Nanogel for Selective Recognition of Nanoparticles in Water Samples

Abstract

Nanoparticles (NPs) represent emerging pollutants that still pose analytical challenges for their detection in environmentally relevant samples due to their extremely low concentrations, high colloidal background, and the need to perform speciation analysis. They are also one of the interfering matrices during the analysis of metal ions and contaminants in water samples. Currently, conventional analytical techniques such as Transmission Electron Microscopy (TEM) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) are used for the detection of NPs, but such techniques require bulky instrumentation and are difficult to be automated for online analysis. In this study, we aim to develop a nanoparticle-imprinted hydrogel (NPIH, NANOGEL) to detect and capture NPs in water samples. The principle of the Nanogel originates from the well-known concept of molecularly imprinted polymers (MIPs). Cadmium sulfide/Selenide/Zinc sulfide core/shell quantum dots (QDs) were used as the template NP, creating specific pore cavities in the Nanogel that can selectively bind to certain analytes. Quantification of NPs detected in water samples was then made possible by transducing this selective detection process into an analytical signal using a quartz crystal microbalance (QCM). The Nanogel was shown to demonstrate good repeatability, reproducibility, and stability in terms of its performance. The high selectivity of the Nanogel was determined to be attributed to the size of cavities and their surface characteristics. Ionic interference was present and, heavy metal cations showed an affinity for the NANOGEL synthesized; however, they were demonstrated to be minimized by the selection of porogenic solvents during the synthesis of NANOGEL. We believe that the Nanogel would provide a highly selective and sensitive approach for the detection of NPs in aqueous samples and the removal of NPs from contaminated water resources. It will serve useful in environmental applications.

1. Introduction

1.1. Nanoparticles (NPs)

Nanoparticles (NPs) are objects with three dimensions in the nanoscale, ranging from 1 to 100 nanometers [1]. This class of objects is either naturally existing, unintentionally formed, or intentionally produced and specifically engineered to provide nano-size and nano-shape-related features [1]. NPs can thus have a variety of different cores, sizes, shapes, and stabilizing shells. Depending on their morphology, size, and chemical properties, NPs can then be broadly divided into various categories. A well-known class of NPs would be quantum dots (QDs), where QDs refer to nanocrystals of a semiconductor material whose size is between single molecules and bulk crystalline solids [2]. Typically ranging in diameters from 2 to 10 nanometres, QDs have a structure consisting of a core, shell, and surface ligands as functional groups. They exhibit quantum mechanical behavior due to the specific size of their energy band gaps [3]. Such properties allow QDs to be used in a wide range of applications, such as solar cells, transistors, medical imaging as well as quantum computing [3]. Aside from QDs, metal NPs and ceramics NPs are also common classes of NPs, with their wide range of applications [4].

With the increasing fields of applications and rising production of NPs, concerns about probable environmental and health risks regarding NPs have also inevitably arisen over the years, and this class of objects has been said to represent emerging environmental pollutants [1]. A few studies have shown the potential toxicity of quantum dots to mammalian cells, fungal cells, plants, and other organisms [4,5,6,7]. For example, recent studies show that quantum dots first interact with the selectively permeable cell membrane layer for mammalian cells, which divides the intracellular space from the surroundings and controls the transit of materials in and out of the cell. Quantum dots have the capability to internalize into mammalian cells using multiple pathways, such as clathrin-mediated endocytosis, caveolae-mediated endocytosis, and micropinocytosis pathways [8]. It can cause apoptosis and inhibit proliferation. Likewise, for plants, the plant cell wall is a key component when it comes to the internalization of quantum dots. Quantum dots are able to bind to cellulose and lignin and can be retained in membrane-bound vesicles in plant cells for a long period. This mainly affects the oxidative processes in plants and causes higher levels of photosynthesis inhibition, an important process for the survival of plants [8]. This shows the importance of detecting nanoparticles, and more specifically, quantum dots, in the environment due to the long-lasting and significant effects they have on living organisms.

NPs in sample filtrates are also a significant interfering matrix in the analysis of metal ions and contaminants [1]. The possibility to remove these NPs through techniques such as ultrafiltration or nanofiltration is present but not commonly employed the routine analysis due to the need for high bar operational pressure. Hence, nanotoxicity is a new scientific discipline which requires the development of appropriate tools for the detection and quantification of NPs. Providing suitable analytical procedures for a reliable study of the fate and pathways of NPs in the environment is thus a crucial prerequisite to assessing the potential risks for environmental and human health arising from nanomaterial production, application, and disposal and quantifying the presence of NPs [1].

