BURA Collection: Brunel Composites Centre (BCC) sits between the knowledge base and industry, supporting partners in industry by transfering academic research in novel composites processing and joining technologies into industrial application.

Micro CT Based Stochastic Design and Flow Analysis of Dry Fiber Preforms Manufactured by Automated Fiber Placement

Thu, 01 Sep 2022 00:00:00 GMT

Title: Micro CT Based Stochastic Design and Flow Analysis of Dry Fiber Preforms Manufactured by Automated Fiber Placement Authors: Ali, MA; Khan, T; Khan, K; Umer, R Abstract: The effective design of channels in dry tape preforms is crucial for achieving desired preform permeability for successful resin injection for composites manufacturing using Automated Fiber Placement (AFP) process. This work investigates the correlation between spatial variability of the preforms and the in-plane permeability using an X-ray Computed Tomography (XCT) based characterization framework. The tomographic images of two different dry carbon tape preforms with different tape widths were used to generate realistic and XCT based stochastic models to be used for numerical permeability predictions. The variability in the tape placement by the robotic head and its effect on preform permeability was also examined through stochastic geometric modeling of the laid preform. A benchmark transient permeability measurement set-up was utilized to obtain experimental in-plane preform permeability through 2D radial mold filling. The in-plane numerical permeability values showed significant scatter, with a coefficient of variance of 75-130%, which deviated from the experimental measurements by approximately one order of magnitude. These findings strongly re-affirm that the experimental permeability measurement technique based on transient mold filling of dry fiber AFP preforms is complex however, the XCT based stochastic modeling technique is an effective way to estimate the permeability of dry fiber AFP preforms virtually.

Rate Dependent Electromechancal Characterization And Modeling Of Graphene Based Fiber Reinforced Polymer Laminates

Sun, 26 Jun 2022 00:00:00 GMT

Title: Rate Dependent Electromechancal Characterization And Modeling Of Graphene Based Fiber Reinforced Polymer Laminates Authors: Ud Din, I; Medhin, Y; Aslam, N; Salman, M; Bathusha, S; Umer, R; Khan, KA Abstract: Fiber reinforced polymer (FRP) composite laminates are used in numerous structures that require high strength-to-weight ratio. The health status of these laminates is traditionally monitored using point strain gauge arrays, fiber optics etc. installed at critical locations. In this work, a composite laminate capable of sensing its own health has been developed using embedded fabric sensor. In this study, a manufacturing protocol is developed for in-situ reduction of graphene oxide (GO) coated fabric into rGO coated fabric. A vacuum assisted resin transfer molding process was used to fabricate the composite laminates with embedded rGO coated fabric sensors. The piezoresistivity of the composite laminate was measured both before and during fabrication. The in-plane tension tests were carried out at three different loading rates (0.2, 2, 20 mm/min) to determine the rate-dependent piezoresistive response of composite laminates. We recorded both the piezoresistivity and load-displacement data simultaneously to obtain the electromechanical response of the fabricated samples.

3D‐Printed Arch‐Structured Tribolayer with Conducting Polymer Coating for Enhanced Triboelectric Energy Harvesting

Wed, 11 Mar 2026 00:00:00 GMT

Title: 3D‐Printed Arch‐Structured Tribolayer with Conducting Polymer Coating for Enhanced Triboelectric Energy Harvesting Authors: Alhosani, ME; Fatma, B; Irshaid, RB; Katsikari, K; Aljaberi, M; Din, IU; Kang, S; Jeon, YP; Khan, KA; Pitsalidis, C Abstract: Three‐dimensional printed (3DP) triboelectric nanogenerators (TENGs) provide a versatile approach for complex and customizable microstructures tailored for efficient energy harvesting and sensing. Here, we demonstrate the fabrication of flexible microstructured TENGs produced via stereolithography 3D printing and subsequently coated with a conducting polymer, PEDOT:PSS (P:P). Three geometries are investigated: pillars, pyramids, and arches, with the arch configuration emerging as a new design combining enhanced mechanical adaptability and improved triboelectric performance. The arch‐shaped TENGs exhibit superior flexibility, structural stability, and a high active surface area, which collectively facilitate efficient energy conversion under repetitive deformation. Furthermore, the incorporation of P:P coating substantially enhances performance, resulting in a more than twentyfold increase in voltage output compared to uncoated counterparts. Among the 3DP structures, the arch geometry consistently delivers better performance, confirming the geometry‐driven performance of 3DP‐TENGs. The optimized arch configuration is found to yield a peak voltage output of ∼101 V, corresponding to a maximum power output of ∼193.6 mW/m 2 . By exploiting the spring‐like behavior of the arch‐shaped tribolayer, a “zero‐gap” TENG architecture is presented, offering a compact and adaptable energy‐harvesting platform as well as pressure‐sensing capabilities. Finally, a wireless pressure‐sensing platform configured as a vehicle parking counter is demonstrated, showcasing the potential of this development for integration into smart infrastructure and environmental monitoring systems. Description: Data Availability Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.; Supporting Information is available online at: https://advanced.onlinelibrary.wiley.com/doi/10.1002/admi.202500963#support-information-section .

Graphene nanoparticles as data generating digital materials in industry 4.0

Mon, 27 Mar 2023 00:00:00 GMT

Title: Graphene nanoparticles as data generating digital materials in industry 4.0 Authors: Ali, MA; Irfan, MS; Khan, T; Khalid, MY; Umer, R Abstract: One of the potential applications of 2D materials is to enhance multi-functionality of structures and components used in aerospace, automotive, civil and defense industries. These multi-functional attributes include sensing, energy storage, EMI shielding and property enhancement. In this article, we have explored the potential of using graphene and its variants as data generating sensory elements in Industry 4.0. We have presented a complete roadmap to cover three emerging technologies i.e. advance materials, artificial intelligence and block-chain technology. The utility of 2D materials such as graphene nanoparticles is yet to be explored as an interface for digitalization of a modern smart factory i.e. “factory-of-the-future”. In this article, we have explored how 2D material enhanced composites can act as an interface between physical and cyber spaces. An overview of employing graphene-based smart embedded sensors at various stages of composites manufacturing processes and their application in real-time structural health monitoring is presented. The technical challenges associated with interfacing graphene-based sensing networks with digital space are discussed. Additionally, an overview of the integration of associated tools such as artificial intelligence, machine learning and block-chain technology with graphene-based devices and structures is also presented. Description: Data availability: All data generated or analyzed during this study are included in this published article.