A dual-function gold–zinc ferrite nanocomposite sensor for colorimetric detection of phosphates in environmental water

Abstract

Excess phosphorus in water systems causes eutrophication and poses significant ecological risks. In contrast, the bioavailable forms of phosphorus are valuable for crop production but are often limited. Therefore, the detection and identification of phosphorus forms in environmental water samples are important from both remediation and resource recovery perspectives. The design of effective nanocomposites offers a solution by enhancing the selectivity and differentiation of phosphates. Plasmonic gold nanoparticles (AuNPs), with inherently high extinction coefficients and unique optical properties, offer novel avenues for detecting phosphates. Magnetic zinc ferrite (ZnFe₂O₄) nanomaterials have higher binding affinities and are selective for phosphates through electrostatic forces and/or inner-sphere complex formation. Herein, Au-embedded ZnFe₂O₄ nanocomposites (AuZnFe₂O₄) were developed with an ability to detect and distinguish between inorganic and organic phosphates in water. UV-visible absorbance spectroscopy was applied to monitor the surface plasmon resonance (SPR) peak shifts and corresponding color changes of the plasmonic AuZnFe₂O₄ nanocomposite upon phosphate addition. Enhanced selectivity and varying adsorption stability were reflected by distinct SPR peak shifts and visible color changes, enabling differentiation between inorganic and organic phosphates. Density functional theory (DFT) simulations further provided mechanistic insights into the distinct chemical interactions and binding energies on the nanocomposite surface responsible for this differentiation. All organic phosphates revealed limits of detection (LODs) in the µM range, with ethion exhibiting the highest sensitivity (0.16 µM). Successful integration of this nanocomposite sensor into complex environmental water samples highlights its potential for rapid, selective, and colorimetry-based phosphate detection in environmental systems.

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Introduction

Global food security has emerged as one of the foremost challenges of the 21st century, exacerbated in part by reliance on phosphate rock, a designated ‘critical raw material’ that supplies the preponderance of phosphorus essential for fertilizer and pesticide production.^1–3 Concurrently, inadequate phosphorus management and recovery from agricultural runoff further strain this finite resource and drive eutrophication, an environmental crisis with significant ecological, economic and health consequences.⁴ The increasing scarcity of bioavailable phosphorus combined with ecological concerns has motivated the development of advanced technologies capable of precisely detecting and quantifying diverse phosphorus species in aquatic systems, such as water and sediments. To this end, effective phosphorus management practices can enhance recovery and recycling capabilities, improve resource management and reduce environmental impact.

From an analytical perspective, total phosphorus measurement remains the predominant indicator for monitoring phosphorus concentrations and assessing water quality, given the complexity, abundance and diversity of phosphorus species relative to other nutrients (i.e., carbon and nitrogen). These phosphorus species exist in both inorganic and organic forms, such as orthophosphates, condensed phosphates, organically bound phosphates, and organophosphorus (OP) compounds.^5,6 Such species are found in a range of sources, including but not limited to industrial, agricultural and consumer products.^7,8 Their toxicity, bioavailability and environmental impacts can vary considerably, depending on the distinct chemical properties and reactivity of each species. Orthophosphates, which can be produced through microwave digestion or oxidation, represent the most readily analyzable and bioavailable inorganic forms.⁹ Depending on the pH value of the water sample, orthophosphates predominantly exist as ions in the form of HPO₄²⁻, H₂PO⁴⁻, and PO₄³⁻, often associating with salts and metals.¹⁰ In contrast, condensed phosphates, also known as polyphosphates or polymerized orthophosphates, are characterized by phosphoanhydride bonds and can adopt linear, cyclic or branched structures (i.e., pyrophosphate, tripolyphosphate and metaphosphate).¹¹ In addition to inorganic forms, organic phosphates represent another class of phosphates, typically quantified by subtracting reactive phosphorus from the total phosphorus content in solution.¹² These organic forms can be classified into five primary categories: phospholipids, nucleic acids, nucleotides, inositol phosphates and phosphonates.¹³ Among these OP compounds, phosphonates are highly toxic to humans and animals, even at trace concentrations. The improper use of OP pesticides has negatively impacted numerous resources, including water, fruits, vegetables and processed foods, causing significant ecological and human health issues.¹⁴ Thus, developing effective and economically viable methods for detecting, detoxifying and removing these persistent OP compounds from the environment is of significant scientific and practical importance.

Feasible and accurate detection techniques that can distinguish between different phosphorus species are vital for effective monitoring of phosphorus in aquatic systems. The current state-of-the-art techniques that facilitate the rapid detection of phosphorus are varied, comprising colorimetry, fluorescence spectroscopy, microfluidic technology and electrochemical and remote sensing technologies.^15–19 However, these methods characteristically measure total phosphorus concentration and are inherently limited to detecting a single type of phosphate, either inorganic or organic. These limitations are further exacerbated by procedural complexity, the requirement for specialized instrumentation, and the limited sensitivity, specificity, and selectivity of sensing materials.

