Environmental Applications Research Articles

Research on Low-Power Digital Integrated Circuit Technology

In today’s diverse and rapidly developing field of low-power technologies, various industries are actively applying these advanced technologies to practical production in order to reduce energy consumption and mitigate environmental pollution. Based on this core concept, this article delves into and compares the principles, advantages, and disadvantages of the low-power technology of passive tag chips with the representative low-power technologies of dual-power and crossed-zero clocking, as well as their respective application areas. Specifically, the article conducts a detailed comparative analysis of the low-power technology of passive tag chips versus dual-power and crossed-zero clocking technologies from three perspectives: power consumption, design approach, and practical application. Through in-depth research, it was found that the low-power technology of passive tag chips holds significant advantages in the logistics industry, making it particularly well-suited for this field; meanwhile, dual-power and crossed-zero clocking technologies perform better in high-performance computing, making them more appropriate for such an application environment.

Underwater Structurally‐Colored Adhesives for Visualized Adhesion Monitoring in Aqueous Media

AbstractAssessment of the local strain/stress changes of adhesives is highly desirable for their service to avoid premature failure. However, monitoring local strain/stress variations in adhesives in practical settings remains challenging, especially in aqueous media. Here, an underwater structurally‐colored adhesive for visualized local strain/stress monitoring in aqueous media is reported. The structurally‐colored adhesive is obtained by shearing composites of poly(butyl acrylate‐co‐acrylic acid) copolymer and carboxylated polystyrene colloidal particles. The resultant structurally‐colored adhesive exhibits underwater adhesive strength (i.e., 238 kPa for stainless steel substrates) to various substrates (e.g., metals and plastics) thanks to hydrophobic segments and carboxyl groups. Notably, they can shift color in response to external force, enabling real‐time visual monitoring of localized strain/stress changes. As a proof of concept, the structurally‐colored adhesive can be used to seal a leaking hole on a bottle or tube, and it can precisely visualize the localized pressure distribution, providing critical information on the adhesion performance and the local pressure. These distinctive properties make the structurally‐colored adhesive suitable for application in wet environments as a real‐time visual pressure tracking device.

Simultaneously Enhanced Low Temperature Li+ Transport Kinetics and Crystal Stability of Nb1.94Mo0.06O5@C Anode Induced by Distorted NbO6 Octahedron

AbstractThe electrochemical performances of lithium‐ion batteries (LIBs) will be significantly degraded under low‐temperature conditions, which restricts their wide application in cold environments. Herein, the low‐temperature transport kinetics of a novel Nb1.94Mo0.06O5@C nanocomposite anode is accelerated greatly via engineering the microstructure and NbO6 octahedron. The detailed crystallographic features are characterized by using synchrotron radiation, spherical electron microscope, and density functional theory simulation methods. Both experimental and simulation analysis suggest that Mo6+ preferentially replaces Nb5+ in the regular octahedral location and distorts the NbO6 octahedron, resulting in a widened c‐axis spacing and a lowered ion diffusion barrier. Coupled with the enhanced electronic conductivity derived from surface carbon layer, Nb1.94Mo0.06O5@C anode exhibits an enhanced charge transfer process, improved Li+ diffusion kinetics, pronounced pseudo‐capacitance process, and excellent low temperature capacity. Furthermore, in situ X‐ray diffraction and ex situ electron microscope elucidate that the structural evolution of Nb1.94Mo0.06O5@C is highly reversible, unveiling its excellent cycling stability. The full cell assembled with LiNi0.6Co0.2Mn0.2O2 cathode demonstrates excellent practicality. This study reveals the critical role of distorting NbO6 octahedron and expanding crystal spacing in facilitating rapid Li+ diffusion and enhancing charge storage performance of Nb2O5 at low temperatures.

 Synthesis and Characterization of Chitosan-Based Schiff Base and Cu(II) Complex from Shrimp Shells and its Application on Catalysis and Bio-sorption

