Water bridge coordination on the metal-rich facets of Gd₂O₃ nanoplates confers high T₁ relaxivity

Abstract

The realization of the nature of water coordination on the solid surfaces may provoke an essential understanding of T₁ relaxation enhancement, especially in nanoparticulate systems. We report herein that the T₁ relaxivity of Gd₂O₃ nanoplates is highly dependent on water coordinating behaviors on different surfaces. Gd₂O₃ nanoplates with metal-rich {100} facets showed an approximately 4-fold higher r₁ value compared to that with oxygen-terminated {111} facets. Density functional theory (DFT) calculations show that the enhanced T₁ relaxivity of Gd₂O₃ {100} nanoplates may be ascribed to the high density of accessible Gd³⁺, fast exchange of water, and more importantly, multicenter (one-to-two) coordination for water molecules with magnetic centers on the metal-rich surface.

---

Introduction

The rise of two-dimensional (2D) nanomaterials has provoked invaluable opportunities for scientists to investigate structure–property relationships in solid state nanochemistry.^1–4 Due to the intriguing electronic and physical properties caused by morphological confinement effects, these 2D nanomaterials have shown unprecedented performance in electronics,^3,5 catalysis,^6–8 energy storage,^9,10 and nanomedicine.^11–13 The classical Solomon–Bloembergen–Morgan (SBM) theory for magnetic resonance imaging (MRI) contrast agents indicates that T₁ relaxation of protons is related to their chemical exchange efficiency in paramagnetic molecular systems.^14,15 However, there is still a major gap to bridge the T₁ relaxivity and water interacting behaviors in nanoparticulate systems. We have recently recognized that iron oxide nanoplates with metal-rich exposed facets showed enhanced T₁ relaxivity, probably due to the more favorable water coordination and chemical exchange on such surfaces compared to spherical nanoparticles.^16,17 One major concern for iron oxide nanoplates is, however, that they are superparamagnetic, and thus the T₁ relaxation enhancement efficiency may be blurrily disturbed by the strong T₂ decaying effect.^18,19 A suitable model to reveal the relationship between the surface structure and the T₁ relaxivity of magnetic nanoparticles is highly desirable, which would arouse great research interest in innovating the design considerations for high-performance MRI contrast agents.^20–25

Traditional theoretic models were established on molecular systems, which only focused on the case that one water molecule (for systems with q = 1) interacts with one paramagnetic metal ion (denoted as one-to-one coordination hereafter).^26–28 For magnetic nanomaterials, however, the packed crystal structure may allow one water molecule to interact with two or more paramagnetic metal ions in their vicinity (multicenter coordination).²⁹ Moreover, a specific surface would permit the fast exchange of water molecules on magnetic centers, thus holding great potential to enhance the T₁ relaxivity. Fortunately, advanced synthetic methodologies allow us to achieve the controlled synthesis of nanomaterials with different surface features.^30,31 We propose here that the metal-rich surface of magnetic nanomaterials could allow water bridging coordination with two magnetic centers (Fig. 1a). Therefore, it is conceivable that the spin-lattice relaxation effects between water molecules and magnetic centers would be significantly enhanced compared with that of the one-to-one situation, which may confer the efficient recovery of proton longitudinal magnetizations within one relaxation time slot (Fig. 1b). Owing to the low magnetic susceptibility and diminished T₂ interference at room temperature, paramagnetic gadolinium oxide (Gd₂O₃) nanoparticles have shown great promise in T₁ contrast imaging.^32,33 Ultrasmall Gd₂O₃ nanoparticles and nanoplates have been reported to show high T₁ relaxivity.^34–36 However, the relationship between the surface structure and the T₁ relaxivity of Gd₂O₃ nanoparticles has rarely been investigated.

Fig. 1 Different phenomena proposed for water coordination on magnetic crystals with different surfaces. (a) Metal-rich surface may permit one-to-two coordination for water, in contrast to traditional one-to-one coordination. (b) Proposed recovery of longitudinal magnetizations for protons with different water coordinating behaviors on solid surfaces.

Herein, we present the successful controlled synthesis of Gd₂O₃ nanoplates with two types of surface exposure, Gd₂O₃{100} and Gd₂O₃{111} facets, respectively. The Gd₂O₃{100} facet is exposed with gadolinium ions at the outermost layer, while the Gd₂O₃{111} facet is terminated by oxygen ions. We illustrated that the metal-rich exposed Gd₂O₃{100} facet plays a decisive role in the enhanced T₁ relaxivity, showing approximately 4-fold higher r₁ values than that of Gd₂O₃{111} nanoplates at different magnetic fields (0.5, 1.5, and 3.0 T). Density functional theory (DFT) calculation confirmed that the water molecule coordinating on the Gd₂O₃{100} facet requires a lower energy than that on the Gd₂O₃{111} facet, indicating a higher coordination efficiency on the Gd₂O₃{100} nanoplates. More importantly, the DFT results also suggested that water hopping and re-coordination on the Gd₂O₃{100} facet require very low transition state energy (0.08 and 0.13 eV, respectively), indicating a distinct mechanism for studying the chemical exchange of water molecules on Gd₂O₃ nanoplates.