The treatment of NPs as a target analyte for quantification has not been extensively researched, and NPs currently still pose analytical challenges for their detection in environmentally relevant samples because of their extremely low concentration, high colloidal background, and the need to perform speciation analysis [1]. Present analytical strategies such as preconcentration techniques, electrothermal atomic absorption spectroscopy (AAS), and single particle Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), can be used for their detection and quantification, but these analytical techniques are difficult to be automated for online analysis, and cannot be considered an inexpensive analytical approach [1]. Other common methods of detection such as Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), and Atomic Force Microscopy (AFM), are not only costly but also time-consuming and require the use of heavy equipment. Moreover, preliminary treatment of samples for such techniques could potentially change the aggregation state and surface chemistry of NPs, and interfere with the detection and quantification process as well [9,10]. There is hence a pressing need to work on the detection methods of NPs in aqueous samples.

1.2. Imprinted Hydrogel

The concept for the selective detection of NPs by a polymeric matrix imprinted with the same NPs is used [10]. A nanoparticle-imprinted hydrogel (NANOGEL) is developed and should be able to detect and capture NPs in water samples [10].

A hydrogel is a three-dimensional network of hydrophilic polymers. NANOGEL adapts the well-known concept of molecularly imprinted polymers (MIPs) [10], where MIPs refer to synthetic polymers with a predetermined selectivity for a given analyte or group of structurally related compounds [10]. MIPs are polymers that have been processed using the molecular imprinting technique (MIT), leaving cavities in the polymer matrix, allowing the polymer to have an affinity for a chosen analyte, which is the template used [11,12,13,14,15,16,17,18]. MIT is based on the formation of a complex between an analyte, which is the template, and a functional monomer [11,12,13,14,15,16,17,18]. A three-dimensional polymer network results in the presence of a large excess of a cross-linking agent. After such polymerization, the template can be removed from the polymer, which now has specific cavities complementary in shape, size, and chemical functionality to the template used. This allows the polymer to recognize and bind selectively to template molecules based on intermolecular interactions like hydrogen bonds, dipole-dipole, and ionic interactions between the template molecule and functional groups present in the polymer matrix.

The NANOGEL is a specific type of MIP, and it utilizes the same principle as mentioned above, where the template used in the formation of the polymer matrix is NPs, for the detection and capture of NPs in water samples [14]. NANOGEL will allow for the detection process to be highly selective and specific. Unlike other techniques, samples do not need to undergo preliminary treatment before the detection process, and this allows for the NPs to be detected properly, without the chance of preliminary treatment methods altering their surface chemistry. In this research study, the template NPs were chosen to be Cadmium sulfide/Selenide/Zinc sulfide (CdS_xSe_1−x/ZnS) core/shell QDs, with carboxylic acid surface ligands and an emission wavelength of 525 nanometres. QDs were chosen as they are used in a wide range of applications [6]. Furthermore, concerns about the toxicity of QDs owing to their heavy metal content have also risen over the years, making the detection of QDs important not only for their possible interference effect in samples, as mentioned above, but also from the clinical and health viewpoints [11,12,13,14,15,16,17,18,19]. The approach for QDs can then later be extended in a similar manner to other nonfluorescent NPs as well [11,12,13,14,15,16,17,18,19].

There are multiple ways to prepare nanogels. Nanogels are prepared by various methods of copolymerization of hydrophilic or water-soluble monomers in the presence of difunctional or multifunctional cross-linkers, including photolithography, micro molding, and homogenous gelation techniques [20]. A strategy adapted from the work of Li and co-workers is used here [10,20]. A polymerization mixture is first prepared using a functional monomer, a cross-linking agent, and a radical initiator. Silica NPs are also added in and serve the purpose of creating a colloidal crystal aggregate for the formation of the silica-based NANOGEL. Template NPs, which are the QDs, are subsequently added in. Upon polymerization through heating, the mixture is frozen into a 3D network of polymers. The template QDs are then removed using hydrofluoric acid, leaving the NANOGEL containing the imprints of the QDs. The removal of this template will form complementary cavities capable of selectively recognizing the analyte.

Table 1. Key characteristics of the nanogel.

Basis of Comparison	Literature and Previously Published Studies	Nanogel for Detection of Nanoparticles in Water Samples
Type of hydrogel	Hydrogels can be responsive to different stimuli, such as temperature, pH, light, electrical conductivity, enzymes, etc. [21].	The nanogel in our study has been imprinted using a particular template of quantum dots, allowing it to have specific binding sites to quantum dots and nanoparticles. It functions responsively, similar to that of an enzyme stimulus, where the enzyme binds to the substrate via the lock and key hypothesis.
Method of synthesis	Synthetic strategies for the preparation of nanogels can be mainly divided into two different categories, that involving the formation of nanogels using preformed polymers versus the other entailing the formation of nanogels via the direct polymerization of monomers [22].	The nanogel in our study was formed via the direct polymerization of monomers in the presence of cross-linkers.
Main advantage of hydrogel usage	Hydrogels have the diversity of creating various adsorbents suitable for capturing potential pollutants [23].	With a different template used during the imprinting process, the nanogel will be able to detect different forms of nanoparticles and allow the quantification to be done with the quartz crystal microbalance.

below shows the key characteristics of the nanogel in the study, as compared to hydrogels with similar applications.

