Materials For Engineering Applications Research Articles

Numerical Heat Transfer Analysis of Carreau Nanofluid Flow over Curved Stretched Surface with Nonlinear Effects and Viscous Dissipation.

The article presents a comprehensive study that thoroughly assesses the effects of Carreau fluid flow over a curved stretch surface. The study meticulously considers various factors, including nonlinear thermal radiation, convective boundary conditions, viscous dissipation, thermophoresis, Brownian motion, and nonlinear mixed convection. By using similarity variables, the problem's governing equations are transformed from nonlinear partial differential equations to nonlinear ordinary differential equations, and then the shooting method is applied to obtain the results. The study also rigorously examines the effect of modifying flow factors on velocity, temperature, and concentration in shear-thickening situations through graphical assessment. Furthermore, according to the corresponding values, a table is provided with data on skin friction, Nusselt, and Sherwood numbers. This study offers new perspectives on the complex mechanisms of Carreau fluids flowing over curved surfaces, with potential applications in materials engineering and fluid mechanics.

One-step preparation of highly efficient adsorbents: Adsorption study of DMP on porous carbon macrobody based on sodium alginate

Porous carbon is a carbon material with a high surface area and abundant pore structure, holding extensive potential applications in the adsorption field. However, current porous carbon materials are complicated to prepare, and most are in powder form, making them difficult to separate from water after adsorption and prone to secondary pollution. This study uses sodium alginate (SA) as a precursor and K2CO3 one-step method to prepare sodium alginate-based macromaterials that can skillfully solve the above problems and explore its adsorption kinetics and thermodynamic characteristics for dimethyl phthalate (DMP). This study's meticulous control of experimental details enabled the fabrication of macroscopic materials. The appropriate temperature and activator blending ratio are critical to material agglomeration. (At 800 °C in a small ceramic boat, macroscopic material C800–2 was prepared with an activator ratio of K2CO3: sodium alginate at 2:1 and under low acid concentration acid washing (0.2 mol/L HCl)). Excessive pyrolysis temperature can lead to severe chemical bond loss, potentially preventing material agglomeration. Excessive doping of the activator may result in carbon framework collapse. While maintaining the macroscopic structure, C800–2 enhanced a 3.8-fold increase in total pore volume and a 4.6-fold increase in surface area. Moreover, at 313 K, its saturated adsorption of DMP reached an impressive 614.98 mg/g. C800–2 material exhibits excellent interference resistance and regeneration capability. The study achieves one-step fabrication of macroscopic materials while retaining superior adsorption performance, providing fundamental data for material engineering applications.

Characterization of Cr-TiB2 composite coating on AISI 1045 steel using hybrid deep neural network-based sandpiper optimization algorithm

The scope of this study is to enhance the performance of AISI 1045 steel for demanding marine applications like connecting rods, axles, and wear-resistant components. Traditional heat treatment methods, including boriding, surface induction hardening, and tempering, improve the steel’s surface hardness. Additionally, the Tungsten Inert Gas (TIG) coating process develops a novel Cr- TiB2 composite coating on the heat-treated AISI 1045 stainless steel. The investigation explores the influence of varying TiB2 content (10%, 20%, and 30%) on the mechanical properties of AISI 1045 steel. Microhardness and tensile characteristics are analyzed, considering the impact of TiB2 percentage. Surface morphology and interfacial bonding are examined using Scanning Electron Microscope (SEM) and Energy Dispersive X-Ray Analysis (EDAX). Results reveal notable improvements, including a 2.65 times increase in microhardness compared to untreated AISI 1045 steel, uniform TiB2 distribution, and a crack-free coating. The addition of TiB2 particles in the Cr- TiB2 composite coating enhances microhardness. Improved mechanical properties are attributed to surface treatments, incorporation of hard and wear-resistant materials (Cr and TiB2) in the composite coating, microstructure modifications, and crack prevention, collectively resulting in increased hardness, wear resistance, and durability. Furthermore, this study introduces a novel hybrid Deep Neural Network-based Sandpiper Optimization Algorithm (DNN-SOA) for predicting experimental outcomes with superior accuracy. This research not only enhances the understanding of the coated steel’s mechanical properties but also presents an innovative predictive model for future material engineering applications, demonstrating the significance of advanced heat treatment and a novel composite coating in improving AISI 1045 steel performance.