Results and discussion

We used gadolinium(III) acetate as the precursor to synthesize Gd₂O₃ nanoplates with {100} facets as the exposed surfaces. A transmission electron microscopy (TEM) image showed that the side length and width are about 120 and 40 nm, respectively (Fig. 2a). A high-resolution TEM (HRTEM) image of a flat nanoplate showed a pair of perpendicularly crossed lattices with a spacing distance of 2.7 Å, which can be matched to the (400) plane of the cubic Gd₂O₃ phase (Fig. 2b). The in-plane fast Fourier transformation (FFT) pattern suggested the [100] zone axis (Fig. 2b, inset). Additionally, the HRTEM image of a perpendicular nanoplate showed interplanar distances of 2.7, 5.4, and 10.8 Å corresponding to the (400), (200), and (100) planes of the cubic Gd₂O₃ phase, respectively, indicating that the obtained Gd₂O₃ nanoplates (named Gd₂O₃{100} square nanoplates) are only one unit cell in thickness (Fig. 2c). It is worth noting that the Gd₂O₃{100} facet is a metal-rich surface terminated by gadolinium ions (Fig. 2d and S1†). We can also tune the length and width of the Gd₂O₃ nanoplates by controlling the molar ratio of the surfactant to the precursor (Fig. S2†). The synthesis of Gd₂O₃{111} nanoplates using gadolinium oleate as the precursor showed a dendritic morphology in the in-plane direction (named Gd₂O₃{111} dendritic nanoplates) with an edge length of about 65 nm (Fig. 2e). The HRTEM image of a flat plate exhibited a lattice spacing distance of 1.9 Å corresponding to the (440) plane of the cubic Gd₂O₃ phase. The in-plane FFT pattern indicated the [111] zone axis (Fig. 2f and inset). The HRTEM image of perpendicular plates further showed the (222) plane with a spacing distance of 3.2 Å (Fig. 2g). Altogether, it is concluded that the obtained nanoplates are exposed with the Gd₂O₃{111} facet on the surfaces. In contrast, the Gd₂O₃{111} facet is terminated by oxygen ions rather than gadolinium ions (Fig. 2h and S1†). The role of sodium oleate during the formation of Gd₂O₃{111} nanoplates is likely to serve as both facet controlling agents in the early stage of nucleation and particle coalescence molecules during the later stage of growth of the Gd₂O₃{111} nanoplates (Fig. S3†).^37,38

Fig. 2 TEM and HRTEM images of (a–c) Gd₂O₃{100} and (e–g) Gd₂O₃{111} nanoplates. The interplanar distances of 2.7, 5.4, 10.8, 1.9, and 3.2 Å are assigned to the (400), (200), (100), (440), and (220) planes of the cubic Gd₂O₃ phase, respectively. The insets show the cartoon models (a, e) and FFT patterns (b, f) corresponding to two nanoplates, respectively. Crystal structure side views of (d) Gd₂O₃{100} and (h) Gd₂O₃{111} facets. (i, j) XRD patterns indicate an enhanced diffraction peak for (400) and (440) planes, corresponding to the Lamer assembled Gd₂O₃{100} and Gd₂O₃{111} nanoplates, respectively.

We then used X-ray diffraction (XRD) patterns to identify the crystalline phase of these two Gd₂O₃ nanoplates. Both Gd₂O₃{100} and Gd₂O₃{111} nanoplates showed a typical cubic phase (JCPDS: 012-0797) rather than a monoclinic structure, which are consistent with those derived from the HRTEM images and FFT patterns. Interestingly, the XRD pattern of the Gd₂O₃{100} nanoplates showed an enhanced diffraction peak at 33.2 degrees corresponding to the (400) planes, probably due to the face-by-face Lamer assembly structure on the substrate for XRD measurements (Fig. 2i and inset).³⁹ Likewise, the Gd₂O₃{111} nanoplates showed an enhanced diffraction peak at 47.5 degrees corresponding to the (440) planes in the XRD pattern (Fig. 2j and inset). These results further confirmed that both Gd₂O₃{100} and Gd₂O₃{111} nanoplates are dominated with an ultrathin plate structure. The X-ray photoelectron spectroscopy (XPS) analysis of the Gd₂O₃ nanoplates revealed two distinctive peaks at binding energies of 142.6 and 1187.3 eV coresponding to Gd 4d and Gd 3d5 transitions, respectively (Fig. S4†).

