Yoon-Ji Yim, Young-Hoon Yoon, Seong-Hwang Kim
et al.
Carbon nanotubes (CNTs) have garnered significant interest in the field of nanotechnology owing to their unique structure and exceptional properties. These materials find applications across a diverse array of fields, including electronics, environmental science, energy, and biotechnology. CNTs serve as potent reinforcing agents in polymer composites; even minimal additions can significantly improve the mechanical, electrical, and thermal properties of polymers. With the growing demand for polymer composites across various industries, there is an anticipation for CNT/polymer composites to evolve in increasingly diverse directions. This paper reviews recent advancements in the manufacturing techniques of various CNT/polymer composites and discusses the enhancements in their mechanical, electrical, and thermal properties. Furthermore, it explores the potential applications of these composites.
This paper systematically reviews the research progress and application prospects of machine learning technologies in the field of polymer materials. Currently, machine learning methods are developing rapidly in polymer material research; although they have significantly accelerated material prediction and design, their complexity has also caused difficulties in understanding and application for researchers in traditional fields. In response to the above issues, this paper first analyzes the inherent challenges in the research and development of polymer materials, including structural complexity and the limitations of traditional trial-and-error methods. To address these problems, it focuses on introducing key basic technologies such as molecular descriptors and feature representation, data standardization and cleaning, and records a number of high-quality polymer databases. Subsequently, it elaborates on the key role of machine learning in polymer property prediction and material design, covering the specific applications of algorithms such as traditional machine learning, deep learning, and transfer learning; further, it deeply expounds on data-driven design strategies, such as reverse design, high-throughput virtual screening, and multi-objective optimization. The paper also systematically introduces the complete process of constructing high-reliability machine learning models and summarizes effective experimental verification, model evaluation, and optimization methods. Finally, it summarizes the current technical challenges in research, such as data quality and model generalization ability, and looks forward to future development trends including multi-scale modeling, physics-informed machine learning, standardized data sharing, and interpretable machine learning.
S. Pervaiz, Taimur A. Qureshi, Ghanim Kashwani
et al.
Composite materials are a combination of two or more types of materials used to enhance the mechanical and structural properties of engineering products. When fibers are mixed in the polymeric matrix, the composite material is known as fiber-reinforced polymer (FRP). FRP materials are widely used in structural applications related to defense, automotive, aerospace, and sports-based industries. These materials are used in producing lightweight components with high tensile strength and rigidity. The fiber component in fiber-reinforced polymers provides the desired strength-to-weight ratio; however, the polymer portion costs less, and the process of making the matrix is quite straightforward. There is a high demand in industrial sectors, such as defense and military, aerospace, automotive, biomedical and sports, to manufacture these fiber-reinforced polymers using 3D printing and additive manufacturing technologies. FRP composites are used in diversified applications such as military vehicles, shelters, war fighting safety equipment, fighter aircrafts, naval ships, and submarine structures. Techniques to fabricate composite materials, degrade the weight-to-strength ratio and the tensile strength of the components, and they can play a critical role towards the service life of the components. Fused deposition modeling (FDM) is a technique for 3D printing that allows layered fabrication of parts using thermoplastic composites. Complex shape and geometry with enhanced mechanical properties can be obtained using this technique. This paper highlights the limitations in the development of FRPs and challenges associated with their mechanical properties. The future prospects of carbon fiber (CF) and polymeric matrixes are also mentioned in this study. The study also highlights different areas requiring further investigation in FDM-assisted 3D printing. The available literature on FRP composites is focused only on describing the properties of the product and the potential applications for it. It has been observed that scientific knowledge has gaps when it comes to predicting the performance of FRP composite parts fabricated under 3D printing (FDM) techniques. The mechanical properties of 3D-printed FRPs were studied so that a correlation between the 3D printing method could be established. This review paper will be helpful for researchers, scientists, manufacturers, etc., working in the area of FDM-assisted 3D printing of FRPs.
Laetitia Bolte, Heiner Gers-Barlag, Guido Heinsohn
et al.
