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135 articles for “assisted optimization”
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Machine Learning Assisted Optimization of Nanoscale MOSFET Parameters Using TCAD Simulation
Abstract: This paper presents a machine learning (ML) assisted framework for the multi-objective optimization of nanoscale bulk n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) with a 10 nm physical gate length, high-k HfO₂ gate dielectric, and TiN metal gate. Technology computer-aided design (TCAD) simulations employing drift-diffusion transport, Shockley-Read-Hall recombination, Lombardi mobility degradation, and density- gradient quantum correction models are used to generate a parametric dataset of 2,400 device configurations spanning gate length (L), …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 10–19 Read article
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AI-Assisted Optimization of Supersonic Airfoil Shapes Using CFD Coupling
Abstract: This paper presents a novel framework for optimizing supersonic airfoil geometries through integrated artificial intelligence and computational fluid dynamics coupling. Traditional gradient-based optimization methods for high-speed aerodynamic shapes suffer from computational expense and convergence difficulties in non-convex design spaces. The proposed methodology employs a deep neural network surrogate model trained on high-fidelity Reynolds-Averaged Navier-Stokes solutions to approximate aerodynamic performance metrics across the design space. A hybrid particle swarm-genetic algorithm searches …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 Read article
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Optimized Design and Control of Oil Exploitation Strategies: An Assisted Approach
Abstract: Because there are so many factors and scenarios to consider, optimizing oil exploitation tactics requires complicated decision-making. Conventional approaches frequently concentrate on particular elements of the design infrastructure, which restricts their capacity to fully handle the process. In order to maximize a set of oil exploitation variables in a hierarchical fashion, this research proposes a novel assisted optimization technique that combines mathematical algorithms with engineering analysis. By grouping variables into …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 29–34 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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Artificial Intelligence-Assisted Multi-Objective Optimization of Agricultural Biomass-Reinforced Polymer Composites
Abstract: Agricultural biomass can reduce the environmental burden of polymer composites, yet its heterogeneous structure creates competing effects on strength, moisture resistance, density, and process ability. This study developed an artificial intelligence-assisted framework for balanced composite formulation. Experimental data of agricultural biomass reinforced polymer composites were gathered, harmonized and validated using leakage controlled validation. The mechanical and physical properties were predicted by artificial neural networks and conventional regression models. Explainable analysis …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Experimental Validation and Implementation Framework for Optimized Methane Yield Prediction in Anaerobic Digestion
Abstract: The correct validation and realistic application of optimized anaerobic digestion (AD) models are essential steps in transferring biogas production systems to real-life. This paper outlines an experimental validation and deployment pipeline of an AI-optimized model of the methane yield prediction model based on the application of more advanced machine learning and Bayesian optimization methods. Others The validated surrogate-assisted optimization model was tested with controlled laboratory-scale AD experiments at optimized operating …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 25–32 Read article
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AI-Assisted Defect Detection in Polymer Composite Insulators Using an Optimised Ensemble Deep Learning Framework for Structural Health Monitoring
Abstract: Polymer composite insulators, particularly those made from silicone rubber and epoxy resins, are increasingly adopted in high-voltage transmission systems due to their superior electrical insulation, lightweight design, hydrophobicity, and environmental durability. Despite their advantages, these materials are susceptible to surface degradation, mechanical cracking, and flashover under prolonged exposure to environmental pollutants, thermal stress, and electrical aging. Accurate, real-time condition assessment of these composite insulators is critical for ensuring operational safety, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 253–261 Read article
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Development of Compact RF Filters for Modern Wireless Communication Systems
Abstract: Modern wireless communication systems such as 5G, 6G, Internet of Things (IoT), satellite communication, radar systems, and smart wireless networks require compact and highly efficient RF filters for reliable signal transmission and interference suppression. RF filters are important components that allow desired frequency signals to pass while rejecting unwanted frequencies and noise. With the rapid growth of wireless devices and limited spectrum resources, the demand for miniaturized, low-loss, multi-band, and …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 2, 2026 Read article
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Recent Developments in Hybrid and Nanostructured Basalt Fiber Composites: A Review of Mechanical and Processing Innovations
Abstract: This review delivers a critical analysis of recent advancements in basalt fiber-reinforced hybrid composites (BFRHCs), emphasizing their transformative potential for advanced structural and high-performance applications. Basalt fibers, derived from volcanic rock, exhibit superior tensile strength, excellent thermal stability, and chemical resistance, offering a sustainable and cost-effective alternative to conventional glass and carbon fibers. Hybridization of basalt fibers with synthetic (e.g., carbon, glass) and natural fibers (e.g., flax, hemp) results in …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 885–894 Read article
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New trends in Radio Frequency design and making things smaller
Abstract: Recent improvements in wireless communication, the Internet of Things (IoT), and 5G/6G networks have made people want small, powerful radio frequency (RF) equipment. With an emphasis on how developments in materials engineering, circuit architecture, and packaging technologies are redefining RF system integration, this article offers a thorough evaluation of current developments in RF downsizing. System-on-Chip (SoC), System-in-Package (SiP), and Antenna-in-Package (AiP) ideas, which allow tightly integrated RF front-ends with enhanced …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 2, 2025 · pp. 28–34 Read article
