Novel Sensing Technique Improves Detection of Electric Fields, Mechanical Distortions in Materials

Detection of electric fields and mechanical distortions in materials is critical to a range of applications, from micro-electromechanical systems (MEMS) to atomic-scale sensing and electronics. However, technologies for sensing these electric fields and mechanical distortions at high frequency with high sensitivity and spatial resolution are difficult to devise.

Researchers at the Institute for Molecular Engineering at the University of Chicago have developed a novel sensing technique for electric fields and mechanical distortions based on defects – missing atoms – in silicon carbide crystals. Silicon carbide crystals are a technologically mature wafer-scale material used for MEMS and high-power electronics applications.

The new method is all-optical, contactless, and easy to use, providing a pathway to create broad sets of new technological applications for device and material characterization. The findings were published online July 16 in the Proceedings of the National Academy of Sciences.

The technique was developed out of surprising discoveries from two different research projects. In the first project, defects in silicon carbide were illuminated with near-ultraviolet and near-infrared light, which unexpectedly revealed a dramatic increase in their emitted signal. This result was later understood as an effect of manipulating the electronic configuration of these defects, thereby modifying their behavior.

The second used an electromechanical device built into the silicon carbide substrate to manipulate the spin of the defects for quantum information applications. The researchers unexpectedly found that they could use these defects to spatially image the local electric fields.

“These results were entirely unexpected and offer an exciting new direction for engineering technologies with atomic-scale sensors,” said Gary Wolfowicz, a postdoctoral researcher at the Institute for Molecular Engineering who performed the measurements. Ultimately, the researchers discovered that electric fields influenced the effect of the light on the defects.

Combining these two discoveries led to the creation of a novel sensing technique. By shining light upon the silicon carbide crystal, the defects emit their own light that directly depends on the local electric field. The defects are therefore local “observers” of changes in the material. As the defects are point-like in space (atomically pinpointed within the crystal), they can provide very high spatial resolution of the local fields.

The authors investigated the effect of electric fields in a variety of experimental conditions, particularly the dependence on the rate of electric field fluctuations. Unlike other techniques, the sensitivity to electric fields is extremely high at radio and microwave frequencies. The authors further developed the method to measure the characteristic frequencies of the electric field, providing critical information for measuring the performance of electrical devices and MEMS.

The researchers used this sensing technique to measure mechanical waves – sound waves –  in a MEMS device called a surface acoustic wave resonator. By applying a voltage to the device, the surface of the substrate material, silicon carbide, starts to ripple and oscillate millions of time per second.

“This ability to image sound and mechanical waves in nanostructures using light will enable us to explore new classes of materials and devices,” said Sam Whiteley, graduate student at the Institute for Molecular Engineering and co-author of the paper.   

Characterizing a device for three-dimensional information would be challenging using conventional commercial methods. Using this new technique, the defects provided all spatial and frequency information on the mechanical oscillations.

Citation: “Electrometry by optical charge conversion of deep defects in 4H-SiC.” Wolfowicz et al, Proceedings of the National Academy of Sciences, July 16, 2018. https://doi.org/10.1073/pnas.1806998115

Funding: National Science Foundation, Army Research Laboratory, US Department of Energy.

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