Damage Localization and Severity Assessment in Composite Structures Using Deep Learning Based on Lamb Waves.

In composite structures, the precise identification and localization of damage is necessary to preserve structural integrity in applications across such fields as aeronautical, civil, and mechanical engineering. This study presents a deep learning (DL)-assisted framework for simultaneous damage localization and severity assessment in composite structures using Lamb waves (LWs). Previous studies have often focused on either damage detection or localization in composite structures.

Knee osteoarthritis severity detection using deep inception transfer learning.

Osteoarthritis (OA) is a prevalent condition resulting in physical limitations. Early detection of OA is critical to effectively manage this condition. However, the diagnosis of early-stage arthritis remains challenging.

Deep Learning-Based Microscopic Damage Assessment of Fiber-Reinforced Polymer Composites.

Fiber-reinforced polymers (FRPs) are increasingly being used as substitutes for traditional metallic materials across various industries due to their exceptional strength-to-weight ratio. However, their orthotropic properties make them prone to multiple forms of damage, posing significant challenges in their design and application. During the design process, FRPs are subjected to various loading conditions to study their microscopic damage behavior, typically assessed through scanning electron microscopy (SEM).

A Review on Traditional and Artificial Intelligence-Based Preservation Techniques for Oil Painting Artworks.

Oil paintings represent significant cultural heritage, as they embody human creativity and historical narratives. The preservation of these invaluable artifacts requires effective maintenance practices to ensure their longevity and integrity. Despite their inherent durability, oil paintings are susceptible to mechanical damage and chemical deterioration, necessitating rigorous conservation efforts.

Bridging theory and practice: A comprehensive algorithm for imageless total knee arthroplasty.

Total knee arthroplasty (TKA) is a surgical procedure to treat severe knee osteoarthritis. Among several techniques available for performing TKA, imageless TKA is known for achieving precise alignment while minimizing invasiveness. This work proposes a comprehensive algorithm for imageless TKA device to calculate the varus/valgus and flexion/extension angles, as well as resection depths for cutting planes at distal femur and proximal tibia.

Femoral coordinate system based on articular surfaces: Implications for computer-assisted knee arthroplasty.

Osteoarthritis knee can be restored by total knee arthroplasty (TKA). Imageless TKA requires several anatomical points to construct a reference coordinate system to measure bone resections and implant placement. Inaccuracies in the definition of the coordinate system lead to malalignment and failure of the implant.

Nanorod-like Structure of ZnO Nanoparticles and ZnO Clusters Using 4-Dimethylamino Benzaldehyde Liquid to Study the Physicochemical and Antimicrobial Properties of Pathogenic Bacteria.

To study their physicochemical and antimicrobial properties, zinc oxide nanoparticles were synthesized using a simple chemical route and 4-dimethylaminobenzaldehyde (4DB) as an organic additive. ZnO nanoparticles were characterized with XRD analysis, which confirmed the presence of a hexagonal wurtzite structure with different crystalline sizes. The SEM morphology of the synthesized nanoparticles confirmed the presence of nanorods in both modifications of ZnO nanoparticles.

Autonomous Assessment of Delamination Using Scarce Raw Structural Vibration and Transfer Learning.

Deep learning has helped achieve breakthroughs in a variety of applications; however, the lack of data from faulty states hinders the development of effective and robust diagnostic strategies using deep learning models. This work introduces a transfer learning framework for the autonomous detection, isolation, and quantification of delamination in laminated composites based on scarce low-frequency structural vibration data. Limited response data from an electromechanically coupled simulation model and from experimental testing of laminated composite coupons were encoded into high-resolution time-frequency images using SynchroExtracting Transforms (SETs).

Numerical Investigation of Ferrofluid Preparation during In-Vitro Culture of Cancer Therapy for Magnetic Nanoparticle Hyperthermia.

Recently, studies of magnetic nanoparticle (MNP) hyperthermia have attracted significant attention because of the severity of this cancer therapy for culture. Accurate temperature evaluation is one of the key challenges of MNP hyperthermia. Hence, numerical studies play a crucial role in evaluating the thermal behavior of ferrofluids.

Bifunctional iron molybdate as highly effective heterogeneous electro-Fenton catalyst and Li-ion battery anode.

Three-dimensional materials have attracted considerable interest in energy and environmental remediation fields. Iron molybdate (FMO) materials have prepared via a facile hydrothermal technique with glycerol assistance, and their structural and chemical composition confirmed using various physico-chemical techniques. The prepared bi-functional material is a strong candidate for energy storage and electrocatalytic degradation of Methylene blue and Congo red.

Hexagonal nanostructured cobalt oxide @ nitrogen doped multiwalled carbon nanotubes/polypyyrole composite for supercapacitor and electrochemical glucose sensor.

Hexagonal nanostructured cobalt oxide @ N-doped MWCNT /polypyyrole (CoO/PPy@N-MWCNT) composite was produced by an ultrasonication-mediated solvothermal method for electrochemical supercapacitor and glucose sensor applications. The structural and electrochemical properties of the CoO/PPy@N-MWCNT were confirmed by various spectroscopic and microscopic techniques. The as-prepared electrode showed an excellent capacitance of ∼872 F/g at 0.

Ultrasonication-mediated nitrogen-doped multiwalled carbon nanotubes involving carboxy methylcellulose composite for solid-state supercapacitor applications.

In this study, a novel nanohybrid composite containing nitrogen-doped multiwalled carbon nanotubes/carboxymethylcellulose (N-MWCNT/CMC) was synthesized for supercapacitor applications. The synthesized composite materials were subjected to an ultrasonication-mediated solvothermal hydrothermal reaction. The synthesized nanohybrid composite electrode material was characterized using analytical methods to confirm its structure and morphology.

