Teruyuki
Nakato
*a,
Riki
Kato
b,
Wataru
Ishitobi
a,
Emiko
Mouri
a,
Hiroki
Iwase
c and
Nobuyoshi
Miyamoto
*b
aDepartment of Applied Chemistry, Kyushu Institute of Technology, 1-1 Sensui-cho, Tobata, Kitakyushu, Fukuoka 804-8550, Japan. E-mail: terunakato@gmail.com
bDepartment of Life, Environment, and Applied Chemistry, Faculty of Engineering, Fukuoka Institute of Technology, 3-30-1 Wajiro-higashi, Higashi-ku, Fukuoka 811-0295, Japan
cNeutron Science and Technology Center, Comprehensive Research Organization for Science and Society (CROSS), Tokai, Ibaraki 319-1106, Japan
First published on 18th November 2025
Binary colloids of two different nanosheet species are promising systems for novel integrated materials because of their multicomponent and multiphase coexistence utilizable in novel smart materials. Among the binary colloids, niobate–clay binary nanosheet colloids are characterized by unusual photochemical functions and phase separation at a mesoscopic (∼several tens of micrometers) scale. The present study clarifies the colloidal state of the clay nanosheets in the mesostructured aqueous binary colloid of hexaniobate and fluorohectorite clay nanosheets by using small-angle neutron scattering (SANS) with the contrast variation technique. Compared to small-angle X-ray scattering (SAXS) that preferentially detects the niobate nanosheets, contrast variation SANS measurements can match out each nanosheet species to detect liquid crystalline ordering of each nanosheet species. The SANS results demonstrate the coexistence of two liquid crystalline phases induced by niobate and clay nanosheets, respectively, in the niobate–clay binary nanosheet colloids.
The nanosheet colloids have been extended to binary systems, where two inorganic nanosheet species prepared by delamination of two different layered compounds are stably dispersed in a solvent. The binary nanosheet colloids are end members of multicomponent colloids consisting of different particles.11–15 They generally cause phase separation in the absence of attractive interactions among particles on the basis of entropically driven demixing called depletion. Thus, the multicomponent nature of binary nanosheet colloids results in complicated phase behavior exemplified by multiphase coexistence.16 In addition, physicochemical properties of two nanosheet species can be integrated with unusual functions. We have investigated a binary nanosheet system composed of the hexaniobate nanosheets exfoliated from layered niobate (K4Nb6O17) and clay nanosheets of smectite-type clay minerals such as hectorite, montmorillonite, and fluorohectorite,17 where the niobate is a photocatalytically active semiconductor18,19 and the clay is a carrier of functional organic species.20,21 In fact, unusual photochemical reactions have been discovered in the niobate–clay binary systems.22–24
However, the structure of the niobate–clay binary nanosheet colloids has not been established. This is because of the occurrence of their phase separation at a mesoscopic scale to avoid the detection of the phases by the naked eye,25 although the phase separation of multicomponent colloids usually occurs at an eye-detectable macroscopic scale.26–28 We have recently carried out the characterization of the structure of niobate–clay binary nanosheet colloids by using small-angle X-ray scattering (SAXS) and confocal laser scanning microscopy (CLSM).25 The study has clarified the liquid crystalline ordering of the niobate nanosheets in the binary colloids. The niobate nanosheets are assembled into liquid crystalline domains of several tens of micrometers. In contrast, the clay nanosheets are located in the voids between the niobate domains and are thought to be isotropically present on the basis of the SAXS results.
