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Thermal deformations that occur during formation of long-fiber-reinforced composites have been a continued challenge for manufacturers as the final shape of a given part can be different from the original mold shape. The ensuing dimensional distortions can be difficult to predict due to complex thermo-mechanical behaviour of composite laminates during different forming cycles. This study intends to model the fundamental mechanisms that lead to thermal deformations during forming of a thermoplastic matrix composite comprised of comingled polypropylene and E-glass fibers. While the discussion is framed around a custom-design multi-stage roll-forming process, it is also relevant to a wider range of thermoplastic composites manufacturing processes. A methodology is developed to characterize the thermal mechanical behavior of the material, optimize the manufacturing process, and predict the magnitude of resulting spring-in angle due to thermal deformations. It is found that the process control parameters can be optimized first such that the crystallization of the matrix occurs at an ideal position along the forming line. Once the process is optimized, the developed numerical model, with a thermoelastic material behaviour, can give an adequate prediction of spring-in at the end of the process. Finally, through a comparative study, it is discussed how for other manufacturing processes, such as compression molding, including a thermoviscoelastic liquid/solid material behaviour may be required to yield accurate spring-in predictions. [ABSTRACT FROM PUBLISHER]

Experimental results in the literature indicate notable non-repeatabilities during mechanical testing of woven fabrics, even under the same loading conditions, which may be linked to the presence of defects and uncertainties at meso or micro levels in yarns. Sources of such uncertainties can include both yarn dimensional tolerances and variations in the fiber/matrix material properties. The aim of this article is to conduct a systematic sensitivity analysis on the meso-level uncertainty factors in a typical woven fabric and identify the most significant factors and their interactions under a trellising mode. A finite element model capable of capturing behavior of dry yarns, along with a two-level full-factorial design approach has been employed. Factorial designs are split into two categories of the geometrical and material factors. It is shown how the obtained range of variations from the above statistical designs may be used to capture non-repeatability in some trellising tests. [ABSTRACT FROM AUTHOR]

The design of critical components for aerospace applications involves a number of conflicting functional requirements: reducing fuel consumption, cost, and weight, while enhancing performance, operability and robustness. As several materials systems and concepts remain competitive, a new approach that couples finite element analysis (FEA) and established multicriteria optimization protocols is developed in this paper. To demonstrate the approach, a prototypical materials selection problem for gas turbine combustor liners is chosen. A set of high temperature materials systems consisting of superalloys and thermal barrier coatings is considered as candidates. A thermo-mechanical FEA model of the combustor liner is used to numerically predict the response of each material system candidate. The performance of each case is then characterized by considering the material cost, manufacturability, oxidation resistance, damping behavior, thermomechanical properties, and the FEA postprocessed parameters relating to fatigue and creep. Using the obtained performance values as design criteria, an ELECTRE multiple attribute decision-making (MADM) model is employed to rank and classify the alternatives. The optimization model is enhanced by incorporating the relative importance (weighting factors) of the selection criteria, which is determined by multiple designers via a group decision-making process., Engineering and Applied Sciences

The demand for stretchable strain sensors with customizable sensitivities has increased across a spectrum of applications, spanning from human motion detection to plant growth monitoring. Nevertheless, a major challenge remains in the digital fabrication of scalable and cost‐efficient strain sensors with tailored sensitivity to diverse demands. Currently, there is a lack of simple digital fabrication approaches capable of adjusting strain sensitivity in a controlled way with no changes to the material and without affecting the linearity. In this study, parallel microgates‐based strain sensors whose strain sensitivity can be adjusted systematically throughout an all‐laser‐based fabrication process without any material replacement are presented. The technique employs a two‐step direct laser writing method that combines the well‐established capabilities of laser ablation and laser marking, boasting a varying gauge factor of up to 433% (GF  =  168), while paving the way for the mass production of nanocomposite strain sensors. Parallel microgates‐based strain sensors exhibit a remarkable signal‐to‐noise ratio at ultralow strains (ɛ  =  0.001), rendering them ideal for monitoring the gradual growth of plants. As an application demonstration, the proposed sensors are deployed on tomato plants to capture their growth under varying planting conditions including hydroponic and soil mediums, as well as diverse irrigation regimens. [ABSTRACT FROM AUTHOR]