1.3. Quartz Crystal Microbalance (QCM)

With the NANOGEL, it is then important to find an effective way of transducing the selective detection process into an analytical signal for the quantification of NPs in water samples to be possible. The quartz crystal microbalance (QCM) is a piezoelectric sensor that measures the mass variation per unit area by measuring the change in frequency of a quartz crystal resonator [24,25]. Any deposition or removal of a small mass at the surface of the resonator will result in a disturbance of the resonance and cause a frequency change [24]. Hence, in this study, the NANOGEL is coated onto the QCM sensor chip, using the principle that a frequency change will be detected if there is any detection and uptake of analyte by the NANOGEL, as this uptake causes an increase in mass [24]. A frequency change in terms of a decrease is then expected because the loaded mass would cause the resonator to oscillate slower than normal, creating a frequency shift.

The quantification of the analyte would also be achieved because the frequency change detected is related to the mass by the Sauerbrey equation [25]. This equation describes a linear relationship between the frequency of the oscillating quartz crystal resonator and mass changes:

Δm = −CΔf

(1)

where Δm is the change in mass, C is the constant related to the properties of the quartz crystal, and Δf is the change in frequency [25].

In this study, the QCM sensor chip coated with the NANOGEL will be tested out with various analyte solutions, and frequency change, if any, will be observed. This provides insight into the other analytes that the NANOGEL can detect and uptake, other than the template QDs.

2. Materials and Methods

2.1. Preparation of Polymerization Mixture

The polymerization mixture used for the synthesis of the NANOGEL consisted of 30 μL of Azobisisobutyronitrile (AIBN), 400 μL of Methacrylic acid (MAA), 400 μL of Ethylene glycol dimethacrylate (EGDMA) and 68 mg of purified silica NPs (Table S1: Structure of monomers). 2 mL of ethanol was used as the solvent system. Ethanol was the first solvent of choice, with it being a universal solvent due to the presence of polar and non-polar groups. As mentioned above, the purified silica NPs served the purpose of creating a colloidal crystal aggregate for the formation of the silica-based NANOGEL [8]. AIBN was the radical initiator, MAA was the functional monomer, and EGDMA was the cross-linking agent. The ratio of these reagents was optimized for a more substantial amount of NANOGEL to be synthesized (Table S2: Effect of the ratio of different reagents in the pre-polymerization mixture on the amount of NANOGEL obtained).

2.2. Synthesis of Nanogel

A volume of 60 μL of CdS_xSe_1−x/ZnS core/shell QDs (5 mg/mL), functionalized with carboxylic acid surface ligands, and having an emission wavelength of 525 nanometres, were added into the polymerization mixture as the template QDs. The mixture was then degassed with nitrogen for 5 to 10 min to remove any presence of dissolved oxygen. After degassing, the mixture was heated to polymerization, with stirring, at 80 °C. The temperature of 80 °C works well as it is close to the boiling point of ethanol. The NANOGEL was synthesized from the polymerization reaction. The NANOGEL was then immersed in a solution of 4% hydrofluoric acid (HF) for 6 h to remove the QDs used as a template from the NANOGEL. This allows the formation of the complementary cavities on the NANOGEL, which is capable of selectively recognizing the QDs used previously as a template [10]. The NANOGEL was then obtained by vacuum filtration and dried for 48 h. The NANOGEL was lastly ground into a fine powder with the use of a mortar and pestle. 0.3941 g of pale-yellow NANOGEL powder was obtained (Figure 1).

2.3. Preparation of QCM Sensor Chip

The QCM chip was first cleaned with an ethanol wipe. 2.6 mg of NANOGEL, in the form of a fine powder, was then added to 1 mL of hexanol. The powder was dispersed by shaking the solution. 1.15 μL of the solution was then coated onto the QCM chip and left to dry in the air, at ambient temperature, for 2 h before its use in analysis (Figure S1: NANOGEL-coated QCM chip after air drying).

2.4. Preparation of Sample Solutions

Sample solutions used in QCM analysis were prepared daily to ensure the freshness of samples. The analyte, that is the desired NPs, was dissolved in deionized water. Varying amounts and types of analytes were used to form different sample solutions. All sample solutions were then ultrasonicated for 5 min and subsequently vortexed for 1 min before their use in QCM analysis.

2.5. Regeneration

After each measurement in QCM analysis, the NANOGEL was subjected to a 0.01 M dilute nitric acid solution for 5 min to wash to prevent the effects of carry-over to the next sample measurement. This was followed by deionized water for 30 min to achieve a stable baseline before the next measurement (Figure S2: Frequency changes during regeneration).

2.6. Use of QCM

The QCM used in this study was QCM-8 for AMPSS, along with the MIIPQS analysis software.

2.7. Characterization of Nanoparticles

Aside from the QDs used as the template in the synthesis of the NANOGEL, other NPs varying in size and surface characteristics (Figures S6–S11: Characterization of carbon dots) were also used in the QCM analysis to study the analytes that the NANOGEL was able to detect and uptake. All these NPs were studied using Dynamic Light Scattering (DLS) to obtain their respective particle size and zeta potential measurements. The instrument used was the Malvern Zetasizer.

