Colorimetric sensor array for discriminating and determinating phenolic pollutants basing on different ratio of ligands in Cu/MOFs

Two novel laccase-like nanozymes based on azole ligands for constructing pH-dependent sensor array for recognizing halogenated phenolic pollutants

Halogenated phenolic compounds are widely used in industrial processes such as paper manufacturing and pesticide production. They are priority pollutants that need to be controlled and are discharged with industrial wastewater. Halogenated phenolics have much greater environmental impacts than phenolics due to elevated toxicity and reduced biodegradability caused by halogen substitution. Since the type and location of halogens have great influence on their toxicity and existing differentiation methods rely on large-scale instruments, there is an urgent need to develop new and convenient sensing technologies for the simultaneous identification and detection of halogenated phenols (including fluorophenols, chlorophenols and bromophenols) for more targeted pollution control. In this work, we prepared two novel laccase-like nanozymes using asymmetric azole ligands (thiazole-2-carboxylic acid and imidazole-2-carboxylic acid) coordinated with Cu2+, and constructed a four-channel sensor array by taking advantage of the difference in their ability to catalyze the color development of halogenated phenols and 4-aminoantipyrine under pH = 7 and pH = 8 conditions. The sensor array was able to accurately discriminate eight halogenated phenols in the range of 5-100 μM, and allowing for accurate quantitative analysis. The method has good anti-interference ability to other non-target phenols, and can realize accurate differentiation of halogenated phenols in real water bodies. Even in the presence of high concentrations of common ions or heavy metal ions, halogenated phenolic pollutants can be accurately identified. The good stability and anti-interference ability make the senor array has a great potential for application and is expected to provide a basis for environmental pollution control.

Recent Progress on the Rational Design of Laccase Mimics

Laccase, a type of copper-containing natural oxidase, is known as a green catalyst because only water was produced as the reduction product. It has shown great potential for applications in wastewater treatment, dye degradation, food and pharmaceutical industries, biosensors, and other fields. Despite the above advantages of natural laccase, challenges arise from its inherent instability, recovery difficulties, and the associated high costs exist. To address such issues, a plethora of nanomaterials that possess laccase-mimicking activity, ranging from monometallic ions-containing nanomaterials to multimetal-based composites, was discovered in the past decade. In general, these materials demonstrate considerable performance variability. A comprehensive understanding of the design principles to achieve high laccase-like activity, particularly those on the Cu2+-involved structures and the related electron transfer, is thus demanded. Therefore, in this review, the structure-activity relationship of native laccase was first summarized, followed by the categorization of the recent design strategies of laccase-like nanozymes. After distilling the insights from the currently reported laccase-mimicking nanomaterials, a further prospect on the rational design of laccase mimics with high efficiency in the future was also proposed.

Metal covalent organic frameworks-based laccase-like nanozyme for oxidative degradation and identification of phenolic pollutants

Phenolic compounds are a kind of persistent organic pollutants (POPs), which are always a threat to human and environment due to their strong toxicity and low biodegradability. Therefore, developing a reliable method to simultaneously detect phenolic pollutants is of great importance to environmental safety and human health. Herein, we combined the advantages of metal organic frameworks (MOFs) and covalent organic frameworks (COFs) to prepare two cyclic trinuclear unit-based metal covalent organic framework (MCOFs, denoted as Cu3-TDH COF and Cu3-BDU COF) with large specific surface area, good stability and excellent laccase-like activity. Their oxidative degradation ability toward phenolic pollutants was verified, and a dual-channel nanozyme sensor array based on Cu3-TDH COF and Cu3-BDU COF was constructed for the identification of six phenolic pollutants. Notably, the sensor array can accurately distinguish between different concentrations of phenolic pollutants and different types of phenolic pollutants at the same concentration, even at levels as low as 1 μM. Moreover, three real water samples (rainwater, tap water and wastewater) and 18 unknown samples were also distinguished and differentiated by the sensor array. This study opens up a potential avenue for the design of MCOFs-based nanozyme sensor arrays to simultaneously realize identification and detection of multiple phenolic pollutants.

