The Roles of Morphology on the Relaxation Rates of Magnetic

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The Roles of Morphology on the Relaxation Rates of Magnetic Nanoparticles Lijiao Yang,† Zhenyu Wang,‡ Lengceng Ma,§ Ao Li,† Jingyu Xin,† Ruixue Wei,† Hongyu Lin,† Ruifang Wang,‡ Zhong Chen,§ and Jinhao Gao*,† †

State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, The Key Laboratory for Chemical Biology of Fujian Province, and iChEM, College of Chemistry and Chemical Engineering, ‡Department of Physics, College of Physical Science and Technology, and §Department of Electronic Science, Fujian Key Laboratory of Plasma and Magnetic Resonance, College of Physical Science and Technology, Xiamen University, Xiamen 361005, China S Supporting Information *

ABSTRACT: The shape of magnetic nanoparticles is of great importance in determining their contrast abilities for magnetic resonance imaging. Various magnetic nanoparticles have been developed to achieve high T1 or T2 relaxivities, but the mechanism on how morphology influences the water proton relaxation process is still unrevealed. Herein we synthesize manganesedoped iron oxide (MnIO) nanoparticles of the same volume with six different shapes and reveal the relationship between morphologies and T1/T2 relaxation rates. The morphology of magnetic nanoparticles largely determines the effective radius and the gradient of stray field, which in turn affects the transverse relaxation rate. The longitudinal relaxivity has positive correlation with the surface-area-to-volume ratio and the occupancy rate of effective metal ions on exposed surfaces of magnetic nanoparticles. These findings together with the summary of r2/r1 ratios could help to guide the screening for the optimal shapes of promising T1 or T2 contrast agents. Varying effective radii could be utilized to change negative contrast abilities. The surface-area-to-volume ratio and the amount of effective metal ions on exposed surface are instrumental for tuning positive contrast abilities. These principles could serve as guidelines for design and development of high-performance nanoparticle-based contrast agents. KEYWORDS: morphology, effective radius, T1/T2 relaxivities, magnetic nanoparticles, magnetic resonance imaging

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systematic understanding of the relationship between shapes and relaxivities of MNPs. In the motional average regime (MAR),20 the traditional quantum mechanical outer-sphere theory21 indicates that the T2 relaxivity is highly dependent on the proton’s effective diffusion and the saturation magnetization (Ms) of MNPs. However, this theory is based on the ideal spherical model and perhaps not applicable to other MNPs which have more sophisticated structures or anisotropic morphologies. The Solomon, Bloembergen, and Morgan (SBM) theory22 has well established the mechanism of relaxation for metal complex-based T1 CAs. But it would be problematic to extend this theory to NP-based T1 CAs due to the uncertainty in chemical coordination and the complexity of surface structures. Therefore, it is urgent to develop a perspective on the anisotropic-shaped MNPs and their T1/T2 relaxivities, which will be of great importance for flourishing a fundamental

agnetic nanoparticles (MNPs) have been extensively developed as contrast agents (CAs) for magnetic resonance imaging (MRI) to improve the sensitivity of imaging and diagnosis.1−3 Iron oxide-based nanoparticles (NPs) are one of the most important MNPs for MRI and have been used in clinic due to their high biocompatibility.4,5 In principle, iron oxide NPs can shorten both T1 and T2 relaxation times of water protons in their vicinity and produce T1 and T2 contrast signals. The features of iron oxide NPs, such as size, dopant, crystal structure, magnetic property, and surface structure, can affect the contrast ability. Among them, the shape (morphology) plays a vital role in influencing T1 and T2 contrast enhancement effects of iron oxide NPs.6−8 Previous research reported experimental investigation and modeling of shapedependent relaxivity in nanocrystalline contrast agents.9−12 Recently, a large number of iron oxide NPs with different morphologies, including plates,13 cubes,14 octapods,15 hollow,16,17 and core−shell structures,18,19 have been reported for development of MRI CAs. However, there are few comprehensive investigations on the mechanism of how morphology influences the water proton relaxation process. As of now, we still lack a © XXXX American Chemical Society

