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Atomic Force Microscopy

Atomic Force Microscopy

Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
The AFM Probe
The probe is regarded as the heart of any AFM setup and comprises the...

Atomic Structure

Atomic Structure

The Energies of Atomic Orbitals

The Energies of Atomic Orbitals

In an atom, the negatively charged electrons are attracted to the positively charged nucleus. In a multielectron atom, electron-electron repulsions are also observed. The attractive and repulsive forces are dependent on the distance between the particles, as well as the sign and magnitude of the charges on the individual particles. When the charges on the particles are opposite, they attract each other. If both particles have the same charge, they repel each other.

Subatomic Particles

Subatomic Particles

Dalton was only partially correct about the particles that make up matter. All matter is composed of atoms, and atoms are composed of three smaller subatomic particles: protons, neutrons, and electrons. These three particles account for the mass and the charge of an atom.

The Quantum-Mechanical Model of an Atom

The Quantum-Mechanical Model of an Atom

Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra.

Atomic Orbitals

Atomic Orbitals

An atomic orbital represents the three-dimensional regions in an atom where an electron has the highest probability to reside. The radial distribution function indicates the total probability of finding an electron within the thin shell at a distance r from the nucleus. The atomic orbitals have distinct shapes which are determined by l, the angular momentum quantum number. The orbitals are often drawn with a boundary surface, enclosing densest regions of the cloud.

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Application of Atomic Force Microscopy to Detect Early Osteoarthritis

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The Hessian Blob Algorithm: Precise Particle Detection in Atomic Force Microscopy Imagery.

Brendan P Marsh^1,2, Nagaraju Chada¹, Raghavendar Reddy Sanganna Gari^1,3

¹Department of Physics and Astronomy, University of Missouri, Columbia, Missouri, 65211, United States of America.

Scientific Reports

|January 19, 2018

Summary

This summary is machine-generated.

A new Hessian blob algorithm improves atomic force microscopy (AFM) image analysis by accurately detecting biomolecules. This method offers precise particle detection without manual preprocessing, overcoming limitations of conventional techniques.

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Area of Science:

Biophysics
Nanotechnology
Microscopy

Background:

Atomic force microscopy (AFM) provides high-resolution biological imaging.
Accurate analysis of AFM images relies on robust particle detection.
Conventional methods like threshold and watershed algorithms require manual preprocessing and yield imprecise, parameter-dependent results.

Purpose of the Study:

To introduce a novel algorithm for accurate biomolecule detection in AFM images.
To address the limitations of conventional particle detection methods in AFM analysis.
To provide a stable and precise framework for analyzing biomolecules from large-scale AFM images.

Main Methods:

Development of the Hessian blob algorithm, integrating a scale-space framework with local image curvature.
Formal definition of particle centers and boundaries to subpixel precision.
Direct comparison of the Hessian blob algorithm against conventional AFM particle detection techniques.

Main Results:

The Hessian blob algorithm accurately detects biomolecules, outperforming conventional methods.
Particle boundaries determined by the Hessian blob are independent of user-defined parameters.
The algorithm demonstrates robustness against common imaging artifacts and noise.

Conclusions:

The Hessian blob algorithm offers a significant advancement in AFM image analysis for biomolecules.
It provides precise, reproducible particle detection without manual image preprocessing.
This method establishes a stable framework for reliable biomolecular analysis using AFM.