Construction of a CuO2@PDA Nanozyme with Switchable Dual Enzyme-Mimic Activities for Colorimetric Sensing of Catechol and Hydroquinone

The development of metal-based redox nanozymes represents a new frontier in pollutant sensing. In this field, designing highly active nanozymes and precisely regulating their enzymatic activity are key challenges. In this work, we report the construction of a copper peroxide@polydopamine (CuO2@PDA) nanozyme with dual enzyme-like activity, mimicking the active centers of laccase and peroxidase. Here, CuO2 acts as the catalytic center, while PDA serves as a carrier to prevent CuO2 aggregation and promotes conversion of CuII/CuI active sites via the reduction effect of its surface catechol groups to complete the catalytic cycle. As expected, the obtained CuO2@PDA nanozyme exhibits significant laccase- and peroxidase-mimetic activities. Moreover, its dual enzymatic activity can be systematically switched by adjusting pH and temperature. Specifically, laccase activity dominates near neutral pH, while CuO2 decomposition into Cu ions and H2O2 at acidic pH triggers peroxidase activity. Similarly, CuO2@PDA exhibits temperature-dependent dual enzymatic activity with peroxidase activity prevailing at low temperatures and laccase activity at high temperatures. According to enzymatic performance and XPS results, a possible catalytic mechanism of the dual enzymatic activity of CuO2@PDA has been proposed. Then, based on the pH-dependent dual enzymatic activity of CuO2@PDA, we constructed a detection system for the isomers of organic pollutants, catechol (CC) and hydroquinone (HQ). The laccase-like activity of CuO2@PDA enables direct oxidation of CC into yellow o-benzoquinone, while HQ discolors the preoxidized substrate generated via the peroxidase-like activity of CuO2@PDA. Moreover, selective sensing for CC and HQ with high sensitivity was achieved in real water samples. This approach can guide the design of nanozymes with multienzymatic activity and unveil their potential uses in environmental pollutant discrimination.

Sensing array based on imidazole-regulated Cu@MOFs nanozymes with enhanced laccase-like activity for the discrimination of phenolic pollutants

BACKGROUND

Phenolic pollutants with high toxicity and low biodegradability can disrupt environmental balance and severely affect human health, whereas existing methods are difficult to implement the rapid and high-throughput detection of multiple phenolic pollutants.

RESULTS

Herein, we developed a four-dimensional colorimetric sensor array based on imidazole-modulated Cu@MOFs for distinguishing and determining phenolic pollutants. Wherein, four Cu@MOFs (ATP@Cu, ADP@Cu, AMP@Cu, and GMP@Cu) nanozyme with laccase-like activity were firstly prepared, and a novel strategy of imidazole-containing molecules-regulated was proposed to improve the laccase-like activity of Cu@MOFs nanozymes. Interestingly, imidazole (IM) exhibited the strongest enhancing effects on the laccase-like activity of the four Cu@MOFs by accelerating electron transfer on the surface of laccase nanozymes and producing more reactive oxygen species. Subsequently, by using Cu@MOFs@IM as the recognition elements of the sensor array, a colorimetric sensor array based on imidazole-modulated Cu@MOFs was developed, and differentiation and classification of phenolic pollutants were carried out using LDA and HCA methods. More importantly, the proposed sensor array could accomplish the identification of 6 phenolic pollutants and their mixtures.

SIGNIFICANCE

Additionally, the designed sensor array was applied to identify these phenolic pollutants in real water samples, further highlighting the potentials for assessing water pollution.

Metal-Organic Framework-Based Nanostructures for Electrochemical Sensing of Sweat Biomarkers

Sweat is considered the most promising candidate to replace conventional blood samples for noninvasive sensing. There are many tools and optical and electrochemical methods that can be used for detecting sweat biomarkers. Electrochemical methods are known for their simplicity and cost-effectiveness. However, they need to be optimized in terms of selectivity and catalytic activity. Therefore, electrode modifiers such as nanostructures and metal-organic frameworks (MOFs) or combinations of them were examined for boosting the performance of the electrochemical sensors. The MOF structures can be prepared by hydrothermal/solvothermal, sonochemical, microwave synthesis, mechanochemical, and electrochemical methods. Additionally, MOF nanostructures can be prepared by controlling the synthesis conditions or mixing bulk MOFs with nanoparticles (NPs). In this review, we spotlight the previously examined MOF-based nanostructures as well as promising ones for the electrochemical determination of sweat biomarkers. The presence of NPs strongly improves the electrical conductivity of MOF structures, which are known for their poor conductivity. Specifically, Cu-MOF and Co-MOF nanostructures were used for detecting sweat biomarkers with the lowest detection limits. Different electrochemical methods, such as amperometric, voltammetric, and photoelectrochemical, were used for monitoring the signal of sweat biomarkers. Overall, these materials are brilliant electrode modifiers for the determination of sweat biomarkers.

