Hybrid Applications Research Articles

ENHANCED AUTHORIZATION FOR SECURE MANAGEMENT OF SENSITIVE DATA IN HYBRID APPLICATIONS

Sensitive data is often managed by cloud-based applications, which can be vulnerable to attackers who seek unauthorized access to this data. Traditional approaches to authorization may not be sufficient to protect sensitive data from such attacks. In this article, we propose an enhanced authorization approach that uses a combination of symmetric and asymmetric cryptography to secure sensitive data. Specifically, we propose generating a unique encryption key per file and a set of public and private keys per user, which are used to encrypt and decrypt the data. We demonstrate the feasibility of our approach with examples in Node.js, showing how to generate public and private keys, encrypt and decrypt files, and store encrypted data on a drive. Our approach provides an effective solution to the problem of managing sensitive data in hybrid applications, while preserving user and developer convenience.

Design and Application of Hybrid Personalized Effective Teaching Strategy based on Learning Style Classification

With the continuous advancement of information technology in vocational education, personalized learning teaching models are deeply integrated with mobile teaching platforms. The online and offline blended teaching model has become a new perspective for higher education teaching reform. However, blended teaching has not yet achieved the expected teaching results in practical applications. How to further improve the effectiveness of blended teaching has become a problem to be solved. After analyzing the necessity of integrating learning styles into effective blended personalized teaching, this article draws on the Felder-Silverman learning style model to guide blended personalized teaching strategies. From four aspects: learning content organization, learning tool support, learning resource organization, and learning evaluation organization, teaching support strategies are designed for different types of learning styles, Finally, taking the task of calculating internal rate of return of investment management project in the course of financial management as an example, this paper introduces the specific application of this teaching strategy in hybrid teaching.

Quantification of snake venom proteomes by mass spectrometry-considerations and perspectives.

The advent of soft ionization mass spectrometry-based proteomics in the 1990s led to the development of a new dimension in biology that conceptually allows for the integral analysis of whole proteomes. This transition from a reductionist to a global-integrative approach is conditioned to the capability of proteomic platforms to generate and analyze complete qualitative and quantitative proteomics data. Paradoxically, the underlying analytical technique, molecular mass spectrometry, is inherently nonquantitative. The turn of the century witnessed the development of analytical strategies to endow proteomics with the ability to quantify proteomes of model organisms in the sense of "an organism for which comprehensive molecular (genomic and/or transcriptomic) resources are available." This essay presents an overview of the strategies and the lights and shadows of the most popular quantification methods highlighting the common misuse of label-free approaches developed for model species' when applied to quantify the individual components of proteomes of nonmodel species (In this essay we use the term "non-model" organisms for species lacking comprehensive molecular (genomic and/or transcriptomic) resources, a circumstance that, as we detail in this review-essay, conditions the quantification of their proteomes.). We also point out the opportunity of combining elemental and molecular mass spectrometry systems into a hybrid instrumental configuration for the parallel identification and absolute quantification of venom proteomes. The successful application of this novel mass spectrometry configuration in snake venomics represents a proof-of-concept for a broader and more routine application of hybrid elemental/molecular mass spectrometry setups in other areas of the proteomics field, such as phosphoproteomics, metallomics, and in general in any biological process where a heteroatom (i.e., any atom other than C, H, O, N) forms integral part of its mechanism.

Prospects for Combined Applications of Nanostructured Catalysts and Biocatalysts for Elimination of Hydrocarbon Pollutants

Due to the presence of environmental problems, it is urgent to improve the processes aimed at the processing and purification of hydrocarbon-containing wastes and wastewaters. The review presents the latest achievements in the development of nanostructured catalysts made from different materials that can be used to purify oil-polluted wastewaters (petroleum refinery wastewater, oilfield-produced water, sulfur-containing extracts from pre-oxidized crude oil and oil fractions, etc.) and eliminate components of hydrocarbon pollutants (polyaromatic hydrocarbons, phenols, etc.). The results of the analysis of possible combinations of chemical and biological catalysts for deeper and more effective solutions to the problems are discussed. The possibilities of highly efficient elimination of hydrocarbon pollutants as a result of the hybrid application of nanoparticles (graphene oxide, mesoporous silica, magnetic nanocatalysts, etc.) or catalytic nanocomposites for advanced oxidation processes and biocatalysts (enzymes, cells of bacteria, mycelial fungi, phototrophic microorganisms and natural or artificial microbial consortia) are analyzed.