Nevertheless, this conclusion is not firm, because the clay nanosheets can form liquid crystalline phases when the lateral size of clay nanosheets is large enough. In our recent study of the niobate–clay binary colloids, where the clay nanosheets obtained from synthetic fluorohectorite are micrometer-sized, we observed that clay nanosheets aggregated and separated from the liquid crystalline domains of niobate nanosheets.25 In contrast, we very recently discovered in the electric alignment study of these binary colloids that some of the clay nanosheets are aligned together with the niobate nanosheets.29 The liquid crystallinity of these niobate–clay binary colloids as well as niobate and clay single-component colloids has been established by their fluidity and birefringence.17,25,30,31
Based on these observations, in the present study, we attempted to unravel the ordered structure of the clay nanosheets in the niobate–clay binary colloids with large clay platelets. We employed the small-angle neutron scattering (SANS) technique. The hexaniobate nanosheet shows a smaller neutron scattering length density (3.26 × 1010 cm−2, as [K2Nb6O17]2−) than the fluorohectorite clay nanosheet (4.24 × 1010 cm−2, as [Mg2.6Li0.46Si4O10F2]0.46−). Thus, the SANS technique detects the clay nanosheets better than the niobate nanosheets in H2O. This is in contrast with the SAXS technique that more preferentially reflects the structure of the niobate nanosheets because the X-ray scattering length density of a niobate nanosheet (3.68 × 1011 cm−2 for [K2Nb6O17]2− (1306 electrons nm−3)) is higher than that of a fluorohectorite clay nanosheet (2.31 × 1011 cm−2 for [Mg2.6Li0.46Si4O10F2]0.46− (819 electrons nm−3)). Moreover, the contrast variation SANS measurements can selectively match out the niobate or clay nanosheets. Herein, we show the presence of an ordered structure of clay nanosheets in the binary nanosheet colloids of hexaniobate and fluorohectorite clay by using contrast variation SANS measurements.
A stock sample of clay colloids was prepared at 30 g L−1 nanosheet concentration in H2O. Synthetic fluorohectorite clay mineral (ideal formula: Na0.46[Mg2.6Li0.46Si4O10F2])33 provided as an aqueous suspension (Topy Industries Co., NHT sol) was centrifuged, by which the clay suspension was separated into three phases: upper supernatant, intermediate viscous sol, and lower sediment phases.31 The sol phase was picked up and dialyzed with water, and then dried at 60 °C. The average lateral particle size of the clay particles was 1–2 µm.31 A binary nanosheet colloid sample was prepared by simply adding a clay colloid to a niobate colloid. For the D2O substitution, half of each stock sample was subjected to centrifugation and the deposit was diluted with D2O, and this treatment was repeated only once in order to avoid severe structural change. Then, we set the nanosheet concentration at 60 and 30 g L−1 for the niobate and clay nanosheet colloids, respectively, in D2O.
These samples of the niobate or clay nanosheet colloids in D2O and H2O were mixed and diluted with water to prepare single-component niobate or clay nanosheet colloids with different D2O
:
H2O volume ratios. Niobate–clay binary nanosheet colloids with different D2O
:
H2O ratios were also prepared by appropriate mixing of the single-component nanosheet colloids of niobate and clay in D2O and H2O followed by dilution with D2O or H2O. The examined D2O
:
H2O ratios were 100
:
0, 85
:
15, 65
:
35, and 20
:
80. The concentration of niobate and clay nanosheets in the samples was set to 20 g L−1.
sin(θ/2)/λ (θ representing the scattering angle). This q-range corresponds to the length scale (d ≡ 2π/q) from 0.6 to 90 nm in real space. The sample suspension was contained in a quartz cell with a 1 mm path length. The exposure time was around 1–5 h. All SANS data were normalized to an absolute scattering intensity using the SANS profile of a glassy carbon standard35 after the necessary data corrections, such as detector efficiency, transmission, and incident neutron intensity. All data were presented after a smoothing calculation using moving average. The samples were not relaxed enough to remove the shear force applied during the sample preparation. Thus, we do not discuss the radial symmetry of the SANS data in relation to the particle orientation.
:
H2O volume ratios. In all the profiles, the upturns toward low-q are observed while the profiles are almost flat in the q range of 1–10 nm−1. Meanwhile, in the profiles of only the solvents without the nanosheets (the dashed lines in Fig. 1A and 2A), a structureless flat profile is observed at q < 10 nm−1. Hence, the upturn in the low-q region is ascribed to the scattering by the nanosheets. In the flat region, incoherent scatterings of solvents and the nanosheets both contribute to the profile so that the intensity is stronger for the samples with less D2O, which has less incoherent scattering than H2O. For all the nanosheet colloids in the present study, we employ the averaged scattering intensities around q ∼ 2 nm−1 as the q-independent experimental constant values of incoherent scattering for each nanosheet colloid so that these constant values are subtracted for further analyses.