Colorimetric detection using nanomaterials can address these issues by providing a convenient and rapid monitoring method that generates visible color changes that can be directly interpreted by the user without specialized instrumentation.²⁰ Noble metal NPs, quantum dots and other nanomaterials produce a visual color change due to the light absorption properties of these materials.²¹ Spectroscopy techniques can determine the surface plasmon resonance (SPR) or localized surface plasmon resonance (LSPR) activity of these plasmonic nanomaterials by analyzing the collective oscillation of free electrons on their surfaces.²² This qualitative visualization, coupled with spectrophotometry, provides detailed quantitative wavelength shifts that are highly dependent on the composition, size, morphology and aspect ratio of the nanomaterial.²³ Few studies have demonstrated that the combination of colorimetry and UV-visible absorbance spectroscopy can effectively identify phosphate species. Our group has previously demonstrated the utility of plasmonic silver (Ag), gold (Au), and bimetallic silver–gold (Ag–Au) NPs for the detection and differentiation of various OP pesticides.²⁴ Similarly, Qian and Lin developed a colorimetric array to detect and differentiate OP pesticides and carbamates.²⁵ The high extinction coefficients of these NPs facilitate lower limits of detection (LODs) and enhanced sensitivity, while providing immediate responses. Other research groups have reported phosphate detection using a colorimetric method based on the anti-aggregation of mercaptoacetic acid-modified AuNPs and Eu³⁺ ions.²⁶ Here, the phosphate binding on Eu³⁺ ions leads to the redispersion of AuNPs with color visualization. He et al. detected phosphate ions using a colorimetric assay based on 4′-(4-mercaptophenyl)-2,2′:6′-2″-terpyridine zinc(II) complex (MPTP-Zn) modified AuNPs, in which Zn²⁺ provides strong affinity towards phosphates.²⁷ More contemporary research has described methylene blue functionalized TiO₂ nanotubes as a colorimetric probe for phosphate detection by leveraging the strong binding affinity between TiO₂ and phosphates.²⁰ Unfortunately, these colorimetric probes and assays were limited to detecting phosphate-containing species broadly and did not enable species-specific identification. Therefore, exploring novel plasmonic nanomaterials for phosphate speciation can enhance the detection and differentiation of its chemical form, improving phosphorus recovery and remediating water streams to mitigate eutrophication.

Successful incorporation of plasmonic metal nanoparticles into metal oxide nanomaterials could offer improved phosphate-selective detection and differentiation via colorimetry. However, designing effective nanocomposites requires careful consideration of each constituent and its metal-phosphate interactions. Noble metal AuNPs exhibit LSPR properties and thiol-specific interactions, while metal oxides predominantly bind phosphates through inner-sphere complexation, involving mononuclear monodentate, mononuclear bidentate, or binuclear bidentate forms.^28,29 ZnFe₂O₄, a spinel ferrite, has garnered attention in biosensing and heavy metal adsorption applications due to the distinctive physicochemical properties of the compound.³⁰ While iron-based metal oxides have been described as promising material candidates with enhanced phosphate selectivity, no prior work has been published on ZnFe₂O₄ nanomaterials for the detection of phosphates.²⁹

In this study, a novel AuZnFe₂O₄ nanocomposite comprising plasmonic AuNPs embedded within zinc ferrite (ZnFe₂O₄) NPs was designed to detect and differentiate organic and inorganic phosphate species in water. While AuNPs facilitate the plasmon resonance activity, zinc ferrite NPs provide a strong affinity towards phosphate compounds. Synergistic interactions within the nanocomposite were hypothesized to lower the LOD while preserving selectivity among phosphate species. The ZnFe₂O₄ NPs were synthesized using a co-precipitation technique followed by annealing, and AuNPs were synthesized using a chemical reduction method. The colorimetric sensing properties of the nanocomposite were evaluated using a UV-visible spectrophotometer. Four different organic phosphates were investigated: L-α-phosphatidylcholine (soybean phospholipid), ethion, malathion, and dimethoate, as well as two inorganic phosphates, sodium pyrophosphate and hexametaphosphate.

These six analytes were selected to represent distinct chemical classes of environmentally relevant phosphorus and to probe different binding motifs on the AuZnFe₂O₄ surface. Specifically, the condensed inorganic polyphosphates sodium pyrophosphate and sodium hexametaphosphate contain P–O–P anhydride linkages and have high charge density. A phosphate ester within a phospholipid matrix (L-α-phosphatidylcholine; soybean phospholipid) was selected to be representative of biomolecule-bound organic phosphorus and organophosphorus pesticides (ethion, malathion, and dimethoate) that contain thiophosphoryl (P=S) functionality and ester substituents. While all targets contain phosphorus, they differ in net charge, the number of phosphoryl oxygen atoms, and the presence/absence of P=S groups and hydrophobic moieties, which collectively drive distinct adsorption configurations and corresponding sensor responses.

To our knowledge, this study represents the first report of rapid detection and differentiation of inorganic and organic phosphates through a simple colorimetric sensing technique coupled with UV-visible absorbance spectroscopy. To further demonstrate the practical application of the detection system, environmental water samples collected from different aquatic systems were analyzed to assess its capability for real-time monitoring of complex environmental samples.

