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Bonagiri LKS, Wang Z, Zhou S, Zhang Y. Precise Surface Profiling at the Nanoscale Enabled by Deep Learning. Nano Lett 2024; 24:2589-2595. [PMID: 38252875 DOI: 10.1021/acs.nanolett.3c04712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Surface topography, or height profile, is a critical property for various micro- and nanostructured materials and devices, as well as biological systems. At the nanoscale, atomic force microscopy (AFM) is the tool of choice for surface profiling due to its capability to noninvasively map the topography of almost all types of samples. However, this method suffers from one drawback: the convolution of the nanoprobe's shape in the height profile of the samples, which is especially severe for sharp protrusion features. Here, we report a deep learning (DL) approach to overcome this limit. Adopting an image-to-image translation methodology, we use data sets of tip-convoluted and deconvoluted image pairs to train an encoder-decoder based deep convolutional neural network. The trained network successfully removes the tip convolution from AFM topographic images of various nanocorrugated surfaces and recovers the true, precise 3D height profiles of these samples.
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Affiliation(s)
- Lalith Krishna Samanth Bonagiri
- Materials Research Laboratory, University of Illinois, Urbana, Illinois 61801, United States
- Department of Mechanical Science and Engineering, University of Illinois, Urbana, Illinois 61801, United States
| | - Zirui Wang
- Department of Materials Science and Engineering, University of Illinois, Urbana, Illinois 61801, United States
| | - Shan Zhou
- Materials Research Laboratory, University of Illinois, Urbana, Illinois 61801, United States
- Department of Materials Science and Engineering, University of Illinois, Urbana, Illinois 61801, United States
| | - Yingjie Zhang
- Materials Research Laboratory, University of Illinois, Urbana, Illinois 61801, United States
- Department of Materials Science and Engineering, University of Illinois, Urbana, Illinois 61801, United States
- Beckman Institute for Advanced Science and Technology, University of Illinois, Urbana, Illinois 61801, United States
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Bonagiri LKS, Panse KS, Zhou S, Wu H, Aluru NR, Zhang Y. Real-Space Charge Density Profiling of Electrode-Electrolyte Interfaces with Angstrom Depth Resolution. ACS Nano 2022; 16:19594-19604. [PMID: 36351178 DOI: 10.1021/acsnano.2c10819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
The accumulation and depletion of charges at electrode-electrolyte interfaces is crucial for all types of electrochemical processes. However, the spatial profile of such interfacial charges remains largely elusive. Here we develop charge profiling three-dimensional (3D) atomic force microscopy (CP-3D-AFM) to experimentally quantify the real-space charge distribution of the electrode surface and electric double layers (EDLs) with angstrom depth resolution. We first measure the 3D force maps at different electrode potentials using our recently developed electrochemical 3D-AFM. Through statistical analysis, peak deconvolution, and electrostatic calculations, we derive the depth profile of the local charge density. We perform such charge profiling for two types of emergent electrolytes, ionic liquids, and highly concentrated aqueous solutions, observe pronounced sub-nanometer charge variations, and find the integrated charge densities to agree with those derived from macroscopic electrochemical measurements.
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Affiliation(s)
- Lalith Krishna Samanth Bonagiri
- Materials Research Laboratory, University of Illinois, Urbana, Illinois61801, United States
- Department of Mechanical Science and Engineering, University of Illinois, Urbana, Illinois61801, United States
| | - Kaustubh S Panse
- Materials Research Laboratory, University of Illinois, Urbana, Illinois61801, United States
- Department of Materials Science and Engineering, University of Illinois, Urbana, Illinois61801, United States
| | - Shan Zhou
- Materials Research Laboratory, University of Illinois, Urbana, Illinois61801, United States
- Department of Materials Science and Engineering, University of Illinois, Urbana, Illinois61801, United States
| | - Haiyi Wu
- Walker Department of Mechanical Engineering and Oden Institute for Computational Engineering & Sciences, The University of Texas at Austin, Austin, Texas78712, United States
| | - Narayana R Aluru
- Walker Department of Mechanical Engineering and Oden Institute for Computational Engineering & Sciences, The University of Texas at Austin, Austin, Texas78712, United States
| | - Yingjie Zhang
- Materials Research Laboratory, University of Illinois, Urbana, Illinois61801, United States
- Department of Materials Science and Engineering, University of Illinois, Urbana, Illinois61801, United States
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