Hybrid System Research Articles

Techno-economic study of a hybrid photovoltaic-diesel system for a remote area in southwest Algeria

Exploiting natural sun and wind resources in remote and isolated areas is undoubtedly an excellent decision to generate electrical energy due to their availability and cleanliness. Various systems were used to generate this energy, such as photovoltaics (PV), wind turbine sand other energy systems. Moreover, for optimum energy use, some of these systems are combined either with each other or with other conventional systems, such as diesel generators with PV systems (i.e., hybrid systems). This work aims to present a technical-economic study of PV/diesel autonomous hybrid systems to supply electrical power for an isolated house located in a hot desert climate, Adrar. For optimizing the hybrid systems, hourly input data of solar radiation and load were used according to two configurations, where the annual load is 11.2 kWh/day. The findings showed that the diesel system had a high cost, with a cost for energy of $0.407/kWh and a fuel price of $0.140/l. Among the hybrid power systems but with significant pollution, the proposed hybrid system 2 kw photovoltaic and diesel generator with 2.3 kW has important economic feasibility, where the energy cost amounted to $0.172/kWh. In addition, CO2 emissions are reduced by approximately 5 tons every year compared to an independent diesel generator system.

Fundamental frequency switching strategies of a seven level hybrid cascaded H-bridge multilevel inverter

This paper presents a novel hybrid cascaded H-bridge multilevel inverter (HCHB MLI) designed to address the growing importance of multilevel inverters in the context of renewable energy sources such as solar, wind, and fuel cells. The proposed topology features eight insulated-gate bipolar transistor (IGBT) switches and utilizes two distinct input direct current (DC) sources: a battery and a capacitor, making it a hybrid system. The control strategy employed in this topology is based on fundamental switching frequency techniques. Simulation results of the proposed topology are conducted using MATLAB/Simulink software, while hardware experimentation with a single-phase H-bridge inverter is also demonstrated in the paper. For pulse generation and IGBT switch control, an Arduino UNO microcontroller is utilized. The output voltage of the single-phase H-bridge inverter is verified through experimentation using a cathode-ray oscilloscope (CRO).

Novel control of PV-wind-battery powered standalone power supply system based LSTM based ANN

Integrated wind-photovoltaic (PV) based standalone electric power supply systems are widely used for various applications. A battery storage system is needed to provide continuous power supply to loads despite changes in loads, wind speed, and solar irradiance. Power quality is crucial in these hybrid systems, as the battery needs to charge from surplus power when generation exceeds the load and discharge to meet load demand. A bidirectional DC to DC converter is used to connect the battery to the network, and maximum power point tracking devices with proper algorithms are incorporated for optimal utilization of PV and wind turbines. Multiple PV systems and wind turbines are considered for proper power supply system ratings. Long short-term memory (LSTM) based artificial neural network (ANN) controllers are implemented for various control units in the hybrid standalone power system. The proposed control techniques improve power quality under various situations. Results are presented using MATLAB/Simulink to evaluate the performance of the proposed method.

Electric vehicle and photovoltaic advanced roles in enhancing the financial performance of a manufacturing and commercial setup

Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network.

Adaptive control for hybrid dynamical systems with user-defined rate of convergence

Adaptive control for hybrid dynamical systems with user-defined rate of convergence

The implementation of an optimized neural network in a hybrid system for energy management

In the face of increasing global energy demand and volatile energy prices, many countries are searching for solutions to ensure their energy independence. One of the most popular solutions is to incorporate renewable energy sources in their energy systems. While there are many advantages to integrating renewable energy sources, it is important to note that their intermittent operation can present challenges. Energy storage and smart grid management systems are key solutions to overcome these challenges and ensure sustainable, reliable use of renewable energy sources. In this article, we present an intelligent electrical energy management system for hybrid energy systems. This management system is based on a multi-layer neural network that has undergone an architecture optimization phase to improve the accuracy of real-time energy management and simplify its implementation. The management model that was built demonstrated highly good performance across a range of test circumstances.