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Next-Generation Membrane Materials: Advances, Applications, and Challenges
Abstract: Advanced membrane materials are better than regular polymers because they are more selective, permeable, and stable. New developments in nanomaterials, composite membranes, and surface engineering are making it possible to do more with water purification, gas separation, biomedical applications, and energy systems. Membrane technologies have become important tools in many areas, including biomedicine, energy systems, gas separation, and water purification. Recent progress in material science has made it possible to …
Published in International Journal of Membranes · Vol. 2, Issue 2, 2025 · pp. 19–28 Read article
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Revolutionizing Culinary Innovation and Sustainability through Smart Kitchen Assistant
Abstract: Introducing a Smart Kitchen Assistant which revolutionizing a culinary experiences with advanced features. This innovative system integrates a precision Vegetable Cutter, optimizing meal preparation efficiency. And a Storage Space ensures organized ingredients readily available for cooking. UV Light Sterilization guarantees hygienic food preparation surfaces, enhancing safety. Additionally, integrated Solar Panels promote sustainability, reducing energy consumption and environmental impact. By seamlessly combining this technology with sustainable practices, our Smart Kitchen Assistant …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 1–16 Read article
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Exploring the Influence of Machining Parameters on Geometric Form and Orientation Controls (23 Design)
Abstract: This work explores the influence of machining parameters using on geometric form controls flatness and straightness as well as orientation control parallelism using an aluminum 6061 workpiece. Due to its good strength, machinability and cost- effectiveness, aluminum 6061 is widely used. In this experimental work, full factorial design is used and each factor has two levels. The response parameters chosen include flatness, straightness, and parallelism, which govern the form and …
Published in Journal of Experimental & Applied Mechanics · Vol. 16, Issue 1, 2025 · pp. 10–16 Read article
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AutoGen Bike: A Self-Sustaining Smart Electric Bike with Integrated AI Safety Systems
Abstract: This is the paper which gives the information about the self-sustaining electric bike. This also tells the idea about how energy is produced during its usage. The “Auto gen bike” is the most useful aspect that can change the future of the electric bikes. This also helps in the conservation of natural resources and nature. This also helps in the accidents happening to the two-wheel vehicle. This is achieved by …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 41–49 Read article
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Enhancing Surface Roughness in the Taguchi Method for Turning Alloy Steel in Wet and Dry Environments
Abstract: The present investigation focuses on evaluating the performance of turning operations in alloy steel with particular emphasis on the effect of cutting parameters on surface roughness. In the machining of alloy steel, tool life and surface integrity are significantly influenced by parameters such as spindle speed, depth of cut, and feed rate. Among these, feed rate has been observed to exert the most prominent effect on surface roughness. To systematically …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 1–6 Read article
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The Role of AI in Modern Circuit Design and Simulation
Abstract: The integration of artificial intelligence (AI) in circuit design and simulation is revolutionizing the electronics industry by enabling faster, more efficient, and innovative design processes. This article explores the transformative role of AI in automating tasks traditionally reliant on manual expertise, such as schematic generation, component optimization, and fault detection. It highlights how machine learning algorithms and generative AI tools are improving design accuracy, reducing time-to-market, and enabling cost-effective prototyping. …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 1, 2025 · pp. 9–14 Read article
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Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Squeeze Casting of Hybrid Aluminum Matrix Composites: A Critical Review of Process Optimization, Reinforcement Strategies, and Performance Outcomes
Abstract: Increasing demand for lightweight, performance-oriented components in automotive, aerospace, and defense industries has driven advancements in squeeze casting, a hybrid technique merging forging and die-casting advantages to produce near-net-shape aluminum matrix composites (AMCs) with superior mechanical-tribological properties. This review critically examines the interplay of process parameters (e.g., squeeze pressure: 70–150 MPa, melt temperature: 650–800°C), reinforcement characteristics (volume fraction ≤10%, particle size: 10–71µm), and interfacial engineering strategies (flux-assisted bonding, ultrasonic dispersion) …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 2, 2025 · pp. 52–60 Read article
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Semiconducting Materials for Emerging Electronics and Technological Applications
Abstract: Semiconducting materials are important for emerging electronic and photovoltaic technologies because their structural, optical and electrical properties can be tailored for specific device applications. In this study, a TiO₂-based composite photoanode is considered as a polymer-assisted semiconducting thin-film system in which inorganic TiO₂ nanoparticles are processed with organic film-forming components to produce a porous layer for dye-sensitised solar cell application. Nanocrystalline TiO₂ nanoparticles were synthesised from titanium isopropoxide using a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 36–50 Read article
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Crack Propagation Analysis in Metallic Alloys: A Comparative Study of Traditional and Advanced Materials
Abstract: A vital component of materials science and engineering, crack propagation analysis is essential to determining the structural integrity and dependability of materials. Designing safe and long-lasting structures for a variety of sectors required an understanding of how cracks begin, spread, and interact with a material's microstructure. To guarantee the performance, safety, and dependability of materials in a variety of applications, crack propagation analysis is essential. It offers insightful information about …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 1, Issue 1, 2023 · pp. 33–41 Read article