Efficient and Accurate pH Determination with pH Test Strips Based on Machine Learning.

The determination of pH values is crucial in various fields, such as analytical chemistry, medical diagnostics, and biochemical research. pH test strips, renowned for their convenience and cost-effectiveness, are commonly utilized for pH qualitative estimation. Recently, quantitative methods for determining pH values using pH test strips have been developed. However, these methods can be prone to errors due to environmental factors, such as lighting conditions, which affect the imaging quality of the pH test strips. To address these challenges, we developed an innovative approach that combines machine learning techniques with pH test strips for the quantitative determination of pH values. Our method involves extracting artificial features from the pH test strip images and combining them across multiple dimensions for comprehensive analysis. To ensure optimal feature selection, we developed a feature selection strategy based on SHAP importance. This strategy helps in identifying the most relevant features that contribute to accurate pH prediction. Furthermore, we integrated multiple machine learning algorithms, employing a robust stacking fusion strategy to establish a highly reliable pH value prediction model. Our proposed method automates the determination of pH values through pH test strips, effectively overcoming the limitations associated with environmental lighting interference. Experimental results demonstrate that this method is convenient, effective, and highly reliable for the determination of pH values.

DNA Nanospheres Assisted Spatial Confinement Signal Amplification for MicroRNA Imaging in Live Cancer Cells.

DNA assemblies are commonly used in biosensing, particularly for the detection and imaging of microRNAs (miRNAs), which are biomarkers associated with tumor progression. However, the difficulty lies in the exploration of high-sensitivity analytical techniques for miRNA due to its limited presence in living cells. In this study, we introduced a DNA nanosphere (DS) enhanced catalytic hairpin assembly (CHA) system for the detection and imaging of intracellular miR-21. The single-stranded DNA with four palindromic portions and extending sequences at the terminal was annealed for assembling DS, which avoided the complex sequence design and high cost of long DNA strands. Benefiting from the multiple modification sites of DS, functional hairpins H1 (modified with Cy3 and BHQ2) and H2 were grafted onto the surface of DS for assembling DS-H1-H2 using a hybridization reaction. The DS-H1-H2 system utilized spatial confinement and the CHA reaction to amplify fluorescence signals of Cy3. This enabled highly sensitive and rapid detection of miR-21 in the range from 0.05 to 3.5 nM. The system achieved a limit of determination (LOD) of 2.0 pM, which was 56 times lower than that of the control CHA circuit with freedom hairpins. Additionally, the sensitivity was improved by 8 times. Moreover, DS-H1-H2 also showed an excellent imaging capability for endogenous miR-21 in tumor cells. This was due to enhanced cell internalization efficiency, accelerated reaction kinetics, and improved biostability. The imaging strategy was shown to effectively monitor the dynamic content of miR-21 in live cancer cells and differentiate various cells. In general, the simple nanostructure DS not only enhanced the detection and imaging capability of the conventional probe but also could be easily integrated with the reported DNA-free probe, indicating a wide range of potential applications.

Chiral Assembly of Perovskite Nanocrystals: Sensitive Discrimination of Amino Acid Enantiomers.

Chirality is a widespread phenomenon in nature and in living organisms and plays an important role in living systems. The sensitive discrimination of chiral molecular enantiomers remains a challenge in the fields of chemistry and biology. Establishing a simple, fast, and efficient strategy to discriminate the spatial configuration of chiral molecular enantiomers is of great significance. Chiral perovskite nanocrystals (PNCs) have attracted much attention because of their excellent optical activity. However, it is a challenge to prepare perovskites with both chiral and fluorescence properties for chiral sensing. In this work, we synthesized two chiral fluorescent perovskite nanocrystal assembly (PNA) enantiomers by using l- or d-phenylalanine (Phe) as chiral ligands. PNA exhibited good fluorescence recognition for l- and d-proline (Pro). Homochiral interaction led to fluorescence enhancement, while heterochiral interaction led to fluorescence quenching, and there is a good linear relationship between the fluorescence changing rate and l- or d-Pro concentration. Mechanism studies show that homochiral interaction-induced fluorescence enhancement is attributed to the disassembly of chiral PNA, while no disassembly of chiral PNA was found in heterochiral interaction-induced fluorescence quenching, which is attributed to the substitution of Phe on the surface of chiral PNA by heterochiral Pro. This work suggests that chiral perovskite can be used for chiral fluorescence sensing; it will inspire the development of chiral nanomaterials and chiral optical sensors.