Received: February 7, 2018 Accepted: April 19, 2018 Published: April 19, 2018 A

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The local gradients of the stray field perturb the magnetic relaxation and dephasing processes of the water protons nearby, shortening the spin−spin relaxation time.27,28 Considering the fact that non-ellipsoidal MNPs have high T2 relaxivities,29 we reason that MNPs with distinct shapes generate the stray field of characteristic local gradients under the background field, which affect the speed of proton’s dephasing and efficient diffusion process in the surrounding area. Our three-dimensional micromagnetic calculations on the MNPs of various shapes elucidate the spatial variation of the stray field, which provides strong evidence on how the shapes of MNPs influence the spin−spin relaxation process. In the stray field of MNPs, protons may undergo several possible dephasing and diffusion routes surrounding the NPs (Figure 3a, the several paths), and only the routes with varying field gradients are considered as efficient diffusion. The geometry of MNPs defines their magnetic shape anisotropy,30 which is an important factor in characterizing the spatial distribution (intensity, direction, and gradient) of the magnetic stray field generated by the NPs. We calculated the spatial distribution of this stray field and summarized the results in Figure 3b (for details see LLG simulations and calculations in Supporting Information). The shape, intensity, and gradient of the stray field are all different for these NPs because of their distinct shape anisotropy. Evidently the stray field of the octapod has both the highest intensity and spatial non-uniformity due to its largest shape anisotropy and thus produces the greatest influence on water proton diffusion and dephasing. In contrast, being the most symmetric of the six shapes in this study, the sphere creates the weakest stray field and least perturbation on the relaxation and dephasing processes of the water protons. For MNPs with distinct shapes, their magnetizations prefer to align with the longest axis of the particle to minimize the magnetic surface charges and the magnetostatic energy of the system.31 Consequently, the magnetic easy direction is along the longer axis of the particle, and the opposite is true for the magnetic hard direction. For non-ellipsoidal particles, the shape anisotropy coefficient (Ksh) can be approximately expressed as Ksh = [(N2 − N1)Ms]μ0Ms/2, where N2 and N1 are the demagnetization factors along the hard and easy directions.32,33 We measured the hysteresis loops of these MnIO NPs of six different shapes at 300 K. The calculations (Table S5) and the magnifying images (Figure S5) show the slopes of magnetic hysteresis loops (equal to the magnetic susceptibility) of the MNPs in low magnetic fields. Our results indicate that their magnetic susceptibility ranks down in the order of octapods, rhombohedra, tetrahedrons, plates, cubes, and spheres (Figure 3c). Because the demagnetization factor is the reciprocal of the hysteresis slope, it ranks in the opposite order.34 Our results clearly show that, under the background magnetic field, the NPs align long axis (easy axis,35 e.g., long body diagonal for rhombohedron) with the field direction so as to minimize both the Zeeman and magnetostatic energies of the system (Figure 3c). This result is in good agreement with the previous studies on the one-dimensional nanorods and nanowires.36,37 Because these NPs are of the same volume, the length of the body diagonal (effective diameter under a magnetic field, denoted as d) for each shape can qualitatively characterize the geometric aspect ratio, thus the demagnetization factor of these samples. Then we define that the effective radius (r*) equals onehalf of the effective diameter. Particles with a sufficient polymer layer may overcome interparticle interactions and resist linear aggregation in magnetic fields.38 We chose the sodium citrate

understanding of the relationship between morphology and relaxivity of MNPs. Herein, we chose well-studied manganese-doped iron oxide (MnIO) NPs as research subjects and fabricated six uniform samples with typical morphologies: spheres, cubes, plates, tetrahedrons, rhombohedra, and octapods. These NPs are of the same geometrical volume in order to evaluate and compare their properties. When Ms values of samples are similar, T2 relaxation rates are mainly dominated by effective radii. A larger effective radius leads to a higher T2 relaxation rate. Nanoparticles with different shapes have distinct effective radii, which play an important role in the intensity of stray fields and the local field inhomogeneity induced by NPs, resulting in the diverse water diffusion processes, thus eventually determine the transverse relaxation rates. The surface-area-to-volume ratio (S/V) and exposed crystal facets are the main contributors to T1 relaxation rate, with the number of effective metal ions on the surface being the key for T1 relaxation. These factors affect proton T1 relaxation by altering the chemical exchange between water molecules and metal ions on the surface of MNPs. We could also screen for optimized T1 or T2 CAs in these samples by comparing their T1 and T2 relaxivities. This work gives an insightful understanding of the processes of T1 and T2 relaxation by anisotropic-shaped MNPs, opening a vision for the development of next-generation NP-based CAs.