Encapsulation in Alginates Hydrogels and Controlled Release: An Overview.

This review aims to gather the current state of the art on the encapsulation methods using alginate as the main polymeric material in order to produce hydrogels ranging from the microscopic to macroscopic sizes. The use of alginates as an encapsulation material is of growing interest, as it is fully bio-based, bio-compatible and bio-degradable. The field of application of alginate encapsulation is also extremely broad, and there is no doubt it will become even broader in the near future considering the societal demand for sustainable materials in technological applications. In this review, alginate's main properties and gelification mechanisms, as well as some factors influencing this mechanism, such as the nature of the reticulation cations, are first investigated. Then, the capacity of alginate gels to release matter in a controlled way, from small molecules to micrometric compounds, is reported and discussed. The existing techniques used to produce alginates beads, from the laboratory scale to the industrial one, are further described, with a consideration of the pros and cons with each techniques. Finally, two examples of applications of alginate materials are highlighted as representative case studies.

Magneto-Induced Janus Adhesive-Tough Hydrogels for Wearable Human Motion Sensing and Enhanced Low-Grade Heat Harvesting.

Janus hydrogels with different properties on the two surfaces have considerable potential in the field of material engineering applications. Various Janus hydrogels have been developed, but there are still some problems, such as stress mismatch caused by the double-layer structure and Janus failure caused by material diffusion in the gradient structure. Here, we report a Janus adhesive-tough hydrogel with polydopamine-decorated Fe3O4 nanoparticles (Fe3O4@PDA) at one side induced by magnetic field to avoid uncontrollable material diffusion in the cross-linking polymerization of acrylamide with alginate-calcium. The magneto-induced Janus (MIJ) hydrogel has an adhesive surface and a tough bulk without an obvious interface to avoid stress mismatch. Due to the intrinsic dissipative matrix and the abundant catechol groups on the adhesive surface, it shows strong adhesion onto various substrates. The MIJ hydrogel has high sensitivity (GF = 0.842) in detecting tiny human motion. Owing to the synergy of Fe3O4@PDA-enhanced interfacial adhesion and heat transfer, it is possible to quickly generate effective temperature differences when adhering to human skin. The MIJ hydrogel achieves a Seebeck coefficient of 13.01 mV·K-1 and an output power of 462.02 mW·m-2 at a 20 K temperature difference. This work proposes a novel strategy to construct Janus hydrogels for flexible wearable devices in human motion sensing and low-grade heat harvesting.

High-Throughput Prediction of the Thermal and Electronic Transport Properties of Large Physical and Chemical Spaces Accelerated by Machine Learning: Charting the ZT of Binary Skutterudites.

Thermal and electronic transport properties are the keys to many technological applications of materials. Thermoelectric, TE, materials can be considered a singular case in which not only one but three different transport properties are combined to describe their performance through their TE figure of merit, ZT. Despite the availability of high-throughput experimental techniques, synthesizing, characterizing, and measuring the properties of samples with numerous variables affecting ZT are not a cost- or time-efficient approach to lead this strategy. The significance of computational materials science in discovering new TE materials has been running in parallel to the development of new frameworks and methodologies to compute the electron and thermal transport properties linked to ZT. Nevertheless, the trade-off between computational cost and accuracy has hindered the reliable prediction of TE performance for large chemical spaces. In this work, we present for the first time the combination of new ab initio methodologies to predict transport properties with machine learning and a high-throughput framework to establish a solid foundation for the accurate prediction of thermal and electron transport properties. This strategy is applied to a whole family of materials, binary skutterudites, which are well-known as good TE candidates. Following this methodology, it is possible not only to connect ZT with the experimental synthetic (carrier concentration and grain size) and operando (temperature) variables but also to understand the physical and chemical phenomena that act as driving forces in the maximization of ZT for p-type and n-type binary skutterudites.

