Hybrid Matrix Research Articles

Room temperature cured silver nanoparticle embedded hybrid nanocomposite coatings: processing and property evaluation

In situ formation of silver nanoparticles in an inorganic–organic hybrid matrix cured at room temperature (30 ± 5 °C).

Synthesis of Y2O3 and graphite-added copper-based hybrid composites by powder metallurgy: Mechanical properties and tribological behavior

In the presented study, Y2O3 and graphite-reinforced Cu matrix hybrid composite materials were prepared using the powder metallurgy method. The aim is to compare the microstructure, density, hardness, and wear behavior of composites with different yttria contents (5, 10, and 15 weight%) and graphite (2 weight%) reinforcements. An increase in the Y2O3 ratio, along with the addition of graphite, resulted in an observed increase in the hardness values of the composites. Additionally, it was observed that Y2O3 and graphite are homogeneously distributed in the copper matrix in the SEM-EDX spectra. Upon examining the microstructures of the composites, it was determined that with the increase in yttrium oxide content, partially yttrium oxide agglomerations formed in some regions. The addition of Y2O3 resulted in a copper sample that is 1,34 times harder than pure copper. Addition of Y2O3 -graphite, samples with 3.301-22.3 % higher wear resistance were obtained.

Development and Characterizations of Microwave Sintered (Al2O3+MoS2) Reinforced Copper-Based Metal Matrix Hybrid composites

Development and Characterizations of Microwave Sintered (Al2O3+MoS2) Reinforced Copper-Based Metal Matrix Hybrid composites

NIR‐emitting Electrochromic Windows for Cold Climate Region Buildings

AbstractElectrochromic devices (ECDs) comprising visible/near‐infrared (NIR) transparent amorphous indium zinc oxide (a‐IZO) outermost layers and novel NIR‐emitting electrolytes are proposed for smart windows of buildings in cold climate regions. The electrolytes are composed of a di‐urethane cross‐linked poly(oxyethylene)(POE)/siloxane hybrid matrix (d‐Ut(600), 600 is the average molecular weight of the POE chains in gmol−1), 1‐butyl‐3‐methylimidazolium chloride ionic liquid, and the Er(tta)3(H2O)2 complex (tta− is 2‐thenoyltrifluoracetonate). The electrolytes, synthesized by sol‐gel route, were obtained as transparent, flexible, and hydrophilic monoliths with nanoscale surface roughness, exhibiting emission in the NIR wavelength region. The first electro‐optical tests, performed in 2019, with an archetypal ECD including amorphous tungsten oxide and crystalline nickel oxide as EC layers, a‐IZO as outermost layers, and d‐Ut(600)400Er(tta)3(H2O)2[Bmim]Cl (400 is the molar ratio of oxyethylene units/Er3+ ion) as the electrolyte, demonstrated rather low coloration efficiency (CEin/CEout) values of −4/+6 cm2 C−1 at 555 nm. After 3 years of storage at rest in the dark and at room temperature, the same device demonstrates a huge performance enhancement, leading to CEin/CEout values about two orders of magnitude higher, apart from higher optical density, and improved cycling stability. In addition, this device offers a bright hot, and semi‐bright warm dual modulation operation suitable for smart windows of skylights, roof lights, upper windows, inclined glazing, and privacy glazing of buildings located in cold climate regions.

Unveiling the Occurrence and Non-Negligible Role of Amino Sugars in Waste Activated Sludge Fermentation by an Enriched Chitin-Degradation Consortium.