The hysteresis curves indicated that both Gd₂O₃{100} and Gd₂O₃{111} nanoplates are paramagnetic at 300 K (Fig. 3a). The unsaturated magnetic moments reached 3.4 and 4.4 emu g⁻¹ for the Gd₂O₃{100} and Gd₂O₃{111} nanoplates under a magnetic field of 5 T at 300 K, respectively, indicating typical paramagnetism. When measured at a low temperature of 5 K, the nearly saturated magnetization (M_s) values of the Gd₂O₃{100} and Gd₂O₃{111} nanoplates are about 88.9 and 96.3 emu g⁻¹, respectively (Fig. 3b). It is interesting that the Gd₂O₃{100} nanoplates showed a slight tendency to be saturated at a high field range (3–5 kOe) at low temperatures, indicating a phase transition on such ultrathin nanoplates. This phenomenon was also observed at the hysteresis curves of other ultrathin Gd₂O₃ nanoplates (Fig. S5†). The typical paramagnetism of the obtained Gd₂O₃ nanoplates has also been evidenced by the thermal dependent zero field cooling (ZFC) and field cooling (FC) curves (Fig. S6†).

Fig. 3 (a, b) Magnetic hysteresis (M–H) loops of Gd₂O₃{100} and Gd₂O₃{111} nanoplates at 300 and 5 K. (c) Bar chart shows the T₁ relaxivity for the two nanoplates at 0.5, 1.5, and 3.0 T. (d) MR phantom study of the two nanoplates at 0.5, 1.5, and 3.0 T. Concentrations correspond to Gd³⁺ ions.

We used sodium citrate as a surface modifier to endow Gd₂O₃ nanoplates with thin-layer coating on the surface and make them water-soluble (Fig. S7†), which is in principle extremely important for studying their intrinsic T₁ relaxivity.^16,17 The T₁ contrast performance of the Gd₂O₃ nanoplates was evaluated at three different magnetic fields (0.5, 1.5, and 3.0 T). The Gd₂O₃{111} nanoplates showed relatively low r₁ values of 3.4, 2.6, and 2.7 mM⁻¹ s⁻¹ at 0.5, 1.5, and 3.0 T, respectively (Fig. 3c). For the Gd₂O₃{100} nanoplates, these r₁ values are 14.5, 11.9, and 12.4 mM⁻¹ s⁻¹ at 0.5, 1.5, and 3.0 T, respectively, which are approximately 4-fold higher than those of the Gd₂O₃{111} nanoplates. Consequently, an MR phantom study of the Gd₂O₃{100} nanoplates showed an excellent T₁ contrast with clearly brighter signals as the metal concentration was increased (Fig. 3d). In contrast, the Gd₂O₃{111} nanoplates showed a weak T₁ contrast due to the low T₁ relaxivity under the same conditions.

DFT study has received increasingly broad applications for interpreting and predicting complex behaviors at the atomic scale in chemical and materials sciences, for example water splitting on the surface of nanoparticles.^40,41 Proton T₁ relaxation is highly dependent on the coordination and chemical exchange of water molecules on the surfaces when nanoparticles were employed. The thermodynamic phenomena and kinetic behaviors between water molecules and magnetic centers are of great importance in T₁ contrast efficiency. Therefore, we investigated the water interacting behaviors with crystal surfaces by means of DFT calculation.

The Gd₂O₃{111} facet is terminated with oxygen ions, while Gd³⁺ ions are at the second outermost layer. The Gd₂O₃{111} facet accommodates 16 surface Gd³⁺ ions in one unit cell, 4 of which are six-coordinated and inaccessible for water (Fig. 4a, top view, and Fig. S8†). The remaining 12 Gd³⁺ ions are in five-coordinated configuration, which still have vacancy to coordinate with one water molecule. DFT calculations indicated that the coordinated water molecules can be in the dissociated molecular form. As shown in Fig. 4a, 5 of 12 five-coordinated Gd³⁺ ions (pink dashed circle) could induce the dissociation of H₂O into two –OH groups with the assistance of nearby oxygen atoms, yielding an average adsorption energy of −1.32 eV. On the other hand, water molecules would be weakly adsorbed on the top sites of the other 7 Gd³⁺ ions with an average adsorption energy of −0.75 eV (Fig. 4a, black dashed circle). The high stability for dissociated water indicated extremely low exchange efficiency such that the dissociated water only acts as a ‘spectator’ during the relaxation process. Thus, the density of the exchangeable water on the {111} facet can be estimated to be ∼3.4 per nm² (Fig. S9†).

Fig. 4 Water coordinating behaviors on (a) Gd₂O₃{111} and (b) Gd₂O₃{100} facets (upper: side view, lower: top view) according to DFT calculations. Blue balls represent Gd³⁺ ions with saturated six-coordinated configuration. Black and pink dashed circles represent one-to-one top coordination and dissociated coordination for water molecules on the Gd₂O₃{111} facet, respectively. The red dashed circle represents one-to-two bridge coordination for water molecules on the Gd₂O₃{100} facet.

