New “Genomic” Method Reveals Atomic Arrangements of Battery Material |



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Scientists from Stony Brook University, the US Department of Energy’s Brookhaven National Laboratory, DOE’s Lawrence Berkeley National Laboratory Materials Project, the University of California-Berkeley, and European collaborators have developed a new way to decipher the structure at atomic level of data materials collected from ground dust samples. They describe their approach and demonstrate its ability to solve the structure of a material that shows the promise of transporting ions through sodium ion batteries in an article just published in the journal Chemistry of materials.

Peter Khalifah |
Peter Khalifah, chemist at Brookhaven Lab / Stony Brook University

“Our approach combines experiment, theory and modern computational tools to deliver the high-quality structural data needed to understand important functional materials, even when only dust samples are available,” said corresponding author Peter Khalifah, who holds an appointment. jointly with Brookhaven Lab and SBU.

The technique is somewhat a form of reverse engineering. Instead of solving the structure directly from the experimental data measured on the dust sample – a problem too complex to be possible for many materials – it uses computer algorithms to construct and evaluate all plausible structures of a material. By analyzing the “genome” associated with a material in this way, it is possible to find the correct structure even when this structure is so complex that conventional methods of solving the structure fail.

For the study described in the paper, powder X-ray diffraction experiments were performed at the ALBA synchrotron in Barcelona, ​​Spain, by European collaborators Matteo Bianchini and Francois Fauth, part of a team led by Christian Masquelier. Scientists used the bright X-rays of that structure to study the atomic arrangement of a cathode material of a sodium ion battery known as NVPF at a variety of temperatures ranging from ambient to very low cryogenic temperatures at which gases atmospheric agents liquefy. This work is necessary because the disturbance in the ambient temperature structure of NVPF disappears when it is cooled to cryogenic temperatures. And while batteries operate near room temperature, deciphering the cryogenic structure of the material is still critically important because only this noise-free, low-temperature structure can provide scientists with a clear understanding of the true chemical bond that is present at room temperature. This chemical bonding environment strongly affects the way ions move through the structure at room temperature and thus affects the performance of NVPF as a battery material.

Structure behind the discovery of the battery
The low temperature structure of NVPF [Na3V2(PO4)2F3] solved in this work. Calculations from the Lawrence Berkeley National Laboratory suggest that sodium (white) atoms can move more easily in planes between the cationic sites of vanadium (teal) and phosphorus (mauve) atoms during battery use.

“The bonding environment around sodium atoms – how many neighbors each has – is essentially the same at low temperature as at room temperature,” Khalifah explained, but trying to capture those details at room temperature is like trying to get the people to sit. children still for a photo. “Everything becomes blurry because the ions are moving too fast for a picture to be taken.” For this reason, some of the bonding environments derived from the ambient temperature data are not correct. Conversely, cryogenic temperatures freeze the motion of sodium ions to provide a true picture of the local environment sodium ions are in when they are not moving.

“When the material is cooled, 24 neighboring sodium ions are forced to choose one of two possible sites and their preferred low-energy ‘sorting’ pattern can be solved,” Khalifah said.

A preliminary analysis of Bianchini powder X-ray diffraction data indicated that the sorting model is very complex. For materials with such complex orders, it is typically not possible to solve their three-dimensional atomic structure using the powder diffraction data.

“The powder diffraction data is flattened to one dimension, so a lot of information is lost,” Khalifah said.

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