Advanced Engineering Materials Research Articles

LIPSS pattern induced by polymer surface instability for myoblast cell guidance

The presented study highlights the efficiency of employing a KrF excimer laser to create diverse types of periodic nanostructures (LIPSS – laser induced periodic surface structures) on polyether ether ketone (PEEK) and polyethylene naphthalate (PEN) substrates. LIPSS structures are very important both in tissue engineering and find also strong application in the field of sensor construction, and SERS analysis. By exposing the polymer films below their ablation threshold to laser fluence ranging from 4 to 16 mJ·cm−2 at 6,000 pulses, we studied both single-phase exposure at beam incidence angles of 0° and 45°, and two-phase exposure. Atomic force microscopy analysis revealed that the laser-treated samples contained distinctive periodic patterns such as waves, globules, and pod-like structures each exhibiting unique surface roughness. Moreover, using analytical methods like EDS and XPS shed light on the changes in the atomic composition, specifically focusing on the C and O elements, as a result of laser exposure. Notably, in almost all cases, we observed an increase in oxygen percentage on the sample surfaces. This increase not only led to a decrease in the contact angle with water but also lowered the zeta potential value, thus showing that the modified samples have enhanced hydrophilicity of the surface and altered electrostatic properties. Last but not least, the samples were assessed for biocompatibility; we studied the interaction of the prepared replicates with mouse myoblasts (C2C12). The impact of globular/dot structures on the cell growth in comparison to pristine or linear LIPSS-patterned surfaces was determined. The linear pattern (LIPSS) induced the myoblast cell alignment along the pattern direction, while dot/globular pattern even enhanced the cytocompatibility compared to LIPSS samples. Through this comprehensive analysis, the research underscores the multifaceted implications of employing KrF excimer laser-induced nanostructures, ranging from surface morphology alterations to biocompatibility enhancements, thus, opening new avenues for advanced material engineering.

Principal Preferred Orientation Evaluation of Steel Materials Using Time-of-Flight Neutron Diffraction

Comprehensive information on in situ microstructural and crystallographic changes during the preparation/manufacturing processes of various materials is highly necessary to precisely control the microstructural morphology and the preferred orientation (or texture) characteristics for achieving an excellent strength–ductility–toughness balance in advanced engineering materials. In this study, in situ isothermal annealing experiments with cold-rolled 17Ni-0.2C (mass%) martensitic steel sheets were carried out by using the TAKUMI and ENGIN-X time-of-flight neutron diffractometers. The inverse pole figures based on full-profile refinement were extracted to roughly evaluate the preferred orientation features along three principal sample directions of the investigated steel sheets, using the General Structure Analysis System (GSAS) software with built-in generalized spherical harmonic functions. The consistent rolling direction (RD) inverse pole figures from TAKUMI and ENGIN-X confirmed that the time-of-flight neutron diffraction has high repeatability and statistical reliability, revealing that the principal preferred orientation evaluation of steel materials can be realized through 90° TD ➜ ND (transverse direction ➜ normal direction) rotation of the investigated specimen on the sample stage during two neutron diffraction experiments. Moreover, these RD, TD, and ND inverse pole figures before and after the in situ experiments were compared with the corresponding inverse pole figures recalculated from the MUSASI-L complete pole figure measurement and the HIPPO in situ microstructure evaluation, respectively. The similar orientation distribution characteristics suggested that the principal preferred orientation evaluation method can be applied to the in situ microstructural evolution of bulk orthorhombic materials and spatially resolved principal preferred orientation mappings of large engineering structure parts.