Decomposition and characterization of bio-oil from coconut shell waste for bio-coke hybrid application as alternative energy resources

Bioenergy sources continue to be developed to solve environmental problems due to agricultural biomass waste and alternative energy sources. Bioenergy from biomass raw materials through the pyrolysis method is a thermochemical conversion technology that produces bio-oil and bio-char. The conversion process of coconut shell (CS) biomass with a size of 60 mesh at a temperature of 500-700°C without adding a catalyst. The results showed that the optimum decomposition process occurred at a temperature of 700°C. Based on the GC-MS analysis of bio-oil from CS, the compound consisting of 58.18% phenol, 18.86% 2.6 dimethoxy-phenol, 1.35% 1-(acetyloxy)-2-propanone, 6.57% 3,5-dimethoxy-4-hydroxytoluene and 2.55% 4-ethyl-2,6-methoxy-phenol was obtained. While the SEM-EDS characterization of bio-char contains the main constituent elements, including 94.37% carbon and minor elements consisting of 5.50% oxygen, 0.09% sodium and 0.05% chlorine. Comprehensive analysis shows that pyrolysis is an efficient and sustainable method for converting CS biomass into material for hybrid bio-coke applications as an alternative renewable energy source.

Solar-Powered Interfacial Evaporation and Deicing Based on a 3D-Printed Multiscale Hierarchical Design.

Solar-powered interfacial heating has emerged as a sustainable technology for hybrid applications with minimal carbon footprints. Aerogels, hydrogels, and sponges/foams are the main building blocks for state-of-the-art photothermal materials. However, these conventional three-dimensional (3D) structures and related fabrication technologies intrinsically fail to maximize important performance-enhancing strategies and this technology still faces several performance roadblocks. Herein, monolithic, self-standing, and durable aerogel matrices are developed based on composite photothermal inks and ink-extrusion 3D printing, delivering all-in-one interfacial steam generators (SGs). Rapid prototyping of multiscale hierarchical structures synergistically reduce the energy demand for evaporation, expand actual evaporation areas, generate massive environmental energy input, and improve mass flows. Under 1 sun, high water evaporation rates of 3.74kg m-2 h-1 in calm air and 25.3kg m-2 h-1 at a gentle breeze of 2 m s-1 are achieved, ranking among the best-performing solar-powered interfacial SGs. 3D-printed microchannels and hydrophobic modification deliver an icephobic surface of the aerogels, leading to self-propelled and rapid removal of ice droplets. This work shines light on rational fabrication of hierarchical photothermal materials, not merely breaking through the constraints of solar-powered interfacial evaporation and clean water production, but also discovering new functions for photothermal interfacial deicing.

Study on the Fabrication of PEDOT:PSS/Si Hybrid Solar Cells Incorporated with F4TCNQ and VTMO

Poly(3,4-ethylenedioxythiophene) (PEDOT):polystyrenesulfonate (PSS)/Si hybrid heterojunction solar cells (HHSCs) are fabricated by a solution-based synthesis method which combines the advantages of PEDOT:PSS and the superior performance of crystalline silicon. The optimized PEDOT:PSS–2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4TCNQ) hole transport layer (HTL) was used to prepare organosilicon solar cells with a short-circuit current density (Jsc) of 33.33 mA/cm2 and a photoelectric conversion efficiency (η) of 13.23%. The HTL films were found to have increased conductivity by the addition of an electron-accepting dopant (F4TCNQ), obtaining well-defined crystallinity and few defects. In addition, an one-step combination of F4TCNQ with a silane coupling agent (vinyltrimethoxysilane, VTMO) was used to improve the textured device, with a notable efficiency of 14.46% and a Jsc of 33.88 mA/cm2. Our study provides an alternative and easy way to establish organic–inorganic hybrid applications with excellent optoelectronic properties and to gain a deeper understanding of organic semiconductors.

