Investigating the optimum parameters of a negative photoresist to prepare a V-grooved diffraction grating on Si using photolithography and reactive ion etching techniques

In this study, the deposition parameters of the SU8 2000.5 negative photoresists have been investigated and optimized for the photolithographic technique. Then, applied the inductive coupled plasma reactive ion etching (ICP RIE) to produce V-shaped groove diffraction grating on a silicon substrate. Spin coater (speed: 1000 rpm) was used to coat the photoresist over the Si substrate. The observed photoresist film thickness was measured by ellipsometry and found to be 800 nm. Interestingly, the film exhibited some stability with increasing the spin speed. The thermogravimetric analysis was used to optimize the baking temperature which was found to be ~105 °C. Contrast curves were obtained experimentally and used to optimize the exposure energy along with the images obtained from the field emission scanning electron microscopy (FESEM). The optimized energy fluence was found to be 17 mJ/cm². It was interesting to observe that the thickness of the photoresists film was increasing with the elevation of the exposure energy fluence. The FESEM images were used to optimize the ICP RIE etching process and the best etching conditions for the Si substrate were ICP power: 150 W, bias power: 100 W, and SF₆ gas flow rate: 32 SCCM (standard cubic centimeters per minute), O₂ gas flow: 8 SCCM, and Ar gas flow of 8 SCCM. It is worth to mention that well-defined V-shaped grooves were observed with a depth of 2 μm under the same experimental conditions.     

Optimal sizing of autonomous hybrid energy system using supply‐demand‐based optimization algorithm

Hybrid energy systems (HESs) comprising photovoltaic (PV) arrays and wind turbines (WTs) are remarkable solutions for electrifying remote areas. These areas commonly fulfil their energy demands by means of a diesel genset (DGS). In the present study, a novel computational intelligence algorithm called supply‐demand‐based optimization (SDO) is applied to the HES sizing problem based on long‐term cost analysis. The effectiveness of SDO is investigated, and its performance is compared with that of the genetic algorithm (GA), particle swarm optimization (PSO), gray wolf optimizer (GWO), grasshopper optimization algorithm (GOA), flower pollination algorithm (FPA), and big‐bang‐big‐crunch (BBBC) algorithm. Three HES scenarios are implemented using measured solar radiation, wind speed, and load profile data to electrify an isolated village located in the northern region of Saudi Arabia. The optimal design is evaluated on the basis of technical (loss of power supply probability [LPSP]) and economic (annualized system cost [ASC]) criteria. The evaluation addresses two performance indicators: surplus energy and the renewable energy fraction (REF). The results reveal the validity and superiority of SDO in determining the optimal sizing of an HES with a higher convergence rate, lower ASC, lower LPSP, and higher REF than that of the GA, PSO, GWO, GOA, FPA, and BBBC algorithms. The performance analysis also reveals that an HES comprising PV arrays, WTs, battery banks, and DGS provides the best results: 238.7 kW from PV arrays, 231.6 kW from WTs, 192.5 kWh from battery banks, and 267.6 kW from the DGS. The optimal HES exhibits a high REF (66.4%) and is economically feasible ($104 323.10/year) and environmentally friendly. The entire load demand of the area under study is met without power loss (LPSP = 0%).     

Preparing thick, defect-free films of anatase titania for dye-sensitized solar cells

Anatase titania (TiO₂) nanoparticle films were prepared on fluorine-doped tin oxide (FTO) and tin-doped indium oxide (ITO) substrates. The films were characterized by X-ray diffraction, scanning electron microscopy, profilometry, Raman spectroscopy, and optical microscopy. The results show that defects are initiated during the sintering step and continue to propagate once the film is cooled. The sintering and annealing steps were controlled by reducing the pressure and the rate of temperature change. These steps reduced the stresses generated during film preparation, allowing thick titania films on both FTO and ITO substrates to be prepared with minimal defects. Using the optimized conditions for film preparation, 20 μm thick films of titania on FTO and ITO substrates were obtained with calculated defect densities of 2.5 and 7.8%. Films as thick as 25 μm were prepared on FTO substrates with a defect density of only 6.0%. Dye-sensitized solar cells (DSSCs) were fabricated using the titania films prepared by both standard and vacuum sintering methods. DSSCs made with 20 μm titania films sintered at intermediate pressures show improvements to short-circuit current, open-circuit voltage, and device efficiency.     

