Work

Towards Accurate Size Predictions of Magnetic Nanoparticles Using Support Vector Regression

Year: 2025

Type: conference-paper

Abstract: This study explores the size of magnetic nanoparticles (MNP) for applications in Magnetic Resonance Imaging (MRI) and Magnetic Particle Imaging (MPI). Emphasizing the critical role of MNP size on their response to alternating magnetic fields, the study unveils a regression model to optimize MNP synthesis towards tailored sizes of MNP. With a limited and broadly distributed data set at hand, the feasibility of building an accurate predictive model based on Support Vector Machines is shown. Integrating such a model into a continuous synthesis setup establishes a feedback loop, enabling real-time control and adaptation of synthesis parameters.

DOI: 10.18690/um.feri.4.2025.43

Authors: Lukas Glänzer, Lennart Göpfert, Thomas Schmitz-Rode, Ioana Slabu

Institution: RWTH Aachen University

Language: English

Topic: Characterization and Applications of Magnetic Nanoparticles

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Funders: European Commission, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, HORIZON EUROPE European Research Council

Awards: Multifunctional Platform Technology for Magnetically Actuated Controlled Drug Release from Biodegradable Scaffolds, MRTgestützte Materialprüfung biodegradierbarer Hybridmaterialien mit inkorporierten magnetischen Nanopartikeln für InvivoAnwendungen

OpenAlex ID: W4410375377

FWCI:

Cites: 11

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Related to: 10