Macroscopic Material Properties Research Articles

Programing Performance of Silk Fibroin Superstrong Scaffolds by Mesoscopic Regulation among Hierarchical Structures.

To design higher-strength natural scaffold materials, wool keratin (WK) rich in α-helix structures is used as a well-defined foreign substrate, which induces the formation of β-crystallites in silk fibroin (SF). Consequently, the macroscopic properties of silk materials (such as the rheological properties of SF hydrogels and the mechanical properties of stents) can be manipulated by governing the change in the hierarchical mesoscopic structure of silk materials. In this work, by monitoring the structure and morphology in the SF gel process, the mechanism of the effect of keratin on SF network formation was speculated, which was further used to design ultra-high-strength protein scaffolds. It has been confirmed that WK accelerates the gelation of SF by reducing the multistep nucleation barrier and increasing the primary nucleation sites, and then establishing a high-density SF domain network. The modulus of the protein composite scaffold prepared by this facile strategy can reach 11.55 MPa, and the MC-3T3 cells can grow well on the scaffold surface. The results suggest that freeze-dried biocompatible SF-based scaffolds are potential candidates for bone tissue engineering.

Modeling of dynamic hydrogel swelling within the pore space of a porous medium

Aim of this work is to model a multiphasic porous material modified with a hydrogel made from a granulate of Superabsorbent Polymers (SAP). The void space of the material is simultaneously filled with two interacting phases, namely a chemically active hydrogel and a multi-component aqueous pore fluid. The hydrogel has the ability to absorb and retain large amounts of the pore fluid. Depending on the pore fluid chemistry, the hydrogel is also able to reverse the absorption process by releasing absorbed solution. The overall material is finally classified as a functional porous material since the macroscopic material properties depend on the interaction within the pore space. For instance, swelling of the hydrogel within the pore space changes the morphology of the porous media and influences the hydraulic permeability and the mechanical stiffness. Absorption and desorption processes are modeled in a thermodynamic-consistent framework, while constitutive equations for mass transfer are proposed in accordance to polymer chemistry. Experiments have been carried out and inherent model parameters are identified by a Monte-Carlo method. The predicted results of the derived model are in good accordance to experimental findings. Through the reversibility of the phase transition process, the material becomes an excellent candidate of a functional porous media, e. g. a sophisticated filter, which adapts its hydraulic permeability to the pore fluid chemistry.

Discrete modelling of hydro-chemo-mechanical performance of clay materials

The truncated octahedron cellular assemblies are used to represent the clay materials which align with experimentally characterised microstructures. The cellular assembly is divided into two interacting graphs: one is the mechanical graph which is developed to describe the deformation behaviour of the material, and the other is physical/chemical graph which is developed to demonstrate the reactive transport in the material. This setting is realistic especially when the mechanically-driven cracking has an impact on the transport pathways. Both graphs can represent the anisotropy and heterogeneity of the materials. The model performance is demonstrated using experimental data on the diffusion of species through Opalinus clay (OPA) – a complex process that involves elastic response, diffusion and anionic exclusion. The accuracy of the model is validated by the simulating the confining pressure and reactions dependency of different species transport through OPA. The model improves the understanding of the microstructure influence on the macroscopic transport properties of porous materials. The developed model can be applied to a variety of scientific and engineering problems, such as hydraulic cracking of gas-bearing shale, radioactive nuclear waste geo-disposal, contaminated soil remediation and geological carbon storage.