This article, through an industrial-level case study, presents workflows employed for decision-making to mitigate cracking of glass fibre reinforced polymer (GFRP) parts in tight radii corner locations, often resulting from displacement-controlled de-moulding processes. Namely, using process simulation to evaluate the cure cycle of the GFRP composite parts, it was possible to optimize the time of de-moulding and reduce the potential for part damage. It was observed that the most significant factors influencing the corner defect were boundary conditions of the part during de-moulding, the workshop temperature and part thickness. The poorest process design case was identified as hot workshop temperature, a laminate with thickness on the upper end of tolerances and a boundary condition where most sides are free, allowing for the development of larger moment forces at the tight corners. Further to this, a de-moulding time chart was developed to account for the changes in material properties as a function of temperature and material thickness, allowing for the in situ decision-making of technicians to reduce the occurrence of corner cracks. [ABSTRACT FROM AUTHOR]

Ice buildup can significantly and negatively impact system performance in various industrial sectors, and has remained a persistent challenge for decades. Many compliant materials exhibit excellent de‐icing performance but are easily eroded by impacts from supercooled water droplets, sand, dust, and debris. A composite panel inspired by animal skin, consisting of a facesheet protecting a nanofluid layer beneath, which exhibits durable anti‐icing and tunable photothermal properties is proposed. The viscous liquid layer beneath the facesheet increases flexural rigidity, preventing large deflections and increasing deformation resistance, which alters ice's adhesion to the surface. The non‐uniform fluid pressure exerted by the viscous nanofluid‐filled composite panels facilitates ice detachment, resulting in ice adhesion strengths as low as τice ≈ 10 kPa. Further, by altering the fluid properties, different additional functionalities can be endowed to the system. Incorporating fumed silica in a fluid‐filled composite panel results in rheopectic behavior, and this doubles their impact resistance when the shear thickening properties are properly tuned. Additionally, the combination of a transparent facesheet and a solar light absorbent nanofluid allows for tunable photothermal properties, further enhancing the anti‐icing performance of the system. This durable and tunable nanofluid‐filled composite panel shows great promise as a multifunctional de‐icing material. [ABSTRACT FROM AUTHOR]

The master S-N curve approach has been previously introduced for assessing the fatigue life of welded components; particularly for weldments in pipelines and marine structures (ASME Sec. VIII Div. 2 and API 579/ASME FFS-1). The approach relies on several past successful industrial applications and has offered two major advancements in fatigue analysis of welded joints using finite element. These advancements include an equivalent structural stress method which provides a mesh-insensitive quantity adjacent to the joint's weld line, and the S-N curve analysis based on the equivalent structural stress. In the present study, the master S-N curve approach is assessed as a possible new methodology to deal with the breathing induced fatigue analysis of steel ‘plate girders’. In fact, when plate girders of steel or composite bridges are subjected to repeated loading of vehicles, the web panels designed according to tension field action undergo relatively repeated large out-of-plane deformations. This phenomenon is known as breathing effect and can result in fatigue cracking at welded web plate boundaries. In this work, first, mesh-insensitivity of the structural stress method is demonstrated for the breathing web of a plate girder. Secondly, through available experimental data, the accuracy of the master S-N curve for fatigue life evaluation of breathing cases is validated. Finally, the application of the master S-N curve approach for fatigue analysis of breathing webs through FE simulation of multiple plate girders is illustrated and the effect of initial out-of-plane displacement as an important geometrical parameter in the girders' fatigue behavior is investigated. [ABSTRACT FROM AUTHOR]