In recent years, metal complexes and biopolymers have gained significant attention in environmental applications such as catalysis and heavy metal removal. Chitosan, a biopolymer derived from chitin, is well-known for its biodegradability, non-toxicity, and strong metal ion affinity, which can be further enhanced through Schiff bases to improve its catalytic and adsorption capabilities. The primary objectives of this study were to investigate whether Cu(II) complex of Chitosan Salicylaldehyde Schiff Base CSSB-Cu(II) can act as an efficient catalyst in hydrogen peroxide decomposition reaction and to find out the raw absorbent which has the highest Cadmium ion removal efficiency from among the absorbents Chitin (CT), Chitosan (CS) and Chitosan Salicylaldehyde Schiff Base (CSSB). CSSB was synthesized using the Schiff condensation reaction between the amino group of CS and the carbonyl compound of salicylaldehyde with the elimination of water molecules and it was complexed with Cu(II) ion to produce CSSB-Cu(II) complex. The catalytic effect of the CSSB-Cu(II) complex on the kinetics of the decomposition of hydrogen peroxide was investigated and compared with CSSB. CSSB-Cu(II) showed a better catalytic effect than CSSB and has a pseudo-first-order catalytic decomposition for H2 O2 . CT, CS, and CSSB were investigated as adsorbents for the Cd(II) removal to determine their cadmium removal efficiencies. This study concludes that the removal efficiency of CSSB was greater than that of CS and CT. The equilibrium data agreed more with the Langmuir model than with the Freundlich model. The IR and electronic spectral data confirm the presence of an imine bond and the existence of the complex in square planar geometry.

Implementation of Business Intelligence for Analysis Data of Drug Sales Using Exploratory Data Analysis (EDA) and Visualization Data Using Looker Studio

This study aims to analyze pharmaceutical sales performance by leveraging big data and advanced information technology tools, providing insights for improved business strategies. Using the Exploratory Data Analysis (EDA) method, the study processes raw sales data through spreadsheet applications to identify key patterns and trends. The findings are then visualized with Looker Studio on an intelligent dashboard tailored to the needs of the marketing team. The dashboard enables quick, data-driven decision-making by displaying performance metrics and trends relevant to sales and marketing strategies. The results reveal critical insights into sales behavior, including high-performing products, regional sales variations, and temporal sales trends. The analysis equips the marketing team with actionable data to refine their strategies, prioritize product focus, and adjust marketing efforts in response to identified patterns. In conclusion, the use of EDA and data visualization provides a structured approach to big data interpretation, allowing the company to optimize business and marketing performance. The study underscores the potential of data-driven dashboards to enhance strategic planning, suggesting broader applications in various data-intensive business environments.

Enhanced detection performance based on a differential ME sensor with strong suppression of vibration interference

Magnetoelectric (ME) sensors have enormous potential for detecting weak magnetic fields because of their high sensitivity, low power consumption, compact size and, low cost. However, inevitable vibration interference limits their application in practical environments, especially in the case of mobile platform mounting. Here, we propose a differential ME sensor, consisting of PZT macro-fiber composites (MFCs) and Metglas laminates. The differential ME sensor has two output terminals with weak mutual mechanical coupling and works in longitudinal vibration mode. MFC cores are polarized in parallel mode to guarantee their consistency of electric characteristics and reversed bias field is provided by attached magnets. Experimental results show that the differential-mode response amplitudes have a gain of −17.6 dB for low-frequency vibration at 2 Hz and ∼6.2 dB for an applied magnetic field at 3 Hz, in comparison with the single-ended mode. In addition, our proposed ME sensor also has a low inherent equivalent magnetic noise of 18.3 pT/√Hz at 1 Hz. Finally, a target detection experiment in the presence of heavy lab noise and strong vibration interference is conducted and the improved detection performance of the proposed differential ME sensor is proved.

BHI-YOLO: A Lightweight Instance Segmentation Model for Strawberry Diseases

In complex environments, strawberry disease segmentation models face challenges, such as segmentation difficulties, excessive parameters, and high computational loads, making it difficult for these models to run effectively on devices with limited computational resources. To address the need for efficient running on low-power devices while ensuring effective disease segmentation in complex scenarios, this paper proposes BHI-YOLO, a lightweight instance segmentation model based on YOLOv8n-seg. First, the Universal Inverted Bottleneck (UIB) module is integrated into the backbone network and merged with the C2f module to create the C2f_UIB module; this approach reduces the parameter count while expanding the receptive field. Second, the HS-FPN is introduced to further reduce the parameter count and enhance the model’s ability to fuse features across different levels. Finally, by integrating the Inverted Residual Mobile Block (iRMB) with EMA to design the iRMA, the model is capable of efficiently combining global information to enhance local information. The experimental results demonstrate that the enhanced instance segmentation model for strawberry diseases achieved a mean average precision (mAP@50) of 93%. Compared to YOLOv8, which saw a 2.3% increase in mask mAP, the improved model reduced parameters by 47%, GFLOPs by 20%, and model size by 44.1%, achieving a relatively excellent lightweight effect. This study combines lightweight architecture with enhanced feature fusion, making the model more suitable for deployment on mobile devices, and provides a reference guide for strawberry disease segmentation applications in agricultural environments.