2.8. Characterization of Nanogel

Fluorescence spectroscopy of the NANOGEL was conducted to determine whether the removal of the QDs used as a template in the synthesis of the NANOGEL by hydrofluoric acid, was successful. The instrument used was the Agilent Technologies Cary Eclipse Fluorescence Spectrophotometer. FT-IR spectroscopy for the study of the chemical properties of the NANOGEL was done using the Shimadzu IRPrestige-21 as well. Brunauer-Emmett-Teller (BET) analysis by the Micromeritics ASAP 2020 Surface Area and Porosity Analyzer was used to study the surface characteristics of the NANOGEL.

3. Results and Discussion

3.1. Characterization of Nanogel

Fluorescence spectroscopy of the NANOGEL filtrate revealed that the removal of the QDs used as a template in the synthesis of the NANOGEL by hydrofluoric acid was successful. The template QD used had an emission wavelength of 525 nanometres, and the fluorescence spectrum showed an emission peak with maximum intensity at around 515–525 nanometres upon excitation at 340 nanometres (Figure S5: Fluorescence spectroscopy of NANOGEL filtrate). FT-IR spectroscopy also showed certain chemical properties of the synthesized NANOGEL. Lastly, insights on the surface characteristics of the NANOGEL were obtained from the BET analysis performed.

3.1.1. Fourier Transform Infrared (FT-IR) Spectroscopy

MAA and EGDMA were used as the monomer and crosslinker in the polymerization reaction to form the silica-based NANOGEL. Prominent peaks observed in the FT-IR spectrum of the NANOGEL corresponded to that of poly(methacrylic acid) (PMMA), and it can be concluded that the polymerization reaction for the synthesis of the NANOGEL was successful. From the FT-IR spectrum obtained (Figure 2), it can be seen that there were two distinct and sharp absorption bands at 1149 cm⁻¹ and 1242 cm⁻¹, and these can be attributed to the C-O-C stretching vibration. The bands at 1149 cm⁻¹ and 1104 cm⁻¹ were likely attributed to the asymmetrical and symmetrical C-O-C stretching vibrations [26]. The sharp band at 1705 cm⁻¹ represented the presence of the acrylate carboxyl group, and the band at 941 cm⁻¹ was the characteristic absorption vibration of PMMA. Furthermore, the medium bands observed from 1300 cm⁻¹ to 1400 cm⁻¹ were due to the C-H bending vibrations from the -CH₃ groups, while the medium band observed at 2924 cm⁻¹ was due to the C-H stretching from the -CH₂ and -CH₃ groups. The peak at 721 cm⁻¹ was from the methyl group vibrations.

It was observed that there was the absence of basic amine groups in the NANOGEL, as the structure of the NANOGEL resembled that of PMMA, which is dominated by acidic carboxylic acid groups.

3.1.2. Brunauer-Emmett-Teller (BET) Analysis

As the NANOGEL should be capable of detecting and uptaking analytes, the size of the cavities, otherwise known as the pores, is crucial to its selectivity and was studied using BET analysis. The QDs used for imprinting to create the pore cavities were 5.524 nanometres in diameter. However, the BET analysis obtained showed that the majority of the pores were around 7.5 nanometres in diameter (Figure 3 and Figure 4), being slightly larger than the template QDs used for imprinting, which is reasonable and expected. The sizes of the pores were also seen to range up to 20 nanometres in diameter. Widened pore sizes could be because hydrofluoric acid was used to remove the QD template and silica NPs during the preparation step of template removal for NANOGEL. Hydrofluoric acid is capable of pore widening and results in the enlargement of pores from the size of the template used [27].

In addition, the BET surface area of the NANOGEL was determined to be 4.7829 m²/g, where the surface area can be further divided into the micropore area (2.3705 m²/g) and external surface area (2.4125 m²/g), with the external surface area comprising of the mesopores (2–50 nm) and macropores (>50 nm). Pore volume and pore surface area measurements revealed that the micropores, with micropores being less than 2 nanometres in diameter, take up 49.6% of the total surface area of the NANOGEL, but only 7.19% of the total volume of the NANOGEL, indicating the majority of mesopores. Moreover, the low surface area of the NANOGEL is because protic solvents like ethanol have a stronger solvency, resulting in the formation of larger polymer particles during the polymerization reaction [28].

3.1.3. SEM Analysis

DLS was used to characterize the particle size and zeta potential of the NP aggregates (the Pre-NANOGEL synthesized before template removal). The results obtained showed that the Stober-Fink-Bohn method was indeed successful in synthesizing monodisperse silica nanoparticle aggregates of 200 to 700 nanometers. Reaction conditions used were successfully optimized to give NP aggregates with a targeted size of 200 to 400 nanometres, with the average size being 279.9 nanometres. A Zeta potential of −12.8 millivolts (mV) was also recorded, indicating the tendency of the particles to agglomerate together when in an ethanol solvent system. Ethanol has an average pH of 7.33 and is a potential reason to explain the agglomeration of NP aggregates, as an agglomeration of silica NPs increases with increasing pH [29].

