Hybrid System Research Articles

Andreev reflection in topological nodal-line semimetals superconductor junction

Abstract Andreev reflection is an important quantum tunneling phenomenon in the conductor-superconductor junction. The Andreev reflection coefficients TAR of a hybrid system with s-wave superconductor connected by topological nodal-line semimetals (TNLSMs-SC junction system) is calculated theoretically by using the Landauer-Büttiker formula combined with the nonequilibrium Green’s function method. The results show that when the direction of the boundary state electron and the incident electron are the same, only the bulk states of the TNLSMs involve the Andreev reflection of the hybrid system, and the Andreev reflection coefficients TAR enhance with the increase of the Fermi energy EF . We also study the effect of on-site energy µz and mass term m on the Andreev reflection and find that the Andreev reflection in the system decreases rapidly with the increase of on-site energy µz and mass term m. Moreover, we find that only in the presence of a mass term m, the Andreev reflection coefficients TAR of the system changes with the rise of the Fermi energy EF . When a perpendicular magnetic field is applied in the system, the Andreev reflection coefficients TARin the superconducting gap will appear a series of oscillating peaks. For a hybrid system with the large perpendicular magnetic field applied, we find that the maximum Andreev reflection coefficients TAR=7.2 at the Fermi energy EF = 0.0 and the incident electron energy E = ±0.1. The Andreev reflection coefficients TAR is gradually enhanced in the superconducting gap (incident energy |E| ≤ 0.2) when a disorder is applied to the superconductor region of the system. However, the symmetry of the Andreev reflection coefficients TARis broken when the perpendicular magnetic field is applied to the system. These peculiar transport properties of the TNLSMs-SC junction system are expected to provide theoretical guidance for future applications.

Zeolite‐Based Materials for Catalytic Oxidation of Volatile Organic Compounds

AbstractOwing to the structural stability, modifiable acidity, and abundant pores/channels, zeolite‐based materials can act as catalysts or supports for effective conversion of volatile organic compounds (VOCs). In this review, a series of VOC oxidation processes catalyzed by zeolite‐based materials will be introduced, which include thermal oxidation, photocatalytic degradation, plasma‐driven removal, catalytic ozonation, microwave‐assisted degradation, and hybrid systems, where the specific roles, modification strategies, and structure–performance relationships of zeolites are discussed in depth. The following topics will also be covered, including the catalytic mechanisms of VOC oxidation, types of zeolite‐based materials in VOC catalytic oxidation, operation parameters in the processes, and reactor designs for efficiency optimization and cost control.

Development of optimal energy management strategy for proton exchange membrane fuel cell-battery hybrid system for drone propulsion

Drones powered by fuel cells have been developed to ensure long flight distances. Due to the low dynamic responsiveness of proton exchange membrane fuel cell (PEMFC) systems, they must be integrated with batteries to fully meet the power demand profiles of drones. In this study, a dynamic model of a PEMFC-battery hybrid system for drone propulsion is developed in MATLAB-Simulink® to establish the optimal energy management strategy (EMS) for ensuring efficient and safe operation. The proposed PEMFC system comprises two modules of an open-cathode PEMFC stack, which are connected in parallel. To estimate the dynamic behavior and performance of PEMFC, one-dimensional dynamic model of PEMFC considering two-phase transport through the gas diffusion layer is developed and simulated. A zero-dimensional dynamic model of the battery was also developed based on an equivalent circuit model. The resulting PEMFC-battery hybrid system model was simulated to determine the power required for the propulsion of the drone according to a flight scenario comprising five phases: takeoff hover, climb, cruise, descent, and landing hover. Three different EMSs are developed and simulated to define the optimal one for the PEMFC-battery hybrid system by comparing the total hydrogen consumption and the final SOC of the battery As a result, the EMS that equally splits the required power between two PEMFCs exhibits the lowest hydrogen consumption during the flight simulation. This study helps provide the optimal system design and control scheme of drones powered by fuel cells.