Cropping bioenergy and biomaterials in marginal land: The added value of the biorefinery concept

A biorefinery is an integrated pattern of farming and conversion activities capable to provide bioenergy and biomaterials as alternative to fossil-based refineries, increasing jobs and income in rural areas. Considering the need to avoid competition with food production in arable land, non-food cropping on marginal land is being explored worldwide focusing on lignocellulosic crops (“second-generation” substrates). The viability of bioenergy and biochemicals from non-food crops in marginal land of Southern Italy was explored, using Brassica carinata as a test crop. An LCA-consistent, integrated evaluation method, named SUMMA (Sustainability multi-scale multi-method Approach) was applied for joint assessment of material, embodied energy, environmental support (emergy) and economic flows and performance. Two hypotheses were tested: (a) cropping for bioenergy (biodiesel + heat); (b) bioenergy and biomaterials within a biorefinery framework. In addition to biodiesel production from seeds, the first hypothesis assumes the conversion of residues (cake meal and straw) into heat for local industrial use, while the second one is based on a lignocellulose-to-chemicals biorefinery. Cropping for bioenergy provides a small net energy yield with no economic return. Instead, converting lignocellulosic residues to high added value biochemicals definitely improves the process performance from both energetic and economic points of view.     

Laminar mixed convection boundary layers induced by a linearly stretching permeable surface

The boundary layer flow on a linearly moving permeable vertical surface is studied when the buoyancy force assists or opposes the flow. Similarity and local similarity solutions are obtained for the boundary layer equations subject to power law temperature and velocity variation. The effect of various governing parameters, such as Prandtl number Pr, injection parameter d, and the mixed convection parameter λ=Gr_x/Re_x², which determine the velocity and temperature distributions, the heat transfer coefficient, and the shear stress at the surface are studied. The heat transfer coefficient increases as λ assisting the flow for all d for uniformly or linearly heated surface and as Pr increases it becomes almost independent of λ. However, as the temperature inversely proportional to the distance up the surface, the buoyancy has no effects on the heat transfer coefficient. Critical buoyancy parameter values are obtained for vanished shear stress and for predominate natural convection. Critical values are also presented for predominate buoyancy shear stress at the surface for assisting or opposing flow. A closed form analytical solution is also presented as a special case of the energy equation.     

A green material from rock: basalt fiber – a review

The nature is continually providing varied resources for creating textile materials for various applications. Although many textile fibers in the nature are provided with the fibrous kind itself it additionally offers raw materials that may be changed and formed into a filament in a way similar to the melt and solution spinning of other textile fibers. Basalt is an igneous rock, which is solidified volcanic lava. In recent years, basalt received attention as a replacement for asbestos fibers. Basalt has emerged as a contender in the fiber reinforcement of composites. Basalt fiber (BF) is capable to withstand very high temperature and can be used in high performance applications. This paper is review of state of art of knowledge of BF, the production methods, properties and its applications.     

Securing Arabic Contents Algorithm for Smart Detecting of Illegal Tampering Attacks

The most common digital media exchanged via the Internet is in text form. The Arabic language is considered one of the most sensitive languages of content modification due to the presence of diacritics that can cause a change in the meaning. In this paper, an intelligent scheme is proposed for improving the reliability and security of the text exchanged via the Internet. The core mechanism of the proposed scheme depends on integrating the hidden Markov model and zero text watermarking techniques. The watermark key will be generated by utilizing the extracted features of the text analysis process using the third order and word level of the Markov model. The Embedding and detection processes of the proposed scheme will be performed logically without the effect of the original text. The proposed scheme is implemented using PHP with VS code IDE. The simulation results, using varying sizes of standard datasets, show that the proposed scheme can obtain high reliability and provide better accuracy of the common illegal tampering attacks. Comparison results with other baseline techniques show the added value of the proposed scheme.     