Biomaterials are increasingly being designed and adapted to a wide range of structural applications, owing to their superior mechanical property-to-weight ratios, low cost, biodegradability, and CO2 capture. Bamboo, specifically, has an interesting anatomy with long tube-like vessels present in its microstructure, which can be exploited to improve its mechanical properties for structural applications. By filling these vessels with a resin, e.g. an applied external loading would be better distributed in the structure. One recent method of impregnating the bamboo is plastination, which was originally developed for preserving human remains. However, the original plastination process was found to be slow for bamboo impregnation application, while being also rather complicated/methodical for industrial adaptation. Accordingly, in this study, an improved plastination method was developed that is 40% faster and simpler than the original method. It also resulted in a 400% increase in open-vessel impregnation, as revealed by Micro-X-ray Computed Tomography imaging. The improved method involves three steps: acetone dehydration at room temperature, forced polymer impregnation with a single pressure drop to − 23 inHg, and polymer curing at 130 °C for 20 min. Bamboo plastinated using the new method was 60% stronger flexurally, while maintaining the same modulus of elasticity, as compared to the virgin bamboo. Most critically, it also maintained its biodegradability from cellulolytic enzymes after plastination, as measured by a respirometric technique. Fourier transform infrared-attenuated total reflection, and thermogravimetric analyses were conducted and showed that the plastinated bamboo's functional groups were not altered significantly during the process, possibly explaining the biodegradability. Finally, using cone calorimetry, plastinated bamboo showed a faster ignition time, due to the addition of silicone, but a lower carbon monoxide yield. These results are deemed as a promising step forward for further improvement and application of this highly abundant natural fiber in engineering structures. [ABSTRACT FROM AUTHOR]

Through the use of post-tensioned (PT) elements in steel beam-column connections, steel buildings under seismic excitations can return to their plumb position, displaying negligible permanent deformation. The cyclic behavior of a PT connection is affected by several design parameters. This paper aims at identifying the significant factors which affect the cyclic response of steel PT connections with top-and-seat angles. A sequential fractional factorial design-of-experiment methodology is used to statistically evaluate the effects of different design factors as well as their interactions on the cyclic response of PT connections. To this end, 3D finite element models are first developed to accurately simulate the cyclic behavior of the connections. After validating the finite element results with the past experimental data, a two-stage (sequential) sensitivity analysis is conducted. Eight potential factors, including the material and geometric properties of steel angles, reinforcing plates, and bolts, are considered. The cyclic response of connections is examined in terms of stiffness, strength, energy dissipation capacity, and residual displacement. From this parametric study, the significance of the design factors is determined with respect to each response. Additionally, regression models are presented to estimate the response quantities for other PT connection configurations with the same beam and column sections. [ABSTRACT FROM AUTHOR]

There remain major concerns over the increasing use and waste of materials and energy resources in multiple manufacturing sectors. To address these concerns, some manufacturers have begun to align their R&D efforts with the circular economy principles: Reduce, Reuse, Recycle and Replace (RRRR). Focusing on advanced composites manufacturing sector, this paper presents an innovative approach for process design and analysis of a new waste heat recovery system for carbon fiber manufacturing. Namely, the stabilization process is known to be one of the most critical steps in the production of carbon fibers, as it consumes the most energy, has the largest factory footprint, is a complex system composed of many components, and is the largest capital investment within the factory line. The heat recovery system in this step of the manufacturing can notably reduce energy consumption, emission, cost, and conversion time, while aiming to maintain the mechanical properties of the final product. Here, via an actual industry-scale fibre production setting, the energy consumption factors were obtained and used to model the total energy and its balance in the thermal stabilization step. Two machine learning approaches with limited data, Artificial Neural Network and Non-Linear Regression were then constructed to predict the energy consumption. Results suggested that using the recovery system by means of a heat exchanger, can yield over 62.7 kW recovery, corresponding to 64% of total exhausted energy from the entire process. The electric energy consumption was reduced from 73.3 kW to 10.2 kW, which corresponded to an 86% improvement in the total energy efficiency. The model also confirmed that, by preheating the make-up air with the recovered energy, the energy performance index of the thermal stabilization can be increased from 0.08 to 0.44, along with a reduction in the process carbon footprint by 28.5 t/y. This is especially crucial as we are turning on smart digitalisation in manufacturing inspired by industry 4.0 concept with limited data. Waste heat recovery system for stabilization process of carbon fiber manufacturing. [Display omitted] • Measurement of key factors in energy and resource flows in the carbon fiber stabilization process. • Development of two machine learning models for prediction of the stabilization energy consumption. • Reducing the energy consumption of stabilization process through a heat recovery system. • The electric energy consumption can be improved up to 86% in the total energy efficiency. • The ANN model confirmed that the energy performance index can be increased from 0.08 to 0.44. [ABSTRACT FROM AUTHOR]