Polyolefins such as high-density polyethylene (HDPE), low-density polyethylene (LDPE), and polypropylene (PP) are among the most widely used packaging materials in the cosmetic industry. Since these materials are in direct contact with cosmetic products, various components of the products are adsorbed to the packaging material’s surface and migrate within the amorphous regions of the polyolefin. This migration process, which occurs in both virgin and post-consumer recyclate (PCR) materials, can lead to deformation of the packaging. In this study, different types of virgin and PCR pellets were examined to investigate their interaction with cosmetic products and to understand the factors influencing the migration process. The migration of cosmetic oils was observed in all pellet samples, depending on the composition of the product and environmental conditions. The process was characterized by the weight gain of the plastic pellets and further identified through nuclear magnetic resonance (NMR) and infrared (IR) spectroscopy. Additionally, differential scanning calorimetry (DSC) and gel permeation chromatography (GPC) measurements were performed to analyze the polymer structure. Components with lower molecular weight (MW), high nonpolarity, and elevated temperatures were found to accelerate the migration process. Moreover, migration occurred more slowly from oil-in-water emulsions with larger droplet sizes compared to water-in-oil systems with smaller droplets. Among the different polyolefins, PP demonstrated a higher uptake of migrating components but at a slower migration rate compared to HDPE and LDPE. When comparing virgin and recycled polyolefins, it was observed that migration was consistently slower in virgin materials than in recycled ones. The ability of oils to migrate is influenced by the molecular structure of the polymers: high density, crystallinity, and low levels of branching reduce both the migration speed (MS) and the maximum saturation, as seen in virgin HDPE. In contrast, materials like LDPE, with a less dense polymer structure, exhibited higher MSs and saturation limits. As a control, polyethylene terephthalate (PET) was used, and it showed no migration due to the polymer’s high density.
Laura Fernandez-Pena, Eduardo Guzman, Francisco Ortega
et al.
The adsorption of mixtures of charged polymers onto solid surfaces presents a big interest in different technological and industrial fields, and in particular, in cosmetics. This requires to deepen on the most fundamental physico-chemical bases governing the deposition, which is generally correlated to the interactions occurring in solution. This work explores the interaction in solution of model polymer mixtures formed by a cationic homopolymer (poly(diallyl-dimethyl-ammonium chloride), PDADMAC) and a zwitterionic copolymer (copolymer of acrylic acid, 3-Trimethylammonium propyl methacrylamide chloride and acrylamide, Merquat 2003), and the adsorption of such mixtures onto negatively charged surfaces. The analysis of the interactions occurring in solution between both polymers performed using dynamic light scattering (DLS), electrophoretic mobility and viscosity measurements, combined with the study of the deposition of the layers of mixtures containing different weight fractions of each polymer using ellipsometry and quartz crystal microbalance with dissipation monitoring (QCM-D) has shown that the interpolymer complexes formed in solution, and their composition, governs the deposition onto the solid surface and the tribological properties of the adsorbed layers as shown the Surface Force Apparatus (SFA) experiments, allowing for a control of the physico-chemical properties and structure of the layers. Furthermore, the use of Self Consistent Mean Fields Calculations (SCF) confirms the picture obtained from the experimental studies of the adsorbed layers, providing a prediction of the distribution of the polymer chains within the adsorbed layers. It is expected that this study can help on the understanding of the correlations existing between the behavior of future associations of innovative and eco-sustainable polymers and their adsorption processes onto solid surface.
Polymer membranes are central to the proper operation of several processes used in a wide range of applications. The production of these membranes relies on processes such as phase inversion, stretching, track etching, sintering, or electrospinning. A novel and competitive strategy in membrane production is the use of additive manufacturing that enables the easier manufacture of tailored membranes. To achieve the future development of better membranes, it is necessary to compare this novel production process to that of more conventional techniques, and clarify the advantages and disadvantages. This review article compares a conventional method of manufacturing polymer membranes to additive manufacturing. A review of 3D printed membranes is also done to give researchers a reference guide. Membranes from these two approaches were compared in terms of cost, materials, structures, properties, performance. and environmental impact. Results show that very few membrane materials are used as 3D-printed membranes. Such membranes showed acceptable performance, better structures, and less environmental impact compared with those of conventional membranes.