Ultra-Fast Degradation of Mustard Gas Simulant by Titanium Dioxide-Phosphomolybdic Acid Sub-1 nm Nanobelts.

The development of novel catalysts for the rapid detoxification of sulfur mustard holds paramount importance in the field of military defense. In this work, titanium dioxide-phosphomolybdic acid sub-1 nm nanobelts (TiO2/PMA SNBs) are employed as effective catalysts for the ultra-fast degradation of mustard gas simulants (2-chloroethyl ethyl sulfide, CEES) with 100% selectivity and a half-life (t1/2, time required for 50% conversion) as short as 12 s, which is the fastest time to the best of the knowledge. Even in dark conditions, this material can still achieve over 90% conversion within 5 min. A mechanism study reveals that the rapid generation rate of 1O2 and O2 •- in the presence of TiO2/PMA SNBs and H2O2 plays a crucial role in facilitating the efficient oxidation of CEES. A filter layer of a gas mask loaded with TiO2/PMA SNBs and H2O2/polyvinylpyrrolidone cross-linked complex (PHP) is constructed, which demonstrates remarkable stability and exhibits exceptional efficacy in the detoxification of CEES in the presence of a small amount of water. This innovation offers great potential for enhancing personal protective equipment in practical applications.

Synergistic Mitochondrial Genotoxicity of Carbon Dots and Arsenate in Earthworms Eisenia fetida across Generations: The Critical Role of Binding.

The escalating utilization of carbon dots (CDs) in agriculture raises ecological concerns. However, their combined toxicity with arsenic remains poorly understood. Herein, we investigated the combined mitochondrial genotoxicity of CDs and arsenate at environmentally relevant concentrations across successive earthworm generations. Iron-doped CDs (CDs-Fe) strongly bound to arsenate and arsenite, while nitrogen-doped CDs (CDs-N) exhibited weaker binding. Both CDs enhanced arsenate bioaccumulation without affecting its biotransformation, with most arsenate being reduced to arsenite. CDs-Fe generated significantly more reactive oxygen species than did CDs-N, causing stronger mitochondrial DNA (mtDNA) damage. Arsenate further exacerbated the oxidative mtDNA damage induced by CDs-N, as evidenced by increased reactive oxygen species, elevated 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-OHdG) levels, and a higher correlation between 8-OHdG and mtDNA damage. This was due to arsenic inhibiting the antioxidant enzyme catalase. This exacerbation was negligible with CDs-Fe because their strong binding with arsenic prevented catalase inhibition. Maternal mitochondrial DNA damage was inherited by filial earthworms, which experienced significant weight loss in coexposure groups coupled with mtDNA toxicity. This study reveals the synergistic genotoxicity of CDs and arsenate, suggesting that CDs could disrupt the arsenic biogeochemical cycle, increase arsenate risk to terrestrial animals, and influence ecosystem stability and health through multigenerational impacts.

AMP Aptamer Programs DNA Tile Cohesion without Canonical Base Pairing.

Tile-based DNA self-assembly provides a versatile approach for the construction of a wide range of nanostructures for various applications such as nanomedicine and advanced materials. The inter-tile interactions are primarily programmed by base pairing, particularly Watson-Crick base pairing. To further expand the tool box for DNA nanotechnology, herein, we have designed DNA tiles that contain both ligands and aptamers. Upon ligand-aptamer binding, tiles associate into geometrically well-defined nanostructures. This strategy has been demonstrated by the assembly of a series of DNA nanostructures, which have been thoroughly characterized by gel electrophoresis and atomic force microscopy. This new inter-tile cohesion could bring new potentials to DNA self-assembly in the future. For example, the addition of free ligand could modulate the nanostructure formation. In the case of biological ligands, DNA self-assembly could be related to the presence of certain ligands.

High Confidence Single Particle Analysis with Machine Learning.

Single particle analysis can effectively determine the heterogeneity between particles based on the local information on a single particle, which is utilized extensively for monitoring chemical reactions and biological activities. However, the study of obtaining ensemble reaction information at the single particle level, which can obtain both the structural and functional heterogeneity of particles as well as the ensemble reaction information, is challenging because the selection of a single particle mainly depends on experience, which will lead to a certain randomness when analyzing the ensemble reaction with single particles. Using machine learning, it is demonstrated that the proposed intelligent single particle analysis strategy can provide single particle and ensemble analyses with high confidence. Convolutional neural network and Gaussian mixture model were utilized to develop a machine learning model for resonance scattering imaging analysis of plasmonic nanoparticles. It can identify the scattered light of single particles and select representative or diverse particles. When single particle scattering imaging is used to obtain ensemble information on the reaction, the error caused by the selection of individual particles can be significantly reduced by selecting representative particles. In addition, the real situation of the reaction can be better revealed by selecting diverse particles. These results indicate that the intelligent single particle analysis strategy has great potential for imaging analysis and biological sensing.

