Work

Navigating predictions at nanoscale: a comprehensive study of regression models in magnetic nanoparticle synthesis

Year: 2024

Type: article

Abstract: root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and standard deviation of residuals. Support vector regression (SVR) exhibited the lowest RMSE values of 3.44 and a standard deviation for the residuals of 5.13. SVR demonstrated a favorable balance between accuracy and consistency among these methods. Qualitative factors like adaptability to online learning and robustness against outliers were additionally considered. Altogether, SVR emerged as the most suitable approach to predict MNP sizes due to its ability to continuously learn from new data and resilience to noise, making it well-suited for real-time applications with varying data quality. In this way, a feasible optimization framework for automated and self-regulated MNP synthesis was implemented. Key challenges included the limited dataset size, potential violations of modeling assumptions, and sensitivity to hyperparameters. Strategies like data regularization, correlation analysis, and grid search for model hyperparameters were employed to mitigate these issues.

Source: Journal of Materials Chemistry B

DOI: 10.1039/d4tb02052a

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

Institution: RWTH Aachen University

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: European Commission, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, H2020 European Research Council

Awards: G5555948971, MRTgestützte Materialprüfung biodegradierbarer Hybridmaterialien mit inkorporierten magnetischen Nanopartikeln für InvivoAnwendungen, Verbundprojekt: Validierung des Innovationspotentials nanomodifizierter Stents zur hyperthermischen Behandlung von stenosierenden Tumoren - ProNano 2.0, Teilvorhaben: Validierung der Nanopartikelherstellung, magnetischen Hyperthermie und ihrer therapeutischen Wirksamkeit