Nina Verdier, Gabrielle Y. Foran, D. Lepage
et al.
With the ever-growing energy storage notably due to the electric vehicle market expansion and stationary applications, one of the challenges of lithium batteries lies in the cost and environmental impacts of their manufacture. The main process employed is the solvent-casting method, based on a slurry casted onto a current collector. The disadvantages of this technique include the use of toxic and costly solvents as well as significant quantity of energy required for solvent evaporation and recycling. A solvent-free manufacturing method would represent significant progress in the development of cost-effective and environmentally friendly lithium-ion and lithium metal batteries. This review provides an overview of solvent-free processes used to make solid polymer electrolytes and composite electrodes. Two methods can be described: heat-based (hot-pressing, melt processing, dissolution into melted polymer, the incorporation of melted polymer into particles) and spray-based (electrospray deposition or high-pressure deposition). Heat-based processes are used for solid electrolyte and electrode manufacturing, while spray-based processes are only used for electrode processing. Amongst these techniques, hot-pressing and melt processing were revealed to be the most used alternatives for both polymer-based electrolytes and electrodes. These two techniques are versatile and can be used in the processing of fillers with a wide range of morphologies and loadings.
Almuqrin Aljawhara H., ALasali Heba Jamal, Sayyed M. I.
et al.
The present work aims to fabricate new inexpensive epoxy-based composites with a concentration described by the formula (90 − x)epoxy + 10Sb2O3 + xPbO, where x = 5, 10, 15, and 20 wt%. The impacts of the substitution of epoxy by PbO on the composite density and radiation shielding properties of the fabricated composites were studied. The density of the fabricated composites varied between 1.30 and 1.49 g·cm−3, enriching the PbO concentration. Utilizing the narrow beam transmission method, the linear attenuation coefficient (LAC) of the fabricated composites was measured using the NaI (Tl) detector as well as radioactive sources Am-241 and Cs-137. The LAC increased by 84% and 18% at gamma-ray energy of 0.059 and 0.662 MeV, when the PbO concentration raised between 5 and 20 wt%, respectively. Then the transmission rate and half-value layer of the fabricated composites were reduced by raising the PbO concentration. Therefore, the fabricated composite has good shielding properties in the low gamma-ray energy interval to be suitable for medical applications and low radioactive waste container constructions.
Dielectric analysis (DEA) is an effective method for monitoring the curing process of epoxy resin (EP) in situ, but the influence of curing temperature on the measurement results limits the application of DEA in curing process monitoring with variable temperature. In this study, the theoretical basis of using the glass transition as a bridge and monitoring the curing degree by ionic conductivity was analyzed. DEA experiments and differential scanning calorimeter (DSC) experiments were carried out and the mathematical model of ionic conductivity, glass transition temperature, and curing degree of the EP established. The parameters in the model were only related to the composition of EP system in the model as verified for implementing curing-degree monitoring of the EP system cured at variable temperature. The FT-IR spectra measurement was carried out and the activation energy of curing reaction was calculated by results of DEA and DSC, which verified the reliability and scientificity of the method. The method of using glass transition as a bridge can monitor the curing degree in the curing process with variable temperature and extends DEA to the monitoring of this process under variable temperatures.
Ralfs Pomilovskis, Eliza Kaulina, Inese Mierina
et al.
