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  • richardmitnick 3:18 pm on April 14, 2018 Permalink | Reply
    Tags: , , , , SLAC Labs,   

    From SLAC: “Scientists Use Machine Learning to Speed Discovery of Metallic Glass” 


    SLAC Lab

    April 13, 2018
    Glennda Chui

    1
    Fang Ren, who developed algorithms to analyze data on the fly while a postdoctoral scholar at SLAC, at a Stanford Synchrotron Radiation Lightsource beamline where the system has been put to use. (Dawn Harmer/SLAC National Accelerator Laboratory)

    SLAC and its collaborators are transforming the way new materials are discovered. In a new report, they combine artificial intelligence and accelerated experiments to discover potential alternatives to steel in a fraction of the time.

    Blend two or three metals together and you get an alloy that usually looks and acts like a metal, with its atoms arranged in rigid geometric patterns.

    But once in a while, under just the right conditions, you get something entirely new: a futuristic alloy called metallic glass that’s amorphous, with its atoms arranged every which way, much like the atoms of the glass in a window. Its glassy nature makes it stronger and lighter than today’s best steel, plus it stands up better to corrosion and wear.

    Even though metallic glass shows a lot of promise as a protective coating and alternative to steel, only a few thousand of the millions of possible combinations of ingredients have been evaluated over the past 50 years, and only a handful developed to the point that they may become useful.

    Now a group led by scientists at the Department of Energy’s SLAC National Accelerator Laboratory, the National Institute of Standards and Technology (NIST) and Northwestern University has reported a shortcut for discovering and improving metallic glass – and, by extension, other elusive materials – at a fraction of the time and cost.

    The research group took advantage of a system at SLAC’s Stanford Synchrotron Radiation Lightsource (SSRL) that combines machine learning – a form of artificial intelligence where computer algorithms glean knowledge from enormous amounts of data – with experiments that quickly make and screen hundreds of sample materials at a time.

    SLAC/SSRL

    This allowed the team to discover three new blends of ingredients that form metallic glass, and to do this 200 times faster than it could be done before, they reported today in Science Advances.

    2
    (Yvonne Tang/SLAC National Accelerator Laboratory)

    “It typically takes a decade or two to get a material from discovery to commercial use,” said Northwestern Professor Chris Wolverton, an early pioneer in using computation and AI to predict new materials and a co-author of the paper. “This is a big step in trying to squeeze that time down. You could start out with nothing more than a list of properties you want in a material and, using AI, quickly narrow the huge field of potential materials to a few good candidates.”

    The ultimate goal, he said, is to get to the point where a scientist could scan hundreds of sample materials, get almost immediate feedback from machine learning models and have another set of samples ready to test the next day – or even within the hour.

    Over the past half century, scientists have investigated about 6,000 combinations of ingredients that form metallic glass, added paper co-author Apurva Mehta, a staff scientist at SSRL: “We were able to make and screen 20,000 in a single year.”

    Just Getting Started

    While other groups have used machine learning to come up with predictions about where different kinds of metallic glass can be found, Mehta said, “The unique thing we have done is to rapidly verify our predictions with experimental measurements and then repeatedly cycle the results back into the next round of machine learning and experiments.”

    There’s plenty of room to make the process even speedier, he added, and eventually automate it to take people out of the loop altogether so scientists can concentrate on other aspects of their work that require human intuition and creativity. “This will have an impact not just on synchrotron users, but on the whole materials science and chemistry community,” Mehta said.

    The team said the method will be useful in all kinds of experiments, especially in searches for materials like metallic glass and catalysts whose performance is strongly influenced by the way they’re manufactured, and those where scientists don’t have theories to guide their search. With machine learning, no previous understanding is needed. The algorithms make connections and draw conclusions on their own, and this can steer research in unexpected directions.

    “One of the more exciting aspects of this is that we can make predictions so quickly and turn experiments around so rapidly that we can afford to investigate materials that don’t follow our normal rules of thumb about whether a material will form a glass or not,” said paper co-author Jason Hattrick-Simpers, a materials research engineer at NIST. “AI is going to shift the landscape of how materials science is done, and this is the first step.”

    Strength in Numbers

    The paper is the first scientific result associated with a DOE-funded pilot project where SLAC is working with a Silicon Valley AI company, Citrine Informatics, to transform the way new materials are discovered and make the tools for doing that available to scientists everywhere.