For the Gd₂O₃{100} facet, there are 8 three-coordinated Gd³⁺ ions in one unit cell, resulting in 8 top sites, 16 bridge sites and 8 hollow sites (Fig. S10†). We found that all these sites are able to be coordinated with water molecules, and the surface is able to accommodate at most 8 water molecules (Fig. 4b, red dashed circle). Test calculations demonstrated that more water addition would lead to multilayer adsorption. For simplicity, we assumed that 8 water molecules occupied the same type sites. According to DFT calculations, the average adsorption energies for the top site, bridge site and hollow site were predicted to be −0.80, −0.74, and −0.81 eV, respectively, indicating that all water molecules on the {100} facet could be highly exchangeable (Fig. S10†). An ideal way to compare the relaxivity difference of the Gd₂O₃{100} and Gd₂O₃{111} facets is the corresponding nanoplates with the same size and morphology. However, the facets exposed on a nanocrystal have a strong correlation with the shape. The Gd₂O₃ crystal of the cubic phase tends to form Gd₂O₃{100} and Gd₂O₃{111} nanoplates with cubic and spherical shapes due to the anisotropic crystal growth under controllable conditions. Thus, so far it has been difficult to obtain Gd₂O₃ nanoplates with the same morphology but with different exposed facets. In this respect, we carefully calculated the densities of water coordination on the Gd₂O₃{100} and Gd₂O₃{111} facets. The density of water coordination on the Gd₂O₃{100} facet was estimated to be ∼6.8 per nm², nearly twice that on the Gd₂O₃{111} facet (Fig. S9†). Thus, the higher density of exchangeable water on Gd₂O₃{100} may offer part of the explanation for the observed higher r₁ values than that of Gd₂O₃{111}. In addition, we disclosed that, besides the one-to-one coordinate mode (top site), there is one-to-two mode on bridge and hollow sites (note that the water molecules on the hollow sites deviated from the central position), resulting in two short and two long Gd–O bonds. Such new coordinated modes would promote spin-lattice relaxation effects between protons and nearby Gd³⁺ ions, which in turn increases the T₁ relaxivity. More significantly, nearly degenerate energies of water coordination on Gd₂O₃{100} suggested that the potential energy surface was very smooth, thus facilitating the fast migration of water from one magnetic center to another.

We further explored the possible migration process of water molecules on the Gd₂O₃{100} facets (Fig. 5a). DFT calculations demonstrated that water migration from one top site to another through a bridging-mediated process was calculated with transition energy barriers as low as 0.08 and 0.13 eV for two transition states TS1 and TS2, respectively, indicating great potential for water dissociation and re-coordination from one Gd³⁺ ion to another Gd³⁺ ion in vicinity (Fig. 5b).^42,43 As reported previously,^44,45T₁ relaxivity is not only related to the coordination status but also much dependent on the kinetic exchange of water molecules on magnetic centers (Fig. 5c and d). Our findings indicated that the Gd₂O₃{100} facet not only provides rich and multicenter sites for water coordination, but also facilitates the migration of water molecules among the magnetic centers, thus enhancing the T₁ relaxivity.

Fig. 5 Water migration on the metal-rich exposed Gd₂O₃{100} facet. (a, b) Simulation and calculated energies for one water molecule migrating from Top1 to Top2 through the bridge-mediated configuration on the Gd₂O₃{100} facet, showing the transition energy barriers as low as 0.08 eV (TS1) and 0.13 eV (TS2). (c) The water coordination and dissociation from position 1 (P1) to P2 and P3, or migration and re-coordination from P2 to P4 during the time slot of T₁ relaxation. (d) P1 to P2 and P3 are considered with moderate recovery for longitudinal magnetizations, while the migration immediately after the dissociation from P2 and re-coordination on P4 may promise cascade recovery of proton longitudinal magnetizations during the time slot of T₁ relaxation.

