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Monitoring of molding processes is one of the most challenging future tasks in polymer processing. In this work, the in situ monitoring of the curing behavior of highly filled EMCs (silica filler content ranging from 73 to 83 wt%) and the effect of filler load on curing kinetics are investigated. Kinetic modelling using the Friedman approach was applied using real-time process data obtained from in situ DEA measurements, and these online kinetic models were compared with curing analysis data obtained from offline DSC measurements. For an autocatalytic fast-reacting material to be processed above the glass transition temperature Tg and for an autocatalytic slow-reacting material to be processed below Tg, time–temperature–transformation (TTT) diagrams were generated to investigate the reaction behavior regarding Tg progression. Incorporating a material containing a lower silica filler content of 10 wt% enabled analysis of the effects of filler content on sensor sensitivity and curing kinetics. Lower silica particle content (and a larger fraction of organic resin, respectively) favored reaction kinetics, resulting in a faster reaction towards Tg1. Kinetic analysis using DEA and DSC facilitated the development of highly accurate prediction models using the Friedman model-free approach. Lower silica particle content resulted in enhanced sensitivity of the analytical method, leading, in turn, to more precise prediction models for the degree of cure.

This study investigated the impact of material properties of epoxy molding compounds on wafer warpage in fan-out wafer-level packaging. As there is currently a lack of comprehensive discussion on the various material property parameters of EMC materials, it is essential to identify the critical influencing factors and quantify the effects of each parameter on wafer warpage. The material properties include Young’s modulus of the epoxy molding compound before and after the glass transition temperature (Tg) range of 25–35 °C (EL) and 235–260 °C (EH), coefficient of thermal expansion (α1, α2), and the temperature change (∆T) between EL and EH. Results show that, within the range of extreme values of material properties, EL and α1 are the critical factors that affect wafer warpage during the decarrier process in fan-out packaging. α1 has a more significant impact on wafer warpage compared with EL. EH, α2, Tg, and ∆T have little influence on wafer warpage. Additionally, the study identified the optimized material property of the epoxy molding compound that can reduce the maximum wafer warpage in the X and Y directions from initial values of 7.34 mm and 7.189 mm to 0.545 mm and 0.45 mm, respectively, resulting in a reduction of wafer warpage of 92.58% (X direction) and 93.74% (Y direction). Thus, this study proposes an approach for evaluating the impact of material properties of epoxy molding compounds on wafer warpage in fan-out wafer-level packaging. The approach aims to address the issue of excessive wafer warpage due to material variation and to provide criteria for selecting appropriate epoxy molding compounds to enhance process yield in packaging production lines.

As the demand for smaller and more multifunctional integrated circuit (IC) products increases, system-in-package (SiP) has emerged as a key trend in IC encapsulation. However, the use of polymer-based materials such as epoxy molding compounds (EMCs) introduces complex flow behaviors during the encapsulation process, often leading to void formation, especially in highly integrated SiP structures. This study employs the Moldex3D 2024 R3 simulation software to perform mold-filling analyses of SiP packages using EMC as the encapsulant. The objective is to investigate why voids are consistently observed in the leftmost column of the strip and to determine how to reduce the void size using the Taguchi optimization method. To replicate the actual vacuum-assisted molding conditions, a 1/5 strip model with venting was established. Results show that the flow dynamics of the polymeric encapsulant are significantly affected by shielding frame geometry. Among various design modifications, adding an additional column of shielding metal frame on the left side of the strip most effectively reduces void formation. This research highlights the importance of polymer flow behavior in void prediction and optimization for advanced SiP packaging, providing practical guidelines for material-driven design improvements in IC encapsulation processes.