Parametric Investigations of Magnetic Nanoparticles Hyperthermia in Ferrofluid using Finite Element Analysis.

Recently, magnetic nanoparticles (MNPs) based hyperthermia therapy has gained much attention due to its therapeutic potential in biomedical applications. This necessitates the development of numerical models that can reliably predict the temporal and spatial changes of temperature during the therapy. The objective of this study is to develop a comprehensive numerical model for quantitatively estimating temperature distribution in the ferrofluid system.

Rotate Vector (RV) Reducer Fault Detection and Diagnosis System: Towards Component Level Prognostics and Health Management (PHM).

In prognostics and health management (PHM), the majority of fault detection and diagnosis is performed by adopting segregated methodology, where electrical faults are detected using motor current signature analysis (MCSA), while mechanical faults are detected using vibration, acoustic emission, or ferrography analysis. This leads to more complicated methods for overall fault detection and diagnosis. Additionally, the involvement of several types of data makes system management difficult, thus increasing computational cost in real-time.

Intelligent Steam Power Plant Boiler Waterwall Tube Leakage Detection via Machine Learning-Based Optimal Sensor Selection.

Boiler waterwall tube leakage is the most probable cause of failure in steam power plants (SPPs). The development of an intelligent tube leak detection system can increase the efficiency and reliability of modern power plants. The idea of e-maintenance based on multivariate algorithms was recently introduced for intelligent fault detection and diagnosis in SPPs.

A review on numerical modeling for magnetic nanoparticle hyperthermia: Progress and challenges.

Recent progress in nanotechnology has advanced the development of magnetic nanoparticle (MNP) hyperthermia as a potential therapeutic platform for treating diseases. Due to the challenges in reliably predicting the spatiotemporal distribution of temperature in the living tissue during the therapy of MNP hyperthermia, critical for ensuring the safety as well as efficacy of the therapy, the development of effective and reliable numerical models is warranted. This article provides a comprehensive review on the various mathematical methods for determining specific loss power (SLP), a parameter used to quantify the heat generation capability of MNPs, as well as bio-heat models for predicting heat transfer phenomena and temperature distribution in living tissue upon the application of MNP hyperthermia.

Facile Synthesis of Triphenylamine Based Hyperbranched Polymer for Organic Field Effect Transistors.

In this study, we reported the synthesis and characterization of a novel hyperbranched polymer (HBPs) [(4-phenyl)amino--4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b;4,5-b']dithiophene] (PTPABDT) composed of benzo[1,2-b:4,5-b']dithiophene (BDT) and triphenyleamine (TPA) constituent subunits by A + B type Stille's reaction. An estimated optical band gap of 1.69 eV with HOMO and LUMO levels of -5.

Novel approach to synthesize NiCoS composite for high-performance supercapacitor application with different molar ratio of Ni and Co.

Here, we developed a new approach to synthesize NiCoS thin films for supercapacitor application using the successive ionic layer adsorption and reaction (SILAR) method on Ni mesh with different molar ratios of Ni and Co precursors. The five different NiCoS electrodes affect the electrochemical performance of the supercapacitor. The NiCoS thin films demonstrate superior supercapacitance performance with a significantly higher specific capacitance of 1427 F g at a scan rate of 20 mV s.

Porous materials of nitrogen doped graphene oxide@SnO electrode for capable supercapacitor application.

The porous materials of SnO@NGO composite was synthesized by thermal reduction process at 550 °C in presence ammonia and urea as catalyst. In this process, the higher electrostatic attraction between the SnO@NGO nanoparticles were anchored via thermal reduction reaction. These synthesized SnO@ NGO composites were confirmed by Raman, XRD, XPS, HR-TEM, and EDX results.

Ni(OH)-decorated nitrogen doped MWCNT nanosheets as an efficient electrode for high performance supercapacitors.

In this study, nickel hydroxide nanoparticles (NPs) decorated with nitrogen doped multiwalled carbon nanotubes (N-MWCNT) hybrid composite was synthesized by thermal reduction process in the presence of cetyl ammonium bromide (CTAB) and urea. The as-synthesized Ni(OH)@N-MWCNT hybrid composite was characterized by FTIR, Raman, XRD, BET, BJH and FE-TEM analyses. These prepared porous carbon hybrid composite materials possessed high specific surface area and sheet like morphology useful for active electrode materials.

Active Vibration Control of a Piezo-Bonded Laminated Composite in the Presence of Sensor Partial Debonding and Structural Delaminations.

In this paper, the active vibration control of a piezo-bonded laminated composite is investigated in the presence of sensor partial debonding and structural delamination. Improved layerwise theory, higher-order electric potential field, and the finite-element method were employed to develop an electromechanically coupled model for the two types of damage (i.e.

Hierarchical Flowerlike 3D nanostructure of CoO@MnO/N-doped Graphene oxide (NGO) hybrid composite for a high-performance supercapacitor.

The present study investigates the fabrication of hierarchical 3D nanostructures with multi-component metal oxides in the presence of highly-porous graphene and characterized for its applications in high-performance supercapacitors. A hierarchical flowers like 3D nanostructure of CoO @MnO on nitrogen-doped graphene oxide (NGO) hybrid composite was synthesized by thermal reduction process at 650 °C in the presence of ammonia and urea. The synthesized CoO@MnO/NGO hybrid composites were studied via Raman, XRD, X-ray XPS, FE-SEM, FE-SEM with EDX, FE-TEM and BET analyses.