Results and discussion

Experimental

Synthesis and characterization. The AuZnFe₂O₄ nanocomposite was fabricated via a chemical reduction method by adding well-dispersed pre-prepared and characterized ZnFe₂O₄ NPs, as shown in Scheme 1.

Scheme 1 (a) Co-precipitation synthesis methodology of ZnFe₂O₄ NPs and (b) chemical reduction methodology along with the fabricated ZnFe₂O₄ NPs to create the AuZnFe₂O₄ nanocomposite (created using BioRender software).

Transmission electron microscopy (TEM) was used to characterize the morphology of the as-synthesized ZnFe₂O₄ NPs. Fig. 1(a) displays homogeneous and agglomerated structures with cubical shapes and an average particle size of 11.1 ± 1.6 nm. The observed agglomeration is likely due to magnetic interactions among the NPs.³¹ At a higher magnification of the expanded region, the HR-TEM revealed lattice spacings of ZnFe₂O₄ NPs throughout most of the region (Fig. 1(b)). The inset image shows the selected area electron diffraction (SAED) of the TEM image and supports the crystallinity of these NPs. The diffraction rings along (220), (311), and (444) confirm the crystal structure of ZnFe₂O₄. The measured interplanar d-spacing values of these NPs are 0.30 nm and 0.26 nm (Fig. 1(c and d), which can be assigned to (220) and (311) planes, respectively. The XRD pattern of the as-synthesized ZnFe₂O₄ NPs shows a high degree of crystallinity in Fig. S1(a). The diffraction peaks at 2θ values of 29.64°, 35.59°, 40.97°, 54.16°, 62.50°, 72.16°, and 75.58° are assigned to (220), (311), (400), (511), (440), (620), and (622), and they match the cubic ZnFe₂O₄ crystal structure (JCPDS card no. 82-1042).³² In addition, several other diffraction peaks were observed at 2θ values of 24.26°, 33.25°, 49.61°, and 64.05°, corresponding to crystal planes (012), (104), (024) and (300), respectively, indicative of a hematite (Fe₂O₃) hexagonal crystal structure (JCPDS card no. 86-055).³³

Fig. 1 (a) TEM image of ZnFe₂O₄ NPs at 60 kx (lower magnification); (b) HR-TEM of an expanded region (orange rectangle) captured at 400 kx (higher magnification) (inset shows its corresponding SAED); (c) and (d) the respective lattice spacings of (220) and (311) crystal planes; (e) the XPS survey spectrum of the as-synthesized ZnFe₂O₄ NPs; (f) Zn 2p binding energy spectrum, (g) Fe 2p binding energy spectrum and (h) O 1 s binding energy spectrum.

The crystallite size of the ZnFe₂O₄ NPs was calculated from the principal diffraction peaks corresponding to the (311), (400), (422), (511), and (440) planes using the Scherrer formula:³⁴

d = κλ/(β cos θ)

where d is the crystallite size (nm), κ is the shape factor (0.943), λ is the X-ray wavelength (1.5406 Å for Cu Kα radiation), β is the full width at half maximum (FWHM) of the diffraction peak (in radians) after baseline correction, and θ is the Bragg angle. Based on these reflections, the average crystallite size was calculated to be 26.4 nm.

The chemical structure of ZnFe₂O₄ NPs was investigated using X-ray photoelectron spectroscopy (XPS). The XPS survey spectra, illustrated in Fig. 1(e), confirmed the presence of key elements Zn, Fe, and O, with atomic percentages of 11.56%, 25.58%, and 62.87%, respectively. The Zn 2p spectrum (Fig. 1(f)) showed characteristic peaks corresponding to Zn 2p3/2 and Zn 2p1/2 peaks at binding energies of 1022.9 eV and 1045.7 eV, respectively. These results confirm that Zn exists in a 2+ oxidation state within ZnFe₂O₄, consistent with previously reported literature.^35,36 The Fe 2p region, presented in Fig. 1(g), displayed peaks at 725.7 eV and 711.8 eV, attributed to Fe2p1/2 and Fe2p3/2 peaks, respectively, along with satellite peaks. This is characteristic of the presence of Fe³⁺ ions in these NPs.³⁷ Furthermore, the O 1 s spectrum, shown in Fig. 1(h), exhibited two distinct peaks at 530.7 eV and 532.7 eV, corresponding to lattice oxygen binding with Fe and Zn, respectively.^35,38 The dominant feature observed in the ZnFe₂O₄ NPs is the primary Fe–O peak.

Similarly, TEM was used to perform detailed morphological characterization of the AuZnFe₂O₄ nanocomposite after embedding AuNPs into ZnFe₂O₄ NPs. TEM imaging (Fig. 2(a) revealed well-dispersed, spherical AuNPs distributed throughout the ZnFe₂O₄ NP clusters across the grid. The lighter regions in the image correspond to Zn ferrite NPs, whereas the darker area represents AuNPs (Fig. 2(b)), which have an average size of 10.2 ± 2.1 nm. The SAED analysis further confirmed the presence of the Au (111) crystal plane (Fig. 2(c), while crystal lattice fringe measurements confirmed the d-spacing of 0.24 nm along the (111) crystal plane (Fig. 2(d)). The XPS characterization of the AuZnFe₂O₄ nanocomposite verified the successful incorporation of AuNPs and the original elemental constituents of ZnFe₂O₄ in the survey spectrum, as shown in Fig. 2(e).