Polysaccharides in extracellular polymeric substances (EPS) can form a hybrid matrix network with proteins, impeding waste-activated sludge (WAS) fermentation. Amino sugars, such as N-acetyl-d-glucosamine (GlcNAc) polymers and sialic acid, are the non-negligible components in the EPS of aerobic granules or biofilm. However, the occurrence of amino sugars in WAS and their degradation remains unclear. Thus, amino sugars (∼6.0%) in WAS were revealed, and the genera of Lactococcus and Zoogloea were identified for the first time. Chitin was used as the substrate to enrich a chitin-degrading consortium (CDC). The COD balances for methane production ranged from 83.3 and 95.1%. Chitin was gradually converted to oligosaccharides and GlcNAc after dosing with the extracellular enzyme. After doing enriched CDC in WAS, the final methane production markedly increased to 60.4 ± 0.6 mL, reflecting an increase of ∼62%. Four model substrates of amino sugars (GlcNAc and sialic acid) and polysaccharides (cellulose and dextran) could be used by CDC. Treponema (34.3%) was identified as the core bacterium via excreting chitinases (EC 3.2.1.14) and N-acetyl-glucosaminidases (EC 3.2.1.52), especially the genetic abundance of chitinases in CDC was 2.5 times higher than that of WAS. Thus, this study provides an elegant method for the utilization of amino sugar-enriched organics.

Dry tribological behaviour of microwave-assisted sintered AA2024 matrix hybrid composites reinforced by TiC/B4C/nano-graphite particles

Abstract This study aimed to produce hybrid composites with a AA2024 matrix reinforced by TiC/B4C/nano-graphite through a microwave-assisted sintering technique at 560 °C for 60 min. The nano-graphite ratio in the produced composite samples was kept constant as 1 wt.%. TiC and B4C were used in equal ratios at 2, 6 and 10 % by weight total to determine their effects on tribological properties. Wear tests were conducted under three different loads: 3, 5 and 10 N. In the hybrid composites produced, an inverse correlation was observed between the increase in reinforcement ratio and sinterability, while a direct correlation relationship was found in hardness and wear resistance. Compared to the sample containing 2 % TiC/B4C in total by weight, a ∼50 % increase in Brinell hardness and a 52–68 % decrease in wear rate was obtained in the sample containing 10 % TiC/B4C. As the reinforcement ratio increased, tribofilm formation increased, and abrasive wear was replaced by mild-oxidative wear type.

Non-linear stability characteristics of randomly distributed CNT-reinforced fiber composite beams under thermo-mechanical loadings

The aim of the present study is to elucidate the non-linear stability characteristics of randomly distributed carbon nanotube-reinforced fiber composite (RD-CNTRFC) beams subjected to thermo-mechanical loading. Effective material properties of RD-CNTRFC are estimated using the Eshelby-Mori-Tanaka approach and Halpin–Tsai micromechanical techniques. The material properties are considered to be temperature-dependent, and the influence of carbon nanotube (CNT) agglomeration is also incorporated in material properties estimation of hybrid matrix. The strain-displacement relations are assumed by incorporating the higher-order shear deformation theory and geometrical nonlinearity (von Kármán). The governing partial differential equations are obtained by minimizing the total potential energy of the beam. Buckling loads of beam subjected to in-plane compressive loads are estimated using Eigen value approach. Similarly, buckling temperatures are also determined by solving Eigenvalue problem iteratively due to temperature-dependent material properties. The non-linear equilibrium paths under thermal and mechanical loadings are traced through iterative Eigenvalue approach. Numerical results are presented to elucidate the influence of various parameters like CNT agglomeration, ply sequences, span-to-depth ratio, boundary conditions, and mass fraction of CNTs.

TiO2-kaolinite composite photocatalyst for industrial organic waste decontamination