Evaluation of treatment and energy efficiencies of an advanced electrochemical system for Chlorella removal equipped with aluminum, graphite, and RGO nanoparticles-coated cathodes

Advanced material sciences and technologies can help to address environmental challenges in order to achieve sustainable development goals by developing innovative materials capable of mitigating energy consumption in treatment systems. In this study, an innovative electrocoagulation unit for algae removal was optimized, and the effects of various variables, including novel cathode materials (i.e., graphite and reduced graphene oxide nanoparticles), on treatment efficiency and energy consumption were evaluated. Reduced graphene oxide nanoparticles were synthesized and then immobilized on the graphite cathode surface with the modified Hummer's method. Stabilization of nanoparticles was achieved with polytetrafluoroethylene. The use of the reduced graphene oxide nanoparticles-coated cathode led to a significant decrease (42.93%) in energy consumption, compared to the case with an aluminum cathode. In the optimum conditions (a current density of 3 mA/cm2, an electrolyte concentration of 2 g/L, an electrode surface area of 56 cm2, a processing time of 60 min, and a sedimentation time of 30 min), the novel electrocoagulation unit, equipped with an aluminum anode and a reduced graphene oxide nanoparticles-coated cathode electrode, achieved removal efficiencies of 72.69% for Chlorella species and 72.96% for turbidity.

Highly Flexible and Self‐Standing Covalent Organic Framework–Metal–Organic Framework (COF–MOF) Composite Crystalline Porous Material (CPM) Membrane for Molecular Separation

AbstractCrystalline porous materials (CPMs), including covalent organic frameworks (COFs) and metal–organic frameworks (MOFs), are promising materials for advanced separation technologies. However, the challenge of transforming nanoscale CPMs into large‐area functional membranes hinders their application in the membrane separation process. Herein, a self‐standing pure COF (TpPa‐1) nanofiber membrane with high crystallinity, good flexibility, excellent mechanical properties, and scalability is prepared using an electrospinning process and polymer sacrificial template strategy. Subsequently, the COF nanofiber membrane is innovatively used to replace traditional inorganic discs, metal meshes, and polymer membranes as porous supports, and the COF–MOF composite CPM membrane is prepared through the tailorable and confined growth of zeolite imidazolium salt frame‐8 (ZIF‐8) on the surface of the COF membrane and in the gaps of the COF nanofibers. The COF–MOF composite membrane exhibits excellent permeability and significantly enhances separation selectivity for organic dyes. Moreover, MOF and COF form an interpenetrating network structure, and their similar chemical properties improve the interfacial stability between the two phases, giving the COF–MOF composite membrane good long‐term separation performance. This is the first self‐standing composite CPM membrane with excellent molecular sieving performance, which provides new insights into the design of high‐performance and robust composite membranes.

Prediction and optimization of Nd: YAG laser transmission micro-channelling on PMMA employing an artificial neural network model

In the present research work, performance enhancement which plays pivotal role in the modern machining techniques during machining of advanced engineering materials has been attributed. An investigation is conducted on the laser transmission micro-channeling of thick transparent PMMA using Nd: YAG laser. The objective is to examine the impact of three key factors, namely pulse frequency, lamp current and cutting speed, on several quality aspects including depth of cut, kerf width, and heat-affected zone (HAZ) width. General full factorial design is used to design the experiments and empirical models (non-linear) are developed to establish the relationship between the control factors and responses. A feed forward back-propagation neural network (FF-BPNN) is used to model the process and subsequently to predict the responses. The successful capability of FF-BPNN in predicting and enhancing the characteristics of micro-channels fabricated on PMMA has been observed. Furthermore, it has been shown that feedforward backpropagation neural networks (FF-BPNN) can serve as a highly effective tool for acquiring a comprehensive model and determining the ideal configuration of process parameters in laser transmission micro-channeling operations. Additionally, FF-BPNN results and model predicted values are compared with non-linear modelling technique. Finally, mean absolute error is calculated to find out the accuracy of both the techniques.