Machine Learning-Based Nanozyme Sensor Array as an Electronic Tongue for the Discrimination of Endogenous Phenolic Compounds in Food

The detection of endogenous phenolic compounds (EPs) in food is of great significance in elucidating their bioactivity and health effects. Here, a novel bifunctional vanillic acid-Cu (VA-Cu) nanozyme with peroxidase-like and laccase-like activities was successfully prepared. The peroxidase mimic behavior of VA-Cu nanozyme can catalyze 3,3',5,5'-tetramethylbenzidine (TMB) to generate oxidized TMB (oxTMB). Owing to the high reducing power of EPs, this process can be inhibited, and the degree of inhibition increases with the increase of reaction time. Additionally, owing to the outstanding laccase mimic behavior of the VA-Cu, it can facilitate the oxidation of various EPs, resulting in the formation of colored quinone imines, and the degree of catalysis increases with the increase of reaction time. Based on the interesting experimental phenomena mentioned above, a six-channel nanozyme sensor array (2 enzyme-mimic activities × 3 time points = 6 sensing channels) was constructed, successfully achieving discriminant analysis of nine EPs. In addition, the combination of artificial neural network (ANN) algorithms and sensor arrays has successfully achieved accurate identification and prediction of nine EPs in black tea, honey, and grape juice. Finally, a portable method for identifying EPs in food has been proposed by combining it with a smartphone.

Nanozyme-Based Microfluidic Chip System for pH-Regulated Pretreatment and Sensitive Sensing

Nanozymes, possessing nanomaterial properties and catalytic activities, offer great opportunities to design sensitive analytical detection systems. However, the low interference resistance of nanozymes poses a significant limitation on the precise detection of target substances. Herein, a nanozyme-based microfluidic chip system for pH-regulated pretreatment and sensitive sensing of cysteine (Cys) is reported. The copper metal-organic framework (Cu MOF) exhibits good cysteine oxidase-like activity at pH 7.0, while demonstrating excellent laccase-like activity at pH 8.0. Taking advantage of the pH-regulated enzyme-like activity, the integrated microfluidic device involving the immobilization of Cu MOF eliminates the interference of dopamine (DA) and accurately detects the target Cys. Compared with the untreated reaction system, the developed nanozyme system shows a significantly improved accuracy in detecting Cys, with an R2 value of 0.9914. This work provides an efficient method to enhance the interference resistance of nanozymes and broadens the application in sample pretreatment.

Amino-Functionalized NDI-Based MOFs as Unusual "Turn On" and "Turn Off" Fluorescent Sensors for Phenolic Pollutants with Double Solvent Channel Response and Iodine Adsorbents

Regulating mixed ligands to change the functional properties of metal-organic frameworks (MOFs) has been an important topic; especially, the structural changes have significant implications for the transformation of sensing response in different solvent channels. Herein, two [Cd (DPNDI) (NH2-BDC)0.5(NO3)]·2.25DMF (1) and [Cd(DPNDI)(NH2-AIPA)]·0.5DMF (2) (DPNDI = N,N-di(4-pyridyl)-1,4,5,8-naphthalenetetracarboxydiimide, NH2-BDC = 2-amino terephthalic acid, NH2-AIPA = 5-aminoisophthalic acid) were synthesized by the solvothermal method. Structural analysis shows that complex 1 has a two-dimensional planar network structure and complex 2 exhibits a three-dimensional network structure, endowing its potential as an efficient fluorescence sensor for phenolic compound detection under different solvent environments. Both complexes showed high fluorescence quenching sensitivity to phenolics in a water medium. Conversely, complex 1 showed a fluorescence enhancement response to phenolic pollutants in an ethanol system with significantly low detection limits and recyclability. The detection limits were 0.58 μM for TNP, 1.3 μM for DNP, and 2.43 μM for PCP. In addition, the uncoordinated amino groups in the complexes promote them to exhibit excellent iodine adsorption performance. Especially, complex 2 can serve as an adsorbent for iodine in cyclohexane solution with better adsorption efficiency than that of complex 1, and its adsorption capacity can reach 505 mg/g. The mixed ligands regulation strategy of NDI-based MOFs will open up an effective avenue for the conversion of fluorescence signals in dual-solvent channels and play simultaneously important roles in multiple applications.