Experiment and dynamic simulation of micro gas turbine combined with concentrated solar power system

The solar micro gas turbine (SMGT) system is a promising solution to address the instability and intermittency of renewable energy sources. Its dynamic characteristics under unstable input conditions and uncertain output load demands are crucial for peak shaving. This paper constructs an SMGT system based on experiments with micro gas turbine (MGT) and concentrated solar power (CSP), analyzing the impact of integrating CSP system on the MGT. Then the performance of the SMGT under varying ambient conditions and load demands is studied. Results show that in grid-connected mode, the turbine speed of MGT and SMGT is determined by ambient temperature and set power, with electrical efficiency decreasing as temperature and DNI increase. The solar receiver in the SMGT should maximize temperature increase while maintaining pressure loss below 55 kPa. Additionally, a higher heat capacity can reduce sensitivity to ambient changes but also extends stabilization time. Under real solar radiation, the SMGT system can keep constant power within 0.6% fluctuation, with a solar share of 36.5%. When combined with photovoltaic, the hybrid system’s maximum power fluctuation does not exceed 2.6%, with a solar share of 48.8%. This study provides guidance for optimizing SMGT systems and their application in peak shaving scenarios.

Enhanced tetracycline degradation using UV/Fenton/titanium dioxide (TiO2) hybrid process

TiO2 was synthesized using neem leaf extract as soft bio template and Titanium (IV) isopropoxide (C12H28O4Ti) as a precursor. Morphological properties revealed well crystalline anatase phase of 19.8 nm size for the biotemplated TiO2 (B-TiO2) compared to 24.2 nm of the non-templated TiO2 (N-TiO2). TEM revealed a nano sheet-like structure for the B-TiO2 and it exhibited a larger SBET surface area (35.45 m2/g) and average pore diameter (5.74 nm) compared to the N-TiO2 (19.72 m2/g) and (2.028 nm) respectively. XPS results showed carbon peaks indicating small bio-carbon doping on the lattice of the TiO2, which can promote charge transfer upon light excitation during photocatalyst reactions. The results of the photoluminescence study indicate reduced PL intensity of the B-TiO2 which signifies the suppression of recombination of charge carriers or electron-hole pairs in the B-TiO2. The photocatalytic activity was assessed by the photodegradation of tetracycline (TC: 50 mg/L) under UV irradiation and the B-TiO2 was employed as a photocatalyst. In the absence of UV light, B-TiO2 catalyst slightly removed TC due to limited active species. However, the degradation of TC increases significantly due to the synergetic effect of the UV/Fenton/B-TiO2 hybrid system. Moreover, the biotemplate exposes the surface of the B-TiO2 which permits improved utilization of all surface-active sites. Quenching experiments were also performed via scavengers, results confirmed that hydroxyl radicals, superoxide radicals and electrons are the key reactive species in the TC degradation. The effects of influential parameters such as B-TiO2 dosage, TC concentration, pH, and Fe2+ to H2O2 molar ratio were also investigated, in addition, the catalyst is stable, as it achieved > 80 % TC degradation efficiency after five reuse cycles.

Fresh water production via atmospheric water harvesting using solar energy for green hydrogen production

Abstract Solar energy is used to drive an atmospheric water harvesting unit to produce fresh water needed for the electrolysis process to produce hydrogen, as well as to drive the electrolyzer. So, the system can be considered as a solar powered hybrid system for fresh water harvesting and green hydrogen production implementing the electrolysis concept. Implementation of the system specially in arid regions with high levels of water scarcity and high relative humidity levels helps in achieving SDGs 3, 7, 9, and 13 progressively, improving health and wellbeing, reducing water scarcity, using clean renewable energy, and limiting climate change. The system is proposed and investigated for the production of both fresh and clean water and green hydrogen gas. To improve the productivity of the overall system, performance enhancement of the atmospheric water harvesting subsystem is experimentally investigated to assure the reliability and continuous operation of the overall green hydrogen hybrid system. It was investigated in summer and winter using different number of porous sheet metals with the silica gel bed. The results show that the productivity of the atmospheric water harvesting system can be increased by a minimum of 6% with one mesh metal sheet and 30% with two meshes, and increases by a maxinmum of 60% with one mech and 260% with two meches.

Thermodynamic investigation of the efficiency of ammonia-powered marine solid oxide fuel cells with gas turbine

Improvement of marine power plants includes increasing their efficiency and drastically reducing emissions of pollutants, which involves transitioning to carbon-free fuels. This article discusses the evolution of a marine power system designed for decarbonization, utilizing ammonia and comprising solid oxide fuel cells with a gas turbine. To enhance efficiency, the system incorporates a steam supply into the fuel burning device of a gas turbine. By adding superheated steam, the system's performance improves significantly. Thermodynamic calculations identified optimal parameters for the gas turbine, which enhances efficiency by utilizing off-gases from the fuel cells. Key parameters include compressor and exhauster pressure ratios, which can be used to increase the specific power. A combined energy system with an overexpansion turbine achieves a total efficiency of 60.62 % at a fuel cell temperature of 1190 K during operation, with the SOFC efficiency being 43.76 %. These findings highlight potential improvements for marine power systems using ammonia and provide insights into the energy conversion processes within such hybrid systems.

