size, high-performance LSC devices,” Klimov said.
Researchers apply adaptive-design strategy to reveal targeted properties in shape-memory alloy
Researchers recently demonstrated how an informatics-based adaptive design strategy, tightly coupled to experiments, can accelerate the discovery of new materials with targeted properties, according to a recent paper published in Nature Communications.
“What we’ve done is show that, starting with a relatively small data set of well-controlled experiments, it is possible to iteratively guide subsequent experiments toward finding the material with the desired target,” said Turab Lookman, a physicist and materials scientist in the Physics of Condensed Matter and Complex Systems group at Los Alamos National Laboratory. Lookman is the principal investigator of the research project.
“Finding new materials has traditionally been guided by intuition and trial and error,” said Lookman.”But with increasing chemical complexity, the combination possibilities become too large for trial-and-error approaches to be practical.”
To address this, Lookman, along with his colleagues at Los Alamos and the State Key Laboratory for Mechanical Behavior of Materials in China, employed machine learning to speed up the process. It worked. They developed a framework that uses uncertainties to iteratively guide the next experiments to be performed in search of a shape-memory alloy with very low thermal hysteresis (or dissipation). Such alloys are critical for improving fatigue life in engineering applications.
“The goal is to cut in half the time and cost of bringing materials to market,” said Lookman. “What we have demonstrated is a data-driven framework built on the foundations of machine learning and design that can lead to discovering new materials with targeted properties much faster than before.” The work made use of Los Alamos’ high-performance supercomputing resources.