In recent years, there has been a significant global shift towards use of polymer matrix composite materials in a wide range of industries, including aerospace, automotive, marine, and sports, among others. Despite the rapid uptake and widespread adoption of this material technology, there are still technical challenges faced daily by manufactures due to the inherent complexities of different composite processing techniques. This paper aims at establishing a new scheme for better quality control management of resin transfer molding (RTM) processing for thermosetting composites, using a Bayesian belief network (BBN). The data were collected through knowledge engineering among the manufacturing experts with the help of real-life application history. A total of 13 governing factors for the RTM process, which would theoretically have a role on the final product quality, were identified. The sensitivity analysis of the BBN showed that the major contributing factors of the quality are the resin viscosity profile, part design features, resin cure peak temperature, and reinforcement permeability. The conditional probability tables were constructed using a quality index from industrial experts, and the causal relationships captured by the BBN were built using knowledge engineering. It is also shown how the basic BBN model can be further updated by integrating the interaction weights between the attributes that define the product quality. [ABSTRACT FROM AUTHOR]

Vehicles experience off-axial loads as well as axial loads during collisions. Hence, it is essential to have oblique loads be involved in investigating thin-walled tubes in vehicles as energy absorbers. In this paper, to find the optimum design of a segmented tube in terms of various collision scenarios, the RSM D-Optimal Design is used along with MULTIMOORA as a multiple-attribute decision-making (MADM) method. The tube consists of three parts having different thicknesses and lengths. Energy absorption, initial peak load, and maximum load in three angles of loads (0∘, 15∘, and 30∘), and masses of the tube were defined as independent objectives. Design points were constructed to obtain all responses through finite elements method (FEM). It was found that the obtained models of responses predict the crashworthiness with acceptable accuracy. Then the optimization provides fifteen Pareto front designs of tubes through fifteen different scenarios. Finally, the integration of MULTIMOORA within a combinative weighting method selected the best tube from the optimums. The contrast between the optimum basic tube and the selected segmented tube demonstrated that the latter was capable of increasing the energy absorption by 24–41%, and reducing the initial peak load by 50–60% for the three applied loads. [ABSTRACT FROM AUTHOR]

