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1927 articles for “failure-prediction AUROC of 0.967” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Autonomous Agentic AI for Adaptive Cure Optimization and Defect Prevention in Thermoset Polymer Composite Manufacturing
Abstract: Thermoset polymer composites occupy a central position in modern structural manufacturing, from aircraft fuselages to wind-turbine blades. Despite progress in resin chemistry and fiber architecture, the “cure process” that transforms compliant preforms into load-bearing structures remains difficult to manage. Manufacturers encounter ‘voids’, “interlaminar delaminations”, and “spring-back distortion” when curing complex or thick-section parts. The cause is not ignorance of the relevant physics, but rather that ‘temperature’, ‘chemistry’, ‘rheology’, and ‘mechanics’ …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 301–320 Read article
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Evaluation of Mucoadhesive Polymers for Nasal Delivery of Herbal Bioactives
Abstract: A study assessed mucoadhesive polymers for intranasal herbal bioactive administration with higher residence time and mucosal permeability. Chitosan, Carbopol® 934P, and HPMC K15M were utilized to manufacture mucoadhesive nasal gels with standardized herbal bioactive fractions. Formulations were examined for pH, viscosity, spreadability, drug content, mucoadhesive strength, in-vitro release, ex-vivo penetration, and short-term stability. All formulations demonstrated a suitable pH for nasal usage and uniform drug content (97.48 ± 1.12% to …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1680–1689 Read article
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AI-Designed Functionally Graded Polymer Composites for Multifunctional Thin Films
Abstract: The design of multifunctional polymer composite thin films requires simultaneous optimization of mechanical, optical, barrier, and thermal properties—objectives often in conflict when using conventional homogeneous materials. This study presents an artificial intelligence-driven framework for designing functionally graded material (FGM) architectures in polymer nanocomposite thin films. We integrated machine learning with physics-based modeling to optimize compositional gradients across film thickness, achieving superior performance compared to homogeneous and discrete multilayer alternatives. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1026–1041 Read article
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Experimental Exploration of Crack and Damage Dynamics of Hybrid FRP Nano Composites
Abstract: Fiber-reinforced polymer (FRP) composites have become essential materials in modern engineering structures because of their excellent strength-to-weight ratio, corrosion resistance, and adaptability in design. Among different fracture modes, Mode I interlaminar fracture where cracks propagate under tensile opening stresses is one of the most critical forms of damage in layered composites. Since delamination occurs within the matrix-rich regions between plies, improving the matrix properties plays a key role in enhancing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 220–232 Read article
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Environmental Impact Assessment of Ocean Energy Converters Using Quantum Machine Learning
Abstract: The accelerating deployment of ocean energy converters (OECs) across tidal, wave, osmotic, and thermal domains necessitates rigorous, data-intensive environmental impact assessment (EIA) frameworks capable of modelling multi-stressor marine ecosystems in real time. Classical machine learning approaches, while operationally mature, encounter scalability bottlenecks and feature correlation limitations when applied to the high-dimensional, non-linear datasets characteristic of offshore monitoring networks. This paper presents a comprehensive quantum machine learning (QML) framework for the …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 1, 2026 · pp. 22–31 Read article
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On the link of global warming and cloudiness in mid hills of Himachal Himalayas, India
Abstract: The present study investigated the monthly, seasonal, and annual cloud cover variability over two stations in the mid hills sub-temperate subhumid zone of Himachal Pradesh, by using Pearson’s correlation coefficient, Mann-Kendall (MK), and Sen’s slope estimator test. Daily data on cloud cover, sunshine hours, maximum and minimum temperature, morning and evening relative humidity, evaporation and rainfall for the period of 22 years (2001–2022) were used in the investigation. In the …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 39–49 Read article
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Forecasting Climate-Driven Healthcare Demand in Agricultural Regions: A Multi-Modal AI Approach
Abstract: The rapidly increasing instability of world climatic regimes has made past meteorological thresholds irrelevant, especially in the agricultural areas where monetary stability and well-being of humans are closely intertwined with an environmental situation. The more the frequency of 1 in every 1000-year events, i.e., heatwaves and catastrophic flooding increase, the greater the rural healthcare systems are in crisis, i.e., unable to predict a surge in demand because of data scarcity, …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 28–38 Read article
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Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article
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AI-Integrated Graphene-Modified Polymer Interfaces for Real-Time Crack Detection and Autonomous Healing in Smart Concrete Structures
Abstract: This study presents the design and development of a graphene-reinforced multifunctional polymer composite interface engineered for structural reinforcement, self-sensing, and autonomous healing applications in cementitious systems. A thermosetting polymer matrix embedded with graphene nanoplatelets (0.25–1.5 wt.%) was developed to establish a conductive polymer nano-composite network. Electrical characterization confirmed a distinct percolation threshold at ~0.6–0.8 wt.%, beyond which a sharp increase in conductivity was observed due to the formation of interconnected …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 30–42 Read article
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Polymeric Micelles for Medicinal Plant Solubilization and Delivery of Bioactive Compounds
Abstract: This study involved the design, fabrication, and characterization of polymeric micellar nanocomposites utilizing amphiphilic block copolymers to effectively encapsulate and transport hydrophobic phytoconstituents. The selected bioactive molecule is curcumin, a polyphenol with limited water solubility. A polymeric system known as PEG-PCL was utilized to fabricate core-shell nanostructures by a solvent evaporation-induced self-assembly method. The resulting nanocomposites exhibited homogeneity and colloidal stability, characterized by a zeta potential of −18.7 ± 1.4 …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 208–219 Read article