Simulation and experimental study of concrete beams reinforced with a natural fiber composite

There is growing interest in utilizing natural fiber-reinforced polymer matrix composites as engineered materials for advanced applications, notably in the development of high-performance ballistic armor components. Achieving superior mechanical properties, particularly toughness, is crucial in this context. Currently, there is ongoing research into the potential of jute fiber-reinforced composites as advanced engineering materials. This study aims to present the findings of an experimental investigation on concrete beams subjected to shear, reinforced with polymer matrix composites incorporating jute fibers through jacketing. Compression bending tests were conducted and analyzed within our laboratory. The results of the experiment revealed a remarkable 69% increase in both stiffness and load capacity of the reinforced beam compared to its unreinforced counterpart.

Enhancing Aluminum-Based Composite Manufacturing: Harnessing Si3N4 Reinforcement via Stir Casting Technique

This study investigates the enhancement of aluminum-based composite manufacturing by incorporating Si3N4 reinforcement via the stir casting technique. Aluminum alloy serves as the matrix material, augmented with ceramic reinforcement particles. The alloy is melted at approximately 700°C in a muffle furnace, with ceramic particles gradually introduced and dispersed homogeneously through continuous stirring at 400 rpm for 10 minutes. The uniform distribution of Si3N4 particles underscores the efficacy of the stirring technique. Addition of 7.5% Si3N4 reinforcement results in substantial improvements across mechanical properties: tensile strength increases by 24.76%, hardness by 24.76%, fatigue strength by 26.78%, and wear resistance by 29.50%. These enhancements highlight the effectiveness of Si3N4 reinforcement in augmenting the performance of aluminum composites. The findings hold significant implications for industries requiring lightweight, high-strength materials, such as aerospace, automotive, and manufacturing, suggesting promising avenues for further research and practical applications in advanced engineering materials.

In situ three-dimensional observation of plasticity onset in a Pt nanoparticle.

Defects in nanocrystals can dramatically alter their physical and chemical behavior. It is thus crucial to understand the defect behavior at the nanoscale to enhance material properties. Here, we report three-dimensional defect characterization at the onset of plasticity in a 550 nm Pt nanoparticle. By combining in situ nano-indentation with Bragg Coherent X-ray Diffraction Imaging (BCDI), we directly observe the strain field inside the Pt particle during indentation, revealing the nucleation and propagation of prismatic dislocation loops. Subsequent post mortem imaging of the complete dislocation network, coupled with multi-reflection BCDI, enabled us to determine the Burgers vectors of the defects revealing sessile dislocations. Finally, by measuring the elastic field inside the crystal during indentation, we estimate that the shear stress required to generate defects is 6.4 GPa, representing the upper theoretical limit of elasticity and setting an unprecedented standard for Pt nanoparticles. Our findings provide fundamental insights into defect dynamics in nanoscale systems, offering invaluable knowledge for advanced materials design and engineering.

Clean Energy Solutions in Data Centers: Leveraging Advanced Materials and AI for Sustainable DevOps Operations

This paper examines how artificial intelligence (AI) and advanced engineering materials contribute to reduced energy consumption in data centers, a key consideration for sustainable DevOps. The topic of study is to use AI to introduce efficiency within data center operations such as maintenance, workload distribution, and cooling systems. Furthermore, the paper discusses the effectiveness of integrating different materials within buildings, including phase change materials and cutting-edge thermal management approaches to minimize energy utilization. Simulation findings reveal the potential to achieve higher efficiency levels in energy use when AI and Advanced Materials are incorporated. Such findings are supported by real-time examples that illustrate its applicability and usefulness in actual working environments. It also examines challenges regarding deployment and reproducibility, presenting suggestions intended to enhance the sustainability of the data centers via technological developments.

Leveraging Deep Neural Networks for Estimating Vickers Hardness from Nanoindentation Hardness.