Highly conductive polymer nanocomposites (CPNs) are promising alternatives to metals for electromagnetic interference (EMI) shielding applications. However, constructing a well-established conductive network within a polymer matrix using conventional processes is still challenging. This research aimed to improve the EMI shielding performance of CPNs by developing highly conductive segregated structures through a facile innovative dispersion mixing process. The nanocomposites were fabricated by dispersing polystyrene beads (PS), CNT, and PEDOT:PSS in deionized water, followed by vacuum filtration, solvent treatment, and hot press molding. The employed technique effectively constructed a highly conductive network in the PS/CNT nanocomposite, resulting in the lowest ever reported percolation threshold of 0.009 vol% among CNT-based segregated structures. Moreover, adding PEDOT:PSS to the nanocomposite as an additional constituent significantly promoted the conductive network by improving the dispersion of CNTs and the interparticle contact. The PS/CNT/PEDOT:PSS (100:2:4 w/w/w) exhibited a high electrical conductivity of 2.352 S/cm with notable specific EMI shielding effectiveness (SE) of 55.7 dB/mm (with dominant absorption mechanism), which is among the best performance reported for CNT-based conductive segregated structures, to the best of our knowledge. In brief, this work proposed a novel approach of using a facile, cost-effective, and eco-friendly method to fabricate highly CPNs for EMI shielding applications. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper reports on the damage mechanisms of 3D circular braided composite tubes under transverse impact, applied by a Split Hopkinson Pressure Bar (SHPB) system. X-ray computed tomography (XCT) was employed to obtain 3D images of the 3D braided composite tubes after the impact test. Effects of impact velocity, braiding angle and the number of braiding layers on the damage mechanisms were researched, using the XCT data. For low impact velocity, it was found that cracks nucleate in weak areas and propagate along the path of least resistance between yarns, which give rise to matrix cracking and debonding between yarns. For high impact velocities, cracks develop along a relatively straight path with fiber breakage under high shear and tensile stresses. The orientation of yarns in the tubes showed a great effect on crack propagation. [ABSTRACT FROM AUTHOR]

The main chemical industrial efforts are to systematically and continuously explore innovative computing methods of optimizing manufacturing processes to provide better production quality with lowest cost. Carbon fiber industry is one of the industries seeks these methods as it provides high production quality while consuming a lot of energy and being costly. This is due to the fact that the thermal stabilization process consumes a considerable amount of energy. Hence, the aim of this study is to develop an intelligent predictive model for energy consumption in thermal stabilization process, considering production quality and controlling stochastic defects. The developed and optimized support vector regression (SVR) prediction model combined with genetic algorithm (GA) optimizer yielded a very satisfactory set-up, reducing the energy consumption by up to 43%, under both physical property and skin-core defect constraints. The developed stochastic-SVR-GA approach with limited training data-set offers reduction of energy consumption for similar chemical industries, including carbon fiber manufacturing. [ABSTRACT FROM AUTHOR]

Bending rigidity is known to play a significant role in the formability of composite fabrics, as it can affect wrinkles formation and reduce the mechanical properties of the final part. However, measuring the highly nonlinear dissipative bending behavior of unconsolidated fabrics undergoing large deformation, is an ongoing challenge. In this article, a customized setup is employed to capture the bending as well as reverse bending responses of unconsolidated fabrics under large deformation (up to ±90° bent angle). As a test case, a typical fiberglass fabric that is thick and has high areal density, as well as a carbon fiber fabric with lower thickness and areal density are considered and compared. In addition, the response of each fabric is compared to that of individual yarns, suggesting that the interlaced architecture and the dissipative behavior of yarns affect the effective bending rigidity, along with the ensuing hysteresis effects during loading-unloading. Furthermore, when the unconsolidated fabrics are oriented off-axis relative to the bending axis, the bending rigidity interacts with the in-plane trellising (reaching a maximum shearing angle of 3.3° at full bent angle), suggesting that the classical laminate theory would not apply in capturing shear-bending coupling in dry fabrics. [ABSTRACT FROM AUTHOR]

In industrial composites applications, drilling is one of the most common operations and complex processes during the final assembly, which can generate undesirable damage to the manufactured part. Data collection from a given composite's fatigue life is often costly and time-consuming. To address this challenge, the current case study aims to adapt a hybrid machine learning framework to predict the fatigue life of the drilled Glass Fiber Reinforced Polymer composite laminates (with both unidirectional and woven lay-ups) under a limited and noisy data assumption. Composite specimens were drilled at various cutting speeds and feed rates. The size of the delamination around the hole was scanned by a microscopic camera. Cyclic three-point bending tests were conducted, and results indicated that the drilling-induced delamination size and the composite lay-up affect the specimens' fatigue lives. The latter were then modeled in two steps. In the first step, an offline deterministic model was established using the group method of data handling along with a singular value decomposition. Pareto multi-objective optimization was applied to prevent overfitting. In the second step, the Kalman filter was employed to update the polynomial of the deterministic model based on minimizing the mean and variance of error between the actual and modeled data. Results showed an excellent learning reliability, with a correlation coefficient of 97.6% and 96.5% in predicting the fatigue life of unidirectional and woven composite laminates, respectively. A sensitivity analysis was performed and indicated that the fatigue life of the samples has been more affected by the drilling feed rate, compared to the cutting speed. [ABSTRACT FROM AUTHOR]