The surface morphology of the NP aggregates was then further studied using SEM. From the low magnification image (Figure 5), the silica NPs appeared to be present in clusters, supporting the indication from the zeta potential measurement of DLS that the particles tend to agglomerate together. Upon increased magnification, it can also be confirmed that the sizes of the individual particles are around that of what was measured from DLS.

As seen in Figure 6 below, the NANOGEL was observed to have an uneven morphology and did not demonstrate uniformity in terms of grain size. Grains ranging in size from 100 nanometres to 300 nanometres were observed and expected to be in the polymerization mixture of the acrylate-based NANOGEL. However, the high magnification SEM image of the NANOGEL still showed the polymer cross-linking structure of the NANOGEL.

3.2. Sensitivity, Linearity, Limit of Detection (LOD), and Limit of Quantification (LOQ)

The NANOGEL was able to detect and uptake the QDs used as a template, that is the CdS_xSe_1−x/ZnS core/shell QDs, with an emission wavelength of 525 nanometres. The calibration plots from Figure 7, as shown below, were linearized by plotting the average frequency change detected by the QCM against the concentration of the analyte in the sample solution (Table S3: Graph of average frequency change against concentration). Limits of Detection (LOD) and Limits of Quantification (LOQ) were calculated using the following equations (

Table 2. Analytical figures of merit for the NANOGEL.

Linear Range/ppb	Sx,y	LOD/ppb	LOQ/ppb
25–2000	0.67482	198.83	602.53

):

$${\mathrm{C}}_{\mathrm{LOD}}=\frac{3.3 \mathrm{Sx},\mathrm{y}}{\left|\mathrm{m}\right|} \& {\mathrm{C}}_{\mathrm{LOQ}}=\frac{10 \mathrm{Sx},\mathrm{y}}{\left|\mathrm{m}\right|},$$

(2)

where Sx,y is the standard error of the regression and m is the gradient of the calibration plot.

3.3. Selectivity Study

Comparison to Non-Imprinted Hydrogel

A non-imprinted hydrogel (NIH) was synthesized using the same experimental procedure as the NANOGEL, with the only difference being the absence of the template QDs in the polymerization mixture. Selectivity of the NANOGEL was then studied by comparing the responses between the NANOGEL and the NIH synthesized to a 1 ppm solution containing the template QDs as the analyte to evaluate whether there is a significant specific binding taking place in the NANOGEL, with the pore cavities made by the template QDs used (Table S4: Selectivity of NANOGEL in comparison to non-imprinted hydrogel (NIH)). Imprinting factor (IF) can be calculated by taking the response from the NANOGEL divided by the response from the NIH, and the specific adsorption ratio (SPR) can also be further calculated using the following equation:

$$\mathrm{SPR}=\frac{\mathsf{\Delta }\mathrm{F}\left(\mathrm{Hydrogel}\right)-\mathsf{\Delta }\mathrm{F}\left(\mathrm{NIH}\right)}{\mathsf{\Delta }\mathrm{F}\left(\mathrm{Hydrogel}\right)} \times 100\%,$$

(3)

where D_NANOGEL and D_NIH refer to the change in frequency detected by the QCM when the NANOGEL and NIH are used respectively.

A relatively high IF of 4.79 was obtained (Figure 8), indicating that there is a large extent of specific binding of the NANOGEL towards the analyte, which in this case, was the template QDs, at a concentration of 1 ppm. An SPR of 121% was also obtained (ΔF(NIH) was negative).

3.4. Properties of Size and Surface Characteristics

Aside from the template QDs as an analyte, other NPs varying in size and surface characteristics were also used as analytes at 1 ppm concentration to determine if the pore cavities in the NANOGEL are selective to other NPs apart from the template QDs used.

The QDs used as templates were the CdSxSe1–x/ZnS core/shell QDs, with carboxylic acid surface ligands and an emission wavelength of 525 nanometres. Similar CdS_xSe_1−x/ZnS core/shell QDs of different emission wavelengths ranging from 490 nanometres to 665 nanometres were first used as analytes, and it was determined that the NANOGEL could detect and uptake these QDs of the different emission wavelengths. The emission wavelength is affected by the size of the QDs, but despite this difference in size, the QDs were still within 5 to 12 nanometres and can enter into the pore cavities of the NANOGEL, as determined by the BET analysis mentioned above. The NANOGEL was further evaluated using larger NPs with carboxylic acid surface ligands, such as the CdTe core-type QDs and the gold NPs, and such NPs were also able to be detected by the NANOGEL (

Table 3. Response of analyte nanoparticles with different particle sizes and surface functional groups onto the NANOGEL-based sensor.

