Brilliant people working towards a common goal

It’s #LoveYourDataWeek so it’s fitting that this week’s #LightSourceSelfie features a data expert. Mathew Cherukara leads the Computational X-ray Science Group at the Advanced Photon Source (APS) at Argonne National Laboratory near Chicago.

Mathew, who is from Kerala in India, works with his colleagues to develop the computational tools, algorithms and machine learning models used to analyse data from the beamlines at the APS. The first time Mathew saw a light source he recalls, “I couldn’t believe that science on this scale was being done every single day”. Mathew also talks about the fact that, after the APS upgrade, the data rates and computational needs will increase 100 to 1,000 times. For Mathew, the best thing about working at a light source is all the brilliant people working towards a common goal. When Mathew isn’t working, he enjoys taking long walks with his dog and we’re treated to a very cute dog moment at the end of the video #LoveYourDog!

APS #LightSourceSelfie

Understanding the physics in new metals

Researchers from the Paul Scherrer Institute PSI and the Brookhaven National Laboratory (BNL), working in an international team, have developed a new method for complex X-ray studies that will aid in better understanding so-called correlated metals. These materials could prove useful for practical applications in areas such as superconductivity, data processing, and quantum computers. Today the researchers present their work in the journal Physical Review X.

In substances such as silicon or aluminium, the mutual repulsion of electrons hardly affects the material properties. Not so with so-called correlated materials, in which the electrons interact strongly with one another. The movement of one electron in a correlated material leads to a complex and coordinated reaction of the other electrons. It is precisely such coupled processes that make these correlated materials so promising for practical applications, and at the same time so complicated to understand.

Strongly correlated materials are candidates for novel high-temperature superconductors, which can conduct electricity without loss and which are used in medicine, for example, in magnetic resonance imaging. They also could be used to build electronic components, or even quantum computers, with which data can be more efficiently processed and stored.

Read more on the BNL website

Image: Brookhaven Lab Scientist Jonathan Pelliciari now works as a beamline scientist at the National Synchrotron Light Source II (NSLS-II), where he continues to use inelastic resonant x-ray scattering to study quantum materials such as correlated metals.

Credit: Jonathan Pelliciari/BNL