Multiscale structural characterization of biocompatible poly(trimethylene carbonate) networks photo-cross-linked in a solvent

Poly(trimethylene carbonate) (PTMC) polymeric networks are biocompatible materials with potential biomedical applications. By combining Dynamic Mechanical Analysis (DMA), Solid State Nuclear Magnetic Resonance (NMR), and tensile testing, it was possible to fully characterize the inner structure and its relationship with the macroscopic properties of photo-crosslinked PTMC materials in a solvent medium. PTMC prepared from macromer with various molecular weights (3 kg/mol, 18 kg/mol, and 32 kg/mol) and with various polymer concentrations within the reactive media were analyzed, with the variation of thermomechanical properties and NMR signal decay characterized as a function of both aforementioned synthesis parameters. DMA and solid state Double Quantum (DQ) 1H NMR investigations demonstrated that the network crosslink density is directly related to the macromer molar mass and polymer concentration. More interestingly, tensile tests confirmed that mechanical behavior depended on the materials’ inner structure, notably their crosslink density. Specifically for the 18 kg/mol PTMC networks, dangling and free chains reinforced the network, exemplified by higher Young’s modulus E values. This multiscale investigation provides a promising and precise approach to tailor the macroscopic behavior of PTMC materials, by controlling their specific inner network structural morphologies during synthesis.

First-principles molecular dynamics studying the solidification of Ti-6Al-4V alloy

Solidification process plays a significant role in macroscopic properties of metallic materials. However, the understanding of this process at the atomic level is still far from complete. In this work, for the first time, the first-principles molecular dynamics simulations are carried out to systematically explore the structural evolution and transport properties of Ti-6Al-4V alloy, one of the commonly used alloys for selective laser melting technology, upon cooling from 2400 K to 1300 K. Firstly, the melting range of this alloy is predicted by simulated density to be about 1850–1950 K, which is in good agreement with the experimental value of 1875–1925 K. Afterwards, the local atomic structure variation with temperature is statistically analyzed by structure factors, partial radial distribution functions, coordination number, bond angle distributions, and Voronoi tessellation. It reveals that Ti-6Al-4V alloy experiences a phase transition from 2400 K to 1300 K. The system changes from a liquid dominated by the icosahedral-like cluster to a solid with body-centered cubic structure, where the 〈0, 5, 2, 6〉 and 〈0, 4, 4, 6〉 polyhedra play an important role. Eventually, the diffusion coefficients of Ti, Al, and V are estimated to investigate the kinetic property of liquid Ti-6Al-4V alloy. From 2400 K to 1950 K, the diffusion coefficients of atoms all obey Arrhenius function, and V atom has the largest diffusion coefficient, followed by the Ti atom, which is very close to the self-diffusion coefficient of pure liquid Ti, and finally the Al atom. This abnormal mass dependence of diffusion coefficient is well explained by activation energy. In conclusion, the present work provides insights into the understanding of structural dynamics and the kinetic properties of such alloy melts, which could guide selective laser melting technology to obtain desired microstructure.

Quantitative Mapping of Molecular Substituents to Macroscopic Properties Enables Predictive Design of Oligoethylene Glycol-Based Lithium Electrolytes.

Molecular details often dictate the macroscopic properties of materials, yet due to their vastly different length scales, relationships between molecular structure and bulk properties can be difficult to predict a priori, requiring Edisonian optimizations and preventing rational design. Here, we introduce an easy-to-execute strategy based on linear free energy relationships (LFERs) that enables quantitative correlation and prediction of how molecular modifications, i.e., substituents, impact the ensemble properties of materials. First, we developed substituent parameters based on inexpensive, DFT-computed energetics of elementary pairwise interactions between a given substituent and other constant components of the material. These substituent parameters were then used as inputs to regression analyses of experimentally measured bulk properties, generating a predictive statistical model. We applied this approach to a widely studied class of electrolyte materials: oligo-ethylene glycol (OEG)–LiTFSI mixtures; the resulting model enables elucidation of fundamental physical principles that govern the properties of these electrolytes and also enables prediction of the properties of novel, improved OEG–LiTFSI-based electrolytes. The framework presented here for using context-specific substituent parameters will potentially enhance the throughput of screening new molecular designs for next-generation energy storage devices and other materials-oriented contexts where classical substituent parameters (e.g., Hammett parameters) may not be available or effective.

