Complex Composite Materials Research Articles

3D Printing of Solvent-Free Supramolecular Polymers.

Additive manufacturing has significantly changed polymer science and technology by engineering complex material shapes and compositions. With the advent of dynamic properties in polymeric materials as a fundamental principle to achieve, e.g., self-healing properties, the use of supramolecular chemistry as a tool for molecular ordering has become important. By adjusting molecular nanoscopic (supramolecular) bonds in polymers, rheological properties, immanent for 3D printing, can be adjusted, resulting in shape persistence and improved printing. We here review recent progress in the 3D printing of supramolecular polymers, with a focus on fused deposition modelling (FDM) to overcome some of its limitations still being present up to date and open perspectives for their application.

RNA-DNA Hybrid Nanoshape Synthesis by Facile Module Exchange.

The preparation of nucleic acid nanostructures has relied predominantly on procedures of additive fabrication in which complex architectures are assembled by concerted self-assembly and sequential addition of building blocks. We had previously established RNA-DNA hybrid nanoshapes with modular architectures that enable multistep synthetic approaches inspired by organic molecular synthesis where additive and transformative steps are used to prepare complex molecular architectures. We report the establishment of module replacement and strand exchange as synthetic transformations in nucleic acid hybrid nanoshapes, which are enabled by minimally destabilizing sequence elements such as a single unpaired overhang nucleotide or a mismatch base pair. Module exchange facilitated by thermodynamic lability triggers adds a powerful transformative approach to the repertoire of additive and transformative synthetic methods for the preparation of complex composite materials.

Distribution of Biominerals and Mineral-Organic Composites in Plant Trichomes.

Biomineralization is a common phenomenon in plants and has been shown to be chemically, functionally and topologically diverse. Silica and calcium carbonate have long been known as structural plant biominerals and calcium phosphate (apatite)–long known from animals–has recently been reported. Strikingly, up to three different biominerals may occur in a single trichome in, e.g., Urticaceae and Loasaceae, and in combination with organic compounds, can form organic/inorganic composite materials. This article presents an extension of previous studies on the distribution of these biominerals in Loasaceae trichomes with a focus on their spatial (three-dimensional) distribution and co-localization with organic substances. Light microscopy and scanning electron microscopy with high-resolution EDX element analyses of sample surfaces and sections illustrate the differential distribution and composition of the different biomineral phases across cell surfaces and cell walls. Raman spectroscopy additionally permits the identification of organic and inorganic compounds side by side. All three biominerals may be found in a nearly pure inorganic phase, e.g., on the plant surfaces and in the barbs of the glochidiate trichomes, or in combination with a larger proportion of organic compounds (cellulose, pectin). The cell lumen may be additionally filled with amorphous mineral deposits. Water-solubility of the mineral fractions differs considerably. Plant trichomes provide an exciting model system for biomineralization and enable the in-vivo study of the formation of complex composite materials with different biomineral and organic compounds involved.

Rapid simulations of hyperspectral near-field images of three-dimensional heterogeneous surfaces.

The scattering-type scanning near-field optical microscope (s-SNOM) has emerged as a powerful tool for resolving nanoscale inhomogeneities in laterally heterogeneous samples. However, most analytical models used to predict the scattering near-field signals are assuming homogenous landscapes (bulk materials), resulting in inconsistencies when applied to samples with more complex configurations. In this work, we combine the point-dipole model (PDM) to the finite-element method (FEM) to account for the lateral and vertical heterogeneities while keeping the computation time manageable. Full images, spectra, or hyperspectral line profiles can be simulated by calculating the self-consistent dipole radiation demodulated at higher harmonics of the tip oscillation, mimicking real experimental procedures. Using this formalism, we clarify several important yet puzzling experimental observations in near-field images on samples with rich typography and complex material compositions, heterostructures of two-dimensional material flakes, and plasmonic antennas. The developed method serves as a basis for future investigations of nano-systems with nontrivial topography.

