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PAST NEWS

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SCAR: DATA-DRIVEN STRUCTURE SOLUTION

February 29, 2019

 

Congratulations to Gayatri (now at Iowa State) and team for developing a new data-driven tool for single crystal structure solution! doi: 10.1021/acs.inorgchem.9b00344

The code is available on GitHub:

https://github.com/CitrineInformatics/crystal-refinement

CONTROLLING TRAP STATES VIA CHEMICAL SUBSTITUTION

February 29, 2019

 

Advanced materials characterization reveals the relationship between the host crystal structure's band gap and the position of trap states. This work is going to help design the next generation of "glow-in-the-dark" materials! 

DIRECTED SEARCH FOR NEW PHOSPHORS PUBLISHED IN NATURE COMMUNICATIONS

October 22, 2018


Machine learning to identify high-efficiency phosphors!

 

Highlighted by the University of Houston, Science Daily, Phys.org and others!

MACHINE LEARNING USED TO DIRECT THE SEARCH FOR SUPERHARD MATERIALS OUT IN JACS!

July 16, 2018

 

Great collaboration developing machine learning to identify new materials.

Highlighted by ChemistryWorld

UNDERSTANDING THE ORIGIN OF PERSISTENT LUMINESCENCE IN STRONTIUM ALUMINATE. 

July 11, 2018

Now we have the recipe to make materials glow-in-the-dark longer!

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MACHINE LEARNING CAN PREDICT THE BAND GAP USING EXPERIMENTALLY MEASURED OPTICAL PROPERTIES 

April 5, 2018

Using machine learning to predict the band gap of solids; >75,000 band gaps predicted in the supporting information!

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OUR NEWEST BORATE PHOSPHOR PUBLISHED IN CHEM. MATER.

March 29, 2018

 

Another new high-efficiency blue phosphor, borates are awesome!