[Display omitted] • A multi-physics, multicriteria design approach developed for material selection of intraoral stents for head and neck cancer (HNC) radiation therapy. • Candidate materials assessed using Raman spectroscopy and mechanical testing pre- and post-treatments to saliva and radiation exposure. • Leaching for toxicity assessed using NMR spectroscopy. • Overall, ethylene vinyl acetate (EVA) was deemed as a non-toxic appropriate candidate to reduce/avoid significant side effects for HNC patients. Radiation therapy (RT) plays a key role in curative-intent treatments for head and neck cancer (HNC). Despite the advancements in RT, high doses of radiation can disrupt the oral cavity homeostasis and result in undesired reactions. Thus, intraoral stents (IOSs) are utilized for patients during RT to prevent unnecessary irradiation to surrounding tissues. However, no studies have compared commonly used IOS materials and their potential toxicity. Therefore, the objective of this study is to perform a detailed assessment of ten IOS materials in order to select the top-ranked material for HNC patients undergoing RT. Thus, beam attenuation measurements, and Raman spectroscopy and mechanical testing were conducted pre- and post-artificial saliva, RT, and artificial saliva and RT exposure. Finally, through a multi-criteria decision making (MCDM) analysis using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), our study demonstrated that Ethylene Vinyl Acetate (EVA) was the top-ranked material. The saliva samples were also tested via nuclear magnetic resonance (NMR) spectroscopy, which showed no leaching of irradiated materials. Taken together, these data suggest that EVA is an appropriate IOS material that can be utilized during RT to reduce significant morbidity for HNC patients and improve their quality of life. [ABSTRACT FROM AUTHOR]

Natural fibre-synthetic fibre hybrid composites provide desirable structural performance and durability, while lessening environmental impact of the final product, which is becoming increasingly important to government regulators and manufacturers. However, a major known challenge using natural fibers is their high moisture absorption, leading to fast degradation rates. Bamboo was recently shown to provide a decreased hydrophilic tendency when plastinated using the S-10 technique35—originally invented to preserve human remains. Building on this finding, this study explores the structural advantage of using plastinated bamboo as a filler material in a typical glass fiber/polypropylene woven composite. Results show that adding 10% (by weight) of the plastinated bamboo can increase the impact absorption capacity of the parent glass fibre composite, without lessening its elastic properties. Such hybrid biocomposites can bring new opportunities for structural applications, while addressing the environmental degradation issue of natural fibres. [ABSTRACT FROM AUTHOR]