The industrially feasible TiO2-clay based photocatalysts are essential to overcome the practical barriers that are intrinsic to currently available clay-based photocatalysts. The present study demonstrates the fabrication of heterogeneous photocatalyst consisting of TiO2 and kaolinite (TKCP) that has shown improved catalytic activity and strength, ensuring industrial viable photocatalyst. TKCP is prepared via an economical method, employing mechanical compression and dehydroxylation, forming TiO2-clay hybrid matrix. Amount of clay primarily determines mechanical strength and photocatalytic efficiency of TKCP where TKCP with the lowest clay percentage results in a homogeneous matrix that consists of tiny TiO2 particles embedded clay sheet-like structure. The TiO2 particles embedded clay sheet-like structure is responsible for the high specific surface area and small pore size, increasing the active surface that is available for effective disintegration of organic contaminants. By increasing clay fraction in TKCP, a significant increase in surface defects can be observed due to large clay fragments and TiO2 agglomerates, which results in flexural strength and catalytic activity decrease. Methylene blue degradation on TKCP with the maximum TiO2 percentage results in the highest pseudo first-order rate constant of 0.58 h−1, exhibiting improved photocatalytic activity due to well-organized matrix and high specific surface area (82.79 m2 g−1). TKCP can be obtained in variable sizes and shapes that ensure dynamic wastewater treatment applications.

Dispersion mechanism of nanoparticles and its role on mechanical, thermal and electrical properties of epoxy nanocomposites - A Review

The combined effect of nano-reinforcements on the mechanical performance of nanocomposites, which are a novel class of epoxy matrix hybrid nanocomposites containing multiwall carbon nanotubes (MWCNT), graphene, and nanodiamonds (NDs), is drawing substantial attention from many research communities. The discussion concentrates on the dispersion techniques adopted for the preparation of epoxy composites containing different types of nanoparticles (3-D fillers, nanofibers, nanotubes, and plate-like fillers). This review paper covers the electrical, thermal, and mechanical properties of carbon nanotubes (CNTs), graphene, and nanodiamond-reinforced epoxy nanocomposites and correlates them with the topographical features, morphology, weight fraction, dispersion state, and surface functionalization of CNTs, graphene, and nanodiamond. This review paper also summarises recent developments in the dispersion method of different carbon nanoparticles in epoxy matrix.

Influence of Green Plantain Peel Ash and Alumina Reinforcement on the Physio-Mechanical Properties of Aluminium Matrix Hybrid Composites

Hybrid composites are gaining increasing interest in the development of aluminium metal matrix (AMCs) for various industrial applications owing to their ability to integrate multiple functionalities within a single material matrix with enhanced physio-mechanical properties as opposed to single-fibre reinforced composites. Green plantain peel ash (GPPA) is an agricultural waste with potential for reinforcement purposes. However, no study has investigated GPPA natural filler as a reinforcement for AMCs. This study, therefore, aims at assessing the influence of variations in GPPA particles and alumina as reinforcements in the fabrication of hybrid composites using Al-Mg-Si alloy as a matrix. This study also reassessed the chemical composition of the GPPA particles and investigated their mechanical properties. However, enhanced mechanical properties, including hardness, tensile strength, and ductility, were observed at varying weight ratios. Results obtained in this study suggest a promising potential application of GPPA particulates as complementing reinforcements in the production of lightweight, strong, and high-performance AMCs well-suited for engineering, aerospace, construction, and packaging applications.

Effect of apple polyphenols on physicochemical properties of pea starch/pulp cellulose nanofiber composite biodegradable films

A pea starch (PS) and pulp cellulose nanofibers (CNF-P) hybrid matrix biodegradable film was prepared using apple polyphenol (AP) as the active substance. SEM and thermogravimetric analyses showed that apple polyphenols could be uniformly distributed and form hydrogen bonds with the matrix, and the increase in crystallinity improved the thermal stability of the films (the final residue of the films increased from 22.66 % to 31.82 %). The TS and EAB of the films reached their maximum values of 11.14 ± 1.73 MPa and 71.55 ± 8.8 %, respectively, at an AP content of 1.5 %. It should be noted that the antioxidant properties of the films were significantly positively correlated with the AP content, and the DPPH radical scavenging rate of the films reached 73.77 % at an AP content of 4.5 %, which was about 49 times higher than that of the control film. The same trend was observed in the UV–vis spectra. In addition, the total color difference and water solubility of the membranes increased from 4.29 ± 0.29 to 31.86 ± 1.90 and from 20.01 ± 0.97 % to 21.70 ± 1.99 %, respectively, and the biodegradability also showed an upward trend. These findings provide a theoretical basis and data support for the development of multifunctional biodegradable food packaging materials.

