Building up accurate atomistic models of biofunctionalized magnetite nanoparticles from first-principles calculations

IF 9.4 1区 材料科学 Q1 CHEMISTRY, PHYSICAL npj Computational Materials Pub Date : 2025-01-25 DOI:10.1038/s41524-024-01476-3
Paulo Siani, Enrico Bianchetti, Cristiana Di Valentin
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Abstract

Biofunctionalized magnetite nanoparticles offer unique multifunctional capabilities that can drive nanomedical innovations. Designing synthetic bioorganic coatings and controlling their molecular behavior is crucial for achieving superior performance. However, accurately describing the interactions between bio-inorganic nanosystem components requires reliable computational tools, with empirical force fields at their core. In this work, we integrate first-principles calculations with mainstream force fields to construct and simulate atomistic models of pristine and biofunctionalized magnetite nanoparticles with quantum mechanical accuracy. The practical implications of this approach are demonstrated through a case study of PEG (polyethylene glycol)-coated magnetite nanoparticles in physiological conditions, where we investigate how polymer chain length, in both heterogeneous and homogeneous coatings, impacts key functional properties in advanced nanosystem design. Our findings reveal that coating morphology controls polymer ordering, conformation, and polymer corona hydrogen bonding, highlighting the potential of this computational toolbox to advance next-generation magnetite-based nanosystems with enhanced performance in nanomedicine.

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来源期刊
npj Computational Materials
npj Computational Materials Mathematics-Modeling and Simulation
CiteScore
15.30
自引率
5.20%
发文量
229
审稿时长
6 weeks
期刊介绍: npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings. Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.
期刊最新文献
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