Influence of Epoxy Resin Curing Kinetics on the Mechanical Properties of Carbon Fiber Composites

Construction and Curing Behavior of Underwater In Situ Repairing Coatings for Offshore Structures

The development of polymeric materials for the repair and reinforcement of damaged sites in water has many practical applications, especially in ocean engineering. However, it is difficult to construct an anticorrosion coating in water. In addition, curing kinetics, which are the key to enhance the performance of coatings, seem to hardly be observed and regulated in an underwater condition. Herein, a novel underwater in situ repairing coating was prepared. Meanwhile, electrochemical impedance spectroscopy (EIS) was applied to observe its curing behavior underwater. Adhesion tests showed that the coatings cured underwater had good adhesion to different substrate surfaces and the ideal ratio of curing agent to epoxy resin was 0.6. Long-term anticorrosive tests demonstrated that the coatings had an excellent anti-corrosion performance. The viscosity changes in different curing stages were well reflected by frequency response characteristics from Bode and Nyquist curves by EIS. Two equivalent electrical circuits were selected to simulate the impedance date at the initial and final curing stage. A formula was put forward to evaluate the curing degree during the curing process. Finally, the effects of temperature and the ingredient ratio on the reaction rate and curing degree were also investigated here. This underwater in situ repairing coating may find applications in many offshore engineering structures in marine environments, and the EIS technique has attractive development and application prospects when observing the curing information of thermosetting resin systems under special circumstances.

Preparation and Characterization of Activated Carbon/Polymer Composites: A Review

Activated carbon (AC) and activated carbon fibers (ACFs) are materials with a large specific surface area and excellent physical adsorption properties due to their rich porous structure, and they are used as electrode materials to improve the performance of adsorbents or capacitors. Recently, multiple studies have confirmed the applicability of AC/polymer compo-sites in various fields by exploiting the unique physical and chemical properties of AC. As the excellent mechanical properties, stability, antistatic and electromagnetic interference (EMI) shielding functions of activated carbon/polymer composite materials were confirmed in recent studies, it is expected that activated carbon can be utilized as an ideal reinforcing material for low-cost polymer composite materials. Therefore, in this review, we would like to describe the fabrication, characterization and applicability of AC/polymer composites.

Experimental Study of Curing Temperature Effect on Mechanical Performance of Carbon Fiber Composites with Application to Filament Winding Pressure Vessel Design

During the forming process of carbon fiber composite pressure vessels, the parameters of the curing and forming processes become one of the critical factors affecting the production cost and forming quality. The curing temperature of 4251 A4/B2 epoxy resin is measured in this research, and the effect of curing temperature on the mechanical properties of composite materials for winding is studied, which is finally verified in the test of pressure vessels. First, the actual curing temperature of the epoxy resin is tested and analyzed using differential scanning calorimetry (DSC). Second, under two different curing regimes, the tensile and flexural properties are tested by making pure epoxy resin matrix test pieces, Naval Ordnance Laboratory (NOL) rings, and carbon fiber composite unidirectional plates that affect the overall performance of composite pressure vessels. At the same time, the test results provide reliable process parameters for numerical simulation and manufacturing of pressure vessels. Finally, the filament-wound 35 MPa type III pressure vessel is cured and carried out using a hydraulic burst test. The results show the resin matrix has good fluidity and excellent interface bonding with carbon fiber when the curing temperature is 112 °C. Compared with the results in curing temperature of 100 °C, the tensile strength of the NOL ring reaches 2260.8 MPa, up by 22%. In the 90° direction, the tensile and flexural strengths of the unidirectional plates increase by 68.86% and 37.42%, respectively. In the 0° direction, the tensile and flexural strengths of the unidirectional plates increase by 5.82% and 1.16%, respectively. The pressure vessel bursting form is reasonable and meets the CGH2R standard. The bursting pressure of the vessel is up to 104.4 MPa, which verifies the rationality of the curing regime used in the curing process of the pressure vessel. Based on the results of this paper, the curing temperature affects the fluidity of the epoxy resin, which in turn affects the interfacial bonding properties of the composite, and the forming quality of the wound components and the pressure vessel, ultimately. When using 4251A4/B2 epoxy resin for wet winding pressure vessels, the choice of a 112 °C curing temperature will help improve the vessel's overall performance. This work could provide reliable experience and insight into the curing process analysis of pressure vessel manufacturing.

Predictive Modeling of Soft Stretchable Nanocomposites Using Recurrent Neural Networks

Human skin is characterized by rough, elastic, and uneven features that are difficult to recreate using conventional manufacturing technologies and rigid materials. The use of soft materials is a promising alternative to produce devices that mimic the tactile capabilities of biological tissues. Although previous studies have revealed the potential of fillers to modify the properties of composite materials, there is still a gap in modeling the conductivity and mechanical properties of these types of materials. While traditional Finite Element approximations can be used, these methodologies tend to be highly demanding of time and processing power. Instead of this approach, a data-driven learning-based approximation strategy can be used to generate prediction models via neural networks. This paper explores the fabrication of flexible nanocomposites using polydimethylsiloxane (PDMS) with different single-walled carbon nanotubes (SWCNTs) loadings (0.5, 1, and 1.5 wt.%). Simple Recurrent Neural Networks (SRNN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU) models were formulated, trained, and tested to obtain the predictive sequence data of out-of-plane quasistatic mechanical tests. Finally, the model learned is applied to a dynamic system using the Kelvin-Voight model and the phenomenon known as the bouncing ball. The best predictive results were achieved using a nonlinear activation function in the SRNN model implementing two units and 4000 epochs. These results suggest the feasibility of a hybrid approach of analogy-based learning and data-driven learning for the design and computational analysis of soft and stretchable nanocomposite materials.