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Machine Learning in Nuclear Medical Applications: A Review of Research Frontiers
Abstract: Nuclear medicine, encompassing PET, SPECT, and targeted radionuclide therapy, generates high-dimensional, quantitative data uniquely suited for machine learning (ML) analysis. This review synthesizes current research applications of ML across six key domains. Positron emission tomography (PET), single-photon emission computed tomography (SPECT), and targeted radionuclide therapy are examples of nuclear medicine modalities that generate high- dimensional, quantitative datasets that are particularly well-suited for machine learning (ML)-driven analysis. These imaging methods provide …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 19–24 Read article
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Polymer Composite-Supported Jackfruit Peel Adsorbent for Enhanced Copper (II) Removal from Wastewater: Batch Equilibrium and Isotherm Analysis
Abstract: The increasing concern of disposal of copper-containing effluents into the environment has led to heightened interest in designing cost-effective, eco-friendly and scalable adsorbent systems. Traditional metals and synthetically engineered sorbents prove to be effective; however, these systems are energy intensive. Agricultural residues entrapped in polymer composite systems constitute an economically feasible solution to this environmental challenge. This work reports on the design, characterization and performance evaluation of an economical adsorbent …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 375–390 Read article
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Machine Learning Assisted Design and Analysis of Polymer Composite Materials for Sustainable Renewable Energy Systems
Abstract: Accurate prediction and optimization of polymer composite properties is of paramount importance in the design of these lightweight, durable, and sustainable materials within renewable energy technologies. This work will provide a holistic machine learning-assisted framework that unites materials informatics with domain-specific features and state-of-the-art ML methodologies in the prediction of the mechanical properties of polymer composites, such as tensile strength. This includes embedding several ensemble models, including Random Forest and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 391–402 Read article
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A Study to Assess the Risk Factors and Symptoms of Dialysis Disequilibrium Syndrome among Patients Undergoing Hemodialysis
Abstract: Dialysis Disequilibrium Syndrome (DDS) is a rare but potentially life-threatening neurological complication associated with hemodialysis, particularly during initiation or in high-risk patients. It is characterized by a spectrum of neurological manifestations ranging from mild symptoms such as headache and nausea to severe outcomes including seizures, coma, and death. Early identification of risk factors and prompt recognition of symptoms are crucial to prevent morbidity and mortality. The present study aimed to …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 Read article
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Structure Property Correlation of Polymer Dielectrics Using Electrical Response Data
Abstract: Polymer dielectrics are foundational to insulation, capacitors, embedded passives, and flexible electronics, where performance is governed by the frequency-dependent electrical response rather than a single dielectric constant. This study presents a spectroscopy-aware structure–property correlation framework that transforms dielectric response data into physically interpretable spectral fingerprints and learns mappings from polymer descriptors to these fingerprints for prediction and interpretation. Broadband spectra are standardized on a log-frequency grid and parameterized using relaxation-informed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 315–324 Read article
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Regional Variation in Amino Acid Composition, Antioxidant and Antimicrobial Activity of Tasar Sericin from North and South Bihar
Abstract: This study investigates geographical differences in biochemical and functional characteristics of sericin obtained from Antheraea mylitta cocoons sourced from two regions of Bihar, India: Bhagalpur (North) and Banka (South). Sericin was isolated via an alkali-assisted autoclaving process. Amino acid profiles were determined using HPLC. Free radical scavenging capacity was measured through DPPH, ABTS, and hydrogen peroxide assays. Antibacterial and antifungal effects were tested against Staphylococcus aureus, Escherichia coli, and Candida …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 2, 2026 Read article
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Computational Modeling of Polymer Semiconductors for Electronic Applications
Abstract: Polymer semiconductors have become important materials in modern electronic applications because they combine semiconducting behavior with mechanical flexibility, low-cost processing, and tunable molecular structure. Their growing use in organic field-effect transistors, organic photovoltaics, organic light-emitting diodes, and flexible sensing devices has increased the need for accurate computational approaches that can predict material properties and device performance before experimental fabrication. This paper reviews the major computational modeling techniques used for polymer …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 132–146 Read article
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Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
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Design and Performance Analysis of Natural Rubber–Silica Nanocomposite Vibration Isolators for Household Appliances
Abstract: Natural rubber (NR) nanocomposites reinforced with surface-modified precipitated silica (SiO2) were synthesized through a two-roll mill compounding and compression-moulding process, then systematically evaluated as passive vibration isolator materials for domestic washing machine applications. Five silica loadings 0, 5, 10, 15, and 20 phr were investigated. A comprehensive characterization suite encompassing tensile testing, Shore A hardness, dynamic mechanical analysis (DMA), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM) revealed clear structure–property …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 554–560 Read article
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Polymer Encapsulants for Photovoltaic Modules: Electrical Insulation Performance and Long-Term Durability under Accelerated UV Exposure
Abstract: Influence on the reliability and service life of PV modules is a major issue, which is influenced by the encapsulant degradation in long-term exposure to the sun's ultraviolet (UV) radiation. A systematic accelerated UV aging study of Ethylene Vinyl Acetate (EVA), Polyolefin Elastomer (POE), and Polyvinyl Butyral (PVB) films under IEC 61215-2:2021 specified test chamber conditions of Q-UV is conducted. The material properties were tested at various exposure intervals including …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 384–408 Read article