Prior to conducting an in vivo study, we first evaluated the potential toxicity of the Gd₂O₃ nanoplates at the cellular level and in living animals. The MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide) assay showed that more than 95% of both HeLa and SMMC-7721 cells were viable after being treated with Gd₂O₃{100} and Gd₂O₃{111} nanoplates for 24 h even with a maximum concentration (with respect to Gd ions) up to 10 μM, indicating good biocompatibility in vitro (Fig. S11†). The histological study further revealed that no organ abnormalities or lesions were found in mice (n = 3) treated with either Gd₂O₃{100} or Gd₂O₃{111} nanoplates (2.0 mg [Gd] per kg mouse body weight) for 24 h, as indicated by the histology of the major organs of the liver, kidney, muscle, heart, lung, and spleen (Fig. S12†). The toxicity of Gd-based agents is mainly related to the release of free Gd³⁺ ions. Our in vitro and in vivo results show that both Gd₂O₃{100} and Gd₂O₃{111} nanoplates are nontoxic in the treatment period of 24 h, suggesting little to no release of free Gd³⁺ ions from Gd₂O₃ nanoplates during this period. The long-term biosafety study should be conducted in future. For in vivo imaging study, we injected either Gd₂O₃{100} or Gd₂O₃{111} nanoplates in mice through a tail vein with a dose of 2.0 mg [Gd] per kg mouse body weight. The T₁ MRI contrast performance was evaluated at a 3.0 T clinical scanner both at coronal and transverse planes at the region of interest (ROI) of the liver, due to the fact that circulating nanoparticles are prone to be accumulated in the liver by a mononuclear phagocyte system (MPS).^46–48 The contrast-enhanced MRI results showed an obviously brighter signal at the liver region after 0.5 h post-injection (p.i.) of Gd₂O₃{100} nanoplates, which continuously increased over time to 2 h p.i. (Fig. 6a). After that, a decreased liver signal was found at 4 h p.i., the reason for which might be multifold: either the excretion of nanoplates from the liver or stacking of nanoplates in the liver will cause the loss of T₁ signal.¹⁷ On the contrary, the Gd₂O₃{111} nanoplates exhibited little to no contrast in T₁ MRI at the ROI under similar conditions (Fig. 6b). We used the ΔSNR (signal-to-noise ratio, ΔSNR = |SNR_post − SNR_pre|/SNR_pre) to quantify the T₁ signal changes in the ROI.⁴⁶ The results implied that the ΔSNR at the ROI treated with Gd₂O₃{100} nanoplates are 2–4 fold higher than those being treated with Gd₂O₃{111} nanoplates at different time points (Fig. 6c and d). These results are consistent with the MR phantom study, further indicating the superior T₁ relaxation enhancement of the Gd₂O₃{100} nanoplates both in vitro and in vivo.

Fig. 6 (a, b) T₁ MRI study in a mouse model injected with Gd₂O₃{100} and Gd₂O₃{111} nanoplates in a dose of 2.0 mg [Gd] per kg mouse body weight. The pre-injection and 0.5, 1, 2, and 4 h post-injection images at coronal (top) and transverse (bottom) planes were acquired focusing the ROI of the liver (yellow dotted circle as shown in the first image). The upper right circles at each of transverse images indicate water. (c, d) Comparison of the quantitative signal changes ΔSNR (signal-to-noise ratio) at the ROI after injection with Gd₂O₃{100} and Gd₂O₃{111} nanoplates at the coronal and transverse planes, respectively.

Conclusions

In conclusion, we report that gadolinium oxide nanoplates with metal-rich Gd₂O₃{100} exposed facets exhibited significantly enhanced T₁ contrast ability, compared to that with oxygen terminated Gd₂O₃{111} facets. The enhanced T₁ relaxivity of the Gd₂O₃{100} nanoplates can be attributed to the following factors: (i) the higher density of water coordination due to the large number of exposed Gd³⁺ ions on the Gd₂O₃{100} nanoplates; (ii) the one-to-two coordinated configurations of water coordination on the metal-rich exposed Gd₂O₃{100} facets permit significantly enhanced spin-lattice relaxation effects; (iii) the smooth potential energy surface for water coordination enables bridge-mediated fast migration among different magnetic sites, thus facilitating cascade recovery of longitudinal magnetizations. The present work by integrating the experimental results with theoretical simulation may not only provoke an essential understanding of T₁ relaxation enhancement effects in nanoparticulate systems, but also shed light on the innovations of T₁ contrast agents for high-performance MRI applications.

Experimental

Materials and characterization

1-Octadecene (ODE, tech. 90%) and oleic acid (tech. 90%) were purchased from Acros. Gadolinium(III) chloride hexahydrate (99.99%) and gadolinium acetate (99.9%) were purchased from Alfa Aesar. Sodium oleate, sodium citrate, iron chlorides and other reagents are purchased from Sinopharm Chemical Reagent Co. Ltd. All chemicals were used as received without further purification. TEM and HRTEM images were recorded on a JEM-2100 microscope at an accelerating voltage of 200 kV. X-ray diffraction (XRD) patterns were recorded by using a Rigaku Ultima IV X-ray diffractometer with Cu Kα radiation. X-ray photoelectron spectroscopy (XPS) measurements were carried out by using a PHI Quantum-2000 photoelectron spectrometer. The hysteresis loops (at 300 K and 5 K) and temperature-dependent magnetization measurements were recorded on a Quantum Design MPMS-XL-7 system. The elemental analysis of metal ions was performed by inductively coupled plasma atomic emission spectroscopy (ICP-AES). The dynamic light scattering measurements were performed on a Malvern Zetasizer nano ZS instrument. The MRI measurements and T₂/T₁ relaxation time testing were performed on a 0.5 T NMI20-Analyst NMR analyzing & imaging system (Niumag Corporation, Shanghai, China) and a 3.0 T imaging system (Philips Medical System, ACHIEVA 3.0 T).