    Founded by former graduate students from Northwestern and Stanford University, Citrine has created a materials science data platform where data that had been locked away in published papers, spreadsheets and lab notebooks is stored in a consistent format so it can be analyzed with AI specifically designed for materials.

    “We want to take materials and chemical data and use them effectively to design new materials and optimize manufacturing,” said Greg Mulholland, founder and CEO of the company. “This is the power of artificial intelligence: As scientists generate more data, it learns alongside them, bringing hidden trends to the surface and allowing scientists to identify high-performance materials much faster and more effectively than relying on traditional, purely human-driven materials development.”

    Until recently, thinking up, making and assessing new materials was painfully slow. For instance, the authors of the metallic glass paper calculated that even if you could cook up and examine five potential types of metallic glass a day, every day of the year, it would take more than a thousand years to plow through every possible combination of metals. When they do discover a metallic glass, researchers struggle to overcome problems that hold these materials back. Some have toxic or expensive ingredients, and all of them share glass’s brittle, shatter-prone nature.

    Over the past decade, scientists at SSRL and elsewhere have developed ways to automate experiments so they can create and study more novel materials in less time. Today, some SSRL users can get a preliminary analysis of their data almost as soon as it comes out with AI software developed by SSRL in conjunction with Citrine and the CAMERA project at DOE’s Lawrence Berkeley National Laboratory.

    “With these automated systems we can analyze more than 2,000 samples per day,” said Fang Ren, the paper’s lead author, who developed algorithms to analyze data on the fly and coordinated their integration into the system while a postdoctoral scholar at SLAC.

    Experimenting with Data

    In the metallic glass study, the research team investigated thousands of alloys that each contain three cheap, nontoxic metals.

    They started with a trove of materials data dating back more than 50 years, including the results of 6,000 experiments that searched for metallic glass. The team combed through the data with advanced machine learning algorithms developed by Wolverton and graduate student Logan Ward at Northwestern.

    Based on what the algorithms learned in this first round, the scientists crafted two sets of sample alloys using two different methods, allowing them to test how manufacturing methods affect whether an alloy morphs into a glass.

    Both sets of alloys were scanned by an SSRL X-ray beam, the data fed into the Citrine database, and new machine learning results generated, which were used to prepare new samples that underwent another round of scanning and machine learning.

    By the experiment’s third and final round, Mehta said, the group’s success rate for finding metallic glass had increased from one out of 300 or 400 samples tested to one out of two or three samples tested. The metallic glass samples they identified represented three different combinations of ingredients, two of which had never been used to make metallic glass before.

    See the full article here .

    Please help promote STEM in your local schools.

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    SLAC Campus
    SLAC is a multi-program laboratory exploring frontier questions in photon science, astrophysics, particle physics and accelerator research. Located in Menlo Park, California, SLAC is operated by Stanford University for the DOE’s Office of Science.

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  • richardmitnick 7:51 pm on October 16, 2017 Permalink | Reply
    Tags: Astronomers proposed the existence of neutron stars in 1934, , , , , , , , , , Neutron stars have some of the strongest gravity you’ll find – black holes have the strongest, SLAC Labs,   

    From Stanford: “Stanford experts on LIGO’s binary neutron star milestone” 

    Stanford University Name
    Stanford University

    October 16, 2017
    Taylor Kubota
    (650) 724-7707
    tkubota@stanford.edu

    On August 17, 2017, the two detectors of Advanced LIGO, along with VIRGO, zeroed in on what appeared to be gravitational waves emanating from a pair of neutron stars spinning together – a long-held goal for the LIGO team.


    VIRGO Gravitational Wave interferometer, near Pisa, Italy

    Caltech/MIT Advanced aLigo Hanford, WA, USA installation


    Caltech/MIT Advanced aLigo detector installation Livingston, LA, USA

    Cornell SXS, the Simulating eXtreme Spacetimes (SXS) project

    Gravitational waves. Credit: MPI for Gravitational Physics/W.Benger-Zib

    ESA/eLISA the future of gravitational wave research

    1
    Skymap showing how adding Virgo to LIGO helps in reducing the size of the source-likely region in the sky. (Credit: Giuseppe Greco (Virgo Urbino group)

    An alert went out to collaborators worldwide and within hours some 70 instruments turned their sites on the location a mere 310 million light-years away.