Efficiency comparison of conformal cooling channels produced by additive and subtractive manufacturing in automotive industry plastic injection moulds: a hybrid application

Efficiency comparison of conformal cooling channels produced by additive and subtractive manufacturing in automotive industry plastic injection moulds: a hybrid application

Application of ultrasonication and PEGylation as green extraction technology for yield intensification of diallyl thiosulfinate (allicin)

The numerous advantages of bioactive phytochemicals like Diallyl thiosulfinate (DATS) or allicin on human health have attracted scientific inventions and innovations in the latest years for the application in formulating dietary supplements, food products and medicines. In order to maximize the extraction of the phytodrug DATS from Allium sativum, an indigenous approach was devised that relies on the hybrid application of ultrasonication and self-aggregation property of nonionic polymers. Under the optimal conditions of several process parameters (including solvent to garlic biomass ratio, ultrasonic amplitude, ultrasonic duty cycle, ultrasonication time), optimal efficiency of DATS extraction was achieved (3.67 mg/g of garlic biomass). From the two-way ANOVA analysis, ultrasound amplitude was found most significant parameter. Additionally, this proposed approach was able to enhance ∼2.67 fold yield of DATS with significantly lower electric power consumption than the conventional technique. Moreover, polyethylene glycol based pH responsive self-assembly carrier system was prepared which helped to maintain a 94% concentration of DATS for around 30 days and reduced the concentration loss of DATS because of molecular degradation. This hybrid extraction-stabilization method can be beneficial for the industrial application of DATS extraction because its bioactivity was well preserved as observed from the in vitro antibacterial experiment.

Translating Video Recordings of Complex Mobile App UI Gestures into Replayable Scenarios

Screen recordings of mobile applications are easy to obtain and capture a wealth of information pertinent to software developers (e.g., bugs or feature requests), making them a popular mechanism for crowdsourced app feedback. Thus, these videos are becoming a common artifact that developers must manage. In light of unique mobile development constraints, including swift release cycles and rapidly evolving platforms, automated techniques for analyzing all types of rich software artifacts provide benefit to mobile developers. Unfortunately, automatically analyzing screen recordings presents serious challenges, due to their graphical nature, compared to other types of (textual) artifacts. To address these challenges, this paper introduces <small>V2S+</small> , an automated approach for translating video recordings of Android app usages into replayable scenarios. <small>V2S+</small> is based primarily on computer vision techniques and adapts recent solutions for object detection and image classification to detect and classify user <i>gestures</i> captured in a video, and convert these into a replayable test scenario. Given that <small>V2S+</small> takes a computer vision-based approach, it is applicable to both hybrid and native Android applications. We performed an extensive evaluation of <small>V2S+</small> involving 243 videos depicting 4,028 GUI-based actions collected from users exercising features and reproducing bugs from a collection of over 90 popular native and hybrid Android apps. Our results illustrate that <small>V2S+</small> can accurately replay scenarios from screen recordings, and is capable of reproducing <inline-formula><tex-math notation="LaTeX">$\approx$</tex-math></inline-formula> 90.2% of sequential actions recorded in native application scenarios on physical devices, and <inline-formula><tex-math notation="LaTeX">$\approx$</tex-math></inline-formula> 83% of sequential actions recorded in hybrid application scenarios on emulators, both with low overhead. A case study with three industrial partners illustrates the potential usefulness of <small>V2S+</small> from the viewpoint of developers.

Improving the accuracy of daily solar radiation prediction by climatic data using an efficient hybrid deep learning model: Long short-term memory (LSTM) network coupled with wavelet transform

Accurate daily solar radiation prediction is a crucial task for the management and generation of solar energy as one of the alternatives to fossil fuels. In this study, the prediction accuracy of new machine learning methods, wavelet long short-term memory (WLSTM), wavelet multi-layer perceptron artificial neural network (WMLPANN), long short-term memory (LSTM), multi-layer perceptron artificial neural network (MLPANN), and multivariate adaptive regression splines (MARS), was assessed for modeling daily solar radiation using various input combinations of climatic data of maximum and minimum relative humidity, potential evapotranspiration, maximum and minimum temperature, precipitation and wind speed from two stations, Brownstown and Carbondale located in Illinois, USA. For accurate assessment of prediction accuracy of the proposed models, four reliable statistical metrics, root mean squared error (RMSE), Nash–Sutcliffe efficiency coefficient (NSE), coefficient of determination (R2), and One-Tailed Wilcoxon Signed-Rank Test were employed. Comparison of results, based on the RMSE values, indicated that the WLSTM method performed better than the WMLPANN, LSTM, MLPANN and MARS methods in the estimation of solar radiation values at both stations. The average RMSE values of WMLPANN, LSTM, MLPANN, and MARS approaches was decreased by 6%, 4%, 7.3%, and 13.5% using WLSTM method at Brownstown Station, by 6%, 5.2%, 13.2%, and 14.3% at Carbondale Station, respectively. The overall results during the testing phase of both stations revealed the successful application of hybridization of the LSTM model with the wavelet transform technique for improving the prediction accuracy of solar radiation based on climatic parameters.