Fig. 2 (a) TEM image of the AuZnFe₂O₄ nanocomposite at 40 kx (lower magnification); (b) HR-TEM of an expanded region captured at 100 kx (higher magnification); (c) the SAED; (d) lattice spacing of Au (111); (e) the XPS survey spectrum; and (f) Au 4f binding energy spectrum of the nanocomposite.

The Au 4f binding energy spectrum showed two pairs of peaks at 82.7 eV and 86.4 eV, assigned to the spin–orbit splitting of Au 4f7/2 and Au4f5/2 peaks, respectively, to reveal that the nanocomposite consists of metallic Au (Fig. 2(f)).^39,40 The individual binding energy spectra of Zn, Fe, and O indicated no compositional changes in the ZnFe₂O₄ NPs, as shown in Fig. S1. Furthermore, angular-dark field-scanning transmission electron microscopy (ADF-STEM) combined with energy-dispersive X-ray (EDX) analysis revealed uniform elemental distribution in both ZnFe₂O₄ NPs and the AuZnFe₂O₄ nanocomposite, as represented in Fig. 3. This uniformity verified the homogeneous integration of plasmonic AuNPs into the ZnFe₂O₄ NPs, which is crucial for the consistency, reliability and accuracy of chemical sensing.⁴¹

Fig. 3 STEM/EDX elemental mapping of ZnFe₂O₄ NPs (a) ADF-STEM image, (b) EDX overlay map and (c–e) individual elemental mapping for Fe, Zn, and O, respectively. STEM/EDX elemental mapping of the AuZnFe₂O₄ nanocomposite. (f) ADF-STEM image, (g) EDX overlay map and (h–k) individual elemental mapping for Au, Fe, Zn, and O, respectively. Scale bar in all images is 50 nm.

Effect of phosphates on the plasmonic activity of the AuZnFe₂O₄ nanocomposite

UV-visible absorbance spectrophotometry was used to evaluate shifts in the wavelength and optical properties of the plasmonic AuZnFe₂O₄ nanocomposite at the surface level upon exposure to inorganic and organic phosphates, with these changes compared against the initial nanocomposite absorption spectrum (Fig. 4). Two inorganic phosphates (sodium pyrophosphate and sodium hexametaphosphate) and four organic phosphates (soybean phospholipids and three OPs such as ethion, malathion, and dimethoate) were used as model compounds to examine the ability of the nanocomposite to detect and differentiate phosphate compounds under identical reaction conditions. The initial concentrations of inorganic phosphates, organic phospholipids and OPs were 0.3 M, 3 µM, and 30 µM, respectively. The characteristic SPR peak for the AuZnFe₂O₄ nanocomposite arises at 520 nm in the UV-visible absorbance spectrum, and the color of the nanocomposite resembled wine-red in color. For each titration, 10 µL of each phosphate solution was continuously added to 30 mL of nanocomposite solution in the presence of phosphate-buffered saline (PBS) solution maintained at pH 7. The results revealed distinct interactions of the AuZnFe₂O₄ nanocomposite with both inorganic and organic phosphorus species, evidenced by unique SPR wavelength shifts (Fig. 3) and distinct color changes of each phosphorus species, as represented in Fig. 4(a).

Fig. 4 UV-visible absorbance spectra of the AuZnFe₂O₄ nanocomposite titrated with phosphates in PBS buffer at pH 7: (a) sodium pyrophosphate, (b) sodium hexametaphosphate, (c) Soybean phospholipid, (d) ethion, (e) malathion and (f) dimethoate. Calibration titration aliquot ranges for each phosphate are summarized in Tables S2 and S3.

Increasing concentrations of sodium pyrophosphate and sodium hexametaphosphates resulted in a slight broadening of the band center near ∼530 nm (Fig. 4(a) and (b)). This interaction was visually confirmed by a color change from wine-red to blueish-grey, signifying the successful interaction of these inorganic phosphates on the surface of the plasmonic nanocomposite. In contrast, exposure to increasing concentrations of all three OP compounds (ethion, malathion, and dimethoate) resulted in the emergence of a new red-shift peak, decreased absorbance intensity and broadening the initial peak at 520 nm (Fig. 4(d–f)). The corresponding wavelengths were accompanied by noticeable and distinct color changes of each OP compound, which can be described and quantified by the SPR wavelength shift (Fig. 5(b)). Ethion showed the highest wavelength shift of 165 nm, while malathion and dimethoate have peak shifts of 116 nm and 135 nm, respectively. The color change of ethion is greyish, while malathion is blueish-purple, and dimethoate is reddish purple (Fig. 5(a)). Interestingly, there was no observed SPR peak shift or broadening of the initial peak at 520 nm upon the interaction between soybean phospholipid and the nanocomposite. However, increased soybean phospholipid concentrations resulted in decreased peak intensity and the emergence of a new peak at 632 nm, coinciding with a color shift from wine-red to purple (Fig. 4(c) and Fig. 5(a)). These distinguishable and unique characteristics of SPR wavelength shifts, accompanied by color changes, provided exceptional capabilities toward screening and differentiation of inorganic phosphates, organic phosphates, and OP compounds from a complex mixture of different phosphorus species in a water sample. Taken together, the differing optical responses of this nanocomposite-based chemical sensing technique suggest potential for screening the tested phosphate types under the controlled conditions used herein; evaluation of mixtures and more rigorous selectivity assessment in representative water matrices will be part of future experiments.