Synthesis of Gd₂O₃{111} nanoplates

The gadolinium oleate complex was synthesized as a precursor through a general procedure reported elsewhere (ref. 16). We synthesized {111} facets exposed Gd₂O₃ nanoplates by decomposition of the gadolinium oleate complex in the presence of oleic acid and sodium oleate. 1-Octadecene (ODE) was used as a solvent with a boiling temperature at 314 °C. The addition of sodium oleate leads to the formation of circular, triangular, and dendritic shaped nanoplates by controlling the molar ratio to the gadolinium oleate precursor. For example, 1 mmol (1.0 g) of the gadolinium oleate complex was dissolved in 15 mL of ODE in the presence of 160 μL of oleic acid. 0.5 mmol (151 mg) of sodium oleate was added to the solution and the system was heated to reflux under an N₂ atmosphere. The reaction was then ceased by removing the heating source after a 2 h reflux and allowed to cool to room temperature. The dendritic Gd₂O₃ nanoplates were obtained by centrifugation and washed with hexane and ethanol solution three times. The formation of circular and triangular shaped Gd₂O₃ nanoplates was carried out by a similar procedure but with the addition of 0.1 mmol (30 mg) and 0.2 mmol (60 mg) of sodium oleate, respectively. The final product was redispersed in hexane and stored at 4 °C for further use.

Synthesis of Gd₂O₃{100} nanoplates

The synthesis of Gd₂O₃{100} nanoplates is followed by the decomposition of the gadolinium(III) acetate precursor in the presence of oleic acid in the solvent of ODE. For example, 0.334 g (1 mmol) of gadolinium acetate were dissolved in 10 mL of ODE solvent with the addition of 0.34 mL (1 mmol) of oleic acid. The system was degassed with nitrogen and heated to reflux with a constant heating rate of ∼8 °C min⁻¹. The reaction was then ceased and allowed to cool to room temperature after 2 h reflux. After the addition of an excess of isopropanol, a white product was obtained through centrifugation. The product was redispersed in hexane and stored at 4 °C for further use. The side length and the width of the Gd₂O₃{100} nanoplates can be controlled by tuning the molar ratio of the precursor to surfactant. The Gd₂O₃{100} nanoplates with a side length and width of 120 × 40 nm and 90 × 15 nm were obtained with the precursor to surfactant molar ratio of 1 : 1 and 1 : 2, respectively.

Preparation of water-soluble Gd₂O₃ nanoplates

The preparation of sodium citrate coated Gd₂O₃ nanoplates was carried out in a straightforward manner as follows: an excess of sodium citrate (10 mg) was dissolved in a flask containing 5 mL of ultra-pure water and 10 mL of tetrahydrofuran, and then the as-prepared hexane-dispersed Gd₂O₃ nanoplates (0.1 mmol) were added to the flask. The solution was then heated to reflux for 2 h before the nanoparticles were transferred to the lower layer. The solution in the lower layer was then collected and centrifuged at 8000 rpm to obtain the precipitate. The final product was redispersed in distilled water (or PBS) and stored at 4 °C for further use.

MR relaxivity and MR phantom study

The Gd₂O₃ nanoplates with various gadolinium metal concentrations were prepared within 1% agar for MR phantom study. The relaxivity and phantom studies of the Gd₂O₃ nanoplates were conducted at three different magnetic fields (0.5, 1.5, and 3.0 T). The longitudinal (r₁) and transverse (r₂) relaxivities of the Gd₂O₃ nanoplates were obtained from the slopes of the reciprocal of each relaxation time against concentration. T₂- and T₁-weighted MR images were acquired with the following parameters: TR/TE = 2000/60 ms (T₂), TR/TE = 300/10 ms (T₁), 128 × 128 matrices, and repetition time = 8.

Density functional theory (DFT) calculations

All the calculations were performed with the density functional theory (DFT) provided by the Vienna ab initio simulation package (VASP). The exchange and correlation were treated with the generalized gradient approximation (GGA) via the Perdew–Burke–Ernzerhof (PBE) function. The 5s²5p⁶4f⁷5d¹6s² shells of the Gd and 2s²2p⁴ shells of O have been considered explicitly in the spin-polarized density functional theory (SDFT) calculations. The GGA + U approach was utilized for all calculations, where the parameters U and J were not entered into the density functional separately but considered as a combined effective interaction parameter. We used U = 7.5 eV, J = 0.6 eV in all GGA + U calculations, resulting in a U_eff of 6.9 eV applied to the 4f orbital of the Gd atoms. A charge density cutoff energy of 400 eV was used for the smooth part of the electronic wave functions and the augmented electron density. Brillouin zone integration was optimized at the Γ-point with a Monkhorst–Pack k-point grid of 1 × 1 × 1 for the bulk and slab model. All the atomic positions in the bulk structure were relaxed, while we fixed the bottom two layers in the slab. The convergence criteria for the energy calculation and structure optimization are set to a self-consistent field tolerance of 1.0 × 10⁻⁵ eV and a maximum Hellmann–Feynman force tolerance of 0.02 eV Å⁻¹. We consider the C-type cubic structure of gadolinium sesquioxide with the space group Ia3̄. We have performed a full optimization (lattice constant and atomic position) of the bulk. The Gd-terminated {100} surface with 8 atomic layers and a vacuum region of 15 Å was employed. The O-terminated {111} surface has been modeled for a 3-atomic-layer slab with 120 atoms, and with the bottom one layer frozen. We performed antiferromagnetic ordering for the Gd magnetic moments. Water adsorption energy is calculated using the following equation: ΔE_ads(H2O) = E_(H2O/surf) − E_(surf) − E_(H2O), where E_(H2O) is the energy of the water molecule, and E_(H2O/surf) and E_(surf) refer to the energies of the chosen surface with or without water, respectively.