A General Signal Amplifier of Self-Assembled DNA Micelles for Sensitive Quantification of Biomarkers.

Owing to the excellent structural rigidity and programmable reaction sites, DNA nanostructures are more and more widely used, but they are limited by high cost, strict sequence requirements, and time-consuming preparation. Herein, a general signal amplifier based on a micelle-supported entropy-driven circuit (MEDC) was designed and prepared for sensitive quantification of biomarkers. By modifying a hydrophobic cholesterol molecule onto a hydrophilic DNA strand, the amphiphilic DNA strand was first prepared and then self-assembled into DNA micelles (DMs) driven by hydrophobic effects. The as-developed DM showed unique advantages of sequence-independence, easy preparation, and low cost. Subsequently, amplifier units DMF and DMTD were successfully fabricated by connecting fuel strands and three-strand duplexes (TDs) to DMs, respectively. Finally, the MEDC was triggered by microRNA-155 (miR-155), which herein acted as a model analyte, resulting in dynamic self-assembly of poly-DNA micelles (PDMs) and causing the recovery of cyanine 3 (Cy3) fluorescence as the DMTD dissociated. Benefiting from the "diffusion effect", the MEDC herein had a nearly 2.9-fold increase in sensitivity and a nearly 97-fold reduction in detection limit compared to conventional EDC. This amplifier exhibited excellent sensitivity of microRNAs, such as miR-155 detection in a dynamic range from 0.05 to 4 nM with a detection limit of 3.1 pM, and demonstrated outstanding selectivity with the distinguishing ability of a single-base mismatched sequence of microRNAs. Overall, the proposed strategy demonstrated that this sequence-independent DNA nanostructure improved the performance of traditional DNA probes and provided a versatile method for the development of DNA nanotechnology in biosensing.

Rational Design of Cascade DNA System for Signal Amplification.

System leakage critically confines the development of cascade DNA systems that need to be implemented in a strict order-by-order manner. In principle, ternary DNA reactants, composed of three single-strand DNA (ssDNA) with a strict equimolar ratio (1:1:1), have been indispensable for successfully cascading upstream entropy-driven DNA circuit (EDC) with downstream circuits, and system leakage will occur with any unbalance of the molar ratio. In this work, we proposed "splitting-reconstruction" and "protection-release" strategies on the potential downstream circuit initiator derived from upstream EDC to guide the construction of EDC-involved cascade systems independent of system leakage derived from unpurified reactants. Both the reconstructed and released downstream circuit initiators were in compliance with the principle of the cascade AND logic gate. Using these two strategies, two cascade systems─EDC2-4WJ-TMSDR and EDC3-HCR─were developed to carry out the designed order, which did not require that the ratio of 1:1:1 be maintained. Furthermore, the inherent property of the upstream EDC could transfer into the downstream circuit, endowing the developed cascade systems with a more powerful signal amplification ability for the sensitive detection of the corresponding initiator strand. These two strategies may provide new insights into the process of constructing EDC-like circuit-involved high-order DNA networks.

The Accurate Imaging of Collective Gold Nanorods with a Polarization-Dependent Dark-Field Light Scattering Microscope.

Anisotropic nanomaterials, such as gold nanorods (AuNRs), could be employed as an orientation platform due to their polarization-dependent surface plasmon resonance. However, a variety of factors would affect the dark-field light scattering imaging of anisotropic nanomaterials, resulting in an unstable signal, which is not advantageous to its further application. In this work, the localized surface plasmon resonance properties of a few AuNRs at different angles were excited by polarization with a conventional dark-field microscope, in which it was found that the ratio of AuNRs' light scattering intensity at different polarization angles (I) to that without a polarizer (I0) reflected the orientation information of AuNRs. Furthermore, the light scattering signal ratio between the parallel polarization (Ip) and that without a polarizer (I0) was closely related with the aspect ratio of AuNRs, which could not be affected by external conditions. To verify this concept, a highly sensitive and selective assay of the alkaline phosphatase activity in human serum was successfully developed based on the chemical etching of AuNRs, resulting in a lower aspect ratio and a lesser Ip/I0. This result holds great promise for polarization-dependent colorimetric nanomaterials and single-particle tracers in living cells.