Fig. 5 (a) The corresponding photo images and color scale of the AuZnFe₂O₄ nanocomposite in the presence of phosphate compounds (sodium pyrophosphate, sodium hexametaphosphate, soybean phospholipids, ethion, malathion, and dimethoate); (b) wavelength shifts accompanied by color changes for each phosphate.

Insight of chemical bonding and interactions

The fundamental question remains: What factors drive the observed variations in color and SPR peak shift changes among different phosphorus species? It has previously been reported that nanomaterials directly interact with the target phosphorus species through chemical interactions that induce processes such as aggregation, dissolution, or precipitation, culminating in a conformational change in their structures.²⁴ It was hypothesized that the plasmonic properties of the AuZnFe₂O₄ nanocomposite and its different molecular interactions with phosphates would play a role in determining both color and SPR peak shifts, which depend on the nature of chemical bonding and aggregation induced by distinct phosphorus species. The red-to-blue transition is the key transduction mechanism in the AuNP-based colorimetric detection technique as AuNPs aggregate upon phosphate exposure and the nanocomposite optical properties change. To evaluate this hypothesis, the morphological characteristics after the phosphorus exposure were examined. The TEM images in Fig. S2 illustrate the aggregation behavior of the nanocomposite after exposure to each phosphorus species, and each phosphate induced varying degrees of aggregation. Notably, no noticeable changes in the size or shape of the individual Au NPs were observed after phosphate exposure. TEM analysis showed no evidence of growth or dissolution of individual AuNPs. These results suggest that aggregation modulates nanocomposite stability. Moreover, higher aggregation of AuNPs in the ethion sample (Fig. S2(d)), compared to the scattering of AuNPs in the nanocomposite in the case of dimethoate, is a distinguishable aggregation level phenomenon, which leads to the different sensitivity of the phosphate structure. Therefore, instability was assessed by comparing the absorbance ratio of the nanocomposite before and after the phosphate exposure (A/A0) during the color changes (Fig. S3). Sedimentation plots revealed that ethion induced the fastest instability, whereas the nanocomposite was the most stable following exposure to dimethoate. These findings imply a higher affinity and stronger binding interaction of the nanocomposite to ethion relative to dimethoate. Among the inorganic phosphates, sodium hexametaphosphate induced greater sedimentation than pyrophosphate. Overall, sedimentation of the plasmonic nanocomposite toward the organic phosphates followed the order: ethion > soybean > malathion > dimethoate, whereas for inorganic phosphates the order was sodium hexametaphosphate > sodium pyrophosphate.

Computational studies were conducted to elucidate the adsorption mechanisms and molecular interactions of the organic and inorganic phosphates with the AuZnFe₂O₄ nanocomposite. Initially, the geometrical structure of the AuZnFe₂O₄-embedded surface along (001), comprising 232 atoms within this supercell, was fully optimized using Density Functional Theory (DFT) calculations, as shown in Fig. 6.

Fig. 6 (a) Side view and (b) top view of the optimized structure of the AuZnFe₂O₄ nanocomposite along (001).