    2
    Artist’s rendering of two merging neutron stars. The rippling space-time grid represents gravitational waves that travel out from the collision, while the narrow beams show the bursts of gamma rays that are shot out just seconds after the gravitational waves. Swirling clouds of material ejected from the merging stars glow with visible and other wavelengths of light. (Image credit: NSF/LIGO/Sonoma State University/A. Simonnet)

    Their combined observations, spanning the electromagnetic spectrum, confirm some of what physicists had theorized about this type of event and also open up new areas of research. Thousands of scientists contributed to this accomplishment, including many at Stanford University, and published the initial findings Oct. 16 in Physical Review Letters and The Astrophysical Journal Letters.

    [For science papers, see https://sciencesprings.wordpress.com/2017/10/16/from-hubble-nasa-missions-catch-first-light-from-a-gravitational-wave-event/ ]

    “It’s a frighteningly disordered, energetic place out there in the universe and gravitational waves added a new dimension to looking at it,” said Robert Byer, professor of applied physics at Stanford and member of LIGO who provided the laser for the initial detector. “For this event, that new dimension was complemented by the signals from the other electromagnetic wavelengths and all those together gave us a completely different view of what’s going on inside the neutron stars as they merged.”

    This observation and the others that are likely to follow could help further the understanding of General Relativity, the origins of elements heavier than iron, the evolution of stars and black holes, relativistic jets that squirt from black holes and neutron stars, and the Hubble constant, which is the cosmological parameter which determines the expansion rate of the universe.

    Stanford and LIGO

    LIGO is led by the Massachusetts Institute of Technology and the California Institute of Technology, but Stanford was brought into the collaboration in 1988, largely due to the ultra-clean, stable lasers developed by Byer. The Byer lab developed the chip for the laser in the initial LIGO detector, which they installed in the early 2000s and lasted the lifetime of the initial LIGO project, which concluded in 2010. Lasers for the Advanced LIGO built upon Byer’s earlier work, an effort led by Benno Wilkie of the Albert Einstein Institute Hannover, a former postdoctoral scholar in Stanford’s Ginzton lab.

    “We were looking for the problems that LIGO couldn’t actually worry about yet. We wanted to find those and solve them before they became roadblocks,” said Byer. “One thing that allowed Stanford to contribute to LIGO in these extraordinary ways is we have this long tradition of engineering and science working together – and that’s not common. Great credit also goes to our extraordinary graduate students who are the glue that hold it all together.”

    Daniel DeBra, professor emeritus of aeronautics and astronautics, designed the original platform for LIGO, a nested system so stable that, in the LIGO detection band, it moves no more than an atom relative to the movement of Earth’s surface. Another crucial element of the vibration isolation system is the silicate bonding technique used to suspend LIGO’s mirrors. As a visiting scholar at Stanford, Sheila Rowan of the University of Glasgow adapted this technique from previous work at Stanford on the Gravity Probe B telescope.

    The Dark Energy Camera (DECam), the instrument used by the Dark Energy Survey, was among the first cameras to see in optical light what the LIGO-VIRGO detectors observed in gravitational waves earlier that morning.

    Dark Energy Survey


    Dark Energy Camera [DECam], built at FNAL


    NOAO/CTIO Victor M Blanco 4m Telescope which houses the DECam at Cerro Tololo, Chile, housing DECam at an altitude of 7200 feet

    DECam imaged the entire area within which the object was expected to be and helped confirm that the event was a unique object – and very likely the event LIGO had seen earlier that day.

    Many people at Stanford and the SLAC National Accelerator Laboratory are part of the Dark Energy Survey team. Aaron Roodman, professor and chair of particle physics and astrophysics at SLAC, developed, commissioned and continues to optimize the Active Optics System of DECam.

    Looking to the future, DeBra and colleagues including Brian Lantz, a senior research scientist who leads the Engineering Test Facility for LIGO at Stanford, are improving signal detection of Advanced LIGO by damping the effects of vibrations on the optics.

