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Related papers: Atomic Force Microscopy Simulations for CO-functio…

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Frequency modulation (FM) Atomic Force Microscopy (AFM) with metal tips functionalized with a CO molecule at the tip apex has provided access to the internal structure of molecules with totally unprecedented resolution. We propose a model…

Materials Science · Physics 2022-05-03 Jaime Carracedo-Cosme , Rubén Pérez

Atomic force microscopy (AFM) with molecule-functionalized tips has emerged as the primary experimental technique for probing the atomic structure of organic molecules on surfaces. Most experiments have been limited to nearly planar…

Atomic force microscopy (AFM) is a key tool for characterising nanoscale structures, with functionalised tips now offering detailed images of the atomic structure. In parallel, AFM simulations using the particle probe model provide a…

Materials Science · Physics 2025-09-03 Jie Huang , Niko Oinonen , Fabio Priante , Filippo Federici Canova , Lauri Kurki , Chen Xu , Adam S. Foster

Atomic force microscopy (AFM) is a mechanical profiling technique that allows to image surfaces with atomic resolution. Recent progress in reducing the noise of this technique has led to a resolution level where previously undetectable…

Materials Science · Physics 2015-06-24 F. J. Giessibl , H. Bielefeldt , S. Hembacher , J. Mannhart

Gaussian process (GP) emulator has been used as a surrogate model for predicting force field and molecular potential, to overcome the computational bottleneck of molecular dynamics simulation. Integrating both atomic force and energy in…

Chemical Physics · Physics 2022-05-13 Hao Li , Musen Zhou , Jessalyn Sebastian , Jianzhong Wu , Mengyang Gu

Atomic force microscopy (AFM or SPM) imaging is one of the best matches with machine learning (ML) analysis among microscopy techniques. The digital format of AFM images allows for direct utilization in ML algorithms without the need for…

Biological Physics · Physics 2025-01-07 Igor Sokolov

High resolution Atomic Force Microscopy (AFM) and Scanning Tunnelling Microscopy (STM) imaging with functionalized tips is well established, but a detailed understanding of the imaging mechanism is still missing. We present a numerical…

Mesoscale and Nanoscale Physics · Physics 2014-08-27 Prokop Hapala , Georgy Kichin , Christian Wagner , F. Stefan Tautz , Ruslan Temirov , Pavel Jelinek

Atomic Force Microscopy (AFM) is a widely employed tool for micro-/nanoscale topographic imaging. However, conventional AFM scanning struggles to reconstruct complex 3D micro-/nanostructures precisely due to limitations such as incomplete…

Computer Vision and Pattern Recognition · Computer Science 2024-01-23 Shuo Chen , Mao Peng , Yijin Li , Bing-Feng Ju , Hujun Bao , Yuan-Liu Chen , Guofeng Zhang

Atomic force microscopy (AFM) enables high-resolution imaging and quantitative force measurement, which is critical for understanding nanoscale mechanical, chemical, and biological interactions. In dynamic AFM modes, however, interaction…

Instrumentation and Detectors · Physics 2025-06-10 Simon Laflamme , Bugrahan Guner , Omur E. Dagdeviren

Tapping mode atomic force microscopy is a standard technique for inspection and analysis at the nanometer scale. The understanding of the non-linear dynamics of the system due to the tip sample interaction is an important prerequisite for a…

Instrumentation and Detectors · Physics 2007-05-23 Robert W. Stark

Amplitude-modulation atomic force microscopy enables observation of fragile molecules at the nanometer scale. To shorten measurement times and capture dynamic molecules, increasing the frame rate is essential. Traditionally, maximum frame…

Applied Physics · Physics 2024-11-26 Kenichi Umeda , Noriyuki Kodera

Various methods of force measurement with the Atomic Force Microscope (AFM) are compared for their ability to accurately determine the tip-surface force from analysis of the nonlinear cantilever motion. It is explained how intermodulation,…

Mesoscale and Nanoscale Physics · Physics 2013-03-12 Daniel Platz , Daniel Forchheimer , Erik A. Tholén , David B. Haviland

This paper develops a resolution enhancement method for post-processing the images from Atomic Force Microscopy (AFM). This method is based on deep learning neural networks in the AFM topography measurements. In this study, a very deep…

Data Analysis, Statistics and Probability · Physics 2018-09-12 Y. Liu , Q. M. Sun , Dr. W. H. Lu , Dr. H. L. Wang , Y. Sun , Z. T. Wang , X. Lu , Prof. K. Y. Zeng

Artificial intelligence (AI) and machine learning have promised to revolutionize the way we live and work, and one of particularly promising areas for AI is image analysis. Nevertheless, many current AI applications focus on post-processing…

Materials Science · Physics 2020-07-31 Boyuan Huang , Zhenghao Li , Jiangyu Li

Machine-learned coarse-grained (CG) models have the potential for simulating large molecular complexes beyond what is possible with atomistic molecular dynamics. However, training accurate CG models remains a challenge. A widely used…

The atomic force microscope (AFM) is a versatile, high-resolution tool used to characterize the topography and material properties of a large variety of specimens at nano-scale. The interaction of the micro-cantilever tip with the specimen…

Materials Science · Physics 2011-09-05 David Busch , Qingze Zou , Baskar Ganapathysubramanian

The accuracy and efficiency of a coarse-grained (CG) force field are pivotal for high-precision molecular simulations of large systems with complex molecules. We present an automated mapping and optimization framework for molecular…

Computational Physics · Physics 2024-08-14 Zhixuan Zhong , Lifeng Xu , Jian Jiang

Intercalation of two dimensional materials, particularly transition metal dichalcogenides, is a noninvasive way to modify electronic, optical and structural properties of these materials. However, research of these atomic-scale phenomena…

Modern physics simulation often involves multiple functions of interests, and traditional numerical approaches are known to be complex and computationally costly. While machine learning-based surrogate models can offer significant cost…

Machine Learning · Computer Science 2025-06-10 Da Long , Zhitong Xu , Guang Yang , Akil Narayan , Shandian Zhe

Despite being the main tool to visualize molecules at the atomic scale, AFM with CO-functionalized metal tips is unable to chemically identify the observed molecules. Here we present a strategy to address this challenging task using deep…

Materials Science · Physics 2025-09-03 Jaime Carracedo-Cosme , Carlos Romero-Muñiz , Pablo Pou , Rubén Pérez
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