Deep Learning for Enhanced Brain Tumor Detection and Classification

The purpose of this research is to build an automated, robust, intelligent and hybrid system for the early diagnosis and classifying of brain tumor. To serve this purpose, the authors propose the Auto Contrast Enhancer, Tumor Detector and Classifier to efficiently provide on-demand contrast improvement of poor contrast MRI images for the early diagnosis and classification of brain tumors. The classifier accomplishes its task through a two-phase approach. During the initial phase, ODTWCHE is employed to enhance image contrast, facilitating accurate diagnosis of brain tumours. In the subsequent phase, the classifier leverages the power of deep transfer learning, utilizing the pre-trained Inception V3 model to refine the diagnostic process further. tumor classification. Compared to state-of-the-art models, including AlexNet, VGG-16, DenseNet-201, VGG-19, GoogLeNet, and ResNet-50, the proposed system showcased its outstanding performance by achieving the highest accuracy of 98.89% on a public dataset that consists of MRI images with varying contrast and brightness levels. The precise detection and classification achieved on this multicolored dataset prove the system's robustness. The authors of the article address the usage of metrics in a variety of contexts, including academia, as well as the possible problems that may result from their improper application. They emphasize how crucial it is to create measurements that align with the system's objectives and to reduce any negative consequences that can skew the data or allow people to manipulate the system's incentives. The authors provide a thorough process for creating metrics that takes into account design considerations, countermeasures for unfavorable effects, and crucial requirements. The paper provides answers for the creation of metrics and gives examples of metrics' failures in many fields. The authors emphasize the significance of understanding how the goal and the data at hand relate to one another, as well as the necessity of compromise and clarity when goals are contradictory or incoherent.A comparative analysis with existing models further confirms that the proposed system consistently outperforms the competition.

Hybrid renewable/grid power systems, an essential for base transceiver station penetration in Rural Nigeria

The energy crisis in Nigeria has continued to impede the rapid expansion of the telecommunication industry, whose operating expenditure is galloping due to over-dependence on diesel generators as an alternative source of power to its base transceiver station (BTS). This fossil-fuel power source has also increased the industry’s carbon footprint. As a solution to these problems, the objective of this work is to provide a sustainable and quality hybrid DC power supply system for BTS that would increase access to information and communication technology or ICT infrastructure. This involves the integration of solar & wind energy with the grid. The sizing of the hybrid sub-systems was designed & simulated using MATLAB Simulink to test for functionality. A prototype of the design system was then implemented with the results showing an average power output that guarantees 21 hours/day of supply. By installing this hybrid system of 1.3 kW, approximately 2.55 kg of diesel (C10H20) would be un-utilized by one BTS, thereby preventing 3.6 kg of CO2 from been emitted to the atmosphere daily. Extrapolating these values shows 930.75 kg of diesel can be saved and reduce 1314 kg of CO2 emission within a year. Hence eliminating the need for diesel-backup generator for a grid connected or non-grid BTS sited in rural areas.

Combining solar panels with plants for sustainable energy and food production: state of the art

The need for alternative energy sources becomes extensive because of the escalating cost of fossil fuels. The goal of this paper is to examine the effectiveness of combining photovoltaics and agriculture for better yield. Photovoltaic (PV) solar plants will compete with farms for available land. In this study, the methodologies are discussed how it is possible to maximize land utilization by placing solar arrays and food crops on the same plot of land. The term is proposed "agrivoltaic system" to describe this setup. Conventional solutions (discrimination of agricultural and energy extracting) were compared to two agrivoltaic schemes with varying density of PV arrays using land equivalent ratios. We utilized a crop model to simulate the amount of sunlight reaching the crop from an array of solar panels and to speculate on the yield reduction that would result from the partial shading. These early findings suggest that agrivoltaic systems may be highly effective; the two densities of PV panels were anticipated to boost worldwide land production by 73%. One possible explanation for the success of these hybrid systems is the presence of facilitation mechanisms analogous to those seen in agroforestry. At the end it is suggested that in places where arable land is rare, new solar plants may find it beneficial to produce both power and food.