Based on the surface arrangements of the metal atoms, eight Zn and Au atoms were identified in equal numbers, along with 16 Fe atoms. The embedded Au atoms were stabilized on this surface by forming Au–O bonds (∼1.973–1.990 Å) with two adjacent oxide nodes of the system. Spin-polarized DFT for the AuZnFe₂O₄ nanocomposite was used to determine the total density of states (DOS) and its partial DOS (PDOS), as shown in Fig. S4. The PDOS plot revealed strong interactions near −2.5 eV due to the overlaps between the 2p orbitals of the O atom of the nanocomposite and the 5d orbitals of the embedded Au atoms. The most stable conformations of the inorganic and organic phosphates adsorbed on the AuZnFe₂O₄ nanocomposite are shown in Fig. 7, with the major geometrical parameters and the adsorption energies listed in Table S1. Importantly, the metal surface favorably chemisorbs all six phosphate molecules with negative adsorption energies, indicating strong interactions and stable complex products, as presented in Fig. 7 (side views) and Fig. S5 (top views). The inorganic phosphates showed significant adsorption onto AuZnFe₂O₄ with ΔE_Ads = −2.54 eV and ΔE_Ads = −1.11 eV for pyrophosphate (Fig. 7(a)) and hexametaphosphate (Fig. 7(b)), respectively. Interestingly, the oxygen atoms of these two inorganic phosphates bind with both Au and Fe sites and form Au–O and Fe–O bonds with distances of ∼2.013–2.344 Å and ∼1.938–2.003 Å, respectively. Among all these adsorbates, one of the organic phosphates, ethion, showed the highest adsorption energy, ΔE_Ads = −4.04 eV, indicating the strongest interaction in Fig. 7(d). This was consistent with the experimental finding that ethion had the highest sensitivity and sedimentation. In this complex, one of the sulfur atoms preferentially binds with an Au on the surface, stretching the S=P bond from 1.920 to 2.002 Å and forming the Au–S bond with 2.266 Å. Like ethion, the other two OP compounds, malathion and dimethoate, were also effectively adsorbed by an Au atom (Fig. 7(d) and (e)), with Au–S bond distances of 2.263 and 2.278 Å, respectively. In addition to the Au–S bond, malathion was also found to bind the Fe atom on the surface with the oxygen of the carbonyl group at a distance of 2.075 Å. Due to these strong interactions, the adsorption energy of malathion was −2.56 eV, which was higher than dimethoate, −2.22 eV. Interestingly, the sulfur atom of the thiophosphoryl functional group in all three OPs, ethion, malathion and dimethoate, preferentially attached and reacted with the surface metal atoms Au and Fe in the nanocomposite. Additionally, phosphatidylcholine (soybean phospholipid) was chemically adsorbed on the surface via both oxygen atoms (Fig. 7(c)), forming Au–O bonds with lengths of 2.066 and 2.059 Å. In this case, the phosphorus-attached oxygen atoms activated the metallic Au atoms on the top of the surface of the nanocomposite, releasing −3.69 eV as the adsorption energy. Based on these DFT computations, all organic and inorganic phosphates were able to chemisorb on the surface of the AuZnFe₂O₄ nanocomposite, and the binding energy of organic phosphates decreased in the following order: ethion > soybean phospholipid > malathion > dimethoate. This outcome confirmed the experimental results, with the exception of the inorganic phosphates. It is noted that hexametaphosphate, as shown in Fig. 7(b), carries a negative charge of −6. The calculated binding energy may be underestimated due to electrostatic repulsion between supercells, a limitation arising from the imperfection in the computational model. Ideally, opposite ions in computations should neutralize the negative charge in a supercell.

Fig. 7 The side view of optimized configurations in phosphate structures on AuZnFe₂O₄: (a) pyrophosphate, (b) hexametaphosphate, (c) phosphatidylcholine, (d) ethion, (e) malathion, and (f) dimethoate, with atoms represented as follows: C in black, N in blue, H in white, P in pink, S in yellow and O in red.

Sensitivity, selectivity of phosphates, and monitoring of environmental water samples

The LOD of this nanocomposite was determined for each phosphate to elucidate the sensitivity of the sensor. The established procedure (3σ method) was used to calculate the LOD as follows: , where k is a numerical factor chosen according to the level of confidence (k = 3), σ is the standard deviation of the nanocomposite solution and S is the slope of the calibration curve (σ value was calculated to be 0.08614). In each case, the absorbance ratio of the SPR peak versus phosphate solution concentration was plotted to calculate the slope of the calibration curve, which showed a linear relationship. The equation of each case and calculated slopes with regression values are reported in Table S2. The calculated LOD values of all inorganic and organic phosphate compounds are displayed in Table 1.

Table 1 LODs for phosphate sensing using the synthesized AuZnFe₂O₄ nanocomposite

Phosphate type	LOD (µM)
Sodium pyrophosphate	6.29
Sodium hexametaphosphate	1.40
Soybean phospholipid	0.37
Ethion	0.16
Malathion	0.46
Dimethoate	0.99

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For each analyte, calibration points were chosen from preliminary titrations to bracket the concentration interval that produced a measurable and approximately linear SPR response (reported as the linearity range in supplementary Table S2), while avoiding signal saturation and excessive sedimentation. These ranges represent calibration windows for the present proof-of-concept system; future work will focus on sensitivity optimization and sample-preparation approaches to better align with routine water-quality monitoring ranges.

The experimental LOD results revealed a similar trend to sedimentation results. Ethion had the highest sensitivity among organic phosphates at 0.16 µM. The computational simulation results also validated the higher sensitivity of the AuZnFe₂O₄ nanocomposite towards ethion. The phospholipid had an LOD of 0.37 µM, while malathion and dimethoate achieved slightly lower LOD values of 0.46 µM and 0.99 µM, respectively. This observation can be further explained by hard-soft acid-base (HSAB) theory.⁴² Here, AuNPs on the surface of the nanocomposite act as soft acids, while thiophosphoryl (P=S) groups in ethion and malathion act as soft bases, and interactions of soft acids and bases or hard acids and bases are stronger. A similar higher sensitivity towards thion group containing OPs has been reported in our previous work for Au and Ag NPs.²⁴ Additionally, higher concentrations of inorganic phosphates demonstrated LODs of 6.29 µM and 1.40 µM for sodium pyrophosphate and hexametaphosphate, respectively. The contrasting sensitivities for these inorganic phosphates highlight the complex interplay between nanoparticle composition and the phosphates' molecular structure.

