North Eastern Regional Institute of Science and Technology (or NERIST) is a science and technology oriented higher education institute in Nirjuli, Itanagar, Papum Pare district, in the Indian state of Arunachal Pradesh. Established in 1984, it is a deemed to be university, autonomous, fully funded and controlled by the Ministry of Human Resource Development, Department of Education, Government of India. The institute is managed by a Board of Management, comprising representatives of Ministry of Education, GOI, the eight beneficiary states of the North Eastern region, AICTE and educationists.
Synthetic dyes from textile and other industrial sectors are persistent pollutants and composed of complex aromatic structures, which makes them resistant to the conventional methods of treatment. In recent years, white rot fungi like Pleurotus spp. have received promising attention as an environmentally friendly green alternative for dye detoxification and decolorization. Extracellular ligninolytic enzymes produced from such white rot fungi (like laccase, LiP or lignin peroxidase, MnP or manganese peroxidase, DyP or dye-decolorizing peroxidase) oxidize a wide spectrum of dyes synergistically. In its mechanism, dye adsorption on the biomass of fungi occurs initially, followed by the disruption of chromophore, breakdown of azo bonds, and the progressive aromatic rings’ degradation by the enzymatic oxidation process. Immobilization strategies, optimization process, and integration with advanced methods of oxidation may make this green method more promising and effective. Overall, Pleurotus strains and their enzymes represent a sustainable, eco-friendly, green, and versatile technique for bioremediation of dye molecules. Wide enzymatic capability and adaptability of such fungi highlight the potential of addition in the systems of next-generation wastewater treatment, principally when united with advanced method schemes that improve the stability, scalability, and safety of the finally treated effluents. This review has been prepared to explore the advantages and challenges associated with the use of Pleurotus species and their enzymes in dye bioremediation. Insightful, systematic and critical discussions have been performed on the potential mechanisms, various factors affecting the decolorization process, potential challenges, bottlenecks, and possible solutions. Techno-economic feasibility of Pleurotus species and their enzyme-based systems in dye’s bioremediation process has also been critically assessed and explored along with conclusion and future perspectives.
This work gives an in-depth discussion on prediction and optimisation of the mechanical properties of FDM-printed polyethylene terephthalate glycol (PETG) parts by applying statistical and machine learning methods. Experimentally, the influence of the three important process variables on the surface roughness (SR) and ultimate tensile strength (UTS) was studied: the melting temperature, the height of the layer, and the infill density. The predictive capacity of the Artificial Neural Network (ANN), Random Forest Regression (RFR) and Response Surface Methodology (RSM) models were developed and compared. RFR model was found to be more accurate than other models with the following values of R2 = 0.94 (training) and R2 = 0.83 (testing) and mean absolute error (MAE) = 2.51 when predicting UTS. The mean error between the experimental and predicted values was lower than 5% accounting for the robustness of the developed model. The process parameters were optimised with multi objective Genetic Algorithm (GA) and produced an optimum UTS of 38.39 MPa and a minimum surface roughness of 5.65 um at 82.42% infill density, 0.26 mm layer height, and 230.26 C melting temperature. The findings are also validated by carrying out microstructural study using SEM image. These findings show how the mechanical performance and surface quality of PETG components that are FDM-printed can be enhanced by combining machine learning and evolutionary optimisation.
This study investigates the microstructural and mechanical effects of incorporating 1.5 wt
GaN HEMTs are essential devices in high-voltage, fast switching operation in 5G and millimeter-wave applications. This research presents an AlGaN/GaN HEMT without buffer (BF-HEMT) featuring an AlGaN back barrier and stacked HfO2/SiN passivation. The device’s characteristics were evaluated using the Sentaurus TCAD tool. Incorporating a 100 nm AlGaN back barrier with 7
In this paper, we focus on a class of fourth order elliptic partial differential equation arising in epitaxial growth theory as follows Delta 2f = det(D2f)+ AG(x), x is an element of Omega C & Ropf;2, where (D2f ) is the Hessian matrix, A is an element of & Ropf; is the parameter which measures the speed of the particle and G(x) is the deposition rate. We fix the problem on the disk with radius T and it is defined by Omega = {(x1, x2) & ratio; x12 + x22 <= T2} C & Ropf;2. We investigate the radial solutions subject to different types of boundary condition. Since the radial problems are nonlinear, non-self-adjoint, fourth order and a parameter A is present, therefore it is not easy to analyze the radial solution. Here, we apply monotone iterative technique to show the existence of at least one solution in continuous space. We manifest some properties of the solutions and provide bounds for the values of the parameter A to separate the existence from non-existence of the radial solution. Exact solution of this problem is not known. To find the approximate solutions, we develop an iterative technique based on Adomian polynomial and Green's function. We place some numerical data that will verify the theoretical results.
