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Cited by 488

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Structure–Relaxivity Relationships of Magnetic Nanoparticles for Magnetic Resonance Imaging

Open access
Zhou, Zijian, Yang, Lijiao, Gao, Jinhao, Chen, Xiaoyuan·2019·Advanced Materials

Abstract

Magnetic nanoparticles (MNPs) have been extensively explored as magnetic resonance imaging (MRI) contrast agents. With the increasing complexity in the structure of modern MNPs, the classical Solomon–Bloembergen–Morgan and the outer‐sphere quantum mechanical theories established on simplistic models have encountered limitations for defining the emergent phenomena of relaxation enhancement in MRI. Recent progress in probing MRI relaxivity of MNPs based on structural features at the molecular and atomic scales is reviewed, namely, the structure–relaxivity relationships, including size, shape, crystal structure, surface modification, and assembled structure. A special emphasis is placed on bridging the gaps between classical simplistic models and modern MNPs with elegant structural complexity. In the pursuit of novel MRI contrast agents, it is hoped that this review will spur the critical thinking for design and engineering of novel MNPs for MRI applications across a broad spectrum of research fields.

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Crossref · 10.1002/adma.201804567

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Metadata

Authors
Zhou, Z., Yang, L., Gao, J., & Chen, X.
Venue
Advanced Materials
Publisher
Wiley
Published
2019-01-02
Volume
31
Issue
8
Pages
e1804567-e1804567
ISSN
  • 0935-9648 (ISSN-L)
  • 1521-4095
OpenAlex
W2907202911
Cited by
488
References
15
FWCI
18.16
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Structure–Relaxivity Relationships of Magnetic Nanoparticles for Magnetic Resonance Imaging. https://app.cochat.ai/papers/10.1002/adma.201804567
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Zhou, Z., Yang, L., Gao, J., & Chen, X. (2019). Structure–Relaxivity Relationships of Magnetic Nanoparticles for Magnetic Resonance Imaging. Advanced Materials. https://doi.org/10.1002/adma.201804567

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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