Hierarchical structure Fe@CNFs@Co/C elastic aerogels with intelligent electromagnetic wave absorption

AbstractDeveloping intelligent electromagnetic wave (EMW) absorption materials with real‐time response‐ability is of great significance in complex application environments. Herein, highly compressible Fe@CNFs@Co/C elastic aerogels were assembled through the electrospinning method, achieving EMW absorption through pressure changes. By varying the pressure, the effective absorption bandwidth (EAB) of Fe@CNFs@Co/C elastic aerogels shows continuous changes from low frequency to high frequency. The EAB of Fe@CNFs@Co/C elastic aerogels is 14.4 GHz (3.36–17.76 GHz), which covers 90% of the range of S/C/X/Ku bands. The theoretical simulation indicates that the external pressure prompts a reduction in the spacing between the fiber layers in the aerogels and facilitates the formation of a 3D conductive network with enhanced attenuation ability of EMW. The uniform distribution of metal particles and appropriate layer spacing can effectively optimize the impedance matching to achieve the best EMW absorption performance. This work state clearly that the hierarchically assembled elastic aerogels composed of metal–organic frameworks (MOFs) derivatives and carbon fibers are ideal dynamic EMW absorption materials for intelligent EMW response.image

Nanoparticles: balancing benefits, ecological risks, and remediation approaches

Nanoparticles are the simplest form of structure, having sizes ranging from 1 to 100 nm and can provide considerably high surface areas through rational design. Their size, shape and structure are responsible for their high reactivity and strength. In the last few decades, nanoparticles have been widely used in many dosage forms due to their excellent solubility, less size and better penetrability. They have attained prominence in various technological advancements because their properties can be tuned as desired via precisely controlling the size, shape, synthesis conditions, and appropriate functionalization. Due to these unique properties, Nanoparticles have acquired a substantial global market in various commercial and domestic applications, including catalysis, imaging, medical applications, sports equipment, sensors, energy-based research, and environmental applications. Due to the increased growth of the production of nanoparticles and their industrial applications, issues relating to toxicity are inevitable. Several reports are available on the benefits of these nanomaterials in various sectors, but relatively more minor literature is available on their effect on the environment and human health. Several heavy metal nanoparticles are reported to be so rigid and stable that their degradation is not readily achievable, leading to much environmental toxicity. This review discusses a brief history, various applications and the possible fate of the Nanoparticles after use. In particular, we describe how Nanoparticles affect the environment, natural resources, natural micro-flora and humankind. It also describes several techniques currently being used to remove nanoparticles.

Bacterial cellulose-graphene oxide composite membranes with enhanced fouling resistance for bio-effluents management

Bacterial cellulose composites hold promise as renewable bioinspired materials for industrial and environmental applications. However, their use as free-standing water filtration membranes is hindered by low compressive strength, fouling, and poor contaminant selectivity. This study investigates the potential of bacterial cellulose-graphene oxide composites membranes for fouling resistance in pressure-driven filtration. Graphene oxide dispersed in poly(ethylene glycol) (PEG-400) is incorporated as a reinforcing filler into 3D network of bacterial cellulose using an in-situ synthesis method. The effect of graphene oxide on in situ fermentation yield and the formation of percolated-network in the composites shows that the optimal membrane properties are reached at a graphene oxide loading of 2 mg/mL. The two-dimensional graphene oxide nanosheets uniformly dispersed into the matrix of bacterial cellulose nanofibers via hydrogen-bonded interactions demonstrated nearly twofold higher water flux (380 L m−2 h−1) with a molecular weight cut-off ranging between 100–200 KDa and a sixfold increase in wet compression strength than pristine BC. When exposed to synthetic organic foulants and bacterial rich feed solutions, the composite membranes showed more than 95% flux recovery. Additionally, the membranes achieved over 95% rejection of synthetic natural organic matter and bacterial rich solutions, showcasing their enhanced fouling resistance and selectivity.