It is crucial to adapt the processing of forest bio-resources into biochemicals and bio-based advanced materials in order to transform the current economic climate into a greener economy. Tall oil, as a by-product of the Kraft process of wood pulp manufacture, is a promising resource for the extraction of various value-added products. Tall oil fatty acids-based multifunctional Michael acceptor acrylates were developed. The suitability of developed acrylates for polymerization with tall oil fatty acids-based Michael donor acetoacetates to form a highly cross-linked polymer material via the Michael addition was investigated. With this novel strategy, valuable chemicals and innovative polymer materials can be produced from tall oil in an entirely new way, making a significant contribution to the development of a forest-based bioeconomy. Two different tall oil-based acrylates were successfully synthesized and characterized. Synthesized acrylates were successfully used in the synthesis of bio-based thermoset polymers. Obtained polymers had a wide variety of mechanical and thermal properties (glass transition temperature from –12.1 to 29.6 °C by dynamic mechanical analysis, Young's modulus from 15 to 1 760 MPa, and stress at break from 0.9 to 16.1 MPa). Gel permeation chromatography, Fourier-transform infrared (FT-IR) spectroscopy, matrix-assisted laser desorption/ionization-time of flight mass spectrometry, and nuclear magnetic resonance were used to analyse the chemical structure of synthesized acrylates. In addition, various titration methods and rheology tests were applied to characterize acrylates. The chemical composition and thermal and mechanical properties of the developed polymers were studied by using FT-IR, solid-state nuclear magnetic resonance, thermal gravimetric analysis, differential scanning calorimetry, dynamic mechanical analysis, and universal strength testing apparatus.
Yueqiong Wang, Hongchao Liu, Tingting Zheng
et al.
The crosslinking network structure is a crucial factor influencing the properties of natural rubber. Therefore, investigating the impact of different vulcanization bond types on the strain-induced crystallization behavior and properties of natural rubber can provide a theoretical foundation for producing high-performance natural rubber. In this study, diverse curing systems were employed to produce vulcanized natural rubbers with varying crosslink types. The crosslinking network structures of the vulcanized rubbers were analyzed using the tube model theory. Additionally, the effects of vulcanization bonds on strain-induced crystallization behavior and tensile properties were examined through in-situ X-ray diffraction and a tensile testing machine. The results revealed that the vulcanizate with monosulfidic bonds, formed under the effective vulcanization (EV) system, primarily comprised chemical crosslinking networks, resulting in a high tensile modulus, low elongation at break, and low tensile strength. Conversely, the vulcanizate under the conventional vulcanization (CV) system exhibited a distinct entanglement network impact compared to the chemical crosslinking network, resulting in a smaller tensile modulus but the highest elongation at break and the largest tensile strength. These differences stemmed from the distinct roles of vulcanization bonds within the crosslinking network. Specifically, the relatively short monosulfidic bond quickly reached the critical degree of orientation for crystallization during stretching, leading to higher crystallinity under the same strain. However, its shorter length caused earlier fracture during stretching, resulting in network heterogeneity, reduced elongation at break, and lower tensile strength. On the other hand, the longer polysulfidic bond underwent fracture recombination during stretching, with slower orientation and delayed crystallization. Nonetheless, this recombination improved network uniformity and integrity due to stress dissipation from the initial fracture, enhancing crystallinity, elongation at break, and tensile strength. This study elucidated the influence of vulcanization crosslinking on the tensile properties of vulcanizates.
Predicting material properties of 3D printed polymer products is a challenge in additive manufacturing due to the highly localized and complex manufacturing process. The microstructure of such products is fundamentally different from the ones obtained by using conventional manufacturing methods, which makes the task even more difficult. As a first step of a systematic multiscale approach, in this work, we have developed an artificial neural network (ANN) to predict the mechanical properties of the crystalline form of Polyamide12 (PA12) based on data collected from molecular dynamics (MD) simulations. Using the machine learning approach, we are able to predict the stress-strain relations of PA12 once the macroscale deformation gradient is provided as an input to the ANN. We have shown that this is an efficient and accurate approach, which can provide a three-dimensional molecular-level anisotropic stress-strain relation of PA12 for any macroscale mechanics model, such as finite element modeling at arbitrary quadrature points. This work lays the foundation for a multiscale finite element method for simulating semicrystalline polymers, which will be published as a separate study.
Angel Garcia-Chung, Matthew F. Carney, James B. Mertens
et al.
