Simulation of AFM/LFM by molecular dynamics: role of lateral force in contact-mode AFM imaging

Komiyama, Masaharu; Tsujimichi, Kazuya; Tazawa, Katsuyuki; Hirotani, Akiyasu; Yamano, Hideo; Kubo, Momoji; Brocławik, Ewa; Miyamoto, Akira

doi:10.1016/0039-6028(96)00097-0

Cited by 12 publications

(11 citation statements)

References 10 publications

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“…To get the nanoscale insight into the mechanism of this polymer wetting, it is necessary to quantitatively describe its surface properties. Thus, we propose in this study a new version of atomic force microscopy (AFM) image simulation 24 called the MD−AFM imaging method. This approach is based on the fundamentals of AFM, and it is applied in the MD simulation of water on PTFE surfaces for the first time.…”

Section: ■ Introductionmentioning

confidence: 99%

Nanoscale Water Contact Angle on Polytetrafluoroethylene Surfaces Characterized by Molecular Dynamics–Atomic Force Microscopy Imaging

Włoch¹,

Terzyk²,

Wiśniewski³

et al. 2018

Langmuir

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The aim of this study is to link polytetrafluoroethylene (PTFE) surface characteristics with its wetting properties in the nanoscale. To do this using molecular dynamics (MD) simulation, three series of rough PTFE surfaces were generated by annealing and compressing and next characterized by the application of the MD version of the atomic force microscopy (AFM) method. The values of specific surface areas were additionally calculated. The TIP4P/2005 water model was used to study the wetting properties of obtained PTFE samples. The simulated water contact angle (WCA) value for the most flat (but slightly rough) sample having PTFE density is equal to 106.94°, and it is close to the value suggested for a perfect PTFE surface on the basis of experimental results. Also, the changes in the WCA with PTFE compression are in the same range as experimentally reported. The obtained MD simulation results make it possible to link, for the first time, the WCA values with the surface MD-AFM root-mean-square roughness and with the PTFE density. Finally, we show that for PTFE wetting in the nanoscale, the line tension is negligible and the Bormashenko's equation reduces to the Cassie-Baxter (CB) model. In fact, our simulation results are close to the CB mechanism.

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Section: ■ Introductionmentioning

confidence: 99%

Nanoscale Water Contact Angle on Polytetrafluoroethylene Surfaces Characterized by Molecular Dynamics–Atomic Force Microscopy Imaging

Włoch¹,

Terzyk²,

Wiśniewski³

et al. 2018

Langmuir

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“…Only by doing so can the action force between the tip and sample in every moment be calculated. Hence, the size of the simulative sample of Komiyama et al (1996) is only 1.5 nm, which is also a flat surface.…”

Section: Introductionmentioning

confidence: 98%

“…And molecular mechanics or molecular dynamics should be used when considering the action force of the probe and the surface of the sample. For example, Komiyama et al (1996) proposed the tip and sample by copper atoms and by using Morse potential (Komiyama et al 1996), discussed the influence of lateral force during the AFM/LFM simulation measurement. However, when using MD to undergo AFM measurement simulation, if the sample is slightly larger, then the calculating quantities would be massive.…”

Section: Introductionmentioning

confidence: 99%

Error analysis and regression mode of the V‐grooved sample in the atomic force microscope simulation measurement mode by the molecular mechanics

2009

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Based on the molecular mechanics, this study uses the two-body potential energy function to construct a trapezoidal cantilever nano-scale simulation measurement model of contact mode atomic force microscopy (AFM) under the constant force mode to simulate the measurement the nano-scale V-grooved standard sample. We investigate the error of offset distance of the cross-section profile when using the probes with different trapezoidal cantilever probe tip radii (9.5, 8.5, and 7.5 A) to scan the peak of the V-grooved standard sample being reduced to one-tenth (1/10) of its size, and use the offset error to inversely find out the regression equation. We analyze how the tip apex as well as the profile of the tip edge oblique angle and the oblique edge angle affects the offset distance. Furthermore, a probe with a larger radius of 9.5 nm is used to simulate and measure the offset error of scan curve, and acquire the regression equation. By the conversion proportion coefficient of size (omega), and revising the size-reduced regression equation during the small size scale, a revised regression equation of a larger size scale can be acquired. The error is then reduced, further enhancing the accuracy of the AFM scanning and measurement.

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“…Molecular simulation is a useful tool to study atomic-scale interactions. It has been used to examine the AFM imaging mechanism, study the factors affecting resolution [16][17][18][19][20][21][22], and establish an appropriate simulation methodology for the explanation of complex imaging mechanism in liquids [23][24][25]. Besides, there has been a recent flurry of researches applying machine learning to AFM, including predicting the molecular structure [26], recognizing and classifying surface features [27][28][29], and fast scanning [30,31].…”

Section: Introductionmentioning

confidence: 99%

Reducing molecular simulation time for AFM images based on super-resolution methods

Dou

Qian

et al. 2021

Beilstein J. Nanotechnol.

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Atomic force microscopy (AFM) has been an important tool for nanoscale imaging and characterization with atomic and subatomic resolution. Theoretical investigations are getting highly important for the interpretation of AFM images. Researchers have used molecular simulation to examine the AFM imaging mechanism. With a recent flurry of researches applying machine learning to AFM, AFM images obtained from molecular simulation have also been used as training data. However, the simulation is incredibly time consuming. In this paper, we apply super-resolution methods, including compressed sensing and deep learning methods, to reconstruct simulated images and to reduce simulation time. Several molecular simulation energy maps under different conditions are presented to demonstrate the performance of reconstruction algorithms. Through the analysis of reconstructed results, we find that both presented algorithms could complete the reconstruction with good quality and greatly reduce simulation time. Moreover, the super-resolution methods can be used to speed up the generation of training data and vary simulation resolution for AFM machine learning.

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Simulation of AFM/LFM by molecular dynamics: role of lateral force in contact-mode AFM imaging

Cited by 12 publications

References 10 publications

Nanoscale Water Contact Angle on Polytetrafluoroethylene Surfaces Characterized by Molecular Dynamics–Atomic Force Microscopy Imaging

Nanoscale Water Contact Angle on Polytetrafluoroethylene Surfaces Characterized by Molecular Dynamics–Atomic Force Microscopy Imaging

Error analysis and regression mode of the V‐grooved sample in the atomic force microscope simulation measurement mode by the molecular mechanics

Reducing molecular simulation time for AFM images based on super-resolution methods

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