Framework for strategic deployment of hybrid offshore solar and wind power plants: A case study of India

Renewable energy sources are gaining prominence as eco-friendly and sustainable alternatives to fossil fuels due to their availability and minimal greenhouse gas emissions. Nonetheless, the critical challenge is the availability of renewable resources, which fluctuates with changes in climatic conditions. This limitation poses a consistent challenge to generating base load power if it relies solely on a single type of renewable resource. Addressing this, integrating multiple renewable sources into hybrid systems has emerged as a viable solution. This study presents a framework, integrating Geographic Information Systems (GIS) and Hybrid Multi-Criteria Decision Making (MCDM) techniques to identify plausible locations for the deployment of Hybrid Offshore Solar and Wind Power Plants (HOSWPP) and the developed framework is demonstrated considering Indian Exclusive Economic Zone (EEZ) as a study area. Using the proposed approach, Indian EEZ region is classified into five suitability classes. The effectiveness of regions within each class is further assessed in terms of complementarity measured using Kendall's coefficient. Findings suggested that Kendall's coefficient for highly suitable class is −0.41 indicating the regions identified in this study are the prime locations for installing HOSWPP. A total of twenty optimal sites for HOSWPP deployment, predominantly in the offshore regions of Tamil Nadu and Gujarat. Eighteen sites are located along Kanyakumari to Thisayanvilai in Tamil Nadu, including areas in the Gulf of Mannar and near Valinokkam are found plausible. The rest of the two sites are in the offshore regions of Gujarat. This study provides a strategic roadmap to increase the renewable footprint, contributing to the global transition towards cleaner energy sources.

Dandelion Optimizer-Based Frequency Controller for a Hybrid power systems Considering Renewables

Dandelion Optimizer-Based Frequency Controller for a Hybrid power systems Considering Renewables

Electrocoagulation-Electro-Fenton hybrid system for dairy wastewater treatment: A comprehensive test and analysis, in aqueous solution

This study aimed to assess the efficacy of a treatment system combining electrocoagulation (EC) and Electro-Fenton (EF) for the remediation of the wastewater dairy industry. Synthetic samples simulating dairy effluent were prepared and subjected to characterization for turbidity, chemistry oxygen demand (COD), and pH. The Box-Behnken design, comprising operating parameters such as electric current (0.5 to 1.5 A), electrolysis time (5 to 17.5 min), initial pH (4.0 to 9.0), and hydrogen peroxide concentration (0 to 9.0 g/L), with three replications at the central point. The combined treatment was conducted in a batch reactor using iron electrodes and subsequently filtered using a qualitative filter paper. Analysis revealed the significance of electric current, electrolysis time, and peroxide concentration at a 5 % probability level for COD reduction. A reduction of 80 % in chemical oxygen demand (COD) and a 99 % reduction in turbidity were achieved by maintaining the original pH of the wastewater and using a combination of an electric current greater than 1 A and an electrolysis time of 11.5 min, without the addition of hydrogen peroxide. The results showed that the treatment followed the standards of the Brazilian legislation.

Modeling tumor-immune interactions using hybrid spheroids and microfluidic platforms for studying tumor-associated macrophage polarization in melanoma