This research presents a comprehensive analysis of deep neural network models (DNNs) for the precise prediction of Vickers hardness (HV) in nitrided and carburized M50NiL steel samples, with hardness values spanning from 400 to 1000 HV. By conducting rigorous experimentation and obtaining corresponding nanoindentation data, we evaluated the performance of four distinct neural network architectures: Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory network (LSTM), and Transformer. Our findings reveal that MLP and LSTM models excel in predictive accuracy and efficiency, with MLP showing exceptional iteration efficiency and predictive precision. The study validates models for broad application in various steel types and confirms nanoindentation as an effective direct measure for HV hardness in thin films and gradient-variable regions. This work contributes a validated and versatile approach to the hardness assessment of thin-film materials and those with intricate microstructures, enhancing material characterization and potential application in advanced material engineering.

Multi-exposure diffraction pattern fusion applied to enable wider-angle transmission Kikuchi diffraction with direct electron detectors

Diffraction pattern analysis can be used to reveal the crystalline structure of materials, and this information is used to nano- and micro-structure of advanced engineering materials that enable modern life. For nano-structured materials typically diffraction pattern analysis is performed in the transmission electron microscope (TEM) and TEM diffraction patterns typically have a limited angular range (less than a few degrees) due to the long camera length, and this requires analysis of multiple patterns to probe a unit cell. As a different approach, wide angle Kikuchi patterns can be captured using an on-axis detector in the scanning electron microscope (SEM) with a shorter camera length. These ‘transmission Kikuchi diffraction’ (TKD) patterns present a direct projection of the unit cell and can be routinely analysed using EBSD-based methods and dynamical diffraction theory. In the present work, we enhance this analysis significantly and present a multi-exposure diffraction pattern fusion method that increases the dynamic range of the detected patterns captured with a Timepix3-based direct electron detector (DED). This method uses an easy-to-apply exposure fusion routine to collect data and extend the dynamic range, as well as normalise the intensity distribution within these very wide (>95°) angle patterns. The potential of this method is demonstrated with full diffraction sphere reprojection and highlight potential of the approach to rapidly probe the structure of nano-structured materials in the scanning electron microscope.

Analysis of fabrics obtained during the archeological excavation sites in Israel

AbstractThe aim of this work is to determine the type of material in the given unknown fabric which was excavated from the various archeological sites in Israel using advanced material technology. The four fabrics that were obtained appeared as fragmentary and very degraded textiles. Therefore, we established the treatment method for these fabrics that would be most suitable to deal with the analysis and identification of the material they are made. Fourier transform infrared spectrometry (FTIR), nuclear magnetic resonance (NMR), energy dispersive x‐ray analysis (EDX), scanning electron microscope (SEM) and differential scanning calorimeter (DSC) analysis were used to confirm the material in the fabric samples. Upon detailed analysis it was concluded that all the fabrics are composed either of the synthetic materials such as nylon 6, polyester, and polyacrylonitrile (PAN). The developed method and analysis present herein has the advantages of being rapid and effective for identification of the fabrics and can be applied to varieties of archeological fabrics.

An FFT-based homogenization scheme for cohesive zones with an application to adhesives and the core material of thin metal sandwich plates

Cohesive Zone Models with finite thickness are widely used for the fracture mechanical modeling of material layers, e.g., adhesive layers. Within this approach, the whole layer is modeled as a cohesive zone. Moreover, computational homogenization techniques are crucial for the development of advanced engineering materials, which are often heterogeneous. Compared to the commonly used Finite Element Method (FEM), solvers based on the Fast Fourier Transform (FFT) are expected to reduce the computational effort needed for the homogenization. Originated from an existing method for the computational homogenization of cohesive zones using FEM, a novel FFT-based homogenization scheme for cohesive zone models is presented. Our implementation of the FFT solver uses a displacement-based Barzilai–Borwein scheme and a non-local ductile damage model for the fracture behavior. Finally, the practical application of the method is discussed using an adhesive layer and the core material of HybrixTM metal sandwich plates as examples.