Polarization Modulation on Charge Transfer and Band Structures of GaN/MoS2 Polar Heterojunctions

As important third-generation semiconductors, wurtzite III nitrides have strong spontaneous and piezoelectric polarization effects. They can be used to construct multifunctional polar heterojunctions or quantum structures with other emerging two-dimensional (2D) semiconductors. Here, we investigate the polarization effect of GaN on the interfacial charge transfer and electronic properties of GaN/MoS2 polar heterojunctions by first-principles calculations. From the binding energy, the N-polarity GaN/MoS2 heterojunctions show stronger structural stability than the Ga-polarity counterparts. Both the Ga-polarity and N-polarity GaN/MoS2 polar heterojunctions have type-II energy band alignments, but with opposite directions of both the built-in electric field and interfacial charge transfer. In addition, their heterostructure types can be effectively modulated by applying in-plane biaxial strains on GaN/MoS2 polar heterojunctions, which can undergo energy band transitions from type II to type I. As a result, it provides a feasible solution for the structural design and integrated applications of hybrid 3D/2D polar heterojunctions in advanced electronics and optoelectronics.

Adaptation of the Solar Spectrum to Improve the use of Sunlight: A Critical Review on Techniques, Applications, and Current Trends

AbstractPhotovoltaic (PV) cells are one of the most common devices to harvest solar radiation and convert it into usable electrical power. However, normal silicone‐based photovoltaic cells work best within the visible light region. Conventional PV panels can use 15–30% of the total energy received, while the remainder is reflected or converted into waste heat. Not only do other wavelengths have lower conversion efficiencies, but they may also increase the cell surface temperature and decrease its overall efficiency. To solve this problem, spectral beam splitting is a potential approach for converting solar energy efficiently. Even though spectral‐splitting systems have high theoretical conversion efficiencies, they have not yet reached the commercial level. The current study describes the advancements in beam‐splitting systems based on thermal PV cells, multijunction cells, nano‐film, conventional, and nanofluids over the last decade. The mechanisms of various splitting system techniques and several hybrid applications are thoroughly discussed in order to provide a comprehensive understanding of solar energy utilization and the considerations influencing system efficiency. Even though the cost increase can be offset by the increased energy conversion efficiency and controlled wavelengths, the system's stability must be addressed for future practical applications.

Hybrid Combination of Network Restructuring and Optimal Placement of Distributed Generators to Reduce Transmission Loss and Improve Flexibility

A high penetration of renewable energy (RE) in utility grids creates the problems of power system flexibility, high transmission losses, and voltage variations. These problems can be solved using a hybrid combination of transmission network restructuring and optimal placement of distributed energy generator (DEG) units. Hence, this work investigated a technologically and economically feasible solution for improving the flexibility of power networks and reducing losses in a practical transmission utility network by implementing a restructuring of the network and optimal deployment of the distributed energy generators (DEGs). Two solutions for this network restructuring were proposed. Furthermore, a grid-oriented genetic algorithm (GOGA) was designed by combining the conventional genetic algorithm (GA) and mathematical solutions to identify optimal DEG placement. A power system restructuring and GOGA flexibility index (PSRGFI) was formulated for the assessment of network flexibility. A cost–benefit assessment was also performed to estimate the payback period for the investment required for restructuring of the network and DEG placement. The least-square approximation technique was applied for load projection for the year 2031 considering the base year 2021. It was established that minimization of transmission losses, reduction in voltage deviations, and improvement of network flexibility were achieved through hybrid application of network restructuring and DEG placement using GOGA. A network loss saving of 61.19 MW was achieved via optimal restructuring and GOGA. For the projected year 2031, the PSRGFI increased from 30.94 to 132.78 after the placement of DEGs using GOGA and optimal restructuring, indicating that network flexibility increased significantly. The payback period for the investment was very small, equal to 0.985 years. The performance of the designed method was superior to the GA-based method, simulated annealing technique, and bee colony algorithm (BCA) used for placement of DEG units in the test network. The study was completed using MATLAB software, considering data from a practical transmission network owned by Rajasthan Rajya Vidyut Prasaran Nigam Ltd. (RVPN), India.