Creating equilibrium glassy states via random particle bonding

Creating amorphous solid states by randomly bonding an ensemble of dense liquid monomers is a common procedure that is used to create a variety of materials, such as epoxy resins, colloidal gels, and vitrimers. However, the properties of the resulting solid do a priori strongly depend on the preparation history. This can lead to substantial aging of the material; for example, properties such as mechanical moduli and transport coefficients rely on the time elapsed since solidification, which can lead to a slow degradation of the material in technological applications. It is therefore important to understand under which conditions random monomer bonding can lead to stable solid states, that is, long-lived metastable states whose properties do not change over time. This work presents a theoretical and computational analysis of this problem and introduces a random bonding procedure that ensures the proper equilibration of the resulting amorphous states. Our procedure also provides a new route to investigate the fundamental properties of glassy energy landscapes by producing translationally invariant ultrastable glassy states in simple particle models.

Annealing Effect on Mechanical and Tribological Behaviors of Nanoscale Mechanics of Zr60Cu25Al5Ag5Ni5 Thin-Layer Metallic Glasses for Engineering Materials Applications.

A new and unique alloy formulation design strategy has been developed in order to fabricate thin-layered metallic glasses (TLMGs) with superior fracture resistance and low coefficient of friction (COF) during the nanoscratching test. Due to the outstanding properties, TFMG could be applied for different uses, such as for surface coating, biomedical, bioimprinting, electronic devices, spacecraft, and railway, all of which need surface fracture resistance. The fabricated Zr-based metallic glass was prepared from Zr, Al, Cu, Ni, and Ag above 99.9 Wt % in purity by arch melting techniques. TFMGs were coated on silicon wafer by sputtering the vapor deposition method from bulk metallic glass then annealed below glass transition temperature Tg ∼ 450 °C for 10, 30, and 60 min. Nanoindentation and nanoscratch tests were used to investigate nanomechanical and nanotribological properties, and atomic force microscopy (AFM) was used to examine the surface morphology and microstructures of TLMG. The nanoindentation data indicated that the average hardness of metallic glasses increased from 9.75 (as-cast MG) to 13.4 GPa (annealed for 60 min). Coefficients of friction for the cast sample, annealed for unannealed, 10, 30, and 60 min, were 0.062, 0.049, 0.039, and 0.03, respectively, as well as the wear depths were 201.56, 148.43, 37.32, and 25.27 nm, respectively. These studies show that the coefficient of friction and wear rate decreases when the annealing time increases as a result of atomic reordering and structural relaxation that occurred at longer annealing times. Furthermore, continuous wear process, wear depth, wear track volume, and contact area decrease with increasing annealing time. This study can be used to design protocols to prepare novel TLMGs, which have outstanding mechanical and tribological properties for engineering materials applications.

Modulational instability and nonlinear dynamics of femtosecond lasers in transparent materials with non-Kerr nonlinearities

Femtosecond laser inscription in transparent materials is a physical process that finds widespread applications in material engineering, particularly in laser micromachining technology. In this process, the nonlinear optical response of the transparent material can be either intrinsic or induced by multiphoton ionization processes. In this work, a generic model is considered to describe the dynamics of femtosecond laser filamentation in transparent materials characterized by non-Kerr nonlinearities, focusing on the influence of multiphoton ionization processes in the generation of an electron plasma of inhomogeneous density. The mathematical model consists of a complex Ginzburg–Landau equation with a generalized saturable nonlinearity, besides the residual nonlinearity related to multiphoton ionization processes. This generalized complex Ginzburg–Landau equation is coupled to a rate equation for time evolution of the electron plasma density, where multiphoton ionizations are assumed to be the sole processes controlling the generation of the electron plasma. Dynamical properties of the model are discussed starting from the continuous-wave regime, where a modulational-instability analysis enables us to determine the stability conditions of continuous-wave modes in the system. The analysis reveals a dominant tendency of continuous-wave stability for relatively large values of the multiphoton ionization order K, provided the femtosecond laser operates in the anomalous dispersion regime. Numerical simulations of the mathematical model feature a family of wavetrains composed of self-focused, well-separated, pulse-shaped optical filaments whose repetition rates are shortened but amplitudes are increased, with an increase in K. Simulations suggest that such nonlinear wavetrain structures do not need the transparent material to be intrinsically nonlinear and that they may also be favored solely by the nonlinearity induced by multiphoton ionization processes in a linear transparent material.