A Review of Advanced Hydrogel Applications for Tissue Engineering and Drug Delivery Systems as Biomaterials

Hydrogels are known for their high water retention capacity and biocompatibility and have become essential materials in tissue engineering and drug delivery systems. This review explores recent advancements in hydrogel technology, focusing on innovative types such as self-healing, tough, smart, and hybrid hydrogels, each engineered to overcome the limitations of conventional hydrogels. Self-healing hydrogels can autonomously repair structural damage, making them well-suited for applications in dynamic biomedical environments. Tough hydrogels are designed with enhanced mechanical properties, enabling their use in load-bearing applications such as cartilage regeneration. Smart hydrogels respond to external stimuli, including changes in pH, temperature, and electromagnetic fields, making them ideal for controlled drug release tailored to specific medical needs. Hybrid hydrogels, made from both natural and synthetic polymers, combine bioactivity and mechanical resilience, which is particularly valuable in engineering complex tissues. Despite these innovations, challenges such as optimizing biocompatibility, adjusting degradation rates, and scaling up production remain. This review provides an in-depth analysis of these emerging hydrogel technologies, highlighting their transformative potential in both tissue engineering and drug delivery while outlining future directions for their development in biomedical applications.

Utilizing graph neural networks for adverse health detection and personalized decision making in sensor-based remote monitoring for dementia care

Background:Sensor-based remote health monitoring is increasingly used to detect adverse health in people living with dementia (PLwD) at home, aiming to prevent hospitalizations and reduce caregiver burden. However, home sensor data is often noisy, overly granular, and suffers from unreliable labeling, data drift and high variability between households. Current anomaly detection methods lack generalizability and personalization, often requiring anomaly-free training data and frequent model updates. Objective:To develop a lightweight, explainable, self-supervised approach with personalized alert thresholds to detect adverse health events in PLwD, using changes in home activity. Methods:We hypothesized that health downturns manifest as detectable shifts in household movement patterns. Our approach leverages a Graph Barlow Twins contrastive model, which uses granular activity data and a macroscopic view to extract noise-robust, high-level and low-level discriminative features that represent daily activity patterns. Household-personalized alert thresholds are calculated based on clinician-set target alert rates, and daily anomaly scores are compared against these thresholds, triggering alerts for the clinical monitoring team. Model attention weights support explainability. Data were collected from a real-world dataset by the UK Dementia Research Institute (August 2019-April 2022). Results:Our model outperformed state-of-the-art temporal graph algorithms in detecting agitation and fall events across three patient cohorts, achieving 81% average recall and 88% generalizability at a target alert rate of 7%. Conclusion:We developed a novel, lightweight, explainable, and personalized Graph Barlow Twins model for real-world remote health monitoring in dementia care, with potential for broader applications in healthcare and sensor-based environments.

Exploring Fault Plane Geometry through Metaheuristic Bat Algorithm (MBA) Analysis of Potential Field Data: Environmental and Engineering Applications

Exploring Fault Plane Geometry through Metaheuristic Bat Algorithm (MBA) Analysis of Potential Field Data: Environmental and Engineering Applications

Tetrafunctionalized Azocalix[4]resorcinarene Dye: A Chromogenic Supramolecule Used for the Selective Liquid-Liquid Extraction and Spectrophotometric Determination of Cu(II)

Background: The detection and extraction of trace metal ions, particularly copper(II), are critical for environmental monitoring and industrial processes. Calixresorcinarene, with its unique cavity structure, offers excellent platforms for designing selective chemosensors and extractants. Functionalization of calixresorcinarene with azo groups can enhance their chromogenic properties, enabling both extraction and detection in a single step. Objective: This study aimed to evaluate its (Azocalix[4]resorcinaren) efficacy as a selective chemosensor for the liquid-liquid extraction and spectrophotometric determination of Cu(II) ions. Methods: Application in Extraction and Detection: The ability of the dye to selectively extract Cu(II) ions from aqueous solutions was investigated via liquid-liquid extraction experiments. The dye-Cu(II) complex formation was monitored by UV-Vis spectrophotometry, with systematic optimization of experimental conditions, including pH, solvent system, and extraction duration. Results: The synthesized azocalix[4]resorcinarene dye exhibited a pronounced selectivity towards Cu(II) ions, forming a stable, colored complex. The complexation induced a distinct bathochromic shift in the absorption spectrum, allowing for precise spectrophotometric detection. Optimal extraction was achieved at a specific pH and solvent combination, with the method demonstrating a low detection limit and high sensitivity. The dye showed minimal interference from other metal ions, confirming its selectivity for Cu(II). Conclusion: The tetrafunctionalized azocalix[4]resorcinarene dye is a highly effective chromogenic agent for the selective extraction and detection of Cu(II) ions. Its robust performance in both extraction efficiency and spectrophotometric detection underscores its potential utility in environmental analysis and industrial applications where trace metal detection is crucial.

