683624 news 1754588884 1755869997 <![CDATA[Finding Clarity in the Noise: A New Way to Recover Hidden Signals at the Nanoscale]]> In the world of nanotechnology, seeing clearly isn’t easy. It’s even harder when you’re trying to understand how a material’s properties relate to its structure at the nanoscale. Tools like piezoresponse force microscopy (PFM) help scientists peer into the nanoscale functionality of materials, revealing how they respond to electric fields. But those signals are often buried in noise, especially in instances where the most interesting physics happens.

Now, researchers at Georgia Tech have developed a powerful new method to extract meaningful information from even the noisiest data, or when, alternatively, the response of the material is the smallest. Their approach, which combines physical modeling with advanced statistical reconstruction, could significantly improve the accuracy and confidence of nanoscale measurement properties.

The team’s findings, led by Nazanin Bassiri-Gharb, Harris Saunders, Jr. Chair and Professor in the George W. Woodruff School of Mechanical Engineering and School of Materials Science and Engineering (MSE), are reported in Small Methods.

Co-lead authors Kerisha Williams, a former MSE Ph.D. student, and Henry Shaowu Yuchi, a former Ph.D. student in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE), spearheaded the study. Other collaborators include Kevin Ligonde, a Ph.D. student in the Woodruff School; Mathew Repasky, a former Ph.D. student in ISyE; and Yao Xie, Coca-Cola Foundation Chair and Professor in ISyE.

This research was initiated through Georgia Tech’s Forming Teams and Moving Teams Forward seed grant program, launched by the Office of the Executive Vice President for Research in 2021. Designed to support cross-disciplinary collaboration, the program helps build research teams that align with the growing national emphasis on large-scale, team-based projects. The grant supported early work by Bassiri-Gharb, Xie, and Juan-Pablo Correa-Baena, associate professor and Goizueta Early Career Faculty Chair in MSE.

Read the full story on the George W. Woodruff School of Mechanical Engineering website.

]]> 2025-08-07T00:00:00-04:00 In the world of nanotechnology, seeing clearly isn’t easy. It’s even harder when you’re trying to understand how a material’s properties relate to its structure at the nanoscale. Tools like piezoresponse force microscopy (PFM) help scientists peer into the nanoscale functionality of materials, revealing how they respond to electric fields. But those signals are often buried in noise, especially in instances where the most interesting physics happens.

Now, researchers at Georgia Tech have developed a powerful new method to extract meaningful information from even the noisiest data, or when, alternatively, the response of the material is the smallest. Their approach, which combines physical modeling with advanced statistical reconstruction, could significantly improve the accuracy and confidence of nanoscale measurement properties.

The team’s findings, led by Nazanin Bassiri-Gharb, Harris Saunders, Jr. Chair and Professor in the George W. Woodruff School of Mechanical Engineering and School of Materials Science and Engineering (MSE), are reported in Small Methods.

]]> 677607 image <![CDATA[IMG_2412.jpg]]> Nazanin Bassiri-Gharb, Harris Saunders, Jr. Chair and Professor in the Woodruff School and MSE, and Yao Xie, Coca-Cola Foundation Chair and Professor in ISyE.

]]> 261520 image/jpeg Ashley Ritchie
George W. Woodruff School of Mechanical Engineering

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