RESULTS AND DISCUSSION Controlled Synthesis and Characterization. We synthesized MnIO (Mn/Fe ratio is 1/6, the optimized ratio provides high relaxivities)23 of different morphologies using a one-pot synthesis method of iron oleate decomposition (details in Experimental Section). The Mn/Fe ratios of these samples were measured by inductively coupled plasma atomic emission spectroscopy (ICP-AES, Supporting Information and Table S2). Transmission electron microscopy (TEM) images (Figure 1a−f and Figure S1) showed that the NPs of six shapes are uniform with high yield (>90%). They are spheres (diameter of 15 nm), cubes (side length of 12 nm), plates (hexagonal, side length of 12 nm and thickness of 5 nm), tetrahedrons (regular, side length of 25 nm), rhombohedra (oblique parallelepiped, side length of 13.5 nm with a tilt angle of 60°), and octapods (average edge length between two nearby arms of 30 nm and each corner angle of 40°). Their geometrical volumes are comparable (Figure 1g and Table S3), but the surface areas are significantly different (Figure 1h and Table S4). The high-resolution TEM (HRTEM) images (Figure S2) show clear lattice distances of 0.30 nm to the (220), 0.49 nm attributed to the (111), and 0.26 nm attributed to the (311) facets of inverse spinel manganese doped magnetite. The lattice distances are slightly larger than those of IO due to the doping of Mn(II).23 The structures of these MnIO NPs are further confirmed by comparing their X-ray diffraction (XRD) patterns (Figure S3) with those of inverse spinel Mn0.43Fe2.57O4 (JCPDS no. 01−089−2807) and IO NPs of magnetite (JCPDS no. 01−088−0315). All the X-ray photoelectron spectroscopy (XPS) spectra (Figure S4) show clear peaks at 710.8 eV (Fe 2p3/2) and 724.0 eV (Fe 2p1/2),24 peaks at 641.2 eV (Mn 2p3/2) and 653.1 eV (Mn 2p1/2),25 indicating the existence of Fe(III) and Mn(II). Furthermore, the energy-dispersive X-ray (EDX) element mapping (Figure 2) demonstrates that Mn(II) ions and Fe(III) ions are evenly distributed in MnIO NPs. Stray Field Gradients and Local Field Inhomogeneity. Magnetic nanoparticles create spatially non-uniform stray fields due to the anisotropic nature of magnetic dipole interactions.26 B

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Figure 1. TEM images of monodispersed MnIO (Mn/Fe ratio is about 1/6) NPs with different shapes, (a) spheres (diameter of 15 nm), (b) cubes (side length of 12 nm), (c) plates (hexagonal, side length of 12 nm and thickness of 5 nm), (d) tetrahedrons (regular, side length of 25 nm), (e) rhombohedra (oblique parallelepiped, side length of 13.5 nm with a tilt angle of 60°), and (f) octapods (average edge length between two nearby arms of 30 nm and each corner angle of 40°). (g) The similar geometrical volumes of these MnIO NPs. (h) The different surface areas of these MnIO NPs.