3D Printed Metallic Pillar Nanomechanical Resonators Decorated with TiO2 Nanotubes for Highly Sensitive Environmental Applications

AbstractMicro and nanomechanical devices offer enhanced sensing capabilities for detecting biological and chemical small molecules. However, miniaturization necessitates advanced fabrication processes and complex measurement systems, hindering routine sensor analysis. While alternative methods like 3D printing show promise, challenges such as low device resolution persist due to intrinsic damping of polymer inks. In this study, an array of micrometric pillar resonators is fabricated in Ti6Al4 V alloy using additive manufacturing based on laser powder bed fusion technology. These metallic nanomechanical resonators exhibit a very high quality factor with minimal difference between air and vacuum measurements due to low intrinsic damping. Furthermore, titania nanotubes grown on the pillars via anodic oxidation heighten sensitivity for molecular dye degradation evaluation. Leveraging the weak coupling phenomenon among the pillars in the array, these devices facilitate large‐scale parallelized measurements, here demonstrated with real‐time analysis of dye degradation process. This approach to creating mass sensing devices via metallic additive manufacturing can usher in a new generation of highly performing resonating sensor arrays, offering a cost‐effective and efficient alternative to traditional silicon microfabrication methods.

Cascaded utilization of magnetite nanoparticles@onion-like carbons from wastewater purification to supercapacitive energy storage.

Developing high-performance carbon-based materials for environmental and energy-related applications produces solid waste with secondary pollution to the environment at the end of their service lives. It is still challenging to utilize these functional materials in a sustainable manner in different fields. In this study, we demonstrate a cascaded utilization of an Fe3O4@onion-like carbon (Fe3O4@OLC) structure from wastewater adsorbents to a supercapacitor electrode. The structure was formed by carbonizing Fe3O4@oleic acid monodisperse nanoparticles into interconnected Fe3O4@OLCs and subsequent insufficient acid etching. The hollow OLCs in the outside region of the hybrid structure provide high surface area and the encapsulated Fe3O4 nanoparticles in the inside region offer high ferromagnetism. The three-dimensionally interconnected graphitic layers are advantageous for efficient separation and high conductivity. As a result, the maximum saturation adsorption capacity of insufficiently etched interconnected Fe3O4@OLCs can reach up to 90.2 mg g-1 and they can be efficiently separated under a magnetic field. Furthermore, the hybrid structure is thermally transformed into N-doped HOLCs, which are demonstrated to be a high-performance supercapacitor electrode with high specific capacitance and high electrochemical stability. The cascaded utilization of the hybrid structure in this study is meaningful for eco-friendly development of functional materials for environmental and energy storage applications.

Unraveling the roles of atomically-dispersed Au in boosting photocatalytic CO2 reduction and aryl alcohol oxidation

Atomically-dispersed metal-based materials represent an emerging class of photocatalysts attributed to their high catalytic activity, abundant surface active sites, and efficient charge separation. Nevertheless, the roles of different forms of atomically-dispersed metals (i.e., single-atoms and atomic clusters) in photocatalytic reactions remain ambiguous. Herein, we developed an ethylenediamine (EDA)-assisted reduction method to controllably synthesize atomically dispersed Au in the forms of Au single atoms (AuSA), Au clusters (AuC), and a mixed-phase of AuSA and AuC (AuSA+C) on CdS. In addition, we elucidate the synergistic effect of AuSA and AuC in enhancing the photocatalytic performance of CdS substrates for simultaneous CO2 reduction and aryl alcohol oxidation. Specifically, AuSA can effectively lower the energy barrier for the CO2→*COOH conversion, while AuC can enhance the adsorption of alcohols and reduce the energy barrier for dehydrogenation. As a result, the AuSA and AuC co-loaded CdS show impressive overall photocatalytic CO2 conversion performance, achieving remarkable CO and BAD production rates of 4.43 and 4.71 mmol g−1 h−1, with the selectivities of 93% and 99%, respectively. More importantly, the solar-to-chemical conversion efficiency of AuSA+C/CdS reaches 0.57%, which is over fivefold higher than the typical solar-to-biomass conversion efficiency found in nature (ca. 0.1%). This study comprehensively describes the roles of different forms of atomically-dispersed metals and their synergistic effects in photocatalytic reactions, which is anticipated to pave a new avenue in energy and environmental applications.

On the lifespan of Enchytraeus crypticus - impact of iron (nanomaterial and salt) on aging.