Nanoparticles	Functional Groups	Emission λ (nm)	Size/nm	Zeta Potential/mV	Detection by NANOGEL
CdSxSe1−x/ZnS core/shell QDs	carboxyl	490	6.284	3.71	Yes
CdSxSe1−x/ZnS core/shell QDs *	carboxyl	525	5.524	−1.35	Yes
CdSxSe1−x/ZnS core/shell QDs	carboxyl	575	9.537	−9.35	Yes
CdSxSe1−x/ZnS core/shell QDs	carboxyl	630	7.726	−23.1	Yes
CdSxSe1−x/ZnS core/shell QDs	carboxyl	665	11.49	−25.1	Yes
CdTe core-type QDs	carboxyl	510	12.45	−27.5	Yes
CdTe core-type QDs	carboxyl	570	13.65	−44.0	Yes
CdTe core-type QDs	carboxyl	610	10.60	−47.6	Yes
CdTe core-type QDs	carboxyl	770	16.00	−49.2	Yes
Gold NPs	carboxyl	NE **	8.576	−14.2	Yes
Gold NPs	carboxyl	NE **	10.38	−14.6	Yes
Gold NPs	carboxyl	NE **	12.16	−12.0	Yes
Gold NPs	carboxyl	NE **	36.18	−1.15	No
Carbon dots	carboxyl	NE **	0.7363	−9.70	Yes
Carbon dots	carboxyl and amine	NE **	1.185	3.28	No
CdSe/ZnS core/shell QDs	amine	NE **	15.50	−61.6	No
CdSe/ZnS core/shell QDs	alkyl	NE **	2.052	−26.1	No

Note: * Template used for NANOGEL; ** NE—not established.

). However, as pore cavities of the NANOGEL only varied from 5 to 20 nanometres, NPs larger than 20 nanometres were found unable to be detected when used as analytes. This confirmed the size selectivity of the NANOGEL, which was supported by the data obtained from the BET analysis.

The NANOGEL was also determined to exhibit selectivity based on the surface characteristics of the analyte. NPs within the size of the pore cavities, with carboxylic acid surface ligands, were able to be detected by the NANOGEL. On the other hand, the NANOGEL was unable to detect and uptake NPs with alkyl and amine surface ligands as functional groups, despite these NPs falling within the size of the pore cavities as well. A possible explanation for this is due to the surface characteristics of the template QDs used [5]. The template QDs itself had carboxylic acid surface ligands, resulting in the NANOGEL adapting a selectivity to other analytes with similar surface ligands. The similar structure and shape of these surface ligands result in the NANOGEL possessing a memory effect on such analytes, thus resulting in such analyte recognition properties [30].

3.5. Effect of pH

The pH effect on the NANOGEL was studied by varying the pH of the deionized water sample, with 1 ppm of template QDs as analyte. As seen in Figure 9, it was observed that solutions that have extremely acidic and basic pH caused a negative frequency change (frequency increase) (Table S5: Effect of pH on QCM response).

Some of the coated NANOGEL were removed from the surface of the QCM chip after the NANOGEL was exposed to such solutions (Figure S3: NANOGEL on the surface of the QCM chip before (left) and after (right) exposure to solutions with extreme acidic and basic pH). With a decrease in the mass at the surface of the chip, the quartz crystal resonator would oscillate faster than normal, and a negative frequency change, in terms of an increase, is experienced. This finding would mean that the pH of water samples used for analysis has to be adjusted to pH 4 to 6, because the frequency change, caused by the detection and uptake of analyte by the NANOGEL, can only be observed at such pH levels.

3.6. Effect of Ionic Solutions (Potential Matrix in Real Sample Analysis)

The effect of potential matrix ions on the NANOGEL was then studied by introducing different concentrations of ionic solutions (10 ppm and 100 ppm) into the deionized water sample, likewise with the 1 ppm template QDs as analyte.

When the analyte is present in ionic solutions containing heavy metal ions such as lead, copper, and cadmium, a significantly larger frequency change than those with alkali and alkali earth metals (Na⁺, K⁺, Mg²⁺, Ca²⁺) is detected by the NANOGEL (Figure 10) (Table S6: Effect of cations on QCM response). With 100 ppm ionic interference, the frequency change detected is at least 225% higher. This demonstrates the strong affinity of the heavy metal cations to adsorb onto the NANOGEL, and a potential explanation is the fact that the NANOGEL is a polymer chain with several carboxylic acid functional groups. Such carboxylic acid functional groups have a strong chelation ability with these heavy metal ions [31].

On the other hand, a negative frequency change is again detected by the NANOGEL when the analyte is present in ionic solutions containing carbonate and phosphate anions (Figure 11) (Table S7: Effect of anions on QCM response). Carbonate and phosphate anions are highly alkaline in nature [32], and as mentioned above, solutions with such pH can remove some of the NANOGEL from the surface of the chip, resulting in a decrease in mass at the surface of the resonator, causing a negative frequency change.