    Other faculty are improving the sensitivity of the Fermi Large Area Telescope (LAT), a instrument helmed by Peter Michelson, a professor of physics, that can both confirm the existence of a binary neutron star system and rule out other possible sources. Its sister instrument on Fermi, the Gamma-Ray Burst Monitor, detected a gamma ray burst coming from the location given by LIGO and VIRGO 14 seconds after the gravitational wave signal.

    LIGO is offline for scheduled upgrades for the next year, but many of the researchers are already working on LIGO Voyager, the third-generation of LIGO, which is anticipated to increase the sensitivity by a factor of 2 and would lead to an estimated 800 percent increase in event rate.

    “This is only a beginning. There are many innovations to come and I don’t know where we’re going to be in 10 years, 20 years, 30 years,” said Michelson. “The window is open and there are going to be mind-blowing surprises. That, to me, is the most exciting.”

    What’s so special about neutron stars

    A neutron star results when the core of a large star collapses and the atoms get crushed. The protons and electrons squeeze together and the remaining star is about 95 percent neutrons. A tablespoon full of neutron stars weighs as much as Mt. Everest.

    “Neutron stars have some of the strongest gravity you’ll find – black holes have the strongest – and thus they give us handles on studying strong-field gravity around them to see if it deviates at all from General Relativity,” said Mandeep Gill, the outreach coordinator at KIPAC at SLAC and Stanford, and a member of the Dark Energy Survey collaboration.

    Astronomers proposed the existence of neutron stars in 1934. They were first found in 1967, and then in 1975 a radio telescope observed the first instance of a binary neutron star system. From that discovery, Roger Blandford, professor of physics at Stanford, and colleagues confirmed predictions of the General Theory of Relativity.

    Blandford said the calculations related to the system Advanced LIGO saw are even more complicated because the stars are much closer together and could only be completed by a computer. This observation continues to support the General Theory of Relativity but Gill is hopeful that additional binary neutron star systems may begin to inform extension to the theory that could reveal how it fits with quantum theory, dark energy and dark matter.

    “One of the things I find terribly exciting about these observations is that not only do they confirm aspects of astronomical and relativistic precepts but they actually teach us things about nuclear physics that we don’t properly understand,” said Blandford. “We certainly have many things that we’ve speculated about and thought about – and I have to believe that some of that will be right – but some of it will be much more interesting than what we could anticipate.”

    As we observe more of these systems, which scientists anticipate, we may finally understand long-standing mysteries of neutron stars, like whether they have earthquakes on their crust or if, as suspected, they have small mountains that send out their own gravitational wave signal.

    “Even though we’ve been doing astronomy since the dawn of civilization, every time we turn on new instruments, we learn new things about what’s going on in the universe,” said Lantz. “If the elements heavier than iron are actually made in events like this, that stuff is here on Earth and it’s likely that was generated by events like this. It gives you sort of a way to reach out and touch the stars.”

    Blandford is also KIPAC Division Director in the Particle Physics and Astrophysics Directorate and professor of particle physics and astrophysics at SLAC; Byer is also a professor in SLAC’s Photon Science Directorate.

    Additional Stanford contributors to the LIGO multi-messenger observation include Edgard Bonilla, Riccardo Bassiri, Elliot Bloom, David Burke, Robert Cameron, James Chiang, Carissa Cirelli, C.E. Cunha, Christopher Davis, Seth Digel, Mattia Di Mauro, Richard Dubois, Martin Fejer, Warren Focke, Thomas Glanzman, Daniel Gruen, Ashot Markosyan, Manuel Meyer, Igor Moskalenko, Nicola Omedai, Elena Orlando, Troy Porter, Anita Reimer, Olaf Reimer, Leon Rochester, Aaron Roodman, Eli Rykoff, Brett Shapiro, Rafe Schindler, Jana B. Thayer, John Gregg Thayer, Giacomo Vianello and Risa Wechsler.

    See the full article here .

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    Leland and Jane Stanford founded the University to “promote the public welfare by exercising an influence on behalf of humanity and civilization.” Stanford opened its doors in 1891, and more than a century later, it remains dedicated to finding solutions to the great challenges of the day and to preparing our students for leadership in today’s complex world. Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto. Since 1952, more than 54 Stanford faculty, staff, and alumni have won the Nobel Prize, including 19 current faculty members

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  • richardmitnick 3:17 pm on August 11, 2017 Permalink | Reply
    Tags: SLAC Labs, , ,   

    From Symmetry: “A new search for dark matter 6800 feet underground” 

    Symmetry Mag

    Symmetry

    08/08/17
    Manuel Gnida

    Prototype tests of the future SuperCDMS SNOLAB experiment are in full swing.