Iron oxide nanomaterials (Fe3O4 NMs) have important biomedical and environmental applications, e.g. drug delivery, chemotherapy, magnetic resonance imaging contrast agents, etc. However, the environmental risks of such Fe3O4 are not fully assessed, particularly for soil living invertebrates, which are among the ones in the first line of exposure. Research has showed that longer-term exposure time is required to assess hazards of NMs, not predicted when based on shorter time and are therefore recommended. Thus, in the present study the effects of Fe3O4 NMs and FeCl3 were assessed in the terrestrial environment, using the soil model species Enchytraeus crypticus (Oligochaeta), throughout its entire lifespan (202 days). Two animals' density were used: 1 (D1) and 40 (D40) animals per replicate, in LUFA 2.2 soil. The endpoints were survival and reproduction monitored over-time, up to 202 days. Results showed that density clearly affected the toxicity response, with higher toxicity and lower lifespan in D1 compared to D40. Overall, FeCl3 was more toxic than Fe3O4 NM in terms of reproduction, however, adult animals can be at higher (long-term) risk when exposed to Fe3O4 NM. Differences might be linked to slower Fe kinetics for the Fe3O4 NMs, i.e., slower Fe dissolution and release of ions.

Glyphosate formulations cause mortality and diverse sublethal defects during embryonic development of the amphibian Xenopus laevis

The human impact on environmental landscapes, such as land use, climate change or pollution, is threatening global biodiversity and ecosystems maintenance. Pesticides like the herbicide glyphosate have garnered considerable attention due to their well-documented harmful effects on non-target species. During application, the active ingredient glyphosate is utilized in various formulations, each containing different additive adjuvants. However, the possible effects of these formulations on amphibians - the group with the highest decline rates among vertebrates - remain largely unknown.Therefore, the present study investigated the effects of four glyphosate formulations (Glyphosat TF, Durano TF, Helosate 450 TF, Kyleo) on the embryonic development of the model organism Xenopus laevis (South African clawed frog). Embryos at the 2-cell stage were exposed to various concentrations of glyphosate formulations (glyphosate: 0.01 – 100 mg/L), and mortality as well as sublethal effects on different organs and tissues were analyzed. The results indicated that the formulations had different effects, particularly on the mortality of Xenopus laevis embryos. At sublethal concentrations, the formulations altered the embryos' external appearance, leading to malformations such as reduced eye and head size. In addition, exposure to formulations impaired heart morphology and function, and the expression of heart-specific genes was altered at a molecular level.Our results confirmed that glyphosate formulations had a stronger effect on Xenopus laevis embryogenesis than pure glyphosate. Therefore, it is crucial to evaluate both, the active ingredient and the co-formulations independently, as well as the combined, commercially available products, during pesticide risk assessments and renewal procedures of agrochemicals. The severe global decline of amphibians, partly due to herbicide use, highlights the need for strict and efficient monitoring of environmental pesticide loads and application areas.

Hierarchical TiO2 nanostructures sensitized with MoS2 nanosheets: an efficient and reusable heterojunction photocatalyst for sunlight-assisted degradation of organic dye pollutants

Abstract The present study reports the synthesis, characterization, and natural sunlight-driven photocatalytic activity of a novel heterojunction photocatalyst comprised of hierarchical rutile titanium dioxide (r-TiO2) nanostructures and 1T/2H molybdenum disulfide (MoS2)nanosheets. These components were synthesized by solvothermal methods and their effective integration was achieved by using 3- aminopropyltrimethoxysilane as coupling agent. The photocatalytic activity of r-TiO2/MoS2 nanohybrid was explored for the degradation of cationic dye methylene blue (MB), and anionic dye congo red (CR) under natural sunlight. The results reveal that the sunlight-driven photocatalytic activity of pristine r-TiO2 was drastically enhanced upon sensitization with 1T/2H MoS2 nanosheets. The nanohybrid could degrade 99% MB and 98% CR within 150 min with rate constants 25.6×10−3 and 13.2×10−3 min−1respectively. The r-TiO2/MoS2 nanohybrid retained more than 85% of its catalytic activity even after four cycles of reuse. The scavenger test revealed that holes and hydroxyl radicals are mainly responsible for the degradation of MB and CR. The facile synthesis, outstanding catalytic activity under natural sunlight, and excellent recyclability make r-TiO2/MoS2 a promising heterojunction photocatalyst for the degradation of environmental pollutants from wastewater. The present study can provide new insights towards the development of efficient, economical and sustainable photocatalysts for harnessing renewable solar energy for environmental remediation applications.