Lastly, the strong interfering effects from ionic solutions, in general, could also be due to the fact that the NANOGEL has a large surface area to volume ratio for its micropores, as mentioned above. Ions, which can fit into the micropores of the NANOGEL, could hence be potentially adsorbed onto such large surface areas [33]. The presence of increased mesopores areas provides adequate surface area for interactions between the analyte and stationary phases, increasing the binding capacity of the NANOGEL to target the analytes selectively [34]. There is potential for such ionic interference to be reduced by changing the solvent of the polymerization reaction, as the solvent plays a vital role in the polymer synthesis, with the polymer growth stage being highly dependent on the properties of the solvent [28].

3.7. Repeatability Study

The repeatability of the NANOGEL was accessed by analyzing its responses to a 1 ppm solution containing the template QDs as the analyte, for 5 days, with five repeated measurements being taken each day. No large fluctuations were observed (Table S8: Average frequency change across a period of 5 days).

A two-tailed t-test at 95% confidence level was conducted on all the results obtained, that is the average frequency change measured on each of the days. Firstly, the average frequency change across these 5 days was compared to each other, and the statistical tests reveal that there is no significant difference in the frequency change measured, with a p-value of 0.11471 obtained. After which, the average frequency change across these 5 days was also compared to the average frequency change of the 1 ppm solution from the calibration plot (Figure 7), which is 15.8 Hz. A p-value of 0.36023 was obtained, similarly indicating no significant difference. This highlights the consistency of the frequency change detected by the NANOGEL, which is an important factor that affects the performance of the NANOGEL.

3.8. Reproducibility Study

The reproducibility of the NANOGEL was also accessed by analyzing the responses of two more duplicates, with comparison to the calibration plot obtained earlier, as shown in Figure 7 (Table S9: Graph of average frequency change against concentration for the duplicates). Duplicates were prepared by coating the NANOGEL onto different QCM sensor chips to ensure that the responses obtained in terms of frequency do not differ significantly when the NANOGEL is coated onto a different chip.

All three calibration plots on three different sensor chips have similar gradients and R² values (Figure S4: Graph of average frequency change against concentration for the duplicates in comparison to the earlier calibration plot (Figure 7)), indicating a similar change in frequency detected by the QCM with the solutions of different concentrations of template QDs. An ANOVA test is a way to find out if survey or experiment results are significant. To further determine if the duplicates are statistically similar to the calibration plot obtained earlier, the ANOVA test was also performed across all of the measurements at all the respective concentrations of the calibration curve. No significant difference was observed, highlighting the fact that the results obtained from the NANOGEL using QCM were indeed reproducible.

3.9. Stability Study

A short-term stability study was conducted for the NANOGEL for 35 days. Measurements in terms of frequency change were taken for a 1 ppm solution containing the template QDs as an analyte (Table S10: Average frequency change across a period of 35 days). The NANOGEL was stored in a covered petri dish in a dry state at room temperature when not in use.

A decrease in response was not observed after 35 days (Figure 12). To determine whether the differences are significant, a two-tailed t-test was also done to compare the frequency change measured from Day 1 to Day 35 at 95% confidence level. A p-value of 0.89256 indicated that the differences between the responses across these 35 days were not significant. There was also no significant difference when the frequency change of these responses was compared to the average frequency change of 15.8 Hz, of the 1 ppm solution from the calibration plot (Figure 7), with the p-value being 0.16078. However, a long-term stability study of at least 6 months to 1 year can be conducted to further evaluate the stability of the NANOGEL. It is expected that the NANOGEL would exhibit good stability because the NANOGEL is a silica-based hydrogel, and silica-based polymers typically exhibit minimal swelling in the presence of solvents and have excellent thermal stability. They are very stable against oxidation and aging, which are problems commonly faced by many organic polymers. Such attributes will hence allow the NANOGEL to maintain the shape and size of the imprinted pore cavities [35].

3.10. Evaluation of Effect of Solvent Used for Synthesis of Nanogel

When the analyte was present with certain ions in the aqueous solution, such as heavy metal cations, the frequency change observed in solutions was much larger than if the analyte were to be present by itself. Ions are thus proven to be a significant source of interference that can affect the analysis of NPs in water samples, as the actual frequency change caused by the NPs cannot be determined.

Apart from the fact that the carboxylic acid functional groups [31] of the NANOGEL have a strong chelation ability to heavy metal ions, the large surface area to volume ratio of the micropore area also can potentially allow more ions to be adsorbed, leading to a larger frequency change observed. Optimization of the performance of the NANOGEL was hence carried out to reduce the micropore area of the NANOGEL, to decrease ionic interference.

The NANOGEL was previously synthesized using ethanol as the solvent. For the optimization, different solvents were used for the synthesis of the NANOGEL while using the same experimental procedure to determine if there was a reduction in the micropore area of the NANOGEL. The solvent plays a vital role in polymer synthesis as the polymer growth stage is dependent on the properties of the solvent [18]. Since the polymerization reaction was carried out at 80 °C, it was hypothesized that the probability of the bumping of solvents would be lower with solvents with a higher boiling point, reducing the likelihood of the production of vapor bubbles, which can produce more non-mesoporous areas [36]. However, the BET analysis of the NANOGELs synthesized for optimization was unable to be determined due to the malfunction of the Micromeritics ASAP 2020 Surface Area and Porosity Analyzer. Hence, the frequency change of the NANOGELs to different analytes was studied as an alternative to observe there was a decrease in ionic interference when different solvents were used.

