Advancements in nanomaterials for nanosensors: a comprehensive review

Nanoscale Advances, Год журнала: 2024, Номер 6(16), С. 4015 - 4046

Опубликована: Янв. 1, 2024

Nanomaterials (NMs) exhibit unique properties that render them highly suitable for developing sensitive and selective nanosensors across various domains.

Язык: Английский

---

Comparative Analysis of Metal–Thermoplastic Hybrid Circular Structures Under Quasi-static Lateral Loading: Implications for Crashworthiness

Fibers and Polymers, Год журнала: 2025, Номер unknown

Опубликована: Янв. 15, 2025

Язык: Английский

---

Influence of nanoparticles addition on the fatigue failure behavior of metal matrix composites: Comprehensive review

Engineering Failure Analysis, Год журнала: 2023, Номер 155, С. 107751 - 107751

Опубликована: Окт. 28, 2023

Light-weight, high-strength metal matrix composites (MMCs) have been gaining prominence in various industrial applications which the materials are exposed to static and dynamic loading conditions. Unfortunately, micron-sized MMCs frequently encounter challenges such as particle breakage debonding at reinforcement-matrix interface, resulting premature failure due decline their mechanical properties, making them impractical be utilized some crucial applications. On other hand, nanocomposites (MMNCs) proven improve strength, ductility, fracture toughness characteristics, greatly beneficial automotive, aerospace structures, biomaterials. This review provides a comprehensive insight into effect of nanoparticle addition on fatigue performance metals alloys. Firstly, special attention has given factors influencing life MMNCs. Secondly, incorporation common matrixes, including aluminum, magnesium, titanium, steel alloys, is reviewed detail. Finally, summary this future aspects related behavior with nanoparticles cyclic provided.

Язык: Английский

---

Biodegradable 3D printed polylactic acid structures for different engineering applications: effect of infill pattern and density

Journal of Polymer Research, Год журнала: 2023, Номер 31(1)

Опубликована: Дек. 15, 2023

Язык: Английский

---

Machine learning for advancing laser powder bed fusion of stainless steel

Journal of Materials Research and Technology, Год журнала: 2024, Номер 30, С. 4986 - 5016

Опубликована: Апрель 21, 2024

In the dynamic landscape of advanced manufacturing, confluence laser powder bed fusion (LPBF) and machine learning (ML) has recently garnered significant attention in many applications. This review investigates LPBF ML, specifically within specific domain stainless steel. Firstly, it delves into principles, including an overview critical process parameters associated defects. Secondly, paper meticulously addresses distinct challenges posed by steel additive manufacturing (AM), highlighting factors such as chemical composition, anisotropic microstructure, oxide film formation, all which require specialized considerations. Thirdly, spotlight shifts to pivotal role covering predictive modeling for parameters, real-time defect detection, quality control. highlights recent advances, revealing how data-driven approaches can accelerate understanding part qualification. Eventually, this offers insights future integration ML steel, providing valuable perspectives on potential advancements field AM.

Язык: Английский

---

A comprehensive review on fillers and mechanical properties of 3D printed polymer composites

Materials Today Communications, Год журнала: 2024, Номер 40, С. 109617 - 109617

Опубликована: Июнь 21, 2024

Язык: Английский

---

Axial Crashworthiness Characterization of Bio-Inspired 3D-Printed Gyroid Structure Tubes: Cutouts Effect

Fibers and Polymers, Год журнала: 2024, Номер 25(8), С. 3099 - 3114

Опубликована: Июль 8, 2024

Язык: Английский

---

Structural, Mechanical, and In-vitro Characterization of Hydroxyapatite Loaded PLA Composites

Journal of Molecular Structure, Год журнала: 2024, Номер 1306, С. 137862 - 137862

Опубликована: Фев. 23, 2024

Язык: Английский

---

Picking Up the Optimum Triggering Combinations of Crashworthy 3D-Printed Sustainable Structures: An Experimental Study in Al-Kharj Governorate, KSA

Fibers and Polymers, Год журнала: 2024, Номер unknown

Опубликована: Сен. 9, 2024

Язык: Английский

---

Selective Laser Sintering of Polymers: Process Parameters, Machine Learning Approaches, and Future Directions

Journal of Manufacturing and Materials Processing, Год журнала: 2024, Номер 8(5), С. 197 - 197

Опубликована: Сен. 13, 2024

Selective laser sintering (SLS) is a bed fusion additive manufacturing technology that facilitates rapid, versatile, intricate, and cost-effective prototype production across various applications. It supports wide array of thermoplastics, such as polyamides, ABS, polycarbonates, nylons. However, plastic components using SLS poses significant challenges due to issues like low strength, dimensional inaccuracies, rough surface finishes. The operational principle involves utilizing high-power-density fuse polymer or metallic powder surfaces. This paper presents comprehensive analysis the process, emphasizing impact different processing variables on material properties quality fabricated parts. Additionally, study explores application machine learning (ML) techniques—supervised, unsupervised, reinforcement learning—in optimizing processes, detecting defects, ensuring control within SLS. review addresses key associated with integrating ML in SLS, including data availability, model interpretability, leveraging domain knowledge. underscores potential benefits coupling situ monitoring systems closed-loop strategies enable real-time adjustments defect mitigation during manufacturing. Finally, outlines future research directions, advocating for collaborative efforts among researchers, industry professionals, experts unlock ML’s full provides valuable insights guidance researchers regard 3D printing, highlighting advanced techniques charting course investigations.

Язык: Английский

---