After subtracting the constant incoherent scattering, the SANS patterns are replotted as Fig. 1B and 2B. Here, the scattering intensity basically obeys q−2, which is the form factor of isolated 2D nanosheets. Hence, we divide the scattering curves by q−2 in order to extract the excess scattering reflecting nanosheet–nanosheet interactions, as shown in Fig. 1C and 2C. We discuss only the position of the most intense peak at the lowest q value in each pattern in the following discussion. Although the SANS patterns show several bumps at higher q values, their S/N ratios are too low to discuss quantitatively if we take into account error bars of the SANS patterns as indicated in Fig. S1 and S2 (SI).
All the samples show weak broad peaks accompanied by small numbers of higher-order peaks. Because of the fluidity and birefringence of the samples, they are liquid crystalline and the mesophase should be identified as nematic. We estimate the basal spacings from the main SANS peak of each sample fitted by Gauss functions, and the result is summarized in Table S1. The spacings can be recognized as the average inter-sheet spacings of the ordered nanosheets.
For the niobate nanosheet colloid, a broad peak is observed at q ∼ 0.12 nm−1 (d ∼ 53 nm) (Fig. 1C). Although the SAXS pattern of the niobate nanosheet colloid at the same concentration measured in our previous study does not definitively show the peak,25 the current SANS pattern indicates the presence of nematic ordering in the sample. If we employ the basal spacings detected in the SAXS patterns of the niobate nanosheet colloids with higher concentrations,25 the basal spacing of the current sample is estimated as 152 nm based on the relationship between the nanosheet concentration and basal spacing (Fig. S2). Thus, we assign the d value of the SANS peak to the third-order peak with respect to the basal spacing. The upward curvature of the SANS pattern around the low-q limit indicates the presence of lower-order peaks. On the other hand, the clay colloid shows a peak at q ∼ 0.12 nm−1 (d ∼ 53 nm) (Fig. 2C). This value is in harmony with the basal spacing (56 nm) of the clay nanosheet colloid estimated from the SAXS pattern at the same nanosheet concentration.25 These scattering data indicate nematic ordering of each nanosheet in the single-component colloids.
On the other hand, Fig. 1 and 2 clearly show the effect of the D2O/H2O ratio of the solvent on the scattering intensities of the nanosheet colloids. The scattering intensity strongly depends on the D2O/H2O ratio. This is explained by considering that the neutron scattering intensity is proportional to the square of the difference between the neutron scattering length density of the scattering objects and the solvent, and that the neutron scattering length densities of D2O (6.40 × 1010 cm−2) and H2O (−0.56 × 1010 cm−2) are largely different. Since the neutron scattering length densities of the niobate (3.26 × 1010 cm−2) and clay (4.23 × 1010 cm−2) (see the SI for the calculation of these values) are in between the values of D2O and H2O, the scattering of the nanosheets is enhanced or matched out by varying the solvent composition, which is known as the contrast variation technique. The solvent composition for matching out the niobate or clay nanosheets is experimentally determined from the plot of the scattering amplitude (square root of the scattering intensity) s vs. D2O ratio (Fig. 3). By fitting the plots using the following equation
| s = a ([D2O] – [D2O]matched) |
These values are greater than the theoretical values (Table S1 in the SI) of 54% and 70% for the niobate and clay, respectively. The inconsistency would be due to incomplete replacement of H2O for D2O in the preparation of the stock samples. Because the counter cations of the negatively charged colloidal nanosheets (Na+ for clay and propylammonium for niobate) are hydrated, complete replacement of the strongly hydrated water molecules was difficult in our study. Slow hydration kinetics of clay minerals due to the large crystallite size of the mother crystals, which may prevent the samples from reaching equilibrium, also contribute to the discrepancy between the theoretical and experimental values. Moreover, the contribution of these counter cations is not considered in the calculation in Table S1.
However, we can say that when the scattering length densities of the solvent and nanosheets are matched, the scattering of each nanosheet mostly disappeared, which is useful for analyses of the mixture system. As shown in Fig. 2B and C, for the clay system, the scattering intensity after removing the incoherent scattering is the lowest with a D2O ratio of 100% or 85%. In the niobate system, the lowest scattering intensity was observed with a D2O ratio of 65% (Fig. 1B and C). These D2O concentrations at the matching points are larger than the theoretical ones. This is ascribed to incomplete substitution of H2O for D2O because our experimental conditions for the substitution were moderate as written in the Experimental section.