small molecule as a surface stabilizing agent because this simple surface coating makes little augment in the hydrodynamic diameters of NPs, which is important to investigate the effect of morphology on relaxivity of MNPs in this work. The hydrated diameters (number-average diameters) of MnIO NPs (Figure S6, after sodium citrate coating) are 16.36, 22.89, 26.83, 29.32, 35.51, and 38.94 nm for spheres, cubes, hexagonal plates, tetrahedrons, rhombohedra, and octapods, respectively. These results are consistent with the ranking order of demagnetization factor obtained from the hysteresis loops. By aligning the magnetization of MNPs with the body diagonal, the distance between magnetic poles is greater for particles with longer d, thus its magnetostatic energy and the demagnetization factor are smaller. These results are also consistent with the effective diameter (d) and effective radius (r*) (Table S6), which indicates that the concept of the

effective radius (r*) is reasonable. Our micromagnetic calculations clearly illustrate the spatial distribution of the direction and gradient of the stray fields (Figure S7) generated by NPs with different shapes (colors along body diagonal axis display a twodimensional view of the field distribution, rather than the total intensity). Among these NPs, octapods have the strongest stray field owing to their largest effective radius, so their influence on the proton’s dephasing and efficient diffusion process can extend to bigger surrounding areas. Inversely, spheres have the smallest stray field, and their influence on surrounding protons is significantly less in spatial extension. We also calculated the gradients of the stray field with different distances from the MNPs’ surface (Figure 3d). As expected, octapods show the largest gradient, whereas the spheres show the least gradient. The order of their gradients is coincident with the order of their effective radii, that C

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Figure 2. HAADF-STEM images and EDX mapping. From top to bottom, the images are HAADF-STEM, the mapping of Fe (red), Mn (green), and overlapped images (yellow) of MnIO NPs with six typical shapes.

Figure 3. Local field inhomogeneity and stray field gradient induced by magnetic NPs. (a) Scheme of water molecular diffusion and relaxation process around spherical magnetic NPs. The color indicates the intensity of local field induced by magnetic NPs under an external magnetic field (H0). The four arrowed curves represent the possible routes that protons diffuse around MNPs. (b) The spatial distribution of stray field of the six different shapes when the external magnetic field H0 is along the longest diagonal of the MNPs. The color bars illustrate the strength of the stray field. (c) The values of magnetic susceptibility were obtained from the hysteresis loops of the MNPs in the external field range from −50 to 50 Oe at 300 K. The blue arrows indicate the magnetization orientation of the MNPs under magnetic field. The length is the longest body diagonal (2r*) for each shape. (d) The variation of stray field gradient versus the distance from the surface of MNPs. Octapods show the largest gradient and the spheres show the smallest gradient. The order of their gradients is coincident with the order of their magnetic diameters.

is, octapods > rhombohedra > tetrahedrons ≈ hexagonal plates ≈ cubes > spheres. Notably, the shapes with a larger effective diameter also have more and sharper corners ( rhombohedron (4 sharp corners and 4 obtuse corners) > tetrahedron (4 sharp corners) ≈ hexagonal plate (12 obtuse corners) ≈ cube (8 corners) > sphere (0 corners).

The density of surface magnetic charges on these sharp corners is great, which accordingly produce stray fields of high gradient. Our results indicate that the intensity of stray fields produced by MNPs with different shapes is strongly dependent on the effective radius, which in turn affect the proton’s dephasing and diffusion process in the surrounding area (about 3−7 nm distance D

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Figure 4. Relationships among effective radius, saturated magnetization, and T2 relaxivity. (a) The effective radius (r*) and (b) the saturated magnetization (Ms) of MnIO and IO NPs. (c) The T2 relaxivities (r2) of the MnIO and IO NPs at 0.5, 1.5, and 7.0 T. (d) The linear fitting of the ratio of r2 value to the square of saturated magnetization (r2/Ms2) with respect to the square of effective radius (r*). The r2 values were measured at 0.5, 1.5, and 7.0 T. The high linear correlation coefficients indicate that they are in good linear relationships.