As ethanol was the original solvent used for the synthesis of the NANOGEL, other solvents with boiling points lower and higher than that of ethanol were used (

Table 4. Boiling point and dipole moment of the respective solvents.

Solvent	Boiling Point/°C	Dipole Moment [30,31]
Ethanol (original)	78	1.69
DMSO	189	3.96
DMF	153	3.82
Isopropanol	82.5	1.56

). The NANOGELs synthesized with the different solvents were then exposed to the target QDs as analytes in deionized water, with and without ionic interference. Lead was used as the ion of interference due to the largest frequency change detected when present in the solution previously. As seen in Figure 13, the ionic interference was significantly reduced when isopropanol was used as the solvent for synthesis (Table S12: Comparison of the effect of solvent on NANOGEL performance). This proved the initial hypothesis wrong, as solvents with higher boiling points above 80 °C, such as dimethyl sulfoxide (DMSO) and dimethyl formamide (DMF), showed even higher ionic interference as compared to that of ethanol.

Considering the dipole moment of the solvent, a possible explanation is that apart from the boiling point of the solvent, polarity also plays an important role [37]. Porogenic solvents should also be relatively low polarity to reduce interferences during complex formation between the template and the monomer [37]. With the polarity of the solvent influencing polymer morphology to a greater extent, ionic interference of the NANOGEL can be reduced with the use of solvents with low polarity. Despite its low boiling point, isopropanol demonstrates low polarity and the least interference from ions in terms of the frequency change detected. But this comes at the expense of the signal from the nanoparticles as well because IPA generates fewer non-specific binding sites but also fewer binding sites, where non-specific binding sites originate from the disorder of the interaction of the template and polymer. However, the effect of the solvent boiling point on the extent of non-macroporous areas should still be determined by BET analysis, if available, to explain the rejected hypothesis regarding the effect of the boiling point of the solvent. With DMSO and DMF being aprotic solvents, surface area analysis will also allow the effect of aprotic solvents on the surface area to be determined as well [28].

3.11. Use of Nanogel on Real Water Samples

As previous results were all obtained with the analyte being present in deionized water, NANOGEL performance was further tested with real water samples. Tap water was chosen to be the matrix. The analyte, which was chosen to be the template QDs, was spiked into tap water samples, and a standard addition was performed. A significantly larger frequency change was detected by the NANOGEL. This is because the presence of many interfering ions abundant in tap water [38] strongly impacts the performance of the NANOGEL, despite the pH of the water sample being slightly below neutral. As shown in Figure 14 below, there is a large discrepancy between the frequency change in tap water and deionized water. The majority of the frequency change may be attributed to the presence of interfering ions and not the NPs present. The actual NP concentration of tap water cannot be determined directly by a single standard addition method due to the high false positive signal.

A second standard addition was performed, with a mix of tap water and deionized water (volume ratio 1:1), to quantify the ionic interference present in tap water. The 2nd calibration curve has a similar slope as the 1st calibration curve but with a smaller false positive signal (Table S11: Graph of average frequency change against concentration of QDs spiked into water (for different real water samples)). Hence, it was confirmed that a way to remove false positive signals contributed by interfering ions and matrix would need to be developed for the analysis of real samples.

4. Conclusions

The NANOGEL (nanoparticle-imprinted hydrogel) was synthesized following the principle behind MIPs. The Nanogel was thus coated onto the surface of a quartz crystal resonator, and their performance was evaluated by studying their repeatability, reproducibility, selectivity, and stability. The Nanogel showed good repeatability and reproducibility and did not show significant changes in response during the 35-day stability study. The selectivity of the NANOGEL was studied by exposing the Nanogel to various analytes, and the Nanogel was confirmed to be selective based on its size as well as surface characteristics. Only NPs smaller than 20 nanometres were able to enter the pores of a Nanogel imprinted with 20-nanometer NPs and be detected. The selectivity based on acidic surface characteristics originated from the nature of the template used. Lastly, the effect of pH and ions on the Nanogel was also determined. The pH of water samples used for analysis must be adjusted to pH 4 to 6 as the Nanogel is removed from the surface of the quartz crystal resonator when in acidic and basic solutions. Ionic interference was present, and heavy metal cations showed an affinity for the NANOGEL synthesized; however, they can be minimized by the selection of porogenic solvents during the synthesis of NANOGEL. Linear calibration lines were obtained for NPs in a tap water sample by the standard addition method with dual calibration of the original tap water sample and a half-diluted tap water sample. However, an approach to remove the false positive signal from interfering ions and matrix still needs to be developed for the determination of NP concentrations in real samples.