The selectivity of this novel colorimetric AuZnFe₂O₄ nanocomposite sensor was evaluated in the presence of interferents such as Cl⁻, Br⁻, I⁻, NO₃⁻, SO₄²⁻, HCO³⁻, F₆⁻, and CH₃COO⁻. As shown in Fig. S6 and S7, the absorbance responses and color changes were monitored in the presence of these common anion interference substances using environmentally collected water samples. In each case, there was no noticeable new absorbance peak appearance or wavelength peak shift compared to organic phosphates. Smaller wavelength shifts, less than 10 nm, and a blueish-grey color transition were observed in the presence of halogens; however, their colors are distinct compared to phosphates. More importantly, no noticeable color changes or alterations in the UV-vis absorption spectra were observed in the presence of NO₃⁻, HCO₃⁻, and CH₃COO⁻. The strong affinity of Fe, Zn ions, and AuNPs for the phosphate groups is responsible for the higher selectivity of the AuZnFe₂O₄ nanocomposite towards phosphates.

The practicability of this proposed sensor for monitoring environmental water samples was evaluated by testing four samples from Lake Okeechobee, EREC Canal, EREC groundwater, and Sea water from Lake Worth (see the SI; “Sample Collection and Processing” and “Sample Locations and Times” for details). First, ethion was spiked into these water samples, and UV-Vis spectroscopy as well as visible color changes were used to evaluate performance, as presented in Fig. 8. There was an emergence of a new peak around 685 nm in each case, with the color changing to grey from the initial wine-red color. Both lake and canal water showed the same trend with ethion alone, which revealed the emergence of a new peak at 685 nm with decreasing intensity and broadening of the initial peak at 520 nm. This result substantiates both higher selectivity and sensitivity of ethion in a complex environment with many different anions, cations, and molecules. In the case of groundwater and seawater, their SPR peak shifted to 701 nm and 691 nm, respectively. The additional peak shift of 6–16 nm may be the result of the higher salinity of groundwater and seawater. All cases reported a greyish color change, closely resembling the color produced by ethion upon exposure to the developed nanocomposite. Together, these observations provide an initial matrix-feasibility assessment and indicate that the sensor retains a measurable response to phosphate additions in the tested environmental water samples. These results serve as preliminary proof-of-concept evidence for matrix testing.

Fig. 8 (a) UV-vis absorbance spectra of environmental water samples and (b) their corresponding color changes upon exposure to water samples.

Nanosensors, particularly plasmonic nanosensors, have made significant advances in environmental sensing applications due to their unique properties, such as high extinction coefficients and the ability to control their properties by controlling their size, shape, surface chemistry and composition. Several studies have shown that NPs such as gold, silver, titanium dioxide, carbon nanotubes and graphene nanosheets have been used for detecting pesticides.^43–49Table 2 shows a comparison between our research and several studies from the literature.

Table 2 A comparison of this work with relevant studies from the literature

Detection method	Probe/Material	Format	Type of phosphate	LOD		Linear range	Notes	Ref
Colorimetric (nanoparticle dye displacement)	TiO2 nanotubes–methyl blue	UV-vis color change	NaH2PO4·2H2O, ATP, and ADP	0.59 µM		1-40 µM	Validated in spiked lake water with a LOD of 0.68 µM	50
Colorimetric nanoenzyme	MoS2/UiO-66(Fe/Zr) MOF	TMB/H2O2	NaH2PO4·7H2O	6.4 µM		10-100 µM	Zr^4+ provides phosphate ion recognition	51
Colorimetric dip strip	Ascorbic acid/antimony dried on paper; molybdate H2SO4 in liquid	Paper microfluidic device	NaH2PO4	Freshwater: 0.134 ppm		—	Superior shelf life and storage conditions	52
				Seawater: 0.438 ppm
				IR lightbox seawater: 0.156 ppm
Colorimetric with magnetic preconcentration (PMB)	Fe3O4@SiO2@C18 capturing PMB-CTAB ion pair	Preconcentration and UV-Vis	KH2PO4	0.3 P L^−1		1.0-30.0 µg P L^−1	Tolerates common anions and validated with CRM	53
Electrochemical (renewable electrode)	Boron-doped diamond (BDD)	Voltammetric	KH2PO4	0.004 mg L^−1		0.02–0.4; 0.4–3 mg L^−1	Dual-analyte; segmented ranges	54
Fluorescent (lanthanide MOF)	Eu/Ce/UiO-66-(COOH)2 nanoprobe (ratiometric)	Fluorescent	Na3PO4	0.247 µM		0.3-20 µM	Aqueous sensing; ratiometric robustness	55
Colorimetric	AuNPs, AgNPs, and Ag–Au NPs	UV-vis color change	Ethion, fenthion, parathion, malathion and paraoxon-ethyl	AuNPs	Ethion: 150 µM	—	—	56
					Fenthion: 190 µM
					Parathion: 420 µM
					Malathion: 1.1*10^−2 µM
					Paraoxon-ethyl: 0 µM
				AgNPs	Ethion: 24 µM
					Fenthion: 41 µM
					Parathion: 54 µM
					Malathion: 150 µM
					Paraoxonyl-ethyl: 0 µM
				Ag–Au NPs	Ethion: 750 µM
					Fenthion: 830 µM
					Parathion: 3600 µM
					Malathion: 6300 µM
					Paraoxonyl-ether: 0 µM
Colorimetric	AuZnFe2O4	UV-vis color change	Ethion, malathion, dimethoate, soybean phospholipid, NaPyroP, and NahexametaP	Ethion: 0.16 µM		Ethion: 700 – 1400 µM	Validated in spiked environmental water	This study
				Malathion: 0.46 µM		Malathion: 1000–1400 µM
				Dimethoate: 0.99 µM		Dimethoate: 1000–6000 µM
				Soybean phospholipid: 0.37 µM		Soybean: 0.5–2.5 µM
				NaPyroP: 6.29 µM		NaPyroP: 35–500 µM
				NahexametaP: 1.40 µM		NahexametaP: 6000–12 500 µM