We report on the cure characterization, based on inline monitoring of the dielectric parameters, of a commercially available epoxy phenol resin molding compound with a high glass transition temperature (>195 °C), which is suitable for the direct packaging of electronic components. The resin was cured under isothermal temperatures close to general process conditions (165–185 °C). The material conversion was determined by measuring the ion viscosity. The change of the ion viscosity as a function of time and temperature was used to characterize the cross-linking behavior, following two separate approaches (model based and isoconversional). The determined kinetic parameters are in good agreement with those reported in the literature for EMCs and lead to accurate cure predictions under process-near conditions. Furthermore, the kinetic models based on dielectric analysis (DEA) were compared with standard offline differential scanning calorimetry (DSC) models, which were based on dynamic measurements. Many of the determined kinetic parameters had similar values for the different approaches. Major deviations were found for the parameters linked to the end of the reaction where vitrification phenomena occur under process-related conditions. The glass transition temperature of the inline molded parts was determined via thermomechanical analysis (TMA) to confirm the vitrification effect. The similarities and differences between the resulting kinetics models of the two different measurement techniques are presented and it is shown how dielectric analysis can be of high relevance for the characterization of the curing reaction under conditions close to series production.

An epoxy compound’s polymer structure can be characterized by the glass transition temperature (Tg) which is often seen as the primary morphological characteristic. Determining the Tg after manufacturing thermoset-molded parts is an important objective in material characterization. To characterize quantitatively the dependence of Tg on the degree of cure, the DiBenedetto equation is usually used. Monitoring polymer network formation during molding processes is therefore one of the most challenging tasks in polymer processing and can be achieved using dielectric analysis (DEA). In this study, the morphological properties of an epoxy resin-based molding compounds (EMC) were optimized for the molding process using response surface analysis. Processing parameters such as curing temperature, curing time, and injection rate were investigated according to a DoE strategy and analyzed as the main factors affecting Tg as well as the degree of cure. A new method to measure the Tg at a certain degree of cure was developed based on warpage analysis. The degree of cure was determined inline via dielectric analysis (DEA) and offline using differential scanning calorimetry (DSC). The results were used as the response in the DoE models. The use of the DiBenedetto equation to refine the response characteristics for a wide range of process parameters has significantly improved the quality of response surface models based on the DoE approach.

As one of the most widely used packaging materials, epoxy composite (EP) offers excellent insulation properties; however, its intrinsic low thermal conductivity (TC) limits its application in high-frequency and high-power devices. To enhance the TC of EP, six highly thermally conductive inorganic fillers, namely, Al2O3, MgO, ZnO, Si3N4, h-BN, and AlN, were incorporated into the EP matrix at varying contents (60–90 wt.%). The resulting epoxy molding compounds (EMCs) demonstrated significant improvement in thermal conductivity coefficient (λ) at high filler contents (90 wt.%), ranging from 0.67 W m−1 K−1 to 1.19 W m−1 K−1, compared to the pristine epoxy composite preform (ECP, 0.36 W m−1 K−1). However, it was found that the interfacial thermal resistance (ITR) between EP and filler materials is a major hindrance restricting TC improvement. In order to address this challenge, graphene nanosheets (GNSs) and carbon nanotubes (CNTs) were introduced as additives to reduce the ITR. The experimental results indicated that CNTs were effective in enhancing the TC, with the optimized EMC achieving a λ value of 1.14 W m−1 K−1 using 60 wt.% Si3N4 + 2 wt.% CNTs. Through the introduction of a small amount of CNT (2 wt.%), the inorganic filler content was significantly reduced from 90 wt.% to 60 wt.% while still maintaining high thermal conductivity (1.14 W m−1 K−1). We propose that the addition of CNTs helps in the construction of a partial heat conduction network within the EP matrix, thereby facilitating interfacial heat transfer.

Thermoplastic (TP) composites, known for their ease of handling, suitability for high production rates, and recyclability, are emerging as a promising alternative to thermoset-based composites. The expected growth in TP-based composites in automotive, sports, and aerospace industries may result in increased post industrial waste. To address this, we repurposed our in-house process scrapped carbon fibre-reinforced polycarbonate tapes into sheet moulding compounds (SMCs) and Hybridised SMCs (Hy-SMCs) using compression moulding. In Hy-SMCs, the top and bottom layers were unidirectional tapes, while the core section had randomly oriented platelets in a 50:50 ratio. Our evaluation included qualitative and thermo-mechanical standard tests. The incorporation of unidirectional tapes in Hy-SMCs significantly improved the tensile and flexural properties of SMCs. Specifically, these enhancements resulted in an impressive 81 to 85% increase in mechanical strength compared to the standard aluminium grade. Additionally, Hy-SMCs exhibited a 120 to 130% increase in tensile and flexural properties compared to SMCs. Fractography revealed a complex relation between fractured surfaces, with multimode failures in both SMCs and Hy-SMCs. Also, the non-destructive evaluation showed platelet reorientation during consolidation and localised voids with increased specimen thickness.

