Atomic force microscopy is an impressive tool with which to directly resolve the bonding structure of organic compounds. The methodology usually involves chemical passivation of the probe-tip termination by attaching single molecules or atoms such as CO or Xe (refs ). However, these probe particles are only weakly connected to the metallic apex, which results in considerable dynamic deflection. This probe particle deflection leads to pronounced image distortions, systematic overestimation of bond lengths, and in some cases even spurious bond-like contrast features, thus inhibiting reliable data interpretation. Recently, an alternative approach to tip passivation has been used in which slightly indenting a tip into oxidized copper substrates and subsequent contrast analysis allows for the verification of an oxygen-terminated Cu tip. Here we show that, due to the covalently bound configuration of the terminal oxygen atom, this copper oxide tip (CuOx tip) has a high structural stability, allowing not only a quantitative determination of individual bond lengths and access to bond order effects, but also reliable intermolecular bond characterization. In particular, by removing the previous limitations of flexible probe particles, we are able to provide conclusive experimental evidence for an unusual intermolecular N-Au-N three-centre bond. Furthermore, we demonstrate that CuOx tips allow the characterization of the strength and configuration of individual hydrogen bonds within a molecular assembly.
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http://dx.doi.org/10.1038/s41565-018-0104-4 | DOI Listing |
Microsc Res Tech
January 2025
School of Electrical & Control Engineering, Shenyang Jianzhu University, Shenyang, China.
The atomic force microscope (AFM) image will be inclined and bent due to the tilt angle between the probe and the sample surface. When the least squares fitting method is used to correct the horizontal distortion of the AFM image, the shape structure that is lower or higher than the sample base will affect the final fitting correction result. In view of the limitations of existing methods and the diversity of AFM images, an AFM image level distortion correction method based on automatic feature marking is proposed.
View Article and Find Full Text PDFCureus
December 2024
Periodontology, SRM Kattankulathur Dental College and Hospital, SRM Institute of Science and Technology, Chengalpattu, IND.
Introduction: To evaluate the enamel abrasion effects of soft, ultra-soft, and nano-bristle toothbrushes using atomic force microscopy (AFM) to guide toothbrush selection for optimal enamel preservation.
Methods: This in vitro study involved 45 extracted human teeth (central and lateral incisors), randomly assigned to three groups (n=15 each): Group I (nano-bristle), Group II (ultra-soft bristle), and Group III (soft bristle). Each specimen underwent 10,000 brushing cycles with a standardized 2 N force to simulate one year of brushing.
Front Behav Neurosci
December 2024
Department of Biological Sciences, Lehigh University, Bethlehem, PA, United States.
Introduction: Anxiety disorders are among the most common mental illnesses in the US. An estimated 31.1% of U.
View Article and Find Full Text PDFACS Nano
January 2025
Institute of Physics and Astronomy, University of Potsdam, 14476 Potsdam-Golm, Germany.
The reduced dimensionality of thin transition metal dihalide films on single-crystal surfaces unlocks a diverse range of magnetic and electronic properties. However, achieving stoichiometric monolayer islands requires precise control over the growth conditions. In this study, we employ scanning probe microscopy to investigate the growth of MnI on Ag(111) via single-crucible evaporation.
View Article and Find Full Text PDFJ Phys Condens Matter
January 2025
Universidade Federal de Santa Maria, Departamento de Física, Santa Maria, RS, 97105-900, BRAZIL.
The study of emerging contaminants (ECs) in water resources has garnered significant attention due to their potential risks to human health and the environment. This review examines the contribution from computational approaches, focusing on the application of machine learning (ML) and molecular dynamics (MD) simulations to understand and optimize experimental applications of ECs adsorption on carbon-based nanomaterials. Condensed matter physics plays a crucial role in this research by investigating the fundamental properties of materials at the atomic and molecular levels, enabling the design and engineering of materials optimized for contaminant removal.
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