Rational Design of Abasic Site-Containing DNA Triplexes To Bind Small Molecules with Low Nanomolar Dissociation Constants.

De novo design of functional biomacromolecules is of great interest to a wide range of fundamental science and technological applications, including understanding life evolution and biomacromolecular structures, developing novel catalysts, inventing medicines, and exploring high-performance materials. However, it is an extremely challenging task and its success is very limited. It requires a deep understanding of the relationships among the primary sequences, the 3D structures, and the functions of biomacromolecules. Herein, we report a rational, de novo design of a DNA aptamer that can bind melamine with high specificity and high affinity (dissociation constant Kd = 4.4 nM). The aptamer is essentially a DNA triplex, but contains an abasic site, to which the melamine binds. The aptamer-ligand recognition involves hydrogen-bonding, π-π stacking, and electrostatic interactions. This strategy has been further tested by designing aptamers to bind to guanosine. It is conceivable that such a rational strategy, with further development, would provide a general framework for designing functional DNA molecules.

CRISPR-Cas12a Coupled with DNA Nanosheet-Amplified Fluorescence Anisotropy for Sensitive Detection of Biomolecules.

DNA nanosheets (DNSs) have been utilized effectively as a fluorescence anisotropy (FA) amplifier for biosensing. But, their sensitivity needs to be further improved. Herein, CRISPR-Cas12a with strong trans-cleavage activity was utilized to enhance the FA amplification ability of DNSs for the sensitive detection of miRNA-155 (miR-155) as a proof-of-principle target. In this method, the hybrid of the recognition probe of miR-155 (T1) and a blocker sequence (T2) was immobilized on the surface of magnetic beads (MBs). In the presence of miR-155, T2 was released by a strand displacement reaction, which activated the trans-cleavage activity of CRISPR-Cas12a. The single-stranded DNA (ssDNA) probe modified with a carboxytetramethylrhodamine (TAMRA) fluorophore was cleaved in large quantities and could not bind to the handle chain on DNSs, inducing a low FA value. In contrast, in the absence of miR-155, T2 could not be released and the trans-cleavage activity of CRISPR-Cas12a could not be activated. The TAMRA-modified ssDNA probe remained intact and was complementary to the handle chain on the DNSs, and a high FA value was obtained. Thus, miR-155 was detected through the obviously decreased FA value with a low limit of detection (LOD) of 40 pM. Impressively, the sensitivity of this method was greatly improved about 322 times by CRISPR-Cas12a, confirming the amazing signal amplification ability of CRISPR-Cas12a. At the same time, the SARS-CoV-2 nucleocapsid protein was detected by the strategy successfully, indicating that this method was general. Moreover, this method has been applied in the analysis of miR-155 in human serum and the lysates of cells, which provides a new avenue for the sensitive determination of biomarkers in biochemical research and disease diagnosis.

Simultaneous Response of Mitochondrial MicroRNAs to Identify Cell Apoptosis with Multiple Responsive Intelligent DNA Biocomputing Nanodevices.

Challenges remained in precisely real-time monitoring of apoptotic molecular events at the subcellular level. Herein, we developed a new type of intelligent DNA biocomputing nanodevices (iDBNs) that responded to mitochondrial microRNA-21 (miR-21) and microRNA-10b (miR-10b) simultaneously which were produced during cell apoptosis. By hybridizing two hairpins (H1 and H2) onto DNA nanospheres (DNSs) that had been previously modified with mitochondria-targeted triphenylphosphine (TPP) motifs, iDBNs were assembled in which two localized catalytic hairpins self-assembly (CHA) reactions occurred upon the co-stimulation of mitochondrial miR-21 and miR-10b to perform AND logic operations, outputting fluorescence resonance energy transfer (FRET) signals for sensitive intracellular imaging during cell apoptosis. Owing to the spatial confinement effects of DNSs, it was discovered that iDBNs had a high efficiency and speed of logic operations by high local concentrations of H1 and H2, making the simultaneous real-time responses of mitochondrial miR-21 and miR-10b reliable and sensitive during cell apoptosis. These results demonstrated that iDBNs were simultaneously responsive to multiple biomarkers, which greatly improved the detection accuracy to identify the cell apoptosis, demonstrating that iDBNs are highly effective and reliable for the diagnosis of major disease and screening of anticancer drugs.