Upcycling Waste Plastics into Multi-Walled Carbon Nanotube Composites via NiCo2O4 Catalytic Pyrolysis

In this work, multi-walled carbon nanotube composites (MWCNCs) were produced by catalytic pyrolysis of post-consumer plastics with aluminium oxide-supported nickel, cobalt, and their bimetallic (Ni/α–Al2O3, Co/α–Al2O3, and NiCo/α–Al2O3) oxide-based catalysts. The influence of catalyst composition and catalytic reaction temperature on the carbon yield and structure of CNCs were investigated. Different temperatures (800, 900, 950, and 1000 °C) and catalyst compositions (Ni, Co, and Ni/Co) were explored to maximize the yield of carbon deposited on the catalyst. The obtained results showed that at the same catalytic temperature (900 °C), a Ni/Co bimetallic catalyst exhibited higher carbon yield than the individual monometallic catalysts due to a better cracking capability on carbon-hydrogen bonds. With the increase of temperature, the carbon yield of the Ni/Co bimetallic catalyst increased first and then decreased. At a temperature of 950 °C, the Ni/Co bimetallic catalyst achieved its largest carbon yield, which can reach 255 mg g−1plastic. The growth of CNCs followed a “particle-wire-tube” mechanism for all studied catalysts. This work finds the potential application of complex oxide composite material catalysts for the generation of CNCs in catalytic pyrolysis of wasted plastic.

Investigation on Lateral Loading on Masonry Walls

5) Though a traditional material used for construction for ages, masonry is a complex composite material, and its mechanical behavior is influenced by a large number of factors, is not generally well understood. This research aims to study the methodology available in the literature to evaluate the increase in performance of masonry by applying different reinforcement options under in-plane lateral loading. Nonlinear static analysis has been carried out as part of this research to achieve the above objectives. Different unreinforced masonry wall panels were analyzed at various load conditions. Material properties for the masonry wall were taken from the experimental test results of previous literature. The walls were first checked for two failure mechanisms. The stress distributions of walls were checked in each step of analysis and shear failure, and rocking failure was found. Each wall was then analyzed for six different reinforcement options. The comparison of results obtained from the reinforced wall analysis with that of the unreinforced wall indicated significant increase in lateral load-bearing capacity and decreased wall displacement with reinforcement. The maximum increase in load-bearing capacity was achieved by adding chicken wire mesh or CFRP bands throughout the wall while the maximum decrease in displacement was achieved by adding 12 mm diameter bars at the spacing of one meter.

Considering Nonsurface Scattering in Physical Optics Approximations

This work addresses the issue of volume scattering effects within the context of the physical optics (PO) approach. This decreases the modeling and computational effort to simulate scattering from complex material compositions. It is shown that there is a natural progression from the classical PO for perfect electric conductors over the PO for dielectric scatterers toward the proposed formulation. Four specializations of the general algorithm are presented to emphasize the versatility of this approach. Details regarding the implementation of the proposed examples are described. Results for each of the special cases are shown and compared to commercially available full-wave solvers of CST and FEKO.

Rheology of Fresh Concrete - A Review

Concrete is a heterogeneous, complex composite construction material. Fresh property of concrete is a critical property with significant effect on quality , cost of construction, strength, and durability. Even to this day the workability of fresh concrete is measured by empirical test, notably by slump test in spite of its drawbacks and sometimes with misleading results with less practical significance. There is an urgent need to characterize the flow of fresh concrete b y its rheological properties based on material science approach to overcome the inadequacies of the empirical test methods.Fluid rheology approach is the most fundamental one and describes the concrete flow by at least two parameters namely yield stress and plastic viscosity by considering fresh concrete as a Bingham fluid. Understanding and controlling the two fundamental fresh properties of concrete allow for more economical and better performing concrete mixes with the use of wide range of ingredients.This paper brings out the importance of rheology and advocates the use of fundamental science approach with two parameter tests along with advantages and limitations of using rheometers. Also highlights the use of concrete shear box static tests for wide range of workability requirements with the use of new and marginal materials in concrete industry.