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Conclusions

In this work, a rapid, facile, highly selective and sensitive colorimetric sensing method based on a plasmonic AuZnFe₂O₄ nanocomposite was developed and coupled with UV-Vis absorbance spectroscopy. The chemical interactions of phosphate compounds with the surface of the nanocomposite depend on their molecular structure and binding affinities, leading to distinct SPR peak shifts and corresponding color changes. Computational simulations provided insights into phosphate adsorption and bonding mechanisms of phosphates on the AuZnFe₂O₄ nanocomposite surface, facilitating clear differentiation between inorganic and organic phosphates in water. Moreover, specific OP compounds could be distinguished among other phosphate-containing organic species. Among the OP compounds studied, ethion exhibited the highest detection sensitivity (0.16 µM), while sodium hexametaphosphate demonstrated the highest sensitivity among inorganic phosphates (1.4 M). Further investigation revealed that the time-dependent colloidal instability of the nanocomposite caused aggregation in the presence of phosphates without changing the size of AuNPs. Moreover, the successful performance of environmental water samples validated the significant selectivity and sensitivity of the fabricated AuZnFe₂O₄ nanocomposite towards phosphates in the presence of other ions and molecules. This establishes the practical applications of the AuZnFe₂O₄ nanocomposite for environmental water sample monitoring for the effective detection of phosphate contaminants.

In conclusion, the AuZnFe₂O₄ nanocomposite-based colorimetric sensor shows promise for highly selective, sensitive and rapid detection of phosphates and produced distinct response profiles across the tested inorganic and organic phosphates. However, formal discrimination of organic versus inorganic phosphorus in complex mixtures was not evaluated in this study and will be the focus of future work. The mechanistic elucidation provided in this work serves as a guideline for further phosphate screening and speciation studies. Interference from halogens and sulphates was evident, producing additional shifts in the UV-vis absorption peaks. Future optimization of the nanocomposite composition and assay conditions should focus on improving both analytical sensitivity and selectivity (including mitigation of halide/sulphate interference), as well as robustness metrics such as matrix tolerance, reproducibility, and stability. Characterizing sensitivity across environmentally relevant ranges for each phosphate species will advance sensor development, as phosphate levels vary with the location of the water samples. Additionally, combining this colorimetric approach with electrochemical detection strategies in future studies may further improve sensor accuracy and minimize the incidence of false positive signals, broadening its overall utility for comprehensive environmental monitoring.

Author contributions

A. A. I. and G. P. contributed equally to this work. The manuscript was written through contributions from all authors. All authors have given approval to the final version of the manuscript.

Conflicts of interest

There are no conflicts to declare.

Abbreviations

NPs	nanoparticles
SPR	surface plasmon resonance
ZnFe2O4	zinc ferrite
OP	organophosphorus
LSPR	localized surface plasmon resonance
TEM	transmission electron microscope
SAED	selected area electron diffraction
XRD	X-ray diffraction
XPS	X-ray photoelectron spectroscopy
ADF-STEM	angular-dark field-scanning transmission electron microscopy
EDX	Energy-dispersive X-ray
DFT	Density functional theory
TDOS	total density of states
LOD	limits of detection
HSAB	hard-soft acid-base

Data availability

Supplementary information (SI): additional experimental details, including further structural and morphological characterization, computational analysis, absorbance measurements, and calculations (PDF). See DOI: https://doi.org/10.1039/d5ta02669e.

Acknowledgements

This work was performed at the Joint School of Nanoscience and Nanoengineering, a member of the Southeastern Nanotechnology Infrastructure Corridor (SENIC) and National Nanotechnology Coordinated Infrastructure (NNCI), supported by the NSF (grant ECCS-1542174). Financial support for this work was provided, in part, by the Joint School of Nanoscience and Nanoengineering, the University of North Carolina at Greensboro Office of Research and Sponsored Programs, and the National Science Foundation Science and Technologies for Phosphorus Sustainability (STEPS) (CBET-2019435). We are grateful for financial support from the NSF award 2114682 INFRAMES project, DEVCOM Soldier Center, the UNC Research Opportunities Initiative (ROI) program, and the NC Collaboratory.

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Footnote

† Abed Alqader Ibrahim and Gayani Pathiraja have contributed equally to this work.

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