Automated Design Using Machine Learning in Materials Engineering - An Explicit Forecasts

Every discipline of physics, including materials science, has been profoundly influenced by the arrival of algorithmic breakthroughs in the domain of machine learning. Many important advances have been made by combining materials data (computed and measured) with different machine learning approaches to solve difficult problems like, creating effectual and extrapolative surrogate prototypes for a wide variety of material parameters, down-selecting and screening novel candidate materials for particular application, and structuring novel approaches to accelerate and enhance atomistic and molecular simulations. Although current implementations have shown some of the promise of data-enabled pathways, it has become evident that success in this area will depend on our capacity to interpret, explain, and justify the results of a machine learning approach on the basis of our professional knowledge in the field. This article reviews the most important machine learning applications in materials engineering. In addition, we present a short overview of a number of methods that have proven useful in deriving physically relevant insights, design-centric knowledge, and causal links from materials engineering. Last but not least, we highlight some of the next prospects and obstacles that the materials community will encounter in this dynamic and fast developing industry.

Characterisation of the surface chemistry of carbon materials by temperature-programmed desorption: An assessment

The increasing role assumed by carbon materials in technological applications is intrinsically linked to a better understanding of carbon surface chemistry as a result of reliable methods of analysis. X-ray photoelectron spectroscopy (XPS) and temperature-programmed desorption (TPD) techniques allow to obtain qualitative and quantitative information on individual functional groups on the carbon surface. In this context, TPD has established itself as an alternative technique to the Boehm titration methodology or XPS, being especially adequate for the characterisation of oxygen functional groups on carbon materials with extended porosity. This work reviews the fundamentals and methodology to perform a correct TPD-MS analysis and assessment (qualitatively and quantitatively) of the oxygenated functional groups. The applicability of the information obtained by TPD to correlate the properties of carbon materials with their performance in practical applications is also revised.

Thin Films of Polyaniline-Based Nanocomposites with CeO2 and WO3 Metal Oxides Applied to the Impedimetric and Capacitive Transducer Stages in Chemical Sensors.

There is a recognized need for the development of cost-effective, stable, fast, and optimized novel materials for technological applications. Substantial research has been undertaken on the role of polymeric nanocomposites in sensing applications. However, the use of PANI-based nanocomposites in impedimetric and capacitive electrochemical sensors has yet to be understood. The present study aimed to explore the relationship between the sensitivity and linearity of electrochemical pH sensors and the composition of nanocomposites. Thin films of PANI/CeO2 and PANI/WO3 were deposited via spin coating for characterization and application during the electrochemical impedance and capacitance spectroscopy (EIS and ECS) transduction stages. The findings showed that the optimized performance of the devices was extended not only to the sensitivity but also to the linearity. An increase of 213% in the ECS sensitivity of the PANI/CeO2 compared to the metal oxide and an increase of 64% in the ECS linearity of the PANI/WO3 compared to the polymeric sensitivity were reported. This study identified the structure-property relationship of nanocomposite thin films of PANI with metal oxides for use in electrochemical sensors. The developed materials could be applied in devices to be used in different fields, such as food, environment, and biomedical monitoring.

Tunable Perpendicular Magnetoresistive Sensor Driven by Shape and Substrate Induced Magnetic Anisotropy

AbstractControl of magnetization reversal processes is a key issue for the implementation of magnetic materials in technological applications. The modulation of shape magnetic anisotropy in nanowire structures with a high aspect ratio is an efficient way to tune sharp in‐plane magnetic switching. However, control of fast magnetization reversal processes induced by perpendicular magnetic fields is much more challenging. Here, tunable sharp magnetoresistance changes, triggered by out‐of‐plane magnetic fields, are demonstrated in thin permalloy strips grown on LaAlO3 single crystal substrates. Micromagnetic simulations are used to evaluate the resistance changes of the strips at different applied field values and directions and correlate them with the magnetic domain distribution. The experimentally observed sharp magnetic switching, tailored by the shape anisotropy of the strips, is properly accounted for by numerical simulations when considering a substrate‐induced uniaxial magnetic anisotropy. These results are promising for the design of magnetic sensors and other advanced magnetoresistive devices working with perpendicular magnetic fields by using simple structures.

