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@SLAClab

SLAC National Accelerator Laboratory

@SLAClab
Official account of the U.S. Department of @ENERGY's Silicon Valley national lab, operated by @Stanford. Verify: stanford.io/3P2sIAy
Menlo Park, CA
slac.stanford.edu
Joined November 2009
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  • @SLAClab
    SLAC National Accelerator Laboratory
    @SLAClab
    14h
    Starting small. This photo shows a small fuel cell inside of a sample chamber at our synchrotron. The conditions inside of the sample chamber can be tuned to various pressures, allowing scientists to study fuel cells and other active chemistry under more realistic conditions.
    This photo shows a small fuel cell inside of a sample chamber at SLAC's synchrotron, SSRL. This experimental station allows scientists to study fuel cells under more realistic conditions. Credit: Andy Freeberg/SLAC National Accelerator Laboratory
    1
  • @SLAClab
    SLAC National Accelerator Laboratory
    @SLAClab
    Aug 28
    Cracking the solid-state battery 🔋 Lithium-filled cracks can lead to short circuits & drain charge, but @Stanford & SLAC researchers found that compressing the battery material altered the formation & led to shorter charging times + longer battery life: stanford.io/4iAguO8
    A round shape with tree‑like pattern spreading outward from a dark central area, set against a blurred blue background. Researchers discovered a way to track and suppress harmful intrusions in dendrites that form in solid-state batteries. This top view of the electrolyte shows the dendrites that propagated horizontally.  (Greg Stewart, SLAC National Accelerator Laboratory)
  • @SLAClab
    SLAC National Accelerator Laboratory
    @SLAClab
    Aug 27
    Ancient #TBT Our X-rays once uncovered a 6th century translation of a book by the Greek-Roman doctor Galen, allowing the hidden text to be read for the first time in a thousand years. Learn more: stanford.io/4qGkAGv
    An aged manuscript with worn pages rests open, featuring text written in an ancient script. Two hands gently hold the book, highlighting its fragile nature. An international, multidisciplinary team is using X-rays from SLAC to reveal the hidden text of a medical manuscript by the ancient Greek doctor Galen that was written on parchment in the 6th century and scraped off and overwritten with religious text in the 11th century.

 

Photo by Farrin Abbott/SLAC
    An aged manuscript with worn pages rests open, featuring text written in an ancient script. Two hands gently hold the book, highlighting its fragile nature. An international, multidisciplinary team is using X-rays from SLAC to reveal the hidden text of a medical manuscript by the ancient Greek doctor Galen that was written on parchment in the 6th century and scraped off and overwritten with religious text in the 11th century.

 

Photo by Farrin Abbott/SLAC
    The image shows a detailed view of a medieval manuscript being scanned using modern equipment. The manuscript page is open and visible, displaying handwritten text. Various scanning devices and technology are positioned around the manuscript, focusing on capturing its details. An aged manuscript with worn pages rests open, featuring text written in an ancient script. Two hands gently hold the book, highlighting its fragile nature. An international, multidisciplinary team is using X-rays from SLAC to reveal the hidden text of a medical manuscript by the ancient Greek doctor Galen that was written on parchment in the 6th century and scraped off and overwritten with religious text in the 11th century.

 

Photo by Farrin Abbott/SLAC
    An illuminated manuscript page featuring ancient text in vibrant purple and green hues, resembling Syriac script. The page has a symmetrical design with text columns on each side, bordered by decorative elements. An aged manuscript with worn pages rests open, featuring text written in an ancient script. Two hands gently hold the book, highlighting its fragile nature. An international, multidisciplinary team is using X-rays from SLAC to reveal the hidden text of a medical manuscript by the ancient Greek doctor Galen that was written on parchment in the 6th century and scraped off and overwritten with religious text in the 11th century.

 

Photo by Farrin Abbott/SLAC
  • @SLAClab
    SLAC National Accelerator Laboratory
    @SLAClab
    Aug 26
    A deep underground and extremely cold hunt 🔍 One of the world’s most sensitive dark matter searches, from more than a mile beneath Earth’s surface, has begun collecting its very first scientific data: stanford.io/3UjT71t
    The experiment ready to take data with the aluminum radon barrier installed around the lead and poly shielding, but prior to the installation of the outer water tanks. The cryocoolers, vacuum interface and warm electronics, and deployable calibration system are visible in the foreground with the dilution fridge behind the shield.  (SuperCDMS)
    The inner polyethylene neutron shield being assembled by (left to right) Joseph Mammo (USouthDakota), Warren Perry (UToronto), Prisca Cushman (UMinnesota), Mauro Botas (SNOLAB) and Marco Olivares (SNOLAB). (SuperCDMS)
    The entire SuperCDMS set-up is surrounded by layers of clean shielding materials to prevent stray background radiation from drowning out the signal. Layers of copper, polyethylene, ultra-pure lead and a barrier against radon are used to reduce these backgrounds to acceptable levels. (SuperCDMS)
    1
  • @SLAClab
    SLAC National Accelerator Laboratory
    @SLAClab
    Aug 24
    "Someone's compression will save the world from data-geddon." This is Silicon Valley after all. SLAC researchers have created a novel AI-based neural network that can compress massive amounts of raw data from science experiments without losing detail: stanford.io/4xo1g3E
    A complex infographic shows a cube with a circular pattern on the left, connected by dotted lines to a central geometric shape. On the right, there are two labeled sections. The top section, "Arbitrary Resolution," displays a series of images transitioning from low to high resolution. The bottom section, "Different Scales," shows images ranging from coarse to fine detail. The color scheme is primarily purple and orange on a dark background.
The AI-based method uses neural networks to reduce the overall file size while allowing users to control what information is kept. The neural network encodes features of the measurement at different scales in a compact form. At decoding, users can select a small region of interest to decode, and this can be done at different scales and resolutions, allowing finer features to be recovered when needed. (Credit: Yuan Ni and Greg Stewart/SLAC National Laboratory)
    2