Enhancement Network Security Features Through Intrusion Detection Systems

Abstract: In pursuit of its objectives, the project "Enhancement Network Security features through Intrusion Detection Systems" undertakes a comprehensive exploration of the intricacies surrounding network security, delving into the nuances of intrusion detection methodologies. By dissecting the mechanisms behind both anomaly- and signature-based IDS, the initiative aims not only to implement these systems but also to grasp their underlying principles deeply. Through rigorous experimentation and analysis, the project endeavours to uncover the strengths and limitations of each approach, thereby paving the way for the development of a hybrid system that leverages the best of both worlds. This meticulous approach ensures that the resulting IDS is not only robust but also finely tuned to adapt to the ever-evolving landscape of cyber threats. Furthermore, the integration of machine learning techniques represents a pivotal advancement in the realm of intrusion detection. By harnessing the power of algorithms capable of autonomously learning from data, the IDS transcends static rule-based detection methods, ushering in a new era of adaptive security measures. Through continuous training on vast datasets comprising diverse threat scenarios, the machine learning-enabled IDS hones its ability to discern subtle patterns indicative of malicious activity, thus bolstering its efficacy in safeguarding network assets. Moreover, the implementation of machine learning algorithms fosters a proactive stance against emerging threats, enabling the system to anticipate and mitigate potential breaches before they materialize into fullfledged attacks. This proactive approach not only enhances the overall security posture of organizations but also instils confidence in their ability to stay ahead of the curve in an increasingly hostile digital landscape. The project's goal is to provide companies with a stronger protection against cyberattacks by guaranteeing the availability, confidentiality, and integrity of their networked systems.

Optimal sizing of battery energy storage system for mitigation of RES fluctuation

The integration of renewable energy sources (RES), such as wind and solar, into the electricity grid is crucial in the pursuit of sustainable energy. However, their inherent intermittency poses challenges to grid stability and reliability. Battery Energy Storage Systems (BESS) offer promising solutions to buffer these fluctuations, providing flexibility and scalability. The study examines optimal sizing methods for BESS to mitigate the unpredictability of RES output. It identifies strategies such as forecasting models, stochastic optimization, and hybrid systems that enhance predictability. Additionally, it addresses challenges like battery degradation, safety concerns, and grid integration hurdles. Innovations in Battery Management Systems (BMS) are highlighted for their potential to extend battery life and improve cost-effectiveness. Ultimately, optimizing BESS integration is critical to maximize renewable energy utilization, reduce fossil fuel dependence, and support a sustainable energy future.

Analysis of the Hybrid Power-Heating System in a Single-Family Building, along with Ecological Aspects of the Operation

This study evaluates a hybrid heating system in a single-family building in northeastern Poland, which has a temperate continental climate. The analysis covers two heating seasons in 2021/2022 and 2022/2023. The hybrid heating system includes an air heat pump HPA–08 CS Plus with a heating power of 8.2 kW (AHP), a condensing gas boiler VC146/5–5 with a power of 14 kW (GB–Condens.), and a solid fuel boiler with a power of 11 kW for central heating. Additionally, hot water is heated by a Basic 270 (DHW’s AHP) air–water heat pump with a power of 2 kW, utilizing a tank with a capacity of 270 dm3 equipped with two heating coils. The building’s average electricity consumption is around 5400 kWh/year. A 4.96 kWp photovoltaic installation is installed on the building’s roof at a 40° angle towards the south to supplement the hybrid system. The study aims to assess whether the PV installation can adequately cover the energy needs of the hybrid heat source for heating and hot water. Furthermore, the study calculates the emission of pollutants (CO2, SOx, NOx, CO, and PM10) into the atmosphere. The total annual electricity production from PV installations was 5444.9 kWh in 2021/2022 and 5684.8 kWh in 2022/2023. The excess electricity was stored in the PGE power grid as per the Prosumer settlement rules. The installed PV installation is sufficient to power the following devices annually: AHP, DHW’s AHP, and GB–Condens. However, the daily electricity production from the PV installation is not enough to cover the energy needs of the heat pump for heating during the cold months in Poland (I–III, XI–XII). It can meet the power needs of a PC all year round and can also be stored during the summer months, for example, in energy warehouses or by directly storing it in the PGE power grid. The use of the PV installation resulted in an average reduction in pollutant emissions into the atmosphere: CO2—94.1%, SOx—91.8%, NOx—95.6%, CO—9.7%, and PM10—32.1%.

