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تسجيل مستخدم جديدElectrostatic Discovery Atomic Force Microscopy
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While offering unprecedented resolution of atomic and electronic structure, Scanning Probe Microscopy techniques have found greater challenges in providing reliable electrostatic characterization at the same scale. In this work, we introduce Electrostatic Discovery Atomic Force Microscopy, a machine learning based method which provides immediate quantitative maps of the electrostatic potential directly from Atomic Force Microscopy images with functionalized tips. We apply this to characterize the electrostatic properties of a variety of molecular systems and compare directly to reference simulations, demonstrating good agreement. This approach opens the door to reliable atomic scale electrostatic maps on any system with minimal computational overhead.
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We report a new experimental technique for Kelvin probe force microscopy (KPFM) using the dissipation signal of frequency modulation atomic force microscopy for bias voltage feedback. It features a simple implementation and faster scanning as it requ
ires no low frequency modulation. The dissipation is caused by the oscillating electrostatic force that is coherent with the tip oscillation, which is induced by a sinusoidally oscillating voltage applied between the tip and sample. We analyzed the effect of the phase of the oscillating force on the frequency shift and dissipation and found that the relative phase of 90$^circ$ that causes only the dissipation is the most appropriate for KPFM measurements. The present technique requires a significantly smaller ac voltage amplitude by virtue of enhanced force detection due to the resonance enhancement and the use of fundamental flexural mode oscillation for electrostatic force detection. This feature will be of great importance in the electrical characterizations of technically relevant materials whose electrical properties are influenced by the externally applied electric field as is the case in semiconductor electronic devices.
We report a Kelvin probe force microscopy (KPFM) implementation using the dissipation signal of a frequency modulation atomic force microscopy that is capable of detecting the gradient of electrostatic force rather than electrostatic force. It featur
es a simple implementation and faster scanning as it requires no low frequency modulation. We show that applying a coherent ac voltage with two times the cantilever oscillation frequency induces the dissipation signal proportional to the electrostatic force gradient which depends on the effective dc bias voltage including the contact potential difference. We demonstrate the KPFM images of a MoS$_2$ flake taken with the present method is in quantitative agreement with that taken with the frequency modulated Kelvin probe force microscopy technique.
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 aromatic molecule
s, due to difficulties with interpretation of highly distorted AFM images originating from non-planar molecules. Here we develop a deep learning infrastructure that matches a set of AFM images with a unique descriptor characterizing the molecular configuration, allowing us to predict the molecular structure directly. We apply this methodology to resolve several distinct adsorption configurations of 1S-camphor on Cu(111) based on low-temperature AFM measurements. This approach will open the door to apply high-resolution AFM to a large variety of systems for which routine atomic and chemical structural resolution on the level of individual objects/molecules would be a major breakthrough.
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The Transient Fluctuation Theorem is used to calibrate an Atomic Force Microscope by measuring the fluctuations of the work performed by a time dependent force applied between a collo{i}dal probe and the surface. From this measure one can easily extr
act the value of the interaction force and the relevant parameters of the cantilever. The results of this analysis are compared with those obtained by standard calibration methods. a) present adress: ISIS, Univ.
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