Polarization-dependent phase transition temperature in plasmonic thin films

Nano-engineering the effective, macroscopic properties of composite materials is becoming increasingly important in material sciences and device development. Here, we report on using embedded plasmonic nanorods to modify the effective, as opposed to the intrinsic, phase transition temperature of vanadium oxide, a phase change material vital for infrared imaging and thermochromics. The nanorods function as controllable, nano-sized thermal sources through the excitation and dissipation of surface plasmons. The polarization dependence in the excitation efficiency modifies the effective phase transition temperature by up to 4.2 °C under broadband illumination of 5.0 W. This work constitutes a proof-of-principle demonstration of tunable and reversible plasmonic modulation of the phase transition temperature in a phase change material. It also represents a new strategy of thermo-plasmonic engineering at the nanoscale.

Polymorphic phase boundary in piezoelectric oxides

The design of phase boundaries has now become a consolidated strategy to improve the functional properties of piezoelectric oxides because of the unique properties that may be obtained in their vicinity. In particular, polymorphic phase boundaries (PPBs) have attracted significant interest in recent years because they represent a significant breakthrough in terms of enhanced piezoelectric activity of lead-free piezoelectric oxides. PPBs are temperature-driven phase transitions where both intrinsic and extrinsic contributions maximize, thereby enhancing the macroscopic properties of piezoelectric materials. This tutorial discusses potassium–sodium–niobate-based systems as model materials to reveal some of the most relevant advances in the design of PPBs through compositional modifications. We focus on how PPBs can be modulated by engineered doping and also discuss the direct relation between PPBs and the enhancement of piezoelectric activity. Finally, we briefly describe the main experimental techniques for detecting PPBs.

Discovery of Structural Complexity through Self-Assembly of Molecules Containing Rodlike Components.

Hierarchical structures are important for transferring and amplifying molecular functions to macroscopic properties of materials. In this regard, rodlike molecules have emerged as one of the most promising molecular building blocks to construct functional materials. Although the self-assembly of conventional molecules containing rodlike components generally results in nematic or layered smectic phases, due to the preferred parallel arrangements of rodlike components, extensive efforts have revealed that rational molecular design provides a versatile platform to engineer rich self-assembled structures. Herein, first successes achieved in polyphilic liquid crystals and rod-coil block systems are summarized. Special attention is paid to recent progress in the conjugation of rodlike building blocks with other molecular building blocks through the molecular Lego approach. Rod-based giant surfactants, sphere-rod conjugates, and dendritic rodlike molecules are covered. Future perspectives of the self-assembly of molecules containing rodlike components are also provided.

Restructuring a Deep Eutectic Solvent by Water: The Nanostructure of Hydrated Choline Chloride/Urea.

Deep eutectic mixtures are a promising sustainable and diverse class of tunable solvents that hold great promise for various green chemical and technological processes. Many deep eutectic solvents (DES) are hygroscopic and find use in applications with varying extents of hydration, hence urging a profound understanding of changes in the nanostructure of DES with water content. Here, we report on molecular dynamics simulations of the quintessential choline chloride-urea mixture, using a newly parametrized force field with scaled charges to account for physical properties of hydrated DES mixtures. These simulations indicate that water changes the nanostructure of solution even at very low hydration. We present a novel approach that uses convex constrained analysis to dissect radial distribution functions into base components representing different modes of local association. Specifically, DES mixtures can be deconvoluted locally into two dominant competing nanostructures, whose relative prevalence (but not their salient structural features) change with added water over a wide concentration range, from dry up to ∼30 wt % hydration. Water is found to be associated strongly with several DES components but remarkably also forms linear bead-on-string clusters with chloride. At high water content (beyond ∼50 wt % of water), the solution changes into an aqueous electrolyte-like mixture. Finally, the structural evolution of the solution at the nanoscale with extent of hydration is echoed in the DES macroscopic material properties. These changes to structure, in turn, should prove important in the way DES acts as a solvent and to its interactions with additive components.