Performance evaluation of hybrid electrochemical processes in mature leachate treatment

AbstractBACKGROUNDRecently, hybrid treatment applications have gained attention in the treatment of high‐strength wastewater. In this study, the following hybrid applications were applied: electrocoagulation (EC)‐electrooxidation (EO) (EC‐EO), and EO‐EC. The single EC and EO processes were independently optimized and then hybrid EC‐EO and EO‐EC processes were applied under the optimized conditions. Firstly, the most effective electrode pairs were selected in both EC and EO processes concerning pollutant elimination performance and energy needs. Afterward, the optimum values of the system requirements (initial pH, applied current, inter‐electrode distance, and reaction time) of the EC and EO were determined.RESULTSAlAl in the EC process and a Ti/RuO2‐graphite anode–cathode combination in the EO process were the most effective electrodes. Under optimum conditions (EC process: pH 7, applied current 2 A, reaction time 60 min, and inter‐electrode distance 2 cm; EO process: pH 7, applied current 1 A, reaction time 120 min, and inter‐electrode distance 2.5 cm), the chemical oxygen demand (COD) yields for EC and EO processes were 56.6% and 45.6%, respectively. The hybrid EC‐EO and EO‐EC processes yielded 69.6% and 66.4% COD removal, respectively. Specific energy consumption values for the EC, EO, EC‐EO, and EO‐EC were calculated as 14.1, 41.8, 38.9, and 40.7 kWh kg−1 COD, respectively.CONCLUSIONBased on its pollutant removal efficiencies and energy usage values, the hybrid EC‐EO process was found to provide significant advantages in mature leachate treatment. © 2023 Society of Chemical Industry (SCI).

Design Exploration of Transonic Airfoils for Natural and Hybrid Laminar Flow Control Applications

Designing transonic laminar swept wing at high Reynolds numbers is challenging due to the premature flow transition from the prominent crossflow instabilities (CFIs). Hence, natural laminar flow (NLF) wings are limited to lower sweep angles. In this study, hybrid laminar flow control (HLFC) is used to extend this limit to design low-drag transonic infinite wing. A multi-objective genetic algorithm with competing drag components as objectives is used to design NLF and HLFC airfoils. Optimal design is a tradeoff between the drag reduction from skin friction drag, pressure drag, and suction drag, and does not resemble initial airfoils. Airfoil shape and suction distribution are coupled and optimized simultaneously. Euler flow solver with integral boundary-layer method is coupled with a higher-fidelity Linear Stability Analysis using 2.5D approximation for transition prediction. At wing sweep of 22.5°, Mach number of 0.78, and Reynolds number of 30 million, optimum NLF airfoil has 27% lower drag than an optimum turbulent airfoil. The optimum HLFC airfoil showed a 25% lower total drag than the NLF airfoil. A higher optimum sweep angle was observed for low-drag HLFC airfoil (20.5°) in comparison to the NLF airfoil (16.8°) and both favored an undercut on the lower surface to dampen CFI.

Design and Analysis of Gallium Arsenide-Based Nanowire Using Coupled Non-Equilibrium Green Function for RF Hybrid Applications

This research work uses sp3d5s* tight-binding models to design and analyze the structural properties of group IV and III-V oriented, rectangular Silicon (Si) and Gallium Arsenide (GaAs) Nanowires (NWs). The electrical characteristics of the NWs, which are shielded with Lanthanum Oxide (La2O3) material and the orientation with z [001] using the Non-Equilibrium Green Function (NEGF) method, have been analyzed. The electrical characteristics and the parameters for the multi-gate nanowires have been realized. A nanowire comprises a heavily doped n+ donor source and drains doping and n-donor doping at the channel. The specified nanowire has a gate length and channel length of 15 nm each, a source-drain device length LSD = 35 nm, with La2O3 as 1 nm (gate dielectric oxide) each on the top and bottom of the core material (Si/GaAs). The Gate-All-Around (GAA) Si NW is superior with a high (ION/IOFF ratio) of 1.06 × 109, and a low leakage current, or OFF current (IOFF), of 3.84 × 10-14 A. The measured values of the mid-channel conduction band energy (Ec) and charge carrier density (ρ) at VG = VD = 0.5 V are -0.309 eV and 6.24 × 1023 C/cm3, respectively. The nanowires with hydrostatic strain have been determined by electrostatic integrity and increased mobility, making them a leading solution for upcoming technological nodes. The transverse dimensions of the rectangular nanowires with similar energy levels are realized and comparisons between Si and GaAs NWs have been performed.