A high-efficiency photocatalytic hydrogen evolution system based on nickel-quinoxaline dithiolate complexes and water-soluble CdSe quantum dots

Photocatalytic water splitting of water for hydrogen evolution is one of the effective methods to obtain clean hydrogen energy. In the present work, the following materials were synthesized: two nickel quinoxaline thiolate complexes [NBu4]2 [Ni(qdt)2] (1, Bu = n-butyl, qdt = quinoxaline-dithiol), [NBu4]2 [Ni(qdt)2(NO2)2] (2) and water-soluble MPA-CdSe quantum dots (MPA-CdSe QDs, MPA = 3-mercaptopropionic acid). Subsequently, an efficient three-component photocatalytic hybrid system for hydrogen evolution was developed and tested under visible light irradiation, in which one of the target complex 1 or 2 was used as the catalyst, triethylamine (TEA) was used as the sacrificial electron donor, and MPA-CdSe QDs were used as the light harvesting reagent. The turnover numbers (TON) for H2 evolution of 8974 (vs. complex 1) and 6532 (vs. complex 2) were obtained under the optimal conditions with TEA concentration of 5 %, pH = 12, and concentration of complex 1 or 2 of 1 × 10−5 mol L−1 after 13 h of irradiation (λ > 420 nm) in pure water. The mechanism investigation indicated that critical steps of hydrogen production was formation of hydride intermediates Ni(II)-H and Ni(I)-H spices, followed by the reaction of two Ni(II)-H or Ni(I)-H species with protons generating H2 molecules and regenerating the catalyst Ni(II).

Deciphering the Lipid-Random Copolymer Interactions and Encoding Their Properties to Design a Hybrid System.

Lipid/copolymer colloidal systems are deemed hybrid materials with unique properties and functionalities. Their hybrid nature leads to complex interfacial phenomena, which have not been fully encoded yet, navigating their properties. Moving toward in-depth knowledge of such systems, a comprehensive investigation of them is imperative. In the present study, hybrid lipid/copolymer structures were fabricated and examined by a gamut of techniques, including dynamic light scattering, fluorescence spectroscopy, cryogenic transmission electron microscopy, microcalorimetry, and high-resolution ultrasound spectroscopy. The biomaterials that were mixed for this purpose at different ratios were 1,2-dioctadecanoyl-sn-glycero-3-phosphocholine and four different linear, statistical (random) amphiphilic copolymers, consisting of oligo(ethylene glycol) methyl ether methacrylate as the hydrophilic comonomer and lauryl methacrylate as the hydrophobic one. The colloidal dispersions were studied for lipid/copolymer interactions regarding their physicochemical, morphological, and biophysical behavior. Their membrane properties and interactions with serum proteins were also studied. The aforementioned techniques confirmed the hybrid nature of the systems and the location of the copolymer in the structure. More importantly, the random architecture of the copolymers, the hydrophobic-to-hydrophilic balance of the nanoplatforms, and the lipid-to-polymer ratio are highlighted as the main design-influencing factors. Elucidating the lipid/copolymer interactions would contribute to the translation of hybrid nanoparticle performance and, thus, their rational design for multiple applications, including drug delivery.

Low-power light irradiation based plasmonic photoresponse on quasi-freestanding monolayer/AuNPs hybrid system

Low-power light irradiation based plasmonic photoresponse on quasi-freestanding monolayer/AuNPs hybrid system

Enhancing the circular dichroism of chiral dielectric nanostructure through the addition of a symmetric Au cylinder

Abstract Circular dichroism (CD) spectra play a crucial role in recognition, separation and detection of chiral molecules. Due to the inherent weak CD response of natural chiral molecules, researchers have endeavored to enhance CD signals through various artificial nanostructures. In this study, combining the advantages of both the dielectric and metal materials, we propose a hybrid dielectric-metal nanostructure consisting of a chiral Si nanorod dimer coupled with a symmetric Au cylinder to achieve robust CD responses. Owing to the plasmon resonance of the Au cylinder, the scattering- and absorption-CD of the hybrid system have been enhanced, which result in the enhanced extinction CD response. Furthermore, the distributions of electric field, magnetic field and displacement current density of both the Si dimer and hybrid nanostructure have been meticulously crafted to elucidate the physical mechanisms underlying amplified CD signals. The synergistic coupling between the magnetic fields of dielectric materials and the electric fields of the Au cylinder leads to an increase in the electric field strength and the asymmetry of near-field distributions. Additionally, spatial overlaps between electric and magnetic fields occur. These factors contribute to the enhanced chiral response of the hybrid system. Meanwhile, the CD signal can be flexibly tuned by adjusting the size of the Au cylinder and Si nanorods. This design offers a versatile approach to enhancing the chiral response of dielectric nanostructures.

