When players try to solve word games, they try to piece together clues to find the solution. Sure, it helps to have a solid vocabulary, but finding the right answers to these puzzles is as much about logic and strategy as it is about being a wordsmith.
Using a surprisingly comparable process, an interdisciplinary team of Northwestern Engineering researchers has developed a method to determine how different 2D materials respond to disorder — testing some materials that could eventually replace silicon in new transistors and sensors.
“The analysis method will lead to a better understanding of disorder potentials in 2D materials to help make faster transistors, as well as better gas sensors that can more easily discriminate between different gases,” said Matthew Grayson. , Professor of Electrical and Computer Engineering at McCormick. School of Engineering, and one of the study’s authors.
In the paper “Field-effect Conductivity Scaling for Two-dimensional Materials with Tunable Impurity Density” published June 16 in the journal 2D Materials, researchers have developed a method to determine the imprint of the nearby disorder as seen by a 2D material.
In science, disorder refers to nearby imperfections or charges that could scatter an electron’s otherwise straight path. 2D materials like graphene are particularly susceptible to near-disorder because they are literally several atoms thick, at most.
“Disorder characterization is paramount to understanding and improving the performance of 2D materials,” said Grayson. “This article shows that there is a universal curve that serves as a fingerprint of this disorder. Even though different doses of clutter seem to result in completely different behaviors, these behaviors all represent the individual threads of an overall tapestry.
This is where the similarity lies between science and the games you play on your phone or your printed newspaper.
Using 2D material samples developed by the Hersam and Dravid groups, Grayson and his team implemented a new method for measuring electrical conductivity curves using a cryostat, a device that retains samples at low temperature for microscopic examination. At room temperature, the charges that make up the disorder are free to move around until they reach equilibrium, but when frozen in the cryostat, the disorder is frozen in place.
Each individual conductivity curve looks like a puzzle piece. The researchers then used a rule of thumb to piece together all the curves until they formed a complete picture.
They then used physical arguments to understand why this rule works so well. As a result, they solved the riddle of how each of the materials under study responds to a specific class of imperfections.
“The impressive continuity of this image when all the pieces of the puzzle were in place prompted us to dig deeper into the physics to understand what the underlying reason for this behavior must be,” Grayson said. “The same mindset the general public uses to solve their daily word or crossword puzzles is applied here.”
These findings also have implications for 2D materials research in the future.
“Instead of seeing individual devices made from the same 2D materials as a bunch of puzzle pieces that each need to be studied independently, you can now pinpoint where a given sample fits into the previously solved puzzle,” Grayson said. , “so that each individual piece is instantly recognized as part of a larger picture.
- Chulin Wang, Lintao Peng, Spencer A Wells, Jeffrey D Cain, Yi-Kai Huang, Lawrence A Rhoads, Vinayak P Dravid, Mark C Hersam, Matthew A Grayson. Field-effect conductivity scaling for two-dimensional materials with adjustable impurity density. 2D Materials, 2022; 9 (3): 031002 DOI: 10.1088/2053-1583/ac72b0
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