427.5 ± 20.4, 465.1 ± 16.6, 508.9 ± 15.2, 708.8 ± 10.5, 772.6 ± 2.1, and 152.2 ± 21.7 mM−1 s−1, respectively, which all show significantly better contrast ability than the commercial T2 contrast agent, Feridex (41 mM−1 s−1 at 1.5 T).43 We also measured the r2 values at 7.0 T (Figure S12), and they were 367.3 ± 7.7, 559.3 ± 14.3, 585.0 ± 13.1, 660.4 ± 19.1, 885.9 ± 6.9, 955.6 ± 20.3, and 215.8 ± 6.2 mM−1 s−1 correspondingly. Notably, the octapods have an ultrahigh r2 value of 955.6 mM−1 s−1, which is almost 10 times higher than that of Feraheme (97.8 ± 1.8 mM−1 s−1, Figure S13), an approved MRI contrast agent in clinical practice. The T2 relaxivities show an upward tendency from spheres to octapods under three different magnetic fields (Figure 4c), which consists with the trends of both effective radii and Ms. To further investigate the relationship of effective radius (r*), saturated magnetization (Ms), and T2 relaxivity (r2), we analyzed their values at three different fields, 0.5, 1.5, and 7.0 T. Indeed, T2 relaxivity has positive correlations with the effective radius r* and saturated magnetization Ms for different shapes of solid MNPs (Table S7). We further analyzed the relationship between r2/Ms2 and r*2 at the three different fields.44 The linear correlation coefficients at 0.5, 1.5, and 7.0 T were 0.962, 0.951, and 0.963 (Figure 4d), respectively, which indicate good linear relationship. We also tried the linear fittings of r2/Ms2 and r* for these samples (Figure S14). The linear correlation coefficients were also high with the values of 0.961 (at 0.5 T), 0.946 (at 1.5 T), and 0.954 (at 7.0 T). These results confirm that effective radius and saturated magnetization can eventually determine T2 relaxivities, that is, a high r* and/or Ms could lead to a high r2

from the surface) and eventually influence the transverse relaxation rate. Relationship between Morphology and T2 Relaxivity of MNPs. We synthesized 15 nm IO spheres as a control subject (TEM image see Figure S8). As previously mentioned, effective radius (r*) is the half length of the body diagonal for each sample (Figure 4a). The r*’s of spheres (7.5 nm), cubes (10.4 nm), plates (12.3 nm), tetrahedrons (15.3 nm), rhombohedra (16.2 nm), and octapods (18.4 nm) MnIO were all carefully calculated (Table S7). The effective radii show a rising trend from spheres to octapods. Magnetic hysteresis (M−H) curves suggest that all MnIO NPs exhibit a typical superparamagnetic property at 300 K (Figure S9) with low coercivity of (111) ≈ (311) > (100) (Figure S23). As a result, the cubes with six (100) facets show a relatively low r1 value, and the rhombohedra with six (311) facets showed a medium r1 value (Figure S24). The high r1 values of plates and tetrahedrons (Table S10) are probably because the exposed (111) and (110) surfaces of plates, and four (111) surfaces of tetrahedrons can provide more effective metal ions for chemical exchange with water protons, which enhances the T1 contrast ability.55 The octapods do not show an ultrahigh r1 value probably due to the exposed surfaces of (311). Moreover, the corners may not be as sharp as theoretical calculations. It is further noted that r1 values are closely related to the total numbers of effective metals on all exposed facets for these shapes (Figure 6d), which demonstrates a positive logarithmic relationship (see Supporting Information). The T1-weighted phantom imaging (Figure 6e) at the clinical field of 1.5 T confirms that plates and tetrahedrons show better T1 contrast enhancement effects than other samples.

of MNPs. This study would also be applicable to other solid shapes, such as octahedrons, dumbbell, disks, or nanorods. More sophisticated MNPs (e.g., core−shell, hollow, and cluster structures) may need the effective radii with the volume fraction redefined.44 The r2/r1 ratio is an important factor to predict which contrast agent has T1 or T2 dominated contrast ability for MRI.56 We calculated the r2/r1 ratios of these MnIO NPs at the clinical field of 1.5 T. Particularly, the r2/r1 ratio of plates is the smallest, and the r2/r1 ratio of octapods is the largest (Table S11). This result indicates that the thin plates may be favorable for T1-weighted imaging and the octapods are promising T2 contrast agents (Figure S25). In summary, we studied the relationship between morphologies and T1/T2 relaxation rates using solid MnIO NPs of the same geometric volume as research subjects. In the transverse relaxation process, MNPs with different shapes generate a distinct stray field gradient under the background field, then affect the speed of the proton’s dephasing and the efficient diffusion process in the surrounding area, and finally determine T2 relaxivities. We also proposed the concept of effective radius, which is a key parameter to predict the r2 values of distinctly shaped NPs. T1 relaxivities are closely related to S/V and the exposed facets by regulating chemical exchange between MNPs and water molecules. The number of effective metal ions on exposed facets is a critical index to evaluate r1 values. These findings are extremely helpful for us to better understand the relationship between shapes of MNPs and their relaxation rates, more importantly, to semiquantitatively and even quantitatively predict the T1/T2 relaxivities of given MNPs. We believe that this study offers essential guidelines for designing and screening T1 or T2 CAs, which could contribute greatly to rational development of high-performance and multimodal probes for early and sensitive diagnosis in molecular imaging.