Enhancement of Ni–Zn ferrite nanoparticles parameters via cerium element for optoelectronic and energy applications

This work is concerned with fabricating ferrite nanoparticles of nickel–zinc with the chemical formula: Ni0.55Zn0.45Fe2−xCexO4, 0 ≤ x ≤ 0.011 by co-deposition technique and modifying their electrical, microscopic, spectroscopic, optical, electrical and dielectric properties as advanced engineering materials through doping with the cerium (Ce) element. XRD patterns displayed that the samples have a monophasic Cerium–Nickel–zinc (CNZ) spinel structure without other impurities for cerium concentration (x) ≤ 0.066. Both values of crystallite size and lattice parameters decrease from 33.643 to 23.137 nm and from 8.385 to 8.353 nm, respectively, with the increasing Ce ions substitution content from 0 to 0.066. SEM images indicate that grains of the fabricated compounds are smaller, more perfect, more homogeneous, and less agglomeration than those of the un-doped Ni–Zn nano-ferrites. The maximum intensity of first-order Raman spectral peaks (Eg, F2g(2), A1g(2), and A1g(1)) of CNZ ferrite nanoparticles are observed at about (330, 475, 650, 695) cm−1, respectively, that confirms the CNZ samples have the cubic spinel structure. The direct and indirect optical energy bandgaps of CNZ samples have a wide spectrum of values from semiconductors to insulators according to cerium concentration. The results showed that the values of dielectric constant, dielectric loss factor, and Ac conductivity and the conductivity transition temperature are sensitive to cerium ions content. AC conductivity exhibited by the CNZ samples has the semiconductor materials behavior, where the AC conductivity increases due to temperature or doping concentration. The results indicate that Ni0.55Zn0.45Fe1.944Ce0.066O4 ferrite nanoparticles may be selected for optoelectronic devices, high-frequency circuits, and energy storage applications.

Polymer electrolytes based on protic ionic liquids with perfluorinated anions for safe lithium-ion batteries

The quest for safe and high-performance polymer electrolytes in lithium-ion batteries (LIBs) has led researchers to explore protic ionic liquids (PILs) as potential candidates to be entrapped in polymer matrices. In this context, we present an investigation into solid polymeric systems based on poly(methyl methacrylate) (PMMA) as a host for PILs, featuring 1,8-diazabicyclo-[5,4,0]-undec-7-ene (DBU) cation paired with three different anions: bis(trifluoromethanesulfonyl)imide (TFSI−), trifluoromethanesulfonate (TFO−), and (trifluoromethanesulfonyl-nonafluorobutylsulfonyl)imide (IM14−). Additionally, we explore the lithium-doped IM14-gel-like system to broaden our understanding of these intriguing materials. Through comprehensive thermal analysis, solid-state NMR, and diffusion NMR techniques, we delve into the interactions and structural features of these binary and ternary polymeric systems. Our investigation reveals unique dynamics and ion interactions within the PMMA matrix, shedding light on the potential of these materials for advanced energy storage technologies. Particularly, we highlight the distinctive features of DBUH-IM14 and its specific interaction with the polymeric matrix and the lithium ions, underscoring its significance in advancing safer and more efficient energy storage devices.

Advanced engineering materials and materials processing technologies in dental implant and prosthetic treatment with clinical cases

