19
Apr
2017

The electric cars, manned spacecraft, and must-have devices of tomorrow will all be built with discoveries made today in materials science. But to find the alloys, nanomaterials, and polymers that will enable these future technologies requires scaling up how researchers store, share, analyze, and sift through the surge of materials data from academia, national facilities, and industry.

08
Aug
2016

One of the world’s hubs of computation in particle physics sits inconspicuously at the corner of 56th Street and Ellis Avenue on the University of Chicago campus. Read how work from UChicago's ATLAS group and the Computation Institute helps support cutting-edge research at CERN's Large Hadron Collider.

04
Apr
2016

Superconductors have made advanced technologies such as MRI machines, superconducting generators, and particle accelerators possible in our modern world. Soon, they may make futuristic concepts such as magnetic levitation trains and cheap wind energy more affordable and widespread. But in order to do so, scientists need to realize more of the theoretical potential of superconductivity to pass electric current with zero resistance.

23
Mar
2016

Analyzing telescope images to search for expolanets in distant solar systems requires high-performance computation that is flexible and fast. Using Chameleon, the experimental cloud computing testbed hosted by the Computation Institute and the Texas Advanced Computing Center, a class of students at the University of Arizona built a new analytics software package that will help astronomers find these planetary needles in the cosmic haystack.

16
Feb
2016

The ATLAS experiment at CERN is one of the largest scientific projects in history, with thousands of scientists from around the world working together to analyze the torrents of data flowing from its detectors. A new analytics platform built from open source tools by CI scientists at the ATLAS Midwest Tier Center 2 will make those experiments more efficient.

16
Nov
2015

You’re walking down a nondescript corridor lit by a harsh overhead light. As you exit the passage, you find yourself in an enormous room, dominated by a massive, shiny cylinder suspended in the middle of the chamber. With a flick of your thumb, you’re suddenly floating up towards the ceiling, looking down upon one of the world’s largest and most unique scientific instruments. Another few thumb and head motions, and you’re suddenly a proton, shooting down the beam pipe at the center of the machinery and into a long tunnel.

12
Nov
2015

A new instrument to detect dark matter, one of the biggest mysteries of the universe, goes live 1400 meters underground in Italy. CI scientists will help help build the computing center and analyze the data for this unprecedented, international collaboration.

09
Jan
2015

For December's Inside the Discovery Cloud event, Juan de Pablo, Liew Family Professor in Molecular Engineering at the IME, discussed how his laboratory uses computational approaches to study DNA mapping and self-assembly. Then, Michael Wilde, CI Senior Fellow, and software architect at Argonne National Laboratory discussed methods developed and applied at UChicago and Argonne that help researchers conquer the complexity of high performance computer modeling and better integrate it into the scientific knowledge discovery process.

11
Dec
2014

Hydrated excess protons, also known as H30+ and hydronium cations, are skilled escape artists. In a space full of water, the extra protons can hop from H20 to H20 like an action star leaping train cars. If they find a hydrated channel, protons can use that water-hopping skill to shoot across membranes, as well. Now, new computational chemistry research from the laboratory of CI Senior Fellow Gregory Voth finds that protons don’t even need those tunnels to be filled with water first -- they can actually create their own “water wire” to span the channel and enable their thrilling escape.

08
Dec
2014

Scientists using Argonne's Advanced Photon Source to study the atomic structure of jet engine materials employed the Computation Institute's Swift parallel programming language and the world-class supercomputer Mira to speed up analysis and make experimental adjustments on the fly.