Enzymatic dual-faced Janus structures based on the hierarchical organic-inorganic hybrid matrix for an effective bioremoval and detoxification of reactive blue-19

A novel, dual-faced, and hierarchical type of Janus hybrid structures (JHSs) was assembled through an in situ growing of lipase@cobalt phosphate sheets on the laccase@copper phosphate sponge-like structures. The chemical and structural information of prepared JHSs was investigated by Scanning electron microscopy-energy dispersive X-ray analysis (SEM-EDX), Fourier Transform Infrared Spectroscopy (FTIR), and X-ray diffraction analysis (XRD). The catalytic activity, storage stability, and reusability of JHSs were then investigated. The SEM-EDX analysis clearly confirmed the asymmetric morphology of the fabricated JHSs with two distinct metal distributions. Under optimized synthesis conditions, the prepared JHSs showed 97.8 % and 100 % of laccase and lipase activity, respectively. Compared to the free biocatalysts, the immobilization resulted in ~ a 2-fold increase in laccase and lipase stability at temperatures of >40 °C. The fabricated JHSs maintained 61 % and 90 % of their original laccase and lipase activity upon 12 successive repetition cycles. Up to 80 % of Reactive Blue-19 (RB-19), an anthraquinone-based vinyl sulphone dye, was removed after 5 h treatment with the prepared JHSs (50 % higher than the free forms of laccase and lipase). The dye removal data fitted very well on the pseudo-second-order kinetic model with a rate constant of 0.8 g mg−1 h−1. Following the bioremoval process, bacterial toxicity also decreased by about 70 %. Therefore, the prepared JHSs provide a facile and sustainable approach for the decolorization, biotransformation, and detoxification of RB-19 by integrating enzymatic oxidation and hydrolysis.

A Study of the Influence of Negative Temperatures on the Impact Strength of a Carbon-Fiber Composite with a Hybrid Matrix

A Study of the Influence of Negative Temperatures on the Impact Strength of a Carbon-Fiber Composite with a Hybrid Matrix

Impact Toughness of Carbon Fiber-Reinforced Polymers under Extremely Low Arctic Temperature Conditions: The Role of Hybrid Matrix Components

Impact Toughness of Carbon Fiber-Reinforced Polymers under Extremely Low Arctic Temperature Conditions: The Role of Hybrid Matrix Components

Effect of TiB2 and GNP reinforcements on machinability in drilling of Al7075/TiB2/GNP hybrid composites produced by powder metallurgy

In this study, it has been aimed to investigate the machinability performances by drilling by producing Al7075 matrix hybrid composite samples with graphenenanoplate (GNP) and titaniumdiboride (TiB2) reinforced at different rates by powder metallurgy. The impacts of GNP and TiB2 reinforcing materials on the cutting parameters and wear behavior of the cutting tool have been examined and discussed. As a result of the drilling tests which are carried out by applying different cutting parameters, it was observed that GNP additive has positive impact on the cutting forces, surface roughness, and hole quality in general. As a result of the machining experiments, the lowest cutting force was obtained as 150 N at a feed rate of 0.100 mm/rev and a cutting speed of 60 m/min in the 1% GNP reinforced sample. The minimum roughness value was obtained as 0.886 micron at 60 m/min cutting speed in the 1% GNP reinforced sample. The minimum deviations from cylindricality and circularity were also measured as 0.03 and 8.005 mm from the 1% GNP reinforced sample. While the lubricating effect was low with a GNP ratio of 0.5%, the abrasive effect was observed more with a GNP ratio of 1.5%. While GNP supplementation decreased the diameter deviation and cylindrical deviation values, it increased the perpendicularity deviation values. In general, swarf chip formation occurred with a small amount of flank wear on the cutting tools. While hard TiB2 reinforcement particles in the composite structure were effective in flank wear, the most important cause of chip formation was the presence of ductile aluminum matrix and relatively low cutting speeds. When the entire experimental study was evaluated, it was evaluated that the solid lubricant property of the GNP reinforcement material was effective at the most 1% GNP reinforcement rate.