A bibliometric analysis of cold spray coating process using VOSviewer

Cold spray coating is an Additive Manufacturing technology that is accustomed to amend surfaces of the substrate and improves many benefits in material engineering applications. This is a high-velocity solid state spray technique that uses temperatures sufficiently below the melting point of the products to preserve their chemical and physical properties. A thorough examination of 387 documents found in the Scopus database from 1999 to 2022 was carried out. In this study, we analyzed cold spray research and its evolution using a bibliometric approach and scientometric evaluation using the free tool VOSviewer to create bibliometric maps. These maps help in understanding the overall development, research trends, and major gaps identified in the literature. We identified prolific authors, their work, contribution and collaboration in the field of cold spray research, important publishing sources, and keyword assessment based on co-occurrence using density visualization maps that help in understanding research gaps. Despite several successful experiments, cold spray on brittle materials has received little attention, because of its high specific strength, fatigue resistance, biocompatibility and corrosion resistance, the cold spray has potential applications in aircraft parts, medical implant materials and protective coatings highlighting the need for research in this area.

Effect of oxygen configurations on the mechanical properties of graphene oxide

Understanding the mechanical properties of graphene oxide (GO) is the primary challenge for applications in materials engineering. The degree of oxidation and concentration of epoxide functional groups have been the main focus of previous mechanochemical studies. This work uses the reactive molecular dynamic simulations to reveal that the mechanical behavior of GO is strongly dependent on the epoxide configuration as well as its distribution. In this study, three main epoxide configurations—including top, bridge, and reside groups—decorate monolayer GO sheets with linear and random distributions. The distortion associated with epoxide groups creates diamond-like structures controlling the mechanical properties. Moreover, the orientation of those epoxide functional groups with applied loads has a dramatic impact on the mechanical response of GO. The effect of external electric fields on the mechanical properties of GO is another objective of this study. Findings exhibit that the electric field enhances the tensile toughness. This study demonstrates new aspects of GO as a functional material with potentials to control the mechanical properties through chemical compositions as well as external electric fields.

Preparation of Janus Droplets and Hydrogels with Controllable Morphologies by an Aqueous Two-Phase System on the Superamphiphobic Surface.

Janus particles, having the property integration of each component, have attracted increasing attention due to their considerable potential in the field of material engineering applications. However, organic solvents or sophisticated equipment during the fabrication processes is generally inevitable. Here, we report a facile route to prepare Janus droplets and hydrogels via aqueous two-phase systems (ATPS). Simply merging two polymers, i.e., polyethylene glycol (PEG) and dextran (DEX), as aqueous droplets on a superamphiphobic surface leads to phase separation, provided that their concentrations exceed the threshold in the mixed aqueous droplets, thus generating a Janus structure. Various morphologies of such Janus droplets can be well controlled by manipulating the locations of these two polymers' concentration on the phase diagram, and the evolution of the mixed droplets are deterministic on the basis of the kinetics of their phase separation and the degree of hydrophobicity of the substrate. Introducing monomers and/or nanoparticles, further, into a certain phase of the ATPS droplet followed by photopolymerizing enables Janus hydrogel particles with diverse functionalities to be obtained. The ease and green techniques with which the Janus balance and curvature between two phases of the Janus droplet can be finely tuned point to new directions in designing Janus particles and hold great promises in biological engineering.

Parametric Optimization of Abrasive Water Jet Cutting on AA 5083 through Multiobjective Teaching-Learning Method

The industrial sector is seeing an increase in the development of new technologies on a daily basis. Manufacturing advancements have resulted in low-intensity, inadequate outputs from cutting materials. The application of engineering materials requires cutting to produce the desired shapes and sizes. The material’s fundamental attributes are altered and utilised to improve machinability. Due to its significant benefits over traditional cutting processes, abrasive water jet cutting (AWJC) is now the most popular nonconventional machining for attaining the best cutting of any material. Because of its highly pressurised water power, the substance can quickly be separated from some properties by the use of a small pin with various kinds of abrasives. Due to the time-consuming process of cutting materials, determining optimal cutting conditions for the multiobjective criteria examined is a tough issue in techniques needing large resources. The operational parameters of the abrasive water jet cutting system must be changed in this article to achieve the lowest possible surface roughness while also attaining the maximum possible material removal rate. The abrasive water jet cutting method was utilised in this investigation to see how effectively the AA5083 aluminium alloy could be sliced. Water pressure, transverse speed, stand-off distance, and abrasive flow rate are some of the major cutting parameters that may be adjusted such that the output values such as material removal rate and surface roughness are at their optimal levels.