Tumor-associated macrophages (TAMs), as key components of tumor microenvironment (TME), exhibit phenotypic plasticity in response to environmental cues, causing polarization into either pro-inflammatory M1 phenotypes or immunosuppressive M2 phenotypes. Although TAM has been widely studied for its crucial involvement in the initiation, progression, metastasis, and immune regulation of cancer cells, there have been limited attempts to understand how the metastatic potentials of cancer cells influence TAM polarization within TME. Here, we developed a miniaturized TME model using a 3D hybrid system composed of murine melanoma cells and macrophages, aiming to investigate interactions between cancer cells exhibiting various metastatic potentials and macrophages within TME. The increase in spheroid size within this model was associated with a reduction in cancer cell viability. Examining macrophage surface marker expression and cytokine secretion indicated the development of diverse TMEs influenced by both spheroid size and the metastatic potential of cancer cells. Furthermore, a high-throughput microfluidic platform equipped with trapping systems and hybrid spheroids was employed to simulate the tumor-immune system of complex TMEs and for comparative analysis with traditional 3D culture models. This study provides insight into TAM polarization in melanoma with different heterogeneities by modeling cancer-immune systems, which can be potentially employed for immune-oncology research, drug screening, and personalized therapy. Statement of significanceThis study presents the development of a 3D hybrid spheroid system designed to model tumor-immune interactions, providing a detailed analysis of how melanoma cell metastatic potential influences tumor-associated macrophage (TAM) polarization. By utilizing a microfluidic platform, we are able to replicate and investigate the complex tumor-immune system of the tumor microenvironments (TMEs) under continuous flow conditions. Our model holds significant potential for high-throughput drug screening and personalized medicine applications, offering a versatile tool for advancing cancer research and treatment strategies.

Magnetron sputtering preparation of flexible ZnO/AlN thin-films sensors with hybrid piezoelectric effect for broad-range human motions detection

Wearable sensors with excellent comfort, flexibility and fast response are widely applied in human-machine interactions, artificial skin, motion detection and healthcare monitoring. However, preparation processes of the most of current piezoelectric sensors are relatively expensive and complicate, limiting their mass productions in the applications. This work demonstrates the superior piezoelectric performance and stability of ZnO/AlN flexible thin films prepared by magnetron sputtering for broad-range human motions detection, and first-principles calculation are applied to reveal the complicate piezoelectric effect of the hybrid system. The ZnO/AlN hybrid thin films sensor exhibits superior piezoelectric performance and excellent reliability, with presenting high outputs voltage (3.63 V), high degree of response speed (42.33 ms), water stability and robust performance upon 10000 cycles. First-principles calculations reveal that formation of the ZnO/AlN interface facilitates charge transport and improves efficiency of carrier transport, and results in reduced in band gap and enhanced electrical conductivity. By applying the sensors in human health monitoring, the underlying behaviors can be determined by output voltage of the sensor in real-time. This work offers a sensitive, simple structured and robust solution for human motion detection.

Non-exchange bias hysteresis loop shifts in dense composites of soft-hard magnetic nanoparticles: New possibilities for simple reference layers in magnetic devices

Exchange bias has been extensively studied in both exchange-coupled thin films and nanoparticle composite systems. However, the role of non-exchange mechanisms in the overall hysteresis loop bias is far from being understood. Here, dense soft-hard binary nanoparticle composites are used not only as a novel tool to unravel the effect of dipolar interactions on the hysteresis loop shift but also as a new strategy to enhance the bias of any magnet exhibiting an asymmetric magnetization reversal. Mixtures of equally sized, 6.8 nm, soft maghemite (γ-Fe2O3) nanoparticles (no bias—symmetric reversal) and hard cobalt doped γ-Fe2O3 nanoparticles (large exchange bias—asymmetric reversal) reveal that, for certain fractions of soft particles, the loop shift of the composite can be significantly larger than the exchange-bias field of the hard particles in the mixture. Simple calculations indicate how this emerging phenomenon can be further enhanced by optimizing the parameters of the hard particles (coercivity and loop asymmetry). In addition, the existence of a dipolar-induced loop shift (“dipolar bias”) is demonstrated both experimentally and theoretically, where, for example, a bias is induced in the initially unbiased γ-Fe2O3 nanoparticles due to the dipolar interaction with the exchange-biased hard nanoparticles. These results open a new paradigm in the large field of hysteresis bias and pave the way for novel approaches to tune loop shifts in magnetic hybrid systems beyond interface exchange coupling.

Study of the Influence of the Relative Rigidity of an Elastic Hybrid System Without Damping, on Natural Self-Pulsation, Amplitude and Dynamic Factor Due to Forced Vibration

Abstract The paper aims to study the dynamic behavior of a hybrid elastic system without damping consisting of a beam in a cantilever supported on helical compression springs on which an electric motor is mounted. With the help of the MATHCAD professional program, the influence of the relative stiffness of the elastic bar subjected to bending and the springs subjected to compression was simulated, on the natural pulsation, the amplitude of the vibrations and the dynamic factor of the forced vibrations for two assembly variants of the electric motor

Analytical computation of conditional moments in the extended Cox–Ingersoll–Ross process with regime switching: Hybrid PDE system solutions with financial applications