Predicting the extrudability of complex food materials during 3D printing based on image analysis and gray-box data-driven modelling

Material extrudability is a prerequisite for printing 3D structures with extrusion-based food printing. Food materials with different shear-thinning behaviors were printed to develop predictive models for extrudability. A dataset of 131 unique combinations of materials and printing parameters was collected. Image analysis was employed to rapidly quantify extrudability as determined by mode width, line height and width consistency of line filaments. The relation between the printing pressure and the volumetric flow rate followed a power-law relation, which characterizes the extent of shear-thinning of the food materials. Both regression and classification models were trained and tested using the random forest algorithm. The model performance indicated that extrudability can be predicted with moderate to high accuracy by using rheological measurements and printing parameters as inputs. The predictive workflow developed in this study provides a framework to quantitatively assess and predict extrudability for 3D printing of complex food materials. Industrial relevanceExtrusion-based 3D printing has been applied to customize food designs and can potentially enable personalized nutrition. To achieve this, we need to be able to effectively print complex food materials with high accuracy. Variations in composition and rheological properties of complex food materials make achieving proper extrudability not trivial at this moment, and this limits their applicability to extrusion-based food printing. Here, we developed an image analysis tool to measure line filament extrusion of complex food materials that vary in shear-thinning behaviors. We then built predictive models to estimate material extrudability based on material's shear-thinning properties and printing parameters. Data-driven prediction of material's extrudability can help avoid excessive trial-and error experiments in future.

Data-driven model for ternary-blend concrete compressive strength prediction using machine learning approach

Ternary-blend concrete is a complex composite material, and the nonlinearity in its compressive strength behavior is unquestionable. Entirely many models have been developed to accurately predict the ternary-blend concrete compressive strength, such as ANN, SVM, random forest, decision tree, to mention but a few. This study underscores the better predictive performance and successful application of the least square support vector machine (LSSVM), a machine learning model for predicting the compressive strength of ternary-blend concrete. Coupled simulated annealing (CSA) was applied to the LSSVM model as an optimization algorithm. In addition, the genetic programming (GP) model was used as a benchmark model to compare the performance of the LSSVM-CSA model. The predictive performance of the LSSVM-CSA was compared with that of some of the proposed models in well-known studies where the same datasets were used. The model proposed in this study outperformed other studies, yielding an R2 value of 0.954.

ФЛОТАЦИОННЫЕ РЕАГЕНТЫ ДЛЯ ИЗВЛЕЧЕНИЯ ТОНКОВКРАПЛЕННОГО ЗОЛОТА ИЗ ТРУДНООБОГАТИМЫХ РУД И ТЕХНОГЕННЫХ ПРОДУКТОВ

At the present stage of development of the mineral resource base of precious metals, the wider involvement of refractory ores and technogenic products in the mineral processing is playing a very important role. It is due to these types of mineral resources the main Russian and foreign companies plan to get the increase in the production of gold and other precious metals. Refractory ores are characterized by low content and uneven distribution of valuable components, emulsion dissemination of gold, complex material composition, flotation active silicate and carbonaceous rock components. The main technologies for their processing include combined schemes that provide intensive preliminary preparation of ore, fine and ultrafine grinding. Creation of effective reagents for flotation of fine classes of noble metals, selective depression of gold-free sulfides, like pyrite, pyrrhotite, arsenopyrite, and rock minerals is one of the recognized innovative solutions for intensifying the enrichment process of this type of raw material. The studies performed at IPKON RAS in the framework of the scientific school of Academician V.A. Chanturiya helped to develop and substantiate the novel selective reagents-collectors of dithiocarbamate type (DEDTCm, OPDTC, DBDTC, MDTC) and herbal modifiers that possess complexing properties in relation to noble metals and provide an increase in the recovery of valuable components of gold by 5-7%. A set of analytical methods - scanning electron (LEO 1420VP, Carl Zeiss) and laser microscopy (KEYNCE VK-9700, Shimadzu), X-ray fluorescence spectroscopy (ARL ADVANT’X), ICP –MS (Agilent 725 ICP-OES, Agilent Technologies), X-ray diffractometry (DRON-2.0, XRD 7000, Shimadzu), potentiometry, titrimetric analysis, methods of mathematical statistics helped to study the adsorption layer of the reagents on natural minerals and model sulfides with micro- and nanosized gold. Using an original technique for quantitative assessment of the reagent coating by image analysis (SLM), the surface area of the mineral occupied by the reagent was calculated. A method for selective flotation of gold-containing sulfides using OPDTC and oak bark extract has been developed and tested in the separation of the collective gold-arsenic concentrate of the Olympiada deposit. It showed the possibility of obtaining a gold-pyrite concentrate with an arsenic content of less than 2%. The prospect of using plant modifiers for gold recovery during flotation of complex ores has been substantiated.