Algae-derived biochar nanozyme array for discrimination and detection of multiple pesticides in soil, water and food

Despite the potential of nanozymes combined with sensor arrays for discriminating multiple pesticides simultaneously, they have few practical pesticide sensing uses due to the limited performance of existing nanozymes and the complexity of their preparation. Here, agricultural waste is utilized for the facile synthesis of high-performance biochar nanozymes and the fabrication of biochar nanozyme sensor arrays. The production of autogenous N-doped biochars with abundant surface functional groups and good peroxidase-like activities is achieved with different types of algae. High-performance biochar nanozyme sensor arrays can discriminate pesticides in a concentration range from 1 to 500 μM and in real samples from soil, lake water, seawater, apples, cucumbers, peaches, tomatoes and cabbages. Furthermore, pesticides can be quantified down to 1 μM. The development of high-performance nanozyme sensor arrays based on waste conversion could be a step toward pesticide discrimination and detection, which would improve human and environmental safety.

Fluorescent multichannel sensor array based on three carbon dots derived from Tibetan medicine waste for the quantification and discrimination of multiple heavy metal ions in water

A fluorescent multichannel sensor array has been established based on three carbon dots derived from Tibetan medicine waste for rapid quantification and discrimination of six heavy metal ions. Due to the chelation between metal ions and carbon dots (CDs), this fluorescence "turn off" mode sensing array can quantify six metal ions as low as "μM" level. Moreover, the six heavy metal ions display varying quenching effects on these three CDs owing to diverse chelating abilities between each other, producing differential fluorescent signals for three sensing channels, which can be plotted as specific fingerprints and converted into intuitive identification profiles via principal component analysis (PCA) and hierarchical cluster analysis (HCA) technologies to accurately distinguish Cu2+, Fe3+, Mn2+, Ag+, Ce4+, and Ni2+ with the minimum differentiated concentration of 5 μM. Valuably, this sensing array unveils good sensitivity, exceptional selectivity, ideal stability, and excellent anti-interference ability for both mixed standards and actual samples. Our contribution provides a novel approach for simultaneous determination of multiple heavy metal ions in environmental samples, and it will inspire the development of other advanced optical sensing array for simultaneous quantification and discrimination of multiple targets.

A colorimetric and SERS dual-mode aptasensor for the detection of Shiga toxin type II based on Mn/Fe-MIL(53)@AuNSs

Shiga toxin type II (Stx2), the major virulence component of enterohemorrhagic Escherichia coli, is strongly associated with the life-threatening hemolytic uremic syndrome thus posing a substantial risk to food safety and human health. In this work, a dual-mode aptasensor with colorimetric and surface-enhanced Raman scattering was developed for Stx2 specific detection based on noble metal nanoparticles and Raman reporter loaded metal-organic framework (Mn/Fe-MIL(53)@AuNSs-MBA). The Mn/Fe-MIL(53)@AuNSs could catalyze the H2O2-mediated oxidation of 3,3',5,5'-tetramethylbenzidine (TMB), thereby enabling visual detection. Meanwhile, the SERS signal from MBA can be enhanced by the decorated AuNSs. Under optimal conditions, a linear range of 0.05-500 ng/mL with limit of detection (LOD) of 26 pg/mL was achieved in colorimetric mode and a linear range of 5-1000 ng/mL with LOD of 0.82 ng/mL in SERS mode, in which the dual-mode results complement each other, widening the linear range, increasing the accuracy and reliability of the detection. The method was further applied to the detection of Stx2 in milk with average recovery of 101.1 %, demonstrating its superior potential for bacterial toxin monitoring.