Stress triaxiality effect on void nucleation in ductile metals

AbstractThe stress triaxiality effect on the strain required for void nucleation by particle‐matrix debonding has been investigated by means of micromechanical modelling. A unit‐cell model considering an elastic spherical particle embedded in an elastic‐plastic matrix was developed to the purpose. Particle‐matrix decohesion was simulated through the progressive failure of a cohesive interface. It has been shown that the parameters of matrix‐particle cohesive interface are correlated with macroscopic material properties. Here, a simple relationship for the maximum cohesive opening at interface failure as a function of material fracture toughness and yield stress has been derived. Results seem to confirm that, increasing stress triaxiality, the strain at which void nucleation is predicted to occur decreases exponentially in a similar way as for fracture strain. This result has substantial implications in modelling of ductile damage because it indicates that if the stress triaxiality is high enough, ductile fracture can occur at plastic strain lower than that necessary to nucleate damage for moderate or low stress triaxiality regime.

Metamaterials and Metasurfaces—Historical Context, Recent Advances, and Future Directions

The trajectory of technological progress is ultimately guided by constraints at the physical level. In building a better device or system, we are bound 1) by the properties of the materials available to us and 2) by our understanding of physical phenomena. The physical laws of the universe, immutable as they are, lead us naturally to question whether we may be able to “engineer” raw materials to better allow us to achieve, control, and manipulate natural phenomena for useful purposes. In order to do this, we must first define what we mean by the term “material.” The perception that a material must appear homogeneous to the naked eye (i.e., “a uniform goop, with no discontinuous bits and pieces” [1] ), natural though it may be, is flawed: surely, all materials may be considered heterogeneous on some level of scale, but more importantly, this perspective is tied specifically to the electromagnetic response of these materials to wavelengths of light that are visible to the human eye. For example, although a diamond displays familiar macroscopic properties such as color, luster, and dispersion when viewed under visible light, illumination using X-rays results in a diffraction pattern that reveals its crystalline structure. Thus, the macroscopic properties of a material, e.g. polarizabilities, permittivity, permeability, refractive index, intrinsic bulk or surface impedance, and so on, are revealed only under illumination by wavelengths of light much longer than the size of its scatterers (i.e., its atoms and molecules) and their spacing (e.g., the lattice constants of a crystal). Therefore, it would seem that engineering such macroscopic properties of materials would require control of scattering at length scales of fractions—say several hundredths or even just tenths—of a wavelength, a prohibitive task if dealing in the nanometers or Angstroms. Fortunately, the reach of the electromagnetic spectrum permits us to examine the long-wavelength condition at frequencies where such length scales become much more accessible, such as the microwave and terahertz. Advances in nanoscale fabrication have extended this reach even further to infrared and visible light. At such scales, it becomes possible to synthesize scatterers to exhibit electric and magnetic responses that may then, in analogy to their natural counterparts, be homogenized to describe effective macroscopic electromagnetic properties apparent under illumination by correspondingly long wavelengths.

Photonic materials in circuit quantum electrodynamics

Photonic synthetic materials provide an opportunity to explore the role of microscopic quantum phenomena in determining macroscopic material properties. There are, however, fundamental obstacles to overcome — in vacuum, photons not only lack mass, but also do not naturally interact with one another. Here, we review how the superconducting quantum circuit platform has been harnessed in the last decade to make some of the first materials from light. We describe the structures that are used to imbue individual microwave photons with matter-like properties such as mass, the nonlinear elements that mediate interactions between these photons, and quantum dynamic/thermodynamic approaches that can be used to assemble and stabilize strongly correlated states of many photons. We then describe state-of-the-art techniques to generate synthetic magnetic fields, engineer topological and non-topological flat bands and explore the physics of quantum materials in non-Euclidean geometries — directions that we view as some of the most exciting for this burgeoning field. Finally, we discuss upcoming prospects, and in particular opportunities to probe novel aspects of quantum thermalization and detect quasi-particles with exotic anyonic statistics, as well as potential applications in quantum information science. This Review Article surveys the physics of many-body quantum states formed by microwave photons in circuit quantum electrodynamics environments.