ИННОВАЦИОННЫЕ ПРОЦЕССЫ ГЛУБОКОЙ И ЭКОЛОГИЧЕСКИ БЕЗОПАСНОЙ ПЕРЕРАБОТКИ ТЕХНОГЕННОГО СЫРЬЯ В УСЛОВИЯХ НОВЫХ ЭКОНОМИЧЕСКИХ ВЫЗОВОВ

Innovative processes of deep and complex processing of technogenic raw materials in the context of sustainable development of the mining industry and the economic challenges facing the mining industry should ensure the transition to a circular economy and the maximum use of natural resources. The article reflects the priority scientific and technological research on the involvement of technogenic mineral resources in efficient processing. Presented, developed at ICEMR RAS, including jointly with universities, research and production organizations and enterprises, modern innovative processes of deep and environmentally friendly processing of refractory mineral raw materials of complex material composition (tailings of enrichment of non-ferrous and noble metal ores, poor off-balance ores, slags ferrous and nonferrous metallurgy, sludge of metallurgical production) and hydro-mineral technogenic resources (acidic mineralized bottom-dump waters of mining enterprises of the copper-zinc complex of the Urals, saponite-containing circulating waters of diamond processing factories). Among other things, new directions in the field of selective disintegration of finely dispersed mineral raw materials based on energy effects and deep processing of slags are outlined; increasing the selectivity of enrichment processes; combined processing of technogenic raw materials; resource-saving processing of technogenic and hydro-mineral resources, obtaining secondary products from processing waste. It is shown that in the face of new economic challenges, Russia has sufficient scientific and technological potential in the field of deep and environmentally safe processing of technogenic raw materials in the form of developed and, to varying degrees, tested innovative resource-saving technologies that correspond to the world level, and in a number of technologies are superior to it.

Recursive algorithm for modeling non-linear etching rates in reactive plasma jet based optical surface machining of borosilicate crown glass

Application-specific optical glass properties are achieved by utilizing complex material compositions. This can be problematic in reactive plasma-assisted deterministic surface processing since a non-volatile surface layer may form depending on the glass composition, which affects the etch rate and thereby the local etching depth. In this investigation, a model algorithm is proposed to tackle some restrictions in applying fluorine-based plasma jet as etching tool utilized for freeform surface machining of optics made of complex glass composition, like borosilicate crown glass (e.g., N-BK7®). In this regard, firstly an analytical model is proposed for estimating the depth-dependent etch rate function. Subsequently, a recursive simulation algorithm is introduced for convolving the derived depth-dependent etch rate function with the given dwell time matrix to simulate a deterministic freeform generation process. By the proposed simulation algorithm, the impeding influence of the residual layer on the reduction of etching depth is computed prior to a real experiment in order to scale the local dwell time to ensure the targeted local removal. Finally, the simulated freeform shape is compared with the corresponding result of an etching experiment to validate the feasibility of the proposed approach.

Numerical analysis of the impact of cytoskeletal actin filament density alterations onto the diffusive vesicle-mediated cell transport.