Two-Dimensional Analysis Method for Highly Sensitive Detection of Dual MicroRNAs in Breast Cancer Cells.

Multiple biomarker detection is crucial for early clinical diagnosis, and it is significant to achieve the simultaneous detection of multiple biomarkers with the same nanomaterial. In this work, the hairpin DNA strands were selectively modified on the surface of gold nanorods (AuNRs) to construct two kinds of nanoprobes by rational design. When in the presence of dual microRNAs, AuNRs were assembled to form end-to-end (ETE) and side-by-side (SBS) dimers. Compared with a single AuNR, the dark-field scattering intensity and red color percentage variation of dimers were extremely distinguished, which could be developed for dual microRNA detection by combining the red color percentage and scattering intensity with the data processing method of principal component analysis to construct a two-dimensional analysis method. Especially, the fraction of AuNR dimers presented a linear relationship with the amount of microRNAs. Based on this, microRNA-21 and microRNA Let-7a in breast cancer cells were detected with the detection limits of 1.72 and 0.53 fM, respectively. This method not only achieved the sensitive detection of dual microRNAs in human serum but also realized the high-resolution intracellular imaging, which developed a new way for the oriented assembly of nanomaterials and biological detection in living cells.

Structure-Guided Designing Pre-Organization in Bivalent Aptamers.

Multivalent interaction is often used in molecular design and leads to engineered multivalent ligands with increased binding avidities toward target molecules. The resulting binding avidity relies critically on the rigid scaffold that joins multiple ligands as the scaffold controls the relative spatial positions and orientations toward target molecules. Currently, no general design rules exist to construct a simple and rigid DNA scaffold for properly joining multiple ligands. Herein, we report a crystal structure-guided strategy for the rational design of a rigid bivalent aptamer with precise control over spatial separation and orientation. Such a pre-organization allows the two aptamer moieties simultaneously to bind to the target protein at their native conformations. The bivalent aptamer binding has been extensively characterized, and an enhanced binding has been clearly observed. This strategy, we believe, could potentially be generally applicable to design multivalent aptamers.

Dark-Field Imaging Monitoring of Adenosine Triphosphate in Live Cells by Au NBPs@ZIF-8 Nanoprobes.

Monitoring the fluctuation of adenosine triphosphate (ATP) level in living cells could promote the understanding of metabolic pathways and cell biology. Here, we proposed a highly sensitive, selective, and biocompatible nanoprobe with core-shell structure, namely Au NBPs@ZIF-8 composed by gold nanobipyramids (Au NBPs) and zeolitic imidazolate framework-8 (ZIF-8), for monitoring intracellular ATP level fluctuation in living cells. Because the coordination between ATP and Zn2+ (the metal node of ZIF-8) was much stronger than that between 2-methylimidazole and Zn2+, which caused the decomposition of the ZIF-8 shell and the exposure of Au NBPs in the presence of ATP, it led to the change of the localized surface plasmon resonance scattering properties of nanoprobes under dark-field microscopy. Tricolor (RGB) analysis showed that R/G value had a good linear relationship with the ATP concentrations in the range of 10 µM to 4 mM (R2 = 0.999) with a detection limit of 5.28 µM. This ATP sensing platform also exhibited excellent selectivity in complex intracellular interfering substances. Besides, we realized intracellular ATP real-time imaging in HeLa cells and observed the ATP level fluctuation under dark-field microscopy. The method mentioned here could be further applied for delivery of therapeutics for biomedical applications.

High Resolution of Plasmonic Resonance Scattering Imaging with Deep Learning.

The dark-field microscopy (DFM) imaging technology has the advantage of a high signal-to-noise ratio, and it is often used for real-time monitoring of plasmonic resonance scattering and biological imaging at the single-nanoparticle level. Due to the limitation of the optical diffraction limit, it is still a challenging task to accurately distinguish two or more nanoparticles whose distance is less than the diffraction limit. Here, we propose a computational strategy based on a deep learning framework (NanoNet), which will realize the effective segmentation of the scattered light spots in diffraction-limited DFM images and obtain high-resolution plasmonic light scattering imaging. A small data set of DFM and the corresponding scanning electron microscopy (SEM) image pairs are used to learn for obtaining a highly resolved semantic imaging model using NanoNet, and thus highly resolved DFM images matching the resolution of those acquired using SEM can be obtained. Our method has the ability to transform diffraction-limited DFM images to highly resolved ones without adding a complex optical system. As a proof of concept, a highly resolved DFM image of living cells through the NanoNet technique is successfully made, opening up a new avenue for high-resolution optical nanoscopic imaging.