Grain morphology reconstruction of crystalline materials from Laue three-dimensional neutron diffraction tomography

The macroscopic properties of advanced engineering and functional materials are highly dependent on their overall grain orientation distribution, size, and morphology. Here we present Laue 3D neutron diffraction tomography providing reconstructions of the grains constituting a coarse-grained polycrystalline material. Reconstructions of the grain morphology of a highly pure Fe cylinder and a Cu cube sample are presented. A total number of 23 and 9 grains from the Fe and Cu samples, respectively, were indexed and reconstructed. Validation of the grain morphological reconstruction is performed by post-mortem EBSD of the Cu specimen.

Application of machine learning approach in disordered materials

As a new amorphous material, metallic glass has been widely studied because of its excellent mechanical, physical and chemical properties. Glass-forming ability has always been an important problem restricting the development of amorphous materials. In order to design amorphous materials with good glass-forming ability, a lot of research has been done on the glass-forming ability of amorphous materials. It has been shown that a single factor cannot describe glass-forming ability of amorphous materials. Because of the complex and disordered structure of amorphous materials, it is difficult to understand the structure and nature of amorphous materials comprehensively and clearly by traditional methods. Machine learning method, as a new research paradigm, provides new opportunities for exploring these bottleneck scientific issues in disordered materials. In this paper, some machine learning algorithms, such as support vector machine, artificial neural network and K -means clustering, are briefly introduced. Moreover, we briefly review the application of machine learning approach in amorphous materials, including the classification of amorphous structure, the correlation between amorphous structure and properties, and the prediction of macroscopic properties of amorphous materials. We also discuss the future application of machine learning approach to disordered materials, including the development of comprehensive database, high throughput calculation method and the development of machine learning potential function.

Ion mobility spectrometry - Mass spectrometry coupling for synthetic polymers.

This review covers applications of ion mobility spectrometry (IMS) hyphenated to mass spectrometry (MS) in the field of synthetic polymers. MS has become an essential technique in polymer science, but increasingly complex samples produced to provide desirable macroscopic properties of high-performance materials often require separation of species prior to their mass analysis. Similar to liquid chromatography, the IMS dimension introduces shape selectivity but enables separation at a much faster rate (milliseconds vs minutes). As a post-ionization technique, IMS can be hyphenated to MS to perform a double separation dimension of gas-phase ions, first as a function on their mobility (determined by their charge state and collision cross section, CCS), then as a function of their m/z ratio. Implemented with a variety of ionization techniques, such coupling permits the spectral complexity to be reduced, to enhance the dynamic range of detection, or to achieve separation of isobaric ions prior to their activation in MS/MS experiments. Coupling IMS to MS also provides valuable information regarding the 3D structure of polymer ions in the gas phase and regarding how to address the question of how charges are distributed within the structure. Moreover, the ability of IMS to separate multiply charged species generated by electrospray ionization yields typical IMS-MS 2D maps that permit the conformational dynamics of synthetic polymer chains to be described as a function of their length.

Multiscale analysis of mechanical behavior of multilayer steel structures fabricated by wire and arc additive manufacturing

ABSTRACT The mechanical behavior of multilayer steel structures fabricated via wire and arc additive manufacturing (WAAM) has been investigated from the multiscale perspective. The multimaterial WAAM approach can control a heterogeneous structure and improve its mechanical properties. In this study, WAAM equipment based on plasma arc welding was used to fabricate two pairs of single- and duplex-phase multilayer steel structures using austenitic and martensitic stainless steel wires. The heterogeneity of these structures was characterized through micro-indentation tests. In addition, tensile tests of the multilayer structures were conducted to evaluate the effect of heterogeneity on macroscopic material properties. The deformation behavior of the heterogeneous multilayer steel structures was investigated by comparison with the finite element simulations of tensile tests in which the finite element models were created according to the estimated local elastoplastic properties from the results of micro-indentation tests. The micro-indentation tests revealed that the local mechanical properties significantly change during WAAM in cases where martensitic stainless steel wire was used. Additionally, strain-induced transformation plasticity was particularly observed in duplex cases, caused by the metastable austenite phase formed according to the thermal history and through the mixing of alloy elements. Thus, the heterogeneity of the multilayer steel structures became more complicated than its design, and consequently, its macroscopic mechanical properties exceeded the upper and lower bounds of a micromechanic estimation. The results show the potential to fabricate a structure having a unique mechanical behavior via the multimaterial WAAM approach.