In vivo MRI study

Animal experiments were executed according to the protocol approved by the Institutional Animal Care and Use Committee of Xiamen University. We conducted an in vivo MRI study in a mouse model (∼20 g, female ICR) using a clinical 3 T MRI scanner (Philips Medical System, ACHIEVA 3.0 T). The pre-injection T₁ images of the anaesthetized mice both at the coronal and transverse planes were acquired for comparison purpose. The mice were injected with water-soluble Gd₂O₃{100} or Gd₂O₃{111} nanoplates with a dose of 2.0 mg [Gd] per kg to the mouse body weight. The post-injection (p.i.) time points of 0.5, 1, 2, and 4 h were acquired both at the coronal and transverse planes. All the T₁ images were acquired using a fast spin-echo sequence (FSE) with the following parameters: TR/TE = 300/14 ms, thickness = 1 mm, 144 × 144 matrices, FOV = 100 × 100 mm (coronal) or 50 × 50 mm (transverse), and flip angle = 90°.

Acknowledgements

This work was supported by the National Key Basic Research Program of China (2013CB933901, 2014CB744502, and 2014CB932004), the National Natural Science Foundation of China (21222106, 21521004, 81370042, and 81430041), Fok Ying Tung Education Foundation (142012), and the Intramural Research Program, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health.