Improving capacity for phytoremediation of Vetiver grass and Indian mustard in heavy metal (Al and Mn) contaminated water through the application of clay minerals

One of the consequences of mining is the release of heavy metals into the environment, especially water bodies. Phytoremediation of areas contaminated by heavy metals using Vetiver grass and Indian mustard is cost-effective and environmentally friendly. This study aimed at enhancing remediation of heavy metal contaminated water through the simultaneous hybrid application of clay minerals (attapulgite and bentonite) and Vetiver grass or Indian mustard. A 21-day greenhouse experiment was carried out to investigate the effectiveness of the clay minerals to improve heavy metal phytoremediation. The highest accumulation of aluminium (Al) by Vetiver grass was 371.8 mg/kg in the BT2.5VT treatment, while for Mn, the highest accumulation of 34.71 mg/kg was observed in the AT1VT treatment. However, Indian mustard showed no significant uptake of heavy metals, but suffered heavy metal toxicity despite the addition of clay minerals. From this study, it was evident that bentonite added at 2.5% (w/v) could improve the phytoremediation capacity of Vetiver grass for Al and Mn polluted water. The current laboratory-scale findings provided a basis for field trials earmarked for remediation in a post-mining coal environment in South Africa. This remediation approach can also be adopted in other places.

Assessment of mechanical properties of flax fiber reinforced with Delrin polymer composite

In the material industry, composites are sought after as more affordable and environmentally friendly materials, they play a vital role. Fiber-reinforced polymer composites exhibit excellent mechanical and tribological properties. One of the natural fibers that are both lightweight and biodegradable is flax. However, the mechanical qualities of natural fiber lag behind those of synthetic fiber. To enhance the structural or mechanical application of hybridization, it is therefore important to study the mechanical properties of natural fiber. The mechanical characteristics of natural flax fibre composite materials reinforced with Delrin matrix material are the foundation of the current review. In this work, static mechanical tests like tensile, impact testing and dynamic mechanical tests like wear test, Shore ‘D’ hardness, flexural and compression properties are evaluated for the Delrin as the matrix and the chopped flax fiber as the reinforcement. Measured mechanical test results showed an incremental increase with the addition flax/Delrin. According to the finding’s, non-reinforced epoxy has inferior characteristics to Flax + Delrin composite materials. Making hybrid composites out of natural fiber and Delrin in the future could bring in a new era for composite materials. This improves the performance and degrading life of composite.

Electrical characteristic analysis of Al0.43Ga0.57As cylindrical surrounding double-gate (CSDG) MOSFET: A nano-material sensing approach with fabrication technology

Research in the optimization of quantum structures based on arbitrary alloys has become prominent in recent years. The heterostructures have been designed using the multiple layers of the nanomaterials by regular spacing to satisfy the design rule and to enhance the performance of the MOSFET. The three-dimensional structure of Cylindrical Surrounding Double-Gate (CSDG) MOSFET has been designed using the 2D planar structure of Double-Gate (DG) MOSFET by rotating along the axis outside the gate terminal. This kind of structure has concentric cylindrical layers of the heterostructures aligned in a fashion to form a coaxial array. This exhibits various electrical characteristics when biased and also provides a frequency response matching the RF application requisite. The transient analysis shows that the oscillations went from 47.89 GHz to 61.77 GHz under the La2O3 oxide layer between the gate terminal and bulk. The kink was observed exactly at the −3 V gate voltages where the Hydrogen sensing equipment takes a growth of 650 + 1.25%. The observed characteristics curve makes the next kink at 2 V at positive bias. The experiment was carried out in the environment of 500 ppm hydrogen gas in the chamber for sensing. The analysis has been made clear to study the electrical characteristics of the CSDG MOSFET in the nanometer regime and enhance the operation of RF hybrid applications.