Biopolymer blends have attracted considerable attention in industrial applications due to their notable mechanical properties and biodegradability. This work delves into the innovative combination of butadiene-acrylonitrile (referred to as NBR) with a pectin-based biopolymer (NGP) at a 90:10 mass ratio through a detailed analysis employing mechanical characterization, Fourier transform infrared (FTIR) analysis, thermogravimetric analysis (TGA), and morphology studies using SEM. Additionally, biopolymer's biodegradability under aerobic and anaerobic conditions is tested. The study's findings underscore the superior tensile strength and elongation at break of the NGP/NBR blend in comparison to pure NBR, while also exhibiting a decrease in puncture resistance due to imperfect bonds at the particle-matrix interfaces, necessitating the use of a compatibilizer. In anaerobic conditions, evaluation of biodegradable properties reveals 2% and 12% biodegradability in NBR and NGP/NBR blend, respectively. The degradation properties were also aligned with TGA results highlighting a lower decomposition temperature for NGP. Additionally, this research integrates the application of a conditional value-at-risk (CVaR)-based analysis of the blend's tensile properties to evaluate the uncertainty impact in the experiment. Under risk, a significant enhancement in the tensile performance (by 80%) of the NGP/NBR blend was shown compared to pure NBR. Ultimately, the study shows that adding pectin to the NBR compound amplifies the overall performance of the biopolymer significantly under select criteria., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Tubular flow diverters (FDs) represent an important subset of the endovascular treatment of cerebral aneurysms (CAs), acting to reduce aneurysm inflow, eventually resulting in aneurysm thrombosis and occlusion. eCLIPs (product of Evasc Neurovascular Enterprises, Vancouver, Canada), an innovative non-tubular implant causes flow diversion by bridging the neck of bifurcation CAs. However, in a small subset of challenging bifurcation aneurysms with fusiform pathology, the currently available eCLIPs models do not provide sufficient neck bridging resulting in a gap created between the device structure and the aneurysm/artery wall. To overcome this challenge, a new design of the eCLIPs (VR-eCLIPs) was developed by varying the rib length to cover such an inflow gap. To optimize the new product development process, and avoiding expensive and time-consuming iterative manufacture of prototype devices, we have developed a new finite element model to simulate the crimping and expansion processes of the VR-eCLIPs implant, and assess the possibility of plastic deformation. Results indicated that neither eCLIPs nor VR-eCLIPs experience plastic deformation during the crimping process. Upon full expansion, the ribs of VR-eCLIPs interact with the aneurysm and artery wall to cover the inflow gap that exists in certain challenging anatomies. This process serves as a basis to expedite design development prior to prototype manufacturing., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Modern materials science has witnessed the era of advanced fabrication methods to engineer functionality from the nano- to macroscales. Versatile fabrication and additive manufacturing methods are developed, but the ability to design a material for a given application is still limited. Here, a novel strategy that enables target-oriented manufacturing of ultra-lightweight aerogels with on-demand characteristics is introduced. The process relies on controllable liquid templating through interfacial complexation to generate tunable, stimuli-responsive 3D-structured (multiphase) filamentous liquid templates. The methodology involves nanoscale chemistry and microscale assembly of nanoparticles (NPs) at liquid-liquid interfaces to produce hierarchical macroscopic aerogels featuring multiscale porosity, ultralow density (3.05-3.41 mg cm -3 ), and high compressibility (90%) combined with elastic resilience and instant shape recovery. The challenges are overcome facing ultra-lightweight aerogels, including poor mechanical integrity and the inability to form predefined 3D constructs with on-demand functionality, for a multitude of applications. The controllable nature of the coined methodology enables tunable electromagnetic interference shielding with high specific shielding effectiveness (39 893 dB cm 2 g -1 ), and one of the highest-ever reported oil-absorption capacities (487 times the initial weight of aerogel for chloroform), to be obtained. These properties originate from the engineerable nature of liquid templating, pushing the boundaries of lightweight materials to systematic function design and applications., (© 2023 The Authors. Advanced Materials published by Wiley-VCH GmbH.)

The protein corona forms spontaneously on nanoparticle surfaces when nanomaterials are introduced into any biological system/fluid. Reliable characterization of the protein corona is, therefore, a vital step in the development of safe and efficient diagnostic and therapeutic nanomedicine products. 2134 published manuscripts on the protein corona are reviewed and a down-selection of 470 papers spanning 2000-2021, comprising 1702 nanoparticle (NP) systems is analyzed. This analysis reveals: i) most corona studies have been conducted on metal and metal oxide nanoparticles; ii) despite their overwhelming presence in clinical practice, lipid-based NPs are underrepresented in protein corona research, iii) studies use new methods to improve reliability and reproducibility in protein corona research; iv) studies use more specific protein sources toward personalized medicine; and v) careful characterization of nanoparticles after corona formation is imperative to minimize the role of aggregation and protein contamination on corona outcomes. As nanoparticles used in biomedicine become increasingly prevalent and biochemically complex, the field of protein corona research will need to focus on developing analytical approaches and characterization techniques appropriate for each unique nanoparticle formulation. Achieving such characterization of the nano-bio interface of nanobiotechnologies will enable more seamless development and safe implementation of nanoparticles in medicine., (© 2023 The Authors. Small published by Wiley-VCH GmbH.)