The article deals with materials science issues concerning the application areas in dental engineering. The monograph aims to present the results of the Author’s work against the background of general achievements, indicating the engineering aspects of dental implant-prosthetic treatment. They include clinical cases, most often concerning complete edentulism, with a detailed discussion of the methodology of the material, technological, and structural design of dental prosthetic restorations, especially the impact of additive manufacturing conditions and surface engineering technology on the mechanical properties and structure of prosthetic restorations.The monograph covering the engineering and technical activities of implant prosthetic treatment includes the Author's aspects concerning the development of the methodology of computer-aided design of dental prosthetic restorations and surgical guides ensuring their correct installation in the oral cavity of patients, along with virtual modelling of treatment plans, modelling of the load status of individual elements of implant-prosthetic systems, development of the methodology of computer-aided production of elements of the prosthetic restoration system as well as implants and implant-scaffolds with the use of milling technology in CNC centres and additive manufacturing by selective laser sintering, the results of research on the influence of additive manufacturing conditions on the structure and properties of titanium and its alloy Ti6Al4V and cobalt alloy Co25Cr5W5MoSi containing studies of biochemical properties for applications for implant-prosthetic purposes in dentistry, the results of tests on the influence of ALD atomic layer conditions on the structure and surface properties of metals and their alloys used in implant-prosthetic treatment in dentistry and the results of tests of prosthetic fillings used in the treatment of Tooth decay.The basis for all the described achievements of the monograph are the comprehensive results of research related to the study of the structure and properties of engineering materials, especially titanium and cobalt alloys used in dentistry, subjected to additive manufacturing using the Selective Laser Sintering SLS method and surface treatment using the Atomic Layer Deposition ALD method, as a domain of materials engineering, in the context of the Industry Integrated Idea 3xI 4 model. 0/5.0 and the 6xE 6 Expectation Principle, which there is a paradigm for materials science. What is important in the approach are the results of biological tests of materials produced in such a way, leading to numerous applications in the Author’s clinical practice in cooperation with dentists and the development of a general concept of a research, design, and production centre for prosthetic restorations and virtual acquisition of diagnostic data from cooperating dental clinics.The article is a monographic study referring to numerous of the Author’s publications, patents, and presentations at scientific conferences and invention fairs, in which very extensive source information is provided concerning both a very large number of literature items and extensive factual material, including the results of materiallographic studies and descriptions of clinical cases, although this study also presents numerous aspects not yet published in any previous works.The study presents, among others, detailed prosthetic and implant-prosthetic solutions implemented by the Author of the study and successfully used by patients. Although the study is formally qualified in the engineering and technical sciences in materials engineering, it has strong links with biomedical engineering and the applied area of interventional dentistry.Numerous original publications, patent solutions, completed projects, and awards at the International Innovation Fair discussed in the monograph, as well as clinical experience related to the treatment of thousands of dental patients in our Author’s clinic, confirm the originality of the approach and indicate the innovative nature of the achievements presented in the article so far. Many years of experience have led to the launch of a constantly developed production centre for prosthetic restorations and a virtual structure for obtaining diagnostic data from cooperating dental clinics. The article addresses scientists dealing with materials engineering applied in interventional dentistry and dental engineers in practice dealing with this issue.

Study on Morphology, Microstructure, and Tribo‐Corrosion Behavior of Laser‐Powder‐Bed‐Fusion‐Fabricated Titanium Alloy

The complicated interplay between microstructure and tribo‐corrosion behavior has long been an intriguing problem in the field of advanced materials engineering. In this study, the effects of different laser energy densities (LEDs) on the surface morphology, microstructure, and tribo‐corrosion behavior of Ti–6Al–4V produced using laser powder bed fusion (LPBF) technology are systematically investigated. The surface morphology and microstructure of the specimens are characterized in detail using various characterization techniques such as optical microscopy, scanning electron microscopy, and X‐ray diffraction. Additionally, a self‐assembled friction–corrosion equipment is employed to evaluate the tribo‐corrosion behavior of the samples at different LED settings. In the results, it is shown that the LED has a significant effect on the surface morphology, microstructure, and tribo‐corrosion behavior of the Ti–6Al–4V. Increasing the LED leads to reduced surface roughness, weakened keyhole and segregation phenomena, more distinct β grain boundaries, and coarser acicular α phase. Moreover, the tribo‐corrosion behavior initially improves and then declines with increasing LED. Furthermore, tribo‐corrosion product and mechanism of the Ti–6Al–4V alloy prepared by LPBF are revealed. This study is of great significance for understanding the relationship between the microstructure and tribo‐corrosion behavior of Ti–6Al–4V manufactured by LPBF.