    1
    Chris Smith/SLAC National Accelerator Laboratory)

    When an extraordinarily sensitive dark matter experiment goes online at one of the world’s deepest underground research labs, the chances are better than ever that it will find evidence for particles of dark matter—a substance that makes up 85 percent of all matter in the universe but whose constituents have never been detected.

    The heart of the experiment, called SuperCDMS SNOLAB, will be one of the most sensitive detectors for hypothetical dark matter particles called WIMPs, short for “weakly interacting massive particles.” SuperCDMS SNOLAB is one of two next-generation experiments (the other one being an experiment called LZ) selected by the US Department of Energy and the National Science Foundation to take the search for WIMPs to the next level, beginning in the early 2020s.

    SuperCDMS, at SNOLAB (Vale Inco Mine, Sudbury, Canada)

    “The experiment will allow us to enter completely unexplored territory,” says Richard Partridge, head of the SuperCDMS SNOLAB group at the Kavli Institute for Particle Astrophysics and Cosmology, a joint institute of Stanford University and SLAC National Accelerator Laboratory. “It’ll be the world’s most sensitive detector for WIMPs with relatively low mass, complementing LZ, which will look for heavier WIMPs.”

    LBNL LZ project at SURF

    The experiment will operate deep underground at Canadian laboratory SNOLAB inside a nickel mine near the city of Sudbury, where 6800 feet of rock provide a natural shield from high-energy particles from space, called cosmic rays. This radiation would not only cause unwanted background in the detector; it would also create radioactive isotopes in the experiment’s silicon and germanium sensors, making them useless for the WIMP search. That’s also why the experiment will be assembled from major parts at its underground location.

    A detector prototype is currently being tested at SLAC, which oversees the efforts of the SuperCDMS SNOLAB project.

    Colder than the universe

    The only reason we know dark matter exists is that its gravity pulls on regular matter, affecting how galaxies rotate and light propagates. But researchers believe that if WIMPs exist, they could occasionally bump into normal matter, and these collisions could be picked up by modern detectors.

    SuperCDMS SNOLAB will use germanium and silicon crystals in the shape of oversized hockey pucks as sensors for these sporadic interactions. If a WIMP hits a germanium or silicon atom inside these crystals, two things will happen: The WIMP will deposit a small amount of energy, causing the crystal lattice to vibrate, and it’ll create pairs of electrons and electron deficiencies that move through the crystal and alter its electrical conductivity. The experiment will measure both responses.

    “Detecting the vibrations is very challenging,” says KIPAC’s Paul Brink, who oversees the detector fabrication at Stanford. “Even the smallest amounts of heat cause lattice vibrations that would make it impossible to detect a WIMP signal. Therefore, we’ll cool the sensors to about one hundredth of a Kelvin, which is much colder than the average temperature of the universe.”

    These chilly temperatures give the experiment its name: CDMS stands for “Cryogenic Dark Matter Search.” (The prefix “Super” indicates that the experiment is more sensitive than previous detector generations.)

    The use of extremely cold temperatures will be paired with sophisticated electronics, such as transition-edge sensors that switch from a superconducting state of zero electrical resistance to a normal-conducting state when a small amount of energy is deposited in the crystal, as well as superconducting quantum interference devices, or SQUIDs, that measure these tiny changes in resistance.

    The experiment will initially have four detector towers, each holding six crystals. For each crystal material—silicon and germanium—there will be two different detector types, called high-voltage (HV) and interleaved Z-sensitive ionization phonon (iZIP) detectors. Future upgrades can further boost the experiment’s sensitivity by increasing the number of towers to 31, corresponding to a total of 186 sensors.

    2
    Four SuperCDMS SNOLAB iZIP detectors at the Stanford Nanofabrication Facility. Matt Cherry.

    3
    A SNOLAB Engineering Tower is installed in the dilution fridge to test cryogenic flex-cable readout configurations. Paul Brink.