Recently, nanomaterials have been widely utilized in tissue engineering applications due to their unique properties such as the high surface to volume ratio and diversity of morphology and structure. However, most methods used for the fabrication of nanomaterials are rather complicated and costly. Among different nanomaterials, anodic aluminum oxide (AAO) is a great example of nanoporous structures that can easily be engineered by changing the electrolyte type, anodizing potential, current density, temperature, acid concentration and anodizing time. Nanoporous anodic alumina has often been used for mammalian cell culture, biofunctionalization, drug delivery, and biosensing by coating its surface with biocompatible materials. Despite its wide application in tissue engineering, thorough in vivo and in vitro studies of AAO are still required to enhance its biocompatibility and thereby pave the way for its application in tissue replacements. Recognizing this gap, this review article aims to highlight the biomedical potentials of AAO for applications in tissue replacements along with the mechanism of porous structure formation and pore characteristics in terms of fabrication parameters.

Natural fibers are gaining wide attention due to their much lower carbon footprint and economic factors compared to synthetic fibers. The moisture affinity of these lignocellulosic fibres, however, is still one of the main challenges when using them, e.g., for outdoor applications, leading to fast degradation rates. Plastination is a technique originally used for the preservation of human and animal body organs for many years, by replacing the water and fat present in the tissues with a polymer. This article investigates the feasibility of adapting such plastination to bamboo natural fibres using the S-10 room-temperature technique in order to hinder their moisture absorption ability. The effect of plastination on the mechanical properties and residual moisture content of the bamboo natural fibre samples was evaluated. Energy dispersive x-ray spectroscopy (EDS) and X-ray micro-computed tomography (Micro-CT) were employed to characterize the chemical composition and 3-dimensional morphology of the plastinated specimens. The results clearly show that, as plastination lessens the hydrophilic tendency of the bamboo fibres, it also decreases the residual moisture content and increases the tensile strength and stiffness of the fibers., Competing Interests: The authors declare no conflict of interest.

As the use of superparamagnetic iron oxide nanoparticles (SPION) in biomedical applications increases (e.g. for targeting drug delivery and imaging), patients are likely to be exposed to products containing SPION. Despite their high biomedical importance, toxicity data for SPION are limited to date. The aim of this study is to investigate the cytotoxicity of SPION and its ability to change cell medium components. Bare and poly(ethylene glycol)-co-fumarate (PEGF)-coated SPION with narrow size distributions were synthesized. The particles were prepared by co-precipitation using ferric and ferrous salts with a molar Fe3+/Fe2+ ratio of 2. Dulbecco's modified Eagle's medium (DMEM) and primary mouse fibroblast (L929) cell lines were exposed to the SPION. Variation of cell medium components and cytotoxicity due to the interactions with nanoparticles were analyzed using ultraviolet and visible spectroscopy (UV/vis) and the 3-[4,5-dimethylthiazol-2yl]-2,5-diphenyltetrazolium bromide (MTT) assay methods, respectively. The toxicity amount has been traditionally identified by changes in pH and composition in cells and DMEM due to the tendency of SPION to adsorb proteins, vitamins, amino acids and ions. For in vitro toxicity assessments, a new surface passivation procedure is proposed which can yield more reliable quantitative results. It is shown that a more reliable way of identifying cytotoxicity for in vitro assessments is to use particles with saturated surfaces via interactions with DMEM before usage.