In this paper, we introduce a novel analytical approach for the computation of the nth conditional moments of an m-state regime-switching extended Cox–Ingersoll–Ross process driven by a continuous-time finite-state irreducible Markov chain. This approach is applicable for all integers n≥1 and m≥1, thereby ensuring wide-ranging utility. The key of our investigation is a complex hybrid system of inter-connected PDEs, derived through a utilization of the Feynman–Kac formula for regime-switching diffusion processes. Our exploration into the solutions of this hybrid PDE system culminates in the derivation of exact closed-form formulas for the conditional moments for diverse values of n and m. Additionally, we study the asymptotic characteristics of the first conditional moments for the 2-state regime-switching Cox–Ingersoll–Ross process, particularly focusing on the effects of the symmetry inherent in the Markov chain’s intensity matrix and the implications of various parameter configurations. Highlighting the practicality of our methodology, we conduct Monte Carlo simulations to not only corroborate the accuracy and computational efficacy of our proposed approach but also to demonstrate its applicability to real-world applications in financial markets. A principal application highlighted in our study is the valuation of VIX futures and VIX options within a dynamic, mean-reverting, hybrid regime-switching framework. This exemplifies the potential of our analytical method to significantly impact contemporary financial modeling and derivative pricing.

Dynamic Double Event-Triggered Anti-Disturbance Tracking Control for a 2-DOF Small Unmanned Helicopter.

This article devises a new dynamic double event-triggered anti-disturbance tracking control scheme for a 2-degree of freedom (DOF) laboratory helicopter subject to external time-varying disturbances and load fluctuation by using the generalized proportional-integral observer technique. The helicopter system is separated into two subsystems in the proposed control method, i.e., the pitch subsystem and the yaw subsystem. Each subsystem includes a discrete-time dynamic double event-triggering mechanism (DDETM), and the control laws of the two subsystems are independent of each other. There are two triggering conditions in the designed double triggering mechanism: one is designed based on the system states and the other is based on the lumped disturbance estimation. These two triggering conditions form a competitive relationship such that the controller updates the control signal as long as one of the triggering conditions is satisfied. Theoretical analysis is provided for achieving the better communication and control performance of the proposed DDETM-based robust control method. Through rigorous stability analysis, it is proved that the closed-loop hybrid system is globally ultimately bounded. At last, numerical simulations show that the suggested control strategy not only reduces the event-triggering number, but also improves the initial dynamic performance of the system.

Optimizing hybrid renewable energy based automated railway level crossing in Bangladesh: Techno-economic, emission and sensitivity analysis

The railway system in Bangladesh, particularly the level crossing system, needs significant advancements, including a shift towards using renewable energy to power these crossings. As a solution, this study proposes optimal hybrid systems powered by renewable energy on an automated railway level crossing system, which is reliable, efficient, and sustainable. The main contribution of this study is to introduce an optimal hybrid renewable energy-based automated railway level crossing system in Bangladesh, focusing on technical and economic evaluation, emissions, and sensitivity assessment using HOMER Pro. The proposed system examines the optimal outcome for a 1 kW vertical-axis wind turbine and a 0.440 kW photovoltaic system at five selected locations. The results reveal satisfactory net present cost values amounting to USD 8495, USD 8505, USD 8564, USD 8262, and USD 8357 for Narayanganj, Cox’s Bazaar, Noakhali, Dinajpur, and Rajshahi respectively. Moreover, HOMER Pro indicates that the photovoltaic-wind turbine–grid-connected model offers a lower Cost of Energy which is around 0.03 USD/kWh compared to other configurations. The Internal Rate of Return for the selected locations are 20 %, 33.7 %, 31.5 %, 5.2 %, and 4.6 % for Narayanganj, Cox’s Bazaar, Noakhali, Dinajpur, and Rajshahi, respectively. The developed structure is projected to have a payback period ranging from 4.57 to 13.29 years across the five selected locations. Furthermore, the proposed systems reduce greenhouse gas emissions by up to 44.23 % compared to a grid-only system. Additionally, sensitivity analysis is performed by varying wind speed and solar irradiation to emphasize the robustness of the proposed systems.

