Frequency and Amplitude Optimizations for Magnetic Particle Spectroscopy Applications

Nowadays, there is a growing interest in the field of magnetic particle spectroscopy (MPS)-based bioassays. MPS monitors the dynamic magnetic response of surface-functionalized magnetic nanoparticles (MNPs) upon excitation by an alternating magnetic field (AMF) to detect various target analytes. This technology has flourished in the past decade due to its low cost, low background magnetic noise interference from biomatrix, and fast response time. A large number of MPS variants have been reported by different groups around the world, with applications ranging from disease diagnosis to foodborne pathogen detection, and virus detection. However, there is an urgent need for guidance on how to optimize the sensitivity of MPS detection by choosing different types of MNPs, AMF modalities, and MPS assay strategies (i.e., volume- and surface-based assays). In this work, we systematically study the effect of AMF frequencies and amplitudes on the responses of single- and multi-core MNPs under two extreme conditions, namely, the bound and unbound states. Our results show that some modalities such as dual-frequency MPS utilizing multicore MNPs are more suitable for surface-based bioassay applications, whereas, single-frequency MPS systems using single- or multi-core MNPs are better suited for volumetric bioassay applications. Furthermore, the bioassay sensitivities for these modalities can be further improved by careful selection of AMF frequencies and amplitudes..

Medienart:

Preprint

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

arXiv.org - (2022) vom: 10. Nov. Zur Gesamtaufnahme - year:2022

Sprache:

Englisch

Beteiligte Personen:

Chugh, Vinit Kumar [VerfasserIn]
di Girolamo, Arturo [VerfasserIn]
Krishna, Venkatramana D. [VerfasserIn]
Wu, Kai [VerfasserIn]
Cheeran, Maxim C-J [VerfasserIn]
Wang, Jian-Ping [VerfasserIn]

Links:

Volltext [kostenfrei]

Themen:

000
530
620
Computer Science - Systems and Control
Electrical Engineering and Systems Science - Systems and Control
Physics - Instrumentation and Detectors

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XAR037862022