    4
    High-density Vacuum Interface Board developed at Fermilab for readout of cryogenic detectors. Paul Brink.

    5
    SNOLAB prototype HV detector fabricated and packaged by Matt Cherry (SLAC) in SNOLAB prototype hardware. Matt Cherry.

    6
    SNOLAB Engineering Tower assembled by Tsuguo Aramaki (SLAC) and Xuji Zhao (Texas A&M). Paul Brink

    Working hand in hand

    The work under way at SLAC serves as a system test for the future SuperCDMS SNOLAB experiment. Researchers are testing the four different detector types, the way they are integrated into towers, their superconducting electrical connectors and the refrigerator unit that cools them down to a temperature of almost absolute zero.

    “These tests are absolutely crucial to verify the design of these new detectors before they are integrated in the experiment underground at SNOLAB,” says Ken Fouts, project manager for SuperCDMS SNOLAB at SLAC. “They will prepare us for a critical DOE review next year, which will determine whether the project can move forward as planned.” DOE is expected to cover about half of the project costs, with the other half coming from NSF and a contribution from the Canadian Foundation for Innovation.

    Important work is progressing at all partner labs of the SuperCDMS SNOLAB project. Fermi National Accelerator Laboratory is responsible for the cryogenics infrastructure and the detector shielding—both will enable searching for faint WIMP signals in an environment dominated by much stronger unwanted background signals. Pacific Northwest National Laboratory will lend its expertise in understanding background noise in highly sensitive precision experiments. A number of US universities are involved in various aspects of the project, including detector fabrication, tests, data analysis and simulation.

    The project also benefits from international partnerships with institutions in Canada, France, the UK and India. The Canadian partners are leading the development of the experiment’s data acquisition and will provide the infrastructure at SNOLAB.

    “Strong partnerships create a lot of synergy and make sure that we’ll get the best scientific value out of the project,” says Fermilab’s Dan Bauer, spokesperson of the SuperCDMS collaboration, which consists of 109 scientists from 22 institutions, including numerous universities. “Universities have lots of creative students and principal investigators, and their talents are combined with the expertise of scientists and engineers at the national labs, who are used to successfully manage and build large projects.”

    SuperCDMS SNOLAB will be the fourth generation of experiments, following CDMS-I at Stanford, CDMS-II at the Soudan mine in Minnesota, and a first version of SuperCDMS at Soudan, which completed operations in 2015.

    “Over the past 20 years we’ve been pushing the limits of our detectors to make them more and more sensitive for our search for dark matter particles,” says KIPAC’s Blas Cabrera, project director of SuperCDMS SNOLAB. “Understanding what constitutes dark matter is as fundamental and important today as it was when we started, because without dark matter none of the known structures in the universe would exist—no galaxies, no solar systems, no planets and no life itself.”

    See the full article here .

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    Symmetry is a joint Fermilab/SLAC publication.


     
  • richardmitnick 3:03 pm on May 4, 2011 Permalink | Reply
    Tags: , SLAC Labs,   

    From SLAC Today: “Seen Around SLAC: HELEN Has a New Home” 

    by Lori Ann White

    A 30-year-old laser built to simulate the conditions at the heart of a nuclear explosion arrived at SLAC last week, where members of the Linac Coherent Light Source’s Laser Science and Technology Department want to put it to a more peaceful use.
    i1
    SLAC LCLS

    The High Energy Laser Embodying Neodymium, or HELEN, is a neodymium-doped glass laser originally commissioned at Britain’s Atomic Weapons Establishment in 1979 in a ceremony presided over by Queen Elizabeth. But now that AWE [Atomic Weapons Establishment. in Britain] has a new, more powerful laser of its own called Orion, HELEN needed a new home, and LCLS scientists were only too happy to oblige.

    ‘ I’m very excited about this laser,’ said LCLS laser physicist Greg Hays, whose job it was to bring HELEN safely over from England. It may be 30 years old, he said, but it will still pack a punch in the kilo-joule range once it’s up and running: ‘ It’s essentially the grandfather of the National Ignition Facility at Lawrence Livermore National Laboratory, which is the world’s largest and most energetic laser, with a goal of achieving nuclear fusion and energy gain in the laboratory for the first time.

    The laser will probably be focused on the target chamber for the LCLS’s Matter in Extreme Conditions instrument.”

     
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