What is it about?
The magnetic field around a moving magnetic particle enables tracking its location and rotation. This capability allows for the study and understanding of underlying forces in physical systems such as fluidized beds and mixing systems. Our work demonstrates that neural networks can be effectively trained to track the location and rotation of a magnetic particle.
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Why is it important?
The trained networks can process data at high speeds with great accuracy, leading to two key benefits: 1. Sensors can have an increased sampling frequency, resulting in better data resolution. 2. This capability allows for real-time monitoring of the particle.
Perspectives
I hope this article sparks greater interest in the magnetic particle tracking technique. It is easy to set up and perform, does not require special expertise, and is economically viable.
Mohit Nahar Prashanth
University of Kansas
Read the Original
This page is a summary of: A neural network-based algorithm for the reconstruction and filtering of single particle trajectory in magnetic particle tracking, Review of Scientific Instruments, May 2024, American Institute of Physics,
DOI: 10.1063/5.0183533.
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