Application of Recycled Filling to Improve the Purification Performance of Confectionery Wastewater in a Vertical Anaerobic Labyrinth Flow Bioreactor

Anaerobic wastewater treatment is, in many cases, a justified alternative to typical activated sludge processes, from a technological, economic, and ecological point of view. The optimisation of fermentation reactors is primarily concerned with increasing the biodegradation of organic compounds and biogas production, as well as improving efficiency in the removal of nitrogen and phosphorus compounds. The aim of the research was to determine the impact of using low-cost recycled filling on the efficiency of treating real confectionery wastewater in a vertical anaerobic labyrinth flow bioreactor. The experiments focused on selecting the organic loading rate that would allow for the effective biodegradation and removal of pollutants, as well as the efficient production of biomethane. It was found that the tested reactor can operate efficiently at a maximum organic loading rate (OLR) of 7.0–8.0 g of chemical oxygen demand (COD)/L·d. In this OLR range, high efficiency was guaranteed for both wastewater treatment and biogas production. However, increasing the OLR value to 8.0 g COD/L·d had a significant negative effect on the methane (CH4) content in the biogas. The most efficient variants achieved a biodegradation efficiency of around 90% of the organic compounds, a CH4 content of over 70% in the biogas, and a biogas yield of over 400 L/kg of COD removed. A significant influence of the applied OLR on the ratio of free organic acids (FOS) to total alkaline capacity (TAC) and pH was observed, as well as a strong correlation of these indicators with the specific biogas yield and CH4 content. The application of a solution based on the use of a hybrid system of anaerobic granulated sludge and an anaerobic filter resulted in an efficient treatment process and an almost complete elimination of suspensions from the wastewater.

Indiscriminate activities of different henipavirus polymerase complex proteins allow for efficient minigenome replication in hybrid systems.

The henipaviruses, including Nipah virus (NiV) and Hendra virus (HeV), are biosafety level 4 (BSL-4) zoonotic pathogens that cause severe neurological and respiratory disease in humans. To study the replication machinery of these viruses, we developed robust minigenome systems that can be safely used in BSL-2 conditions. The nucleocapsid (N), phosphoprotein (P), and large protein (L) of henipaviruses are critical elements of their replication machinery and thus essential support components of the minigenome systems. Here, we tested the effects of diverse combinations of the replication support proteins on the replication capacity of the NiV and HeV minigenomes by exchanging the helper plasmids coding for these proteins among the two viruses. We demonstrate that all combinations including one or more heterologous proteins were capable of replicating both the NiV and HeV minigenomes. Sequence alignment showed identities of 92% for the N protein, 67% for P, and 87% for L. Notably, variations in amino acid residues were not concentrated in the N-P and P-L interacting regions implying that dissimilarities in amino acid composition among NiV and HeV polymerase complex proteins may not impact their interactions. The observed indiscriminate activity of NiV and HeV polymerase complex proteins is different from related viruses, which can support the replication of heterologous genomes only when the whole polymerase complex belongs to the same virus. This newly observed promiscuous property of the henipavirus polymerase complex proteins likely attributed to their conserved interaction regions could potentially be harnessed to develop universal anti-henipavirus antivirals.IMPORTANCEGiven the severity of disease induced by Hendra and Nipah viruses in humans and the continuous emergence of new henipaviruses as well as henipa-like viruses, it is necessary to conduct a more comprehensive investigation of the biology of henipaviruses and their interaction with the host. The replication of henipaviruses and the development of antiviral agents can be studied in systems that allow experiments to be performed under biosafety level 2 conditions. Here, we developed robust minigenome systems for the Nipah virus (NiV) and Hendra virus (HeV) that provide a convenient alternative for studying NiV and HeV replication. Using these systems, we demonstrate that any combination of the three polymerase complex proteins of NiV and HeV could effectively initiate the replication of both viral minigenomes, which suggests that the interaction regions of the polymerase complex proteins could be effective targets for universal and effective anti-henipavirus interventions.