Comprehensive analysis of 3D printed PA6.6 and fiber‐reinforced variants: Revealing mechanical properties and adhesive wear behavior

AbstractWhile 3‐dimensional (3D) printing technology is advancing rapidly, commonly used filament materials are struggling to meet growing expectations. Polyamide (PA) is a material with high potential to replace commonly used low‐performance filament materials, thanks to its cost‐effectiveness and optimal material properties compared to advanced engineering materials. To explore this potential, the thermal, thermomechanical, and mechanical properties (at different temperatures), as well as the wear characteristics, of PA, short carbon fiber reinforced‐PA (SCFR‐PA), and short glass fiber reinforced‐PA (SGFR‐PA) filaments were comparatively examined in this study. Differential scanning calorimeter analysis (DSC), Dynamic Mechanical Thermal Analysis (DMA), uniaxial tensile tests, and Shore D hardness tests were conducted on the 3D printed specimens. The yield strength decreased by 48% and 73%, respectively, for neat PA as compared to room temperature when tested at 40 °C and 60 °C, while for SCFR‐PA, it decreased by 40% and 60%, and for SGFR‐PA, it decreased by 33% and 48%, respectively. The findings obtained from wear tests conducted on both bottom and top surfaces have demonstrated that glass reinforcement yields better results than carbon reinforcement. The experimental findings have been compared with SEM images, revealing their consistency.Highlights This study focuses on the performance evaluation of 3D printed PA and its composites. The mechanical properties of the materials at different temperatures were compared. Adhesive wear behavior is not directly related to fiber type, wear surface or hardness. Morphological analysis was conducted to elucidate the influence of fiber type on mechanical properties and wear behavior.

Engineering internal nanostructure in 3D‐printed materials via polymer molecular weight distribution

AbstractThe distribution of molecular weights in polymers, known as the molecular weight distribution (MWD), plays a significant role in dictating the behavior of polymer self‐assembly and influencing the characteristics of the resulting materials. This study investigates how MWD of macromolecular chain‐transfer agents (macroCTAs) impact internal nanostructures in materials prepared by polymerization‐induced microphase separation (PIMS) 3D printing. In the aim of elucidating this relationship, the study initially harnessed the precision offered by narrow‐MWD macroCTAs, which provide precise control over phase separation, as assessed by atomic force microscopy (AFM) and small‐angle X‐ray scattering (SAXS) measurements. Through systematic variation of macroCTA molecular weights, the dimensions of the distinct domains were precisely tuned from 10 to 90 nanometers and a decrease of materials stiffness was observed with increased domain size. In contrast, the utilization of a broader MWD, achieved by blending two distinct macroCTAs, resulted in increased domain size dispersity and reduced interface sharpness, without significantly affecting the mechanical properties of the 3D‐printed materials. Overall, this approach expands the strategies for manipulating the nanoscale architecture of 3D‐printed PIMS materials, opening new possibilities for printing advanced engineering materials with tailorable properties.

A numerical study on the low-velocity impact response of hybrid composite materials

Composite materials are advanced engineering materials with superior properties to traditional materials. One of the most important disadvantages is the high cost of composite materials. Therefore, producing composite materials from the first to the last stage is a very important process. Homogenization is the most important parameter in production since composites contain more than one material type in their structure. In addition, composite structures are sensitive materials against low-velocity impacts. In this study, the effect of reinforcement material combination and stacking sequence on mechanical properties used in the production of composite materials was investigated by low-velocity impact simulations using LS-DYNA software. The mass of the 12 mm diameter spherical impactor used in the analyzes was determined as 10 kg and low-velocity impact tests were applied at 20 J, 30 J and 40 J energy levels. The composite samples were modeled with 180x100mm dimensions and the contact between the impactor and the sample was made from the center of the composite structure. Numerical analyzes were performed using the Tsai-Wu damage criterion in the LS-DYNA software, and material properties were defined using the "Mat_Enhanced_Composite_Damage (MAT 055)" material card.