:
H2O ratios. Unlike the single-component colloids of niobate or clay nanosheets, the niobate–clay binary colloids do not show the I ∝ q−2 dependence. A downward slope is observed after subtraction of incoherent scattering and form factor of nanosheets (Fig. 4C). In addition, the scattering curve exhibits a broad scattering peak at around q ∼ 0.10 nm−1 with low D2O content (D2O
:
H2O = 20
:
80). The peak position is smaller by 0.02 nm−1 than that of the single-component clay nanosheet colloid.
The overall scattering intensity after subtraction of incoherent scattering (Fig. 4B and C) decreased with the increase of D2O ratio, giving the minimum intensity at D2O
:
H2O = 85
:
15. This is explained by the fact that this condition is in the middle of the matching points of the niobate ([D2O] = 75%) and clay ([D2O] = 90%). It is notable that the scattering intensity and scattering profiles are mostly the same for D2O
:
H2O = 65
:
35 and 100
:
0, which are the closest to the matching out condition for the niobate and clay, respectively. The peak at q ∼ 0.10 nm−1 is still visible under these conditions. These results disclose that both of the niobate and clay nanosheets contribute to the same nematic structure in the niobate–clay binary nanosheet colloids, as discussed later.
However, the present study clarifies the nematic ordering of clay nanosheets in the binary colloids hidden in their SAXS results. As described above, the matching points of niobate and clay are estimated as [D2O] = 75% and 90%, respectively (Fig. 3). The scattering intensity of the peak due to the basal spacing of the nematic phase at [D2O] = 65% (lower by 10% than the matching point of niobate) is the same as that of [D2O] = 100% (higher by 10% than the matching point of clay). If the nematic structure is constructed only using the niobate nanosheets, the scattering intensity at [D2O] = 65%, which is close to the matching point of niobate, must be lower than that at [D2O] = 100%. The same scattering intensity at [D2O] = 65 and 100% indicates that both of the niobate and clay nanosheets contribute to the nematic structure in the binary nanosheet colloids.
On the other hand, the SANS patterns of the niobate–clay binary nanosheet colloids show certain slope after dividing the SANS patterns by q−2 to remove the form factor of 2D nanosheets. This indicates the existence of three-dimensional nature in the colloids. This would be mainly induced by clay nanosheets because the slope is most gentle for the sample in D2O
:
H2O = 85
:
15, which is close to the matching point of clay nanosheets. We assume the coexistence of aggregated clay nanosheets in the binary colloids.
Such a consideration leads to a revised structure of the niobate–clay binary nanosheet colloids. Although SAXS analysis has indicated the liquid crystalline phase composed of the niobate nanosheets, the SANS technique has disclosed the involvement of clay nanosheets in the liquid crystalline domains. Such multi-component liquid crystalline phases have often been observed in binary colloidal liquid crystals of anisotropic particles.16,36 Also, the result is consistent with our very recent observation of the electric alignment of the niobate–clay binary colloids, where some of the clay nanosheets are involved in the electric response of the niobate nanosheets.29
:
D2O ratios match out the scattering due to the niobate nanosheets in the binary colloid to unravel the nematic ordering of the clay nanosheets, which is hidden in the previously reported SAXS analysis of the binary nanosheet colloids. The results suggest that both of the niobate and clay nanosheets are involved in the nematic structure of the binary colloids. Integration of plural nanosheet species in colloidal liquid crystalline phases will open the future applications of the binary colloids to novel functional systems such as sensing, switchable permeation, and selective chemical reactions.
Supplementary information (SI): calculation details of neutron scattering length densities, basal spacings of the lamellar phase evolved in single-component niobate nanosheet colloids plotted against the nanosheet concentration determined by SAXS, SANS patterns of nanosheet colloids with error bars, Gauss fitting of the SANS peaks, basal spacings of the samples estimated by Gauss fitting of the SANS patterns. See DOI: https://doi.org/10.1039/d5sm01056j.
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