CONCLUSIONS Traditional quantum mechanical outer-sphere theory reveals the relationships of T2 relaxivity, saturated magnetization, and the radius of magnetic core, but it is limited to the spherical structures in MRA. Our results are complementary to this theory, as it is applicable to various solid shapes of NPs. In the formula of r2 = (256π2γ2/405)V*Ms2a2/D(1 + L/a), the value of the thickness (L) is equal to zero for solid NPs (not core−shell structure), the volume (V*) is similar for these NPs, the proton gyromagnetic ratio (γ) and the diffusivity of water molecules (D) are constants, so the r2 values are determined by the saturated magnetization (Ms) and the radius of core (a). Our study indicates that the T2 relaxation rate, accurately, has a positive correlation with saturated magnetization and effective radius (proportional to Ms2r*2). In other words, the outer-sphere theory and our experimental results both indicate that the concept of effective radius is a precise and reasonable parameter to predict transverse relaxation rates. Our work also replenishes the theory of MAR and takes into account the effect of shapes in T2 relaxivities. Morphology plays a key role in the gradient and intensity of stray field induced by MNPs and finally influences the T2 relaxivity. Particularly, under an external magnetic fields (H0), the shaped anisotropic MNPs can generate more inhomogeneous local magnetic fields than spherical ones.15 In the longitudinal relaxation process, T1 relaxivities are affected by the surface-area-to-volume ratio and exposed faces due to the different shapes of NPs. The phenomena we observed using six typical shapes are enough to provide comprehensive investigation on the relationship between relaxation rates and shapes

EXPERIMENTAL SECTION Preparation of MnIO and IO Nanoparticles. We used a modified one-pot synthesis method57 to prepare MnIO (Mn:Fe = 1:6) NPs. 0.903 g of iron oleate, 0.104 g of manganese oleate, and 0.186 mL of oleic acid were mixed in 15 mL of 1-octadecene. The mixture was heated and refluxed for 2 h before cooling to room temperature. We strictly controlled the amount of sodium oleate, oleic acid, and heating temperature to prepare MnIO with different shapes. For more details, see Supporting Methods and Table S1. Then the products were separated by centrifugation, washed with ethanol for three times, and dispersed in hexane for further use. The synthesis of IO spheres is similar to the protocol except that manganese oleate was not used as one of the precursors. T1 and T2 Relaxivities Measurement. The water-soluble samples were tested in three different magnetic fields. In the 0.5 T NMI20Analyst NMR system, the T1- and T2-weighted phantom images were acquired by a 2D multislice spin−echo (MSE) sequence: TR/TE = 200/ 2 ms (T1), TR/TE = 2000/40 ms (T2), 512 × 512 matrices. In the 1.5 T HT-MICNMR-60 system, T1- and T2-weighted phantom images were conducted by a spin−echo (SE) sequence: TR/TE = 100/8.3 ms (T1), TR/TE = 5000/37 ms (T2), 128 × 128 matrices, thickness = 0.8 mm, slice = 1. In the Varian 7 T micro MRI, the samples were recorded by T2-weighted fast spin−echo multislice sequence (fSEMS) (TR/TE = 2500/40 ms, 128 × 128 matrices, thickness = 2 mm, slice = 4). In Vivo Liver MRI and Tumor Imaging. All animal experiments were performed according to the protocol approved by Institutional Animal Care and Use Committee of Xiamen University. The experiments were carried out with BALB/c mice on a Varian 7 T micro MRI scanner. The parameters of fSEMS sequence for transverse planes in liver: TR/TE = 2500/32.8 ms, thickness = 1 mm, averages = 4, H

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ACS Nano FOV = 40 × 40 mm. The parameters for sagittal plane for tumor imaging: TR/TE = 2500/40 ms, thickness = 1.5 mm, slice = 8.