High-performance discontinuous carbon-fiber-reinforced thermoplastics (CFRTPs) offer promising manufacturing flexibility and recyclability for advanced composite applications. However, their mechanical performance and reliability strongly depend on the internal fiber architecture, which is largely determined by the molding process. In this study, three distinct compression molding approaches—CFRTP sheet molding compounds (SMCs), bulk molding compounds (BMCs), and free-edge molding compounds (FMCs)—were systematically evaluated to investigate how processing parameters affect fiber orientation, tape deformation, and impregnation quality. X-ray micro-computed tomography (XCT) was employed to visualize and quantify the internal structures of each material, focusing on the visualization and quantification of in-plane and out-of-plane fiber alignment and other internal structure features. The results indicate that CFRTP-SMC retains largely intact tape layers and achieves better impregnation, leading to more uniform and predictable internal geometry. Although CFRTP-BMC exhibits greater tape deformation and splitting due to increased flow, its simpler molding process and better tolerance for tape shape distortion suggest potential advantages for recycled applications. In contrast, CFRTP-FMC shows significant tape fragmentation and poor impregnation, particularly near free edges. These findings underscore the critical role of a controlled molding process in achieving a consistent internal structure for these materials for the first time. This study highlights the utility of advanced XCT methods for optimizing process design and advancing the use of high-performance discontinuous CFRTP in industry.

The electric energy metering box serves as a crucial node in power grid operations, offering essential protection for key components in the distribution network, such as smart meters, data acquisition terminals, and circuit breakers, thereby ensuring their safe and reliable operation. However, the non-metallic housings of these boxes are susceptible to aging under environmental stress, which can result in diminished flame-retardant properties and an increased risk of fire. Currently, there is a lack of rapid and accurate methods for assessing the fire resistance of non-metallic metering box enclosures. In this study, laser-induced breakdown spectroscopy (LIBS), which enables fast, multi-element, and non-contact analysis, was utilized to develop an effective assessment approach. Thermal aging experiments were conducted to systematically investigate the degradation patterns and mechanisms underlying the reduced flame-retardant performance of sheet molding compound (SMC), a representative non-metallic material used in metering box enclosures. The results showed that the intensity ratio of aluminum ionic spectral lines is highly correlated with the flame-retardant grade, serving as an effective performance indicator. On this basis, a one-dimensional convolutional neural network (1D-CNN) model was developed utilizing LIBS data, which achieved over 92% prediction accuracy for different flame-retardant grades on the test set and demonstrated high recognition accuracy for previously unseen samples. This method offers significant potential for rapid, on-site evaluation of flame-retardant grades of non-metallic electric energy metering boxes, thereby supporting the safe and reliable operation of power systems.

Recent years introduced process and material innovations in the design and manufacturing of lightweight body parts for larger scale manufacturing. However, lightweight materials and new manufacturing technologies often carry a higher environmental burden in earlier life cycle stages. The prospective life cycle evaluation of lightweight body parts remains to this day a challenging task. Yet, a functioning evaluation approach in early design stages is the prerequisite for integrating assessment results in engineering processes and thus allowing for a life cycle oriented decision making. The current paper aims to contribute to the goal of a prospective life cycle evaluation of fiber-reinforced lightweight body parts by improving models that enable to predict energy and material flows in the manufacturing stage. To this end, a modeling and simulation approach has been developed that integrates bottom-up process models into a process chain model. The approach is exemplarily applied on a case study of a door concept. In particular, the energy intensity of compression molding of glass fiber and carbon fiber sheet molding compounds has been analyzed and compared over the life cycle with a steel reference part.