References

1. Y. Sun, S. Gao, F. Lei, C. Xiao and Y. Xie, Acc. Chem. Res., 2015, 48, 3–12.
2. H. Zhang, ACS Nano, 2015, 9, 9451–9469.
3. A. K. Geim and K. S. Novoselov, Nat. Mater., 2007, 6, 183–191.
4. M. A. Boles, D. Ling, T. Hyeon and D. V. Talapin, Nat. Mater., 2016, 15, 141–153.
5. D. Akinwande, N. Petrone and J. Hone, Nat. Commun., 2014, 5, 5678.
6. F. Song and X. Hu, J. Am. Chem. Soc., 2014, 136, 16481–16484.
7. K. Zhou and Y. Li, Angew. Chem., Int. Ed., 2012, 51, 602–613.
8. B. Luo, G. Liu and L. Wang, Nanoscale, 2016, 8, 6904–6920.
9. M. F. El-Kady, V. Strong, S. Dubin and R. B. Kaner, Science, 2012, 335, 1326–1330.
10. L. Hu, X. Wu and J. Yang, Nanoscale, 2016, 8, 12939–12945.
11. Z. Liu, J. T. Robinson, X. Sun and H. Dai, J. Am. Chem. Soc., 2008, 130, 10876–10877.
12. H. Wang, X. Yang, W. Shao, S. Chen, J. Xie, X. Zhang, J. Wang and Y. Xie, J. Am. Chem. Soc., 2015, 137, 11376–11382.
13. X. Qian, S. Shen, T. Liu, L. Cheng and Z. Liu, Nanoscale, 2015, 7, 6380–6387.
14. I. Solomon, Phys. Rev., 1955, 99, 559–565.
15. N. Bloembergen and L. O. Morgan, J. Chem. Phys., 1961, 34, 842–850.
16. Z. Zhou, C. Wu, H. Liu, X. Zhu, Z. Zhao, L. Wang, Y. Xu, H. Ai and J. Gao, ACS Nano, 2015, 9, 3012–3022.
17. Z. Zhou, Z. H. Zhao, H. Zhang, Z. Wang, X. Chen, R. Wang, Z. Chen and J. Gao, ACS Nano, 2014, 8, 7976–7985.
18. R. V. Jagadeesh, A.-E. Surkus, H. Junge, M.-M. Pohl, J. Radnik, J. Rabeah, H. Huan, V. Schünemann, A. Brückner and M. Beller, Science, 2013, 342, 1073–1076.
19. J. Huang, Y. Hou, C. Liu, L. Jing, T. Ma, X. Sun and M. Gao, Chem. Mater., 2015, 27, 7918–7925.
20. N. Lee, D. Yoo, D. Ling, M. H. Cho, T. Hyeon and J. Cheon, Chem. Rev., 2015, 115, 10637–10689.
21. T.-H. Shin, Y. Choi, S. Kim and J. Cheon, Chem. Soc. Rev., 2015, 4501–4516.
22. T. Todd, Z. Zhen, W. Tang, H. Chen, G. Wang, Y.-J. Chuang, K. Deaton, Z. Pan and J. Xie, Nanoscale, 2014, 6, 2073–2076.
23. F. Li, D. Zhi, Y. Luo, J. Zhang, X. Nan, Y. Zhang, W. Zhou, B. Qiu, L. Wen and G. Liang, Nanoscale, 2016, 8, 12826–12833.
24. L. Zhang, R. Liu, H. Peng, P. Li, Z. Xu and A. K. Whittaker, Nanoscale, 2016, 8, 10491–10510.
25. R. Hachani, M. Lowdell, M. Birchall, A. Hervault, D. Mertz, S. Begin-Colin and N. T. K. Thanh, Nanoscale, 2016, 8, 3278–3287.
26. R. B. Lauffer, Chem. Rev., 1987, 87, 901–927.
27. P. Caravan, C. T. Farrar, L. Frullano and R. Uppal, Contrast Media Mol. Imaging, 2009, 4, 89–100.
28. P. Caravan, Chem. Soc. Rev., 2006, 35, 512–523.
29. J. Yu, L. Qi and M. Jaroniec, J. Phys. Chem. C, 2010, 114, 13118–13125.
30. Y. Xia, Y. Xiong, B. Lim and S. E. Skrabalak, Angew. Chem., Int. Ed., 2009, 48, 60–103.
31. Y. Wang, J. He, C. Liu, W. H. Chong and H. Chen, Angew. Chem., Int. Ed., 2015, 54, 2022–2051.
32. J. Y. Park, M. J. Baek, E. S. Choi, S. Woo, J. H. Kim, T. J. Kim, J. C. Jung, K. S. Chae, Y. Chang and G. H. Lee, ACS Nano, 2009, 3, 3663–3669.
33. J. S. Ananta, B. Godin, R. Sethi, L. Moriggi, X. Liu, R. E. Serda, R. Krishnamurthy, R. Muthupillai, R. D. Bolskar, L. Helm, M. Ferrari, L. J. Wilson and P. Decuzzi, Nat. Nanotechnol., 2010, 5, 815–821.
34. M. Cho, R. Sethi, J. S. Ananta narayanan, S. S. Lee, D. N. Benoit, N. Taheri, P. Decuzzi and V. L. Colvin, Nanoscale, 2014, 6, 13637–13645.
35. H. Dong, S.-R. Du, X.-Y. Zheng, G.-M. Lyu, L.-D. Sun, L.-D. Li, P.-Z. Zhang, C. Zhang and C.-H. Yan, Chem. Rev., 2015, 115, 10725–10815.
36. T. Paik, T. R. Gordon, A. M. Prantner, H. Yun and C. B. Murray, ACS Nano, 2013, 7, 2850–2859.
37. D. Wang, Y. Kang, X. Ye and C. B. Murray, Chem. Mater., 2014, 26, 6328–6332.
38. Z. Zhou, X. Zhu, D. Wu, Q. Chen, D. Huang, C. Sun, J. Xin, K. Ni and J. Gao, Chem. Mater., 2015, 27, 3505–3515.
39. X. Han, Q. Kuang, M. Jin, Z. Xie and L. Zheng, J. Am. Chem. Soc., 2009, 131, 3152–3153.
40. M. Zobel, R. B. Neder and S. A. J. Kimber, Science, 2015, 347, 292–294.
41. B. Wu, H. Huang, J. Yang, N. Zheng and G. Fu, Angew. Chem., Int. Ed., 2012, 51, 3440–3443.
42. H.-F. Wang, R. Kavanagh, Y.-L. Guo, Y. Guo, G.-Z. Lu and P. Hu, Angew. Chem., Int. Ed., 2012, 51, 6657–6661.
43. X. Meng, J. Guo, J. Peng, J. Chen, Z. Wang, J.-R. Shi, X.-Z. Li, E.-G. Wang and Y. Jiang, Nat. Phys., 2015, 11, 235–239.
44. E. J. Werner, A. Datta, C. J. Jocher and K. N. Raymond, Angew. Chem., Int. Ed., 2008, 47, 8568–8580.
45. P. Caravan, J. J. Ellison, T. J. McMurry and R. B. Lauffer, Chem. Rev., 1999, 99, 2293–2352.
46. J. Huang, L. Bu, J. Xie, K. Chen, Z. Cheng, X. Li and X. Chen, ACS Nano, 2010, 4, 7151–7160.
47. F. Geissmann, S. Gordon, D. A. Hume, A. M. Mowat and G. J. Randolph, Nat. Rev. Immunol., 2010, 10, 453–460.
48. A. Chow, B. D. Brown and M. Merad, Nat. Rev. Immunol., 2011, 11, 788–798.

---

Footnote

† Electronic supplementary information (ESI) available: Experimental details, additional TEM images, M–H and M–T data, DLS data, biocompatibility study and DFT calculations and models. See DOI: 10.1039/c6nr06444b

---