Ameliorative delivery of docetaxel and curcumin using PEG decorated lipomers: A cutting-edge in-vitro/ in-vivo appraisal

The development of a PEG-decorated lipid-polymer hybrid system camouflaged with natural and synthetic chemotherapeutic moieties is an influential approach melding the biomimetic properties of long-circulating vesicles to utilize different mechanisms to dwindle the tumor growth. Therefore, a safe and efficient lipid-coated nano-particulate system (LCNPs) was proposed to investigate the in-vitro, ex-vivo and in-vivo demeanors of such amalgamation.Docetaxel loaded PLGA nanoparticles (DTX-NPs) were prepared by solvent evaporation while curcumin liposomes were mapped out using the film hydration method. Physicochemical characterizations were executed in terms of size, surface morphology, differential scanning calorimetry (DSC) and fourier-transform infrared spectroscopy (FTIR). In-vitro cytotoxicity was effectuated using MCF-7 cell line. Hemolysis, erythrocyte aggregation and acute in-vivo toxicity were carried out to establish the biocompatibility. The hydrodynamic diameters of samples were in the nano-range and corresponded to the findings of scanning electron microscopy (SEM) and atomic force microscopy (AFM). The absence of distinctive peaks of DTX-NPs in FTIR and DSC analysis of LCNPs depicts the shielding of the lipid bilayer over the nanoparticle. Cytotoxicity induced by the LCNPs represented the efficient delivery of cargo to the tumor cells. LCNPs also exhibited the least toxicity under ex-vivo and in-vivo circumstances compared to free drugs. Additionally, histological studies showed no evidence of substantial necrosis. Additionally, histological studies showed no evidence of notable necrosis.

A novel functionalized CuTi hybrid nanocomposites: facile one-pot mycosynthesis, characterization, antimicrobial, antibiofilm, antifouling and wastewater disinfection performance

BackgroundThe continuous progress in nanotechnology is rapid and extensive with overwhelming futuristic aspects. Through modernizing inventive synthesis protocols, a paradigm leapfrogging in novelties and findings are channeled toward fostering human health and sustaining the surrounding environment. Owing to the overpricing and jeopardy of physicochemical synthesizing approaches, the quest for ecologically adequate schemes is incontestable. By developing environmentally friendly strategies, mycosynthesis of nanocomposites has been alluring.ResultsHerein, a novel architecture of binary CuO and TiO2 in nanocomposites form was fabricated using bionanofactory Candida sp., for the first time. For accentuating the structural properties of CuTi nanocomposites (CuTiNCs), various characterization techniques were employed. UV-Vis spectroscopy detected SPR at 350 nm, and XRD ascertained the crystalline nature of a hybrid system. However, absorption peaks at 8, 4.5, and 0.5 keV confirmed the presence of Cu, Ti and oxygen, respectively, in an undefined assemblage of polygonal-spheres of 15–75 nm aggregated in the fungal matrix of biomolecules as revealed by EDX, SEM and TEM. However, FTIR, ζ-potential and TGA reflected long-term stability (− 27.7 mV) of self-functionalized CuTiNCs. Interestingly, a considerable and significant biocide performance was detected at 50 µg/mL of CuTiNCs against some human and plant pathogens, compared to monometallic counterparts. Further, CuTiNCs (200 µg/mL) ceased significantly the development of Staphylococcus aureus, Pseudomonas aeruginosa and Candida albicans biofilms by 80.3 ± 1.4, 68.7 ± 3.0 and 55.7 ± 3.0%, respectively. Whereas, 64.63 ± 3.5 and 89.82 ± 4.3% antimicrofouling potentiality was recorded for 100 and 200 µg/ml of CuTiNCs, respectively; highlighting their destructive effect against marine microfoulers cells and decaying of their extracellular polymeric skeleton as visualized by SEM. Moreover, CuTiNCs (100 and 200 µg/ml) exerted significantly outstanding disinfection potency within 2 h by reducing the microbial load (i.e., total plate count, mold & yeast, total coliforms and faecal Streptococcus) in domestic and agricultural effluents reached >50%.ConclusionThe synergistic efficiency provided by CuNPs and TiNPs in mycofunctionalized CuTiNCs boosted its recruitment as antiphytopathogenic, antibiofilm, antimicrofouling and disinfectant agent in various realms.