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ASSOCIATED CONTENT S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.8b01048. Experimental procedures, characterizations (TEM images, XRD patterns, XPS spectra, M−H curves, and DLS analysis), T1 and T2 relaxivity measurements, in vitro tests and in vivo imaging, magnetic simulations, and other theoretical calculations (PDF)

AUTHOR INFORMATION Corresponding Author

*E-mail: [email protected]. ORCID

Zhong Chen: 0000-0002-1473-2224 Jinhao Gao: 0000-0003-3215-7013 Notes

The authors declare no competing financial interest.

ACKNOWLEDGMENTS We thank Mr. Jonathan Richmond at Newcastle University for language editing. This work was supported by National Natural Science Foundation of China (21771148, 21602186, 21521004, and 81430041), National Key Basic Research Program of China (2014CB744502), IRT_17R66, and Fundamental Research Funds for the Central Universities (20720180033, 20720170088, 20720170020, and 20720160074). REFERENCES (1) Angelovski, G. Heading toward Macromolecular and Nanosized Bioresponsive MRI Probes for Successful Functional Imaging. Acc. Chem. Res. 2017, 50, 2215−2224. (2) Ho, D.; Sun, X.; Sun, S. Monodisperse Magnetic Nanoparticles for Theranostic Applications. Acc. Chem. Res. 2011, 44, 875−882. (3) Reddy, L. H.; Arias, J. L.; Nicolas, J.; Couvreur, P. Magnetic Nanoparticles: Design and Characterization, Toxicity and Biocompatibility, Pharmaceutical and Biomedical Applications. Chem. Rev. 2012, 112, 5818−5878. (4) Wu, L.; Mendoza-Garcia, A.; Li, Q.; Sun, S. Organic Phase Syntheses of Magnetic Nanoparticles and Their Applications. Chem. Rev. 2016, 116, 10473−10512. (5) Ling, D.; Lee, N.; Hyeon, T. Chemical Synthesis and Assembly of Uniformly Sized Iron Oxide Nanoparticles for Medical Applications. Acc. Chem. Res. 2015, 48, 1276−1285. (6) Smith, B. R.; Gambhir, S. S. Nanomaterials for In Vivo Imaging. Chem. Rev. 2017, 117, 901−986. (7) Lee, N.; Yoo, D.; Ling, D.; Cho, M. H.; Hyeon, T.; Cheon, J. Iron Oxide Based Nanoparticles for Multimodal Imaging and Magnetoresponsive Therapy. Chem. Rev. 2015, 115, 10637−10689. (8) Zhou, Z.; Zhu, X.; Wu, D.; Chen, Q.; Huang, D.; Sun, C.; Xin, J.; Ni, K.; Gao, J. Anisotropic Shaped Iron Oxide Nanostructures: Controlled Synthesis and Proton Relaxation Shortening Effects. Chem. Mater. 2015, 27, 3505−3515. (9) Basini, M.; Orlando, T.; Arosio, P.; Casula, M. F.; Espa, D.; Murgia, S.; Sangregorio, C.; Innocenti, C.; Lascialfari, A. Local Spin Dynamics of Iron Oxide Magnetic Nanoparticles Dispersed in Different Solvents with Variable Size and Shape: A 1H NMR Study. J. Chem. Phys. 2017, 146, 034703. (10) Gillis, P.; Roch, A.; Brooks, R. A. Corrected Equations for Susceptibility-Induced T2-Shortening. J. Magn. Reson. 1999, 137, 402− 407. I

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DOI: 10.1021/acsnano.8b01048 ACS Nano XXXX, XXX, XXX−XXX