(Invited, Digital Presentation) Excited State Properties of Low-Dimensional Materials: Insight By Ab-Initio DFT + Mbpt Simulations

The use of emerging low-dimensional materials in technological applications presupposes a detailed knowledge of their chemical and physical properties. In this context ab-initio theoretical methods and simulations are playing a fundamental role.Here I aim to show how the use of parameter-free atomistic simulations can contribute to improve the microscopic understanding of the opto-electronic properties of nanomaterials and to predict new ones. I will show how ab-initio DFT and post-DFT (GW and BSE) calculations, based on Many-Body Perturbation Theory (MBPT), provide a very useful scheme to study i) giant electronic band-gaps renormalization due to low dielectric screening and large quantum confinement ii) strong light-matter interaction iii) fine structure of strongly bound excitons. iv) the influence of electron-phonon interaction on the electronic and optical spectra, v) how doping, molecular functionalization or strain can tune their opto-electronic properties. Main focus will be on different semiconducting 2D materials discovered after graphene, but other dimensionality examples will be discussed.

The Amyloidogenic Peptide Amyloid Beta(16–22) Displays Facet Dependent Conformation on Metal Surfaces

Currently, it is not understood how metal nanoparticles influence the formation of protein fibrils, although recent literature highlights that the shape and chemical composition of such nanoparticles can strongly influence the process. Understanding this process at a fundamental level can potentially unlock routes to the development of new therapeutics, as well as novel materials for technological applications. This requires a microscopic picture of the behaviour of amyloidogenic proteins on metal surfaces. Using replica exchange molecular dynamics simulations, we investigate the conformation of the model amyloidogenic peptide, Aβ(16–22), on different gold and silver surfaces. The conformation of the peptide on gold surfaces also shows a strong facet dependence, with fibril-like conformations being promoted in the 100 surface and inhibited on the 111 surface. A smaller degree of facet dependence is seen for silver with the peptide behaving similar on both of these. The difference in the facet dependence can be related to the difference between direct adsorption onto the gold 111 surface, with a preference towards indirect (water mediated) adsorption onto the other surfaces. This new information on the behaviour of an amyloidogenic peptide on metal surfaces can give insight into the size-dependent effect of nanoparticles on fibril formation and the use of surfaces to control fibrillation.

Biocalcifying Potential of Ureolytic Bacteria Isolated from Soil for Biocementation and Material Crack Repair.

Microbially induced calcium carbonate precipitation (MICP) has been highlighted for its application in civil engineering, and in the environmental and geotechnical fields. Ureolytic activity is one of the most promising bacterial mechanisms in terms of inducing calcium carbonate formation. In this study, four bacterial isolates with high-yield urease production capabilities were obtained from two-step screening using a high-buffered urea medium. The highest urease activity and calcium carbonate formation was observed in Lysinibacillus fusiformis 5.1 with 4.40 × 103 unit/L of urease and 24.15 mg/mL of calcium carbonate, followed by Lysinibacillus xylanilyticus 4.3 with 3.93 × 103 unit/L of urease and 22.85 mg/mL of calcium carbonate. The microstructure of the precipitated crystalline calcium carbonate was observed using scanning electron microscopy. X-ray diffraction analysis confirmed that the main polymorph of the calcium carbonate particle obtained from both isolates was calcite. Examination of the material-crack filling in mortar specimens showed that calcite layers had formed along the crack edges and inside after 10 days, and gradually filled the cracks up to the upper surface. These results showed that these two isolates presented robust characteristics of potential MICP-inducing bacteria for civil engineering and material engineering applications.