PSVII-2 The Impact of Genomic Information Inclusion on Breeding Value Prediction for a Novel Parasite Resistance Indicator Trait in Brazilian Anglo-Nubian Goats: a Pilot Study

Abstract Infection by Haemonchus contortus is the gastrointestinal parasitosis of greatest economic and social importance in the production of goats, being the leading cause of mortality in the Brazilian goat industry. Genetic selection for resistance to parasites in Anglo-Nubian goats has proven to be a viable alternative to traditional methods of controlling gastrointestinal nematodes, producing animals genetically superior in resistance to parasites. This study aimed to evaluate the impact of including genomic information on the estimation of variance components, genetic parameters, and predictive accuracy of genetic values for the new trait Parasitic Resistance (PR) in Anglo-Nubian goats. The PR is generated by measuring Body Condition Score, FAMACHA chart (ranging from 1 to 5), and Fecal Egg Count on a regular scale. These three traits were used as input variables in the CAPRIOVI software, which uses fuzzy logic to create the PR score, ranging from 0 to 10. Animals with lower scores are more likely to be parasitized and require treatment, while animals with higher scores are less likely to be infected. We used information from 352 animals, totaling 3,855 repeated measurements of PR over the years (2001 to 2020) and 1,500 animals in the pedigree. Animals with less than three measurements for any of the three input traits were removed from the dataset. Contemporary groups were built from information from the year of birth, data collection season, birth season, and physiological stage of the animal, considered as fixed effects, and age at the time of data collection as a covariate in an animal repeatability model. A total of 89 animals were genotyped using the Bead Chip Goats SNP50. After quality control, the remaining 38,659 SNPs (Table 1) were used to build the hybrid matrix (H). The variance components (VC) were estimated using the Bayesian Gibbs Sampling method, and breeding values were predicted using the Best Linear Unbiased Prediction (BLUP) and single-step Best Linear Unbiased Prediction (ssGBLUP) methods. The additive genetic variance and heritability estimation ranged from 0.13 to 0.14 and 0.04 to 0.05, respectively (Table 2). The accuracies obtained for PR with BLUP and ssGBLUP were 0.12 and 0.14, respectively, representing a gain of 16.7%. The genomic information (25 % of all animals with phenotypes) with the repeated records improved the predictive model capability based on accuracy. It also improved the VC estimation for PR in Anglo-Nubian goats raised in the Brazilian semi-arid region. These results highlight the positive impact of genetic evaluation of goats for PR, even with few phenotypes and genotyped animals. In addition to elucidating the additive genetic influence of parasite resistance, it can be a great source of information on the selection and production of Anglo-Nubian goats.

The Reaction–Diffusion Models in Biomedicine: Highly Accurate Calculations via a Hybrid Matrix Collocation Algorithm

A hybrid efficient and highly accurate spectral matrix technique is adapted for numerical treatments of a class of two-pint boundary value problems (BVPs) with singularity and strong nonlinearity. The underlying model is a reaction-diffusion equation arising in the modeling of biomedical, chemical, and physical applications based on the assumptions of Michaelis–Menten kinetics for enzymatic reactions. The manuscript presents a highly computational spectral collocation algorithm for the model combined with the quasilinearization method (QLM) to make the proposed technique more efficient than the corresponding direct spectral collocation algorithm. A novel class of polynomials introduced by S.K. Chatterjea is used in the spectral method. A detailed proof of the convergence analysis of the Chatterjea polynomials (ChPs) is given in the L2 norm. Different numerical examples for substrate concentrations with all values of parameters are performed for the case of planar and spherical shapes of enzymes. For validation, these results are compared with those obtained via wavelet-based procedures and the Adomian decomposition scheme. To further improve the approximate solutions obtained by the QLM–ChPs method, the technique of error correction is introduced and applied based on the concept of residual error function. Overall, the presented results with exponential convergence indicate that the QLM–ChPs algorithm is simple and flexible enough to be applicable in solving many similar problems in science and engineering.