Plasmonic Hot-Electron-Painted Au@Pt Nanoparticles as Efficient Electrocatalysts for Detection of H2O2.

Plasmon-driven catalysis of metal nanostructures has garnered wide interest. Here, a photogenerated plasmonic hot-electron painting strategy was reported to form Au@Pt composite nanoparticles (Au@Pt NPs) with high catalytic reactivity without using reducing agents. Au nanoparticles, including Au nanospheres (Au NSs), Au nanorods (Au NRs), and Au nanobipyramids (Au NBPs), generated hot electrons under localized surface plasmon resonance (LSPR) excitation, which made the platinum precursor reduced as a consequence that Pt(0) atoms were painted on the surface of Au NPs to form an asymmetric Pt shell outside the plasmonic Au core. Compared with bare Au NPs, Au@Pt NPs exhibited significantly enhanced electrocatalytic activity toward reduction of H2O2 due to the bimetallic synergistic effect and great dispersion of Au@Pt NP-modified indium tin oxide (Au@Pt NPs/ITO). It exhibited a linear detection of H2O2 in a wide concentration range from 0.5 to 1000 µM with a low detection limit of 0.11 µM (S/N = 3). Therefore, the plasmonic hot-electron-painted Au@Pt NPs represent a novel and simple method for the design of advanced noble asymmetric metal nanomaterials.

DNA Logic Nanodevices for the Sequential Imaging of Cancer Markers through Localized Catalytic Hairpin Assembly Reaction.

Monitoring tumor biomarkers is crucial for cancer diagnosis, progression monitoring, and treatment. However, identifying single or multiple biomarkers with the same spatial locations can cause false-positive feedback. Herein, we integrated the DNA tetrahedron (DT) structures with logic-responsive and signal amplifying capability to construct transmembrane DNA logic nanodevices (TDLNs) for the in situ sequential imaging of transmembrane glycoprotein mucin 1 (MUC1) and cytoplasmic microRNA-21 (miR-21) to cell identifications. The TDLNs were developed by encoding two metastable hairpin DNAs (namely, H1 and H2) in a DT scaffold, in which the triggering toeholds of H1 for miR-21 were sealed by the MUC1-specific aptamer (MUC1-apt). The TDLNs not only had the function of signal amplification owing to the localized catalytic hairpin assembly (CHA) reaction through spatial constraints effect of DT structures but also performed an AND logic operation to output a green Cy3 signal in MCF-7 cells, where MUC1 protein and miR-21 were simultaneously expressed. These results showed that the newly developed TDLNs have better molecular targeting and recognition ability so as to be easily identify cell types and diagnose cancer early.

Efficient and Sustainable in†situ Photo-Fenton Reaction to Remove Phenolic Pollutants by NH2 -MIL-101(Fe)/Ti3 C2 Tx Schottky-Heterojunctions.

Metal-organic frameworks (MOFs) with abundant active sites, a class of materials composed of metal nodes and organic ligands, is widely used for photocatalytic degradation of pollutants. However, the rapid recombination of photoinduced carriers of MOFs limits its photocatalytic degradation performance. Herein, Ti3 C2 Tx nanosheets-based NH2 -MIL-101(Fe) hybrids with Schottky-heterojunctions were fabricated by in situ hydrothermal assembly for improved photocatalytic activity. The photodegradation efficiencies of the NH2 -MIL-101(Fe)/Ti3 C2 Tx (N-M/T) hybrids for phenol and chlorophenol were 96.36 % and 99.83 % within 60 minutes, respectively. The N-M/T Schottky-heterojunction duly transferred electrons to the Ti3 C2 Tx nanosheets surface via built-in electric fields, effectively suppressing the recombination of photogenerated carriers, thereby improving the photocatalytic performance of NH2 -MIL-101(Fe). Moreover, the Fe-mixed-valence in the N-M/T led to improvement in the efficiency of the in situ generated photo-Fenton reactions, further enhancing the photocatalytic activity with more generated reactive oxygen species (ROS). The study proposes a highly effective removal of phenolic pollutants in wastewater.