The interior of a eukaryotic cell is a highly complex composite material which consists of water, structural scaffoldings, organelles, and various biomolecular solutes. All these components serve as obstacles that impede the motion of vesicles. Hence, it is hypothesized that any alteration of the cytoskeletal network may directly impact or even disrupt the vesicle transport. A disruption of the vesicle-mediated cell transport is thought to contribute to several severe diseases and disorders, such as diabetes, Parkinson's and Alzheimer's disease, emphasizing the clinical relevance. To address the outlined objective, a multiscale finite element model of the diffusive vesicle transport is proposed on the basis of the concept of homogenization, owed to the complexity of the cytoskeletal network. In order to study the microscopic effects of specific nanoscopic actin filament network alterations onto the vesicle transport, a parametrized three-dimensional geometrical model of the actin filament network was generated on the basis of experimentally observed filament densities and network geometries in an adenocarcinomic human alveolar basal epithelial cell. Numerical analyzes of the obtained effective diffusion properties within two-dimensional sampling domains of the whole cell model revealed that the computed homogenized diffusion coefficients can be predicted statistically accurate by a simple two-parameter power law as soon as the inaccessible area fraction, due to the obstacle geometries and the finite size of the vesicles, is known. This relationship, in turn, leads to a massive reduction in computation time and allows to study the impact of a variety of different cytoskeletal alterations onto the vesicle transport. Hence, the numerical simulations predicted a 35% increase in transport time due to a uniformly distributed four-fold increase of the total filament amount. On the other hand, a hypothetically reduced expression of filament cross-linking proteins led to sparser filament networks and, thus, a speed up of the vesicle transport.

Generalized modeling of the effective thermal conductivity of particulate composites

Accurate and computationally efficient predictive models for the effective thermal conductivity of composites are needed to accelerate the design of new materials with improved properties and behavior. The predictive capabilities of previously developed models for particulate composites (PC) apply to limited ranges of component properties and proportions. Furthermore, existing material models that account for particle contiguity and filler-matrix thermal contact resistance fail to distinguish between those two effects. In this work, two novel and complementary predictive models for the effective thermal conductivity of two-phase isotropic particulate composites are derived: (i) a simple yet efficient analytical model for non-contiguous filler particles, and (ii) a generalized semi-analytical model accounting for both filler particle contiguity and thermal resistance at the filler-matrix interface. The latter model is powered by a thermal conduction grid solver algorithm that allows the incorporation of an unlimited number of elements and components to match increasingly complex particulate composite material configurations and behaviors. The two models proposed in this work can match previously published experimental data fairly well. The grid model is further leveraged to relate the effective thermal conductivity to filler particle size and size distribution. It is found that the formation of filler conduction chains is favored by well-graded particle size distributions.

Combined reactive plasma jet-laser etching method for technical optical glass containing metal oxides

The machining of optical glass materials with beam technologies enables novel fabrication processes for innovative optical elements with freeform surfaces. However, the complex material composition of optical glass such as N-BK7® is challenging for non-abrasive, pure chemical machining. N-BK7 can be machined utilizing reactive atmospheric plasma jet (RAPJ) etching. However, the etching mechanism results in process-inherent surface composition changes that limit potential applications of RAPJ-machining. A residues layer is formed which causes a temporally changing etching behavior and an increased roughness. Therefore, a process sequence of utilizing RAPJ etching and laser cleaning is proposed and demonstrated that enables to overcome the stated limitations. In this cyclic sequence, N-BK7 optical glass is etched first with a fluorine-containing reactive atmospheric plasma jet resulting in an etched but also residues-modified surface. Thereafter, the residues are removed by pulsed UV laser irradiation without ablation of the glass. This combined laser-enhanced reactive plasma jet etching allows etching of optical glass with a higher average etching rate and smoother machined surfaces.

The Use of Fibers in Bone Tissue Engineering.

Bone tissue engineering aims to restore and maintain the function of bone by means of biomaterial-based scaffolds. This review specifically focuses on the use of fibers in biomaterials used for bone tissue engineering as suitable environment for bone tissue repair and regeneration. We present a bioinspired rationale behind the use of fibers in bone tissue engineering and provide an overview of the most common fiber fabrication methods, including solution, melt, and microfluidic spinning. Subsequently, we provide a brief overview of the composition of fibers that are used in bone tissue engineering, including fibers composed of (i) natural polymers (e.g., cellulose, collagen, gelatin, alginate, chitosan, and silk, (ii) synthetic polymers (e.g., polylactic acid [PLA], polycaprolactone, polyglycolic acid [PGA], polyethylene glycol, and polymer blends of PLA and PGA), (iii) ceramic fibers (e.g., aluminium oxide, titanium oxide, and zinc oxide), (iv) metallic fibers (e.g., titanium and its alloys, copper and magnesium), and (v) composite fibers. In addition, we review the most relevant fiber modification strategies that are used to enhance the (bio)functionality of these fibers. Finally, we provide an overview of the applicability of fibers in biomaterials for bone tissue engineering, with a specific focus on mechanical, pharmaceutical, and biological properties of fiber-functionalized biomaterials for bone tissue engineering. Impact statement Natural bone is a complex composite material composed of an extracellular matrix of mineralized fibers containing living cells and bioactive molecules. Consequently, the use of fibers in biomaterial-based scaffolds offers a wide variety of opportunities to replicate the functional performance of bone. This review provides an overview of the use of fibers in biomaterials for bone tissue engineering, thereby contributing to the design of novel fiber-functionalized bone-substituting biomaterials of improved functionality regarding their mechanical, pharmaceutical, and biological properties.