AutoMF: A hybrid matrix factorization model with deep learning to select anti-viral drugs for Covid-19

In the wake of the novel Covid-19 disease pandemic, the global economy has been affected and health crises are widespread. The disease is still incurable, and no effective treatment exists for it. During the Covid-19 crisis, drug repurposing has proven to be an effective treatment strategy. Drug repositioning is an approach to finding effective drugs for treating new diseases by discovering new efficacy of existing drugs. Studies on drug-virus association can reveal new efficacy. The antiviral drug repositioning problem is defined here as a matrix completion problem in which antiviral drugs go down the rows, while viruses go down the columns. We propose a hybrid model called AutoMF that identifies new drug–virus association. This new hybrid model aims to develop a matrix factorization model with deep learning and use it to predict drug-virus associations for repositioning drugs. In our model, a heterogeneous drug–virus network is used, which combines drug–virus associations, drug-drug similarity matrix, and virus-virus similarity matrix. Matrix factorization can extract latent factors from the drug-virus associations. The sparse nature of the associations may prevent the latent factors from being very effective. To solve this problem, deep learning is used to learn effective latent representations from similarity matrices to incorporate with MF to enhance their latent factor priors. Our model outperforms several recent approaches in comparison to benchmarking tests performed on the DVA dataset. In our approach, we identify antiviral drugs currently being tested in clinical trials or those used currently to treat patients.

Combining ZnPc-liposomes and chitosan on a hybrid matrix for enhanced photodynamic therapy

Photodynamic therapy is an alternative treatment for several pathologies, including cancer. This therapy uses a photosensitizer capable of producing reactive oxygen species through irradiation, promoting cellular death. A limitation of photosensitizers is their low solubility in aqueous media. Hence, developing a suitable carrier for photosensitizers for specific applications is a challenge. Cervical cancer is one of the most common cancers in women, and photodynamic therapy could be an attractive alternative therapeutic approach. In this work, we synthesized films composed of chitosan, polyvinylpyrrolidone, and liposomes containing Zn-phthalocyanine. Photophysical characterization of ZnPc incorporated into films was determined by UV–vis and fluorescence. Film properties such as swelling, mechanical properties, and water vapor permeability were performed. Finally, in vitro, photodynamic evaluation of these films was performed on HeLa cells. The results indicate that incorporating Zn-Pc-liposomes into films decreases cell viability by >95 %.

Utilizing internal resonant scattering to improve photoluminescence energy outcoupling of CsPbBr3/Cs4PbBr6 perovskite phosphor

Although stable perovskite phosphors, i.e., CsPbBr3/Cs4PbBr6, were extensively reported and made great progress, achieving strong photoluminescence (PL) energy outcoupling remains challenging owing to their short Stoke’s shift with serious PL energy absorption. This study utilized internal resonant scattering (IRS) to improve the PL energy outcoupling (PEO) of CsPbBr3/Cs4PbBr6 perovskite phosphor, which was realized by the nanopore-packing perovskite particles (NP-PPs) structure inside a phosphor. The nano-porous matrix hybrid solid–liquid interfacial reaction was developed to construct NP-PPs in a phosphor, and it is optimized to achieve a denser NP-PP structure with an enhanced PEO effect (2.8-fold enhanced PL intensity). Numerical results revealed that the NP-PP structure transforms the PL energy absorption mode to the IRS mode, most of the scattering PL energy evades NP-PPs instead of propagating inside. The optimized phosphor was applied to white devices, and we finally achieved an ultrahigh luminous efficacy of 131.32 lm/W based on green perovskite phosphors. This study provides a general guide for efficient perovskite phosphors utilizing the nano-porous matrix to enable the IRS effect.