Artificial Intelligence Based Data Offloading Technique for Secure MEC Systems

Mobile edge computing (MEC) provides effective cloud services and functionality at the edge device, to improve the quality of service (QoS) of end users by offloading the high computation tasks. Currently, the introduction of deep learning (DL) and hardware technologies paves a method in detecting the current traffic status, data offloading, and cyberattacks in MEC. This study introduces an artificial intelligence with metaheuristic based data offloading technique for Secure MEC (AIMDO-SMEC) systems. The proposed AIMDO-SMEC technique incorporates an effective traffic prediction module using Siamese Neural Networks (SNN) to determine the traffic status in the MEC system. Also, an adaptive sampling cross entropy (ASCE) technique is utilized for data offloading in MEC systems. Moreover, the modified salp swarm algorithm (MSSA) with extreme gradient boosting (XGBoost) technique was implemented to identification and classification of cyberattack that exist in the MEC systems. For examining the enhanced outcomes of the AIMDO-SMEC technique, a comprehensive experimental analysis is carried out and the results demonstrated the enhanced outcomes of the AIMDO-SMEC technique with the minimal completion time of tasks (CTT) of 0.680.     

Optimal Deep Learning Based Ransomware Detection and Classification in the Internet of Things Environment

With the advent of the Internet of Things (IoT), several devices like sensors nowadays can interact and easily share information. But the IoT model is prone to security concerns as several attackers try to hit the network and make it vulnerable. In such scenarios, security concern is the most prominent. Different models were intended to address these security problems; still, several emergent variants of botnet attacks like Bashlite, Mirai, and Persirai use security breaches. The malware classification and detection in the IoT model is still a problem, as the adversary reliably generates a new variant of IoT malware and actively searches for compromise on the victim devices. This article develops a Sine Cosine Algorithm with Deep Learning based Ransomware Detection and Classification (SCADL-RWDC) method in an IoT environment. In the presented SCADL-RWDC technique, the major intention exists in recognizing and classifying ransomware attacks in the IoT platform. The SCADL-RWDC technique uses the SCA feature selection (SCA-FS) model to improve the detection rate. Besides, the SCADL-RWDC technique exploits the hybrid grey wolf optimizer (HGWO) with a gated recurrent unit (GRU) model for ransomware classification. A widespread experimental analysis is performed to exhibit the enhanced ransomware detection outcomes of the SCADL-RWDC technique. The comparison study reported the enhancement of the SCADL-RWDC technique over other models.     

Metal Halide Perovskite Surfaces with Mixed A-Site Cations: Atomic Structure and Device Stability

Mixing cations in the perovskite structure has been shown to improve optoelectronic device performance and stability. In particular, Cs_xMA_1-xPbBr₃ (MA = CH₃NH₃) has been used to build high-efficiency light-emitting diodes. Despite those advantages, little is known about the exact location of the cations in the mixed perovskite film, and how cation distribution affects device properties and stability. By using scanning tunneling microscopy , the exact atomic structure of the mixed cation Cs_xMA_1-xPbBr₃ perovskite interface is revealed. In addition, X-ray photoelectron spectroscopy, ultraviolet photoemission spectroscopy and inverse photoemission spectroscopy are used to study the stability and electronic properties of the Cs_xMA_1-xPbBr₃ perovskite film. Partial substitution of MA⁺ by Cs⁺ induces a modification of the perovskite surface structure, leading to improved device stability is shown. These results provide a better understanding of the key parameters involved in the stability of mixed cation perovskite solar cells.