Development of a novel energy efficient integrated system for concurrent waste water treatment, hydrogen production and carbon capture- A sustainable approach

Microbial Electrochemical Cells (MECs) technology offer a promising, integrated solution for wastewater treatment and hydrogen production. The present research aims to optimize the operation of a hybrid system for achieving high-efficiency wastewater treatment, carbon capture, and hydrogen production. Multi-criteria decision methods are used to identify optimal conditions for maximum performance. Wastewater Flow Rate (WFR), Energy Consumption (EC), Nanocomposites Concentration (NC), and Temperature (T) are chosen as input parameters. Utilizing the Entropy-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method, the optimal outputs were determined for specific input settings. The proposed system exhibited optimal input settings at 1100 m³/day (WFR), 95 kW (EC), 34 mg/L (NC), and 36 °C (T). NC emerged as the most influential parameter, holding a significance weightage of 32%, followed closely by temperature. Under these optimized conditions, the system demonstrated exceptional performance, achieving a Wastewater Treatment Efficiency of 98.1%, Carbon Capture Efficiency of 97%, and a Hydrogen production flow rate of 17.76 m³/hr. This research lays a foundation for sustainable and versatile wastewater management practices, emphasizing the potential of MEC systems in contributing to cleaner and resource-efficient industrial ecosystems.

A hybrid renewable energy system for Hassi Messaoud region of Algeria: modeling and optimal sizing

The growing global energy demand and the need to mitigate greenhouse gas emissions have driven the exploration of sustainable and efficient energy solutions. In Algeria, where the energy sector relies heavily on fossil fuels, integrating renewable energy systems is essential for enhancing energy security and reducing environmental impacts. This study focuses on optimizing a hybrid renewable energy system (HRES) for off-grid applications in the Hassi Messaoud region of Algeria to balance technical performance, economic viability, and environmental sustainability.A hybrid system consisting of photovoltaic (PV) panels, wind turbines (WT), fuel cells (FC), and diesel generators (DG) was modeled and optimized using a genetic algorithm (GA). The optimization process aims to minimize the annual cost of the system while ensuring high reliability, as measured by the loss of power supply probability (LPSP), and maximizing the use of renewable energy. A particle swarm optimization (PSO) approach was also implemented for comparison, highlighting the advantages of the GA in terms of cost distribution and system reliability. The optimized HRES demonstrated that renewable sources (PV and WT) provided 77% of the total energy demand, with an overall system cost of 0.18080$×kWh−1, significantly lower than recent studies, which reported costs between $0.213 and 0.609$×kWh−1. FCs contributed 14% to the load, whereas DGs were limited to 8% to minimize emissions, resulting in annual CO2 emissions of 10,865 kg and a relative emission rate of 3.608 gCO2eq×kWh−1. Economic analysis showed that DGs and FCs accounted for 44% and 24% of the annual cost, respectively, highlighting the impact of backup systems in ensuring reliability.Sensitivity analysis under varying load demands and renewable energy availability confirmed the robustness of the system, and the GA approach was found to be more effective than PSO in maintaining cost efficiency and reliability. Additionally, the social analysis highlighted a renewable fraction (RF) of 91.5%, emphasizing the contribution of the system to sustainable energy practices. These findings validate GA-based optimization as a superior method for designing cost-effective, reliable, and environmentally sustainable HRES, offering significant potential to reduce fossil fuel dependency in industrial applications. These results not only support the broader adoption of renewable energy systems in similar regions but also contribute valuable insights for future research and policy development in the field of energy sustainability.

Evaluating integration methods of a quantum random number generator in OpenSSL for TLS

The rapid advancement of quantum computing poses a significant threat to conventional cryptography. Whilst post-quantum cryptography (PQC) stands as the prevailing trend for fortifying the security of cryptographic systems, the coexistence of quantum and classical computing paradigms presents an opportunity to leverage the strengths of both technologies, for instance, nowadays the use of Quantum Random Number Generators (QRNGs)–considered as True Random Number Generators (TRNGs)–opens up the possibility of discussing hybrid systems. In this paper, we evaluate both aspects, on the one hand, we use hybrid TLS (Transport Layer Security) protocol that leverages the widely used secure protocol on the Internet and integrates PQC algorithms, and, on the other hand, we evaluate two approaches to integrate a QRNG, i.e., Quantis PCIe-240M, in OpenSSL 3.0 to be used by TLS. Both approaches are compared through a Nginx Web server, that uses OpenSSL’s implementation of TLS 1.3 for secure web communication. Our findings highlight the importance of optimizing such integration method, because while direct integration can lead to performance penalties specific to the method and hardware used, alternative methods demonstrate the potential for efficient QRNG deployment in cryptographic systems.