We present the first empirical constraints on the polymer scale describing polymer quantized GWs propagating on a classical background. These constraints are determined from the polymer-induced deviation from the classically predicted propagation speed of GWs. We leverage posterior information on the propagation speed of GWs from two previously reported sources: 1) inter-detector arrival time delays for signals from the LIGO-Virgo Collaboration's first gravitational-wave transient catalog, GWTC1, and 2) from arrival time delays between GW signal GW170817 and its associated gamma-ray burst GRB170817A. For pure-GW constraints, we find relatively uninformative combined constraints of $ν= 0.96\substack{+0.15 \\ -0.21} \times 10^{-53} \, \rm{kg}^{1/2}$ and $μ= 0.94\substack{+0.75 \\ -0.20} \times 10^{-48} \, \rm{kg}^{1/2} \cdot s$ at the $90\%$ credible level for the two polymer quantization schemes, where $ν$ and $μ$ refer to polymer parameters associated to the polymer quantization schemes of propagating gravitational degrees of freedom. For constraints from GW170817/GRB170817A, we report much more stringent constraints of $ν_{\mathrm{low}} =2.66\substack{+0.60 \\ -0.10}\times 10^{-56}$, $ν_{\mathrm{high}} = 2.66\substack{+0.45 \\ -0.10}\times 10^{-56} $ and $μ_{\mathrm{low}} = 2.84\substack{+0.64 \\ -0.11}\times 10^{-52}$, $μ_{\mathrm{high}} = 2.76\substack{+0.46 \\ -0.11}\times 10^{-52}$ for both representations of polymer quantization and two choices of spin prior indicated by the subscript. Additionally, we explore the effect of varying the lag between emission of the GW and EM signals in the multimessenger case.
Xavier Guidetti, Efe C. Balta, Yannick Nagel
et al.
When manufacturing parts using material extrusion additive manufacturing and anisotropic polymers, the mechanical properties of a manufactured component are strongly dependent on the print trajectory orientation. We conduct non-planar slicing and optimize the print trajectories to maximize the alignment between the material deposition direction and the stress flow induced by a predefined load case. The trajectory optimization framework considers manufacturability constraints in the form of uniform layer height and line spacing. We demonstrate the method by manufacturing a load bearing mechanical bracket using a 5-axis 3D printer and a liquid crystal polymer material. The failure strength and stiffness of the optimized bracket are improved by a factor of 44 and 6 respectively when compared with conventional printing.
The objective of this research is to use zinc oxide nanoparticles (ZnONPs) combined with buffing dust to develop footwear insole with antibacterial properties. In addition, performance analysis (mechanical, chemical, and thermal) of fabricated insole is also the integral consideration of this study. With such aim, antimicrobial composite insoles were fabricated via simple solution mixing of ZnONPs and natural rubber latex (NRL) binder along with buffing dusts with optimum ratio. Then, removal of water was considered by mechanical pressing followed by natural drying in sunlight. The chemical bonding and material interactions of composites were investigated using FT-IR and XRD, respectively. TGA analysis confirmed the thermal stability of composites, while SEM and OTR are elucidating the surface morphology and gas barrier properties, respectively. Tensile strength, elongation, flexibility, hardness, and water absorption of prepared composite with optimum NRL content were increased by 39, 31, 30, 38, and 28%, respectively. Finally, 78% antimicrobial performance was achieved against the suspension of (1.5×106 CFU/mL) bacterial strain Staphylococcus aureus.
Ahmed N. Al-hakimi, G.M. Asnag, Fahad Alminderej
et al.
Nanocomposite electrolyte samples, which composed of PVA/CMC blend with selenium nanoparticles (Se NPs), were prepared by a solution cast method. The structure of the samples was analyzed using XRD and FTIR, which confirmed the interactions between PVA/CMC blend and Se NPs. Also, the decreases in the value of optical energy gaps confirm the dispersed selenium nanoparticles into PVA/CMC samples. DSC curve of pure sample showed single glass transition (Tg) temperature peak at 102.17 °C which indicates that the blend components were miscible. SEM micrographs show white granules on the surface of the filled samples, which were assigned to Se NPs. The maximum electrical conductivity was found with PVA/CMC/0.80 wt % Se NPs is 2.24 × 10−6 S/cm at room temperature with 20 MHz. The antibacterial activity index showed an increase in the diameters zone with increasing the selenium nanoparticles concentration. The results confirm that adding of selenium nanoparticles to PVA/CMC blend caused to increase the antibacterial activity of samples that suggests the potential of this nanocomposite to be used in many antimicrobial applications and has the possibility for usage in food packaging industries.