Comprehensive monitoring of talus slope deformation and displacement back analysis of mechanical parameters based on back-propagation neural network

Landslides are regarded as significant geological hazards across the world, causing serious economic losses and casualties. The understanding on deformation characteristics and failure mechanisms of landslides plays the vital roles in slope stability evaluation and reinforcement design. In this study, the deformation characteristics and failure mechanism of the Xiaomiaoling talus slope were analyzed based on field monitoring data. In addition, as it was difficult to measure the shear strength parameters of the rock–soil mixture due to its complex spatial structure and variable material composition, a displacement back analysis based on the back-propagation neural network (DBA-BPNN) was proposed to determine the shear strength parameters of the rock–soil mixture. The analytical results show that deformation of the Xiaomiaoling talus slope was that of a typical traction landslide, which has the characteristics of progressive failure, and major slope deformation was triggered by excavation and rainfall. According to field monitoring data, the shear strength parameters of the rock–soil mixture could be determined. The predicted cohesion and internal friction angle of the rock–soil mixture were 10.84 kPa and 19.51°, respectively, and the predicted and test values were in good agreement. The method proposed in this paper can provide references for the design and construction in geotechnical engineering.

Improved environmental stability of thermoelectric ceramics based on intergrowths of Ca3Co4O9–Na0.75CoO2

Ceramics based on calcium and sodium cobaltates are promising high-temperature thermoelectric oxide materials with complementary advantages. Ca3Co4O9 is stable at high temperatures, whereas Na0.75CoO2 can be easily processed as a textured ceramic with excellent thermoelectric properties. Na0.75CoO2, however, lacks long-term stability and degrades in even a relatively mild humid environment. In this work, we present a novel approach to the synthesis of complex composite materials based on intergrowths of sodium and calcium cobaltates that have excellent thermoelectric performance and improved stability. We synthesized samples with the mixed composition (3-x)Ca3Co4O9–4x(Na0.75CoO2) in an over-pressured oxygen atmosphere. Samples with the mixed Ca–Na composition developed textured microstructures composed of intergrowths of both end-members, as revealed by transmission electron microscopy. We also examined the thermoelectric performance of the investigated materials after exposure to high humidity and found that the composition with x = 0.8 (Ca:Na = 2.75) has long-term stability.

Complex additives for concretes on the base of caprolactam

In the modern construction operations, complex multifunctional additives are the most in demand. Application and development of chemical additives enable to consider the modern concrete as a complex composite material, with the properties surpassed the combinations of the properties of its components. In the paper, the action mechanisms of various types of plasticizers and superplasticizers are studied as well as their impact on the properties of concrete mixture and concrete. The most popular plasticizers of concrete mixtures are superplasticizer C-3, alkaline waste of caprolactam process, and technical lignosulphonates. The products of oligomerization of ɛ-caprolactam in the organic substance medium or its interaction with various sustances of synthetic or natural origin are considered perspective multifunctional additives of building mixes. In the paper, the properties of additives obtained by the method of mechanochemical activation of the mixture containing oligomers of ɛ-caprolactam, superplasticizer C-3, technical lignosulphonate, and inorganic salts are researched. The carried out investigation has demonstrated improved plasticizing and water retention properties of the additives as well as acceleration of concrete stress generation at the early strength stage. Based on the research findings for the obtained complex additives for the concrete B40, it was stated that the additives obtained by mechanochemical activation of the initial mixture perform as effective plasticizers and concrete hardeners.