Microstructure and Mechanical/Elastic Performance of Biobased Poly (Butylene Furanoate)-Block-Poly (Ethylene Oxide) Copolymers: Effect of the Flexible Segment Length.

The aim of this paper is to extend knowledge on biobased poly(butylene furanoate)–block–poly (ethylene oxide) (PBF-b-PEO) copolymers’ performance by studying the effect of the PEO segment’s molecular weight on the microstructure and materials behavior. As crystallization ability of PEO depends on its molecular weight, the idea was to use two PEO segment lengths, expecting that the longer one would be able to crystallize affecting the phase separation in copolymers, thus affecting their mechanical performance, including elasticity. Two series of PBF-block-PEOs with the PEO segments of 1000 and 2000 g/mol and different PBF/PEO segment ratios were synthesized by polycondensation in melt, injection molded to confirm their processability, and subjected to characterization by NMR, FTIR, DSC, DMTA, WAXS, TGA, and mechanical parameters. Indeed, the PEO2000 segment not only supported the crystallization of the PBF segments in copolymers, but at contents at least 50 wt % is getting crystallizable in the low temperature range, which results in the microstructure development and affects the mechanical properties. While the improvement in the phase separation slightly reduces the copolymers’ ability to deformation, it is beneficial for the elastic recovery of the materials. The investigations were performed on the injection molded samples reflecting the macroscopic properties of the bulk materials.

Coupling of microstructural and macrostructural computational approaches for asphalt pavements under rolling tire load

AbstractTo combine the advantages of microstructural finite element (FE) models of asphalt composites and macrostructural FE models of pavement structures subjected to rolling tire load, this article introduces a novel consistent simulation chain. Starting with experimental tests of asphalt mortar, an existing microstructural FE model of a Stone Mastic Asphalt, which contains coarse aggregates, asphalt mortar and air voids, is parameterized and validated. The microstructural model is then applied to identify macroscopic (homogenized) material properties of the asphalt mixture that are used in FE computations of two pavement structures under rolling tire load. The macrostructural pavement computations are evaluated by a new macro–micro‐interface that generates realistic time‐dependent displacement boundary conditions representing the rolling tire loading conditions for the microstructural model. A verification and exemplary microstructural computations at rolling tire load boundary conditions show that the introduced simulation chain allows for the investigation of the processes, stresses, and strains inside the asphalt composite at realistic loading conditions. Results can, for example, be used to improve the experimental tests on the component level as well as to gain a better understanding of the interacting processes in asphalt mixtures under rolling tire load.

Thermal properties of graphene-based polymer composite materials: A molecular dynamics study

Interfaces between graphene play a crucial yet poorly understood role in the transport of heat in graphene-based composite materials. The primary focus of this study was on developing a quantitative understanding of the mechanism underlying the heat flow through the structure of a graphene-based polymer matrix composite material. The macroscopic thermal properties of the composite material were studied to provide an effective way to improve thermal conductivity for polymers. Molecular dynamics simulations were performed to understand the thermal resistance of interfaces between graphene and to optimize the condition of the interface for nanoscale thermal reinforcement. A modified Maxwell Garnett effective medium theory was used to predict the thermal conductivity of the composite material. The results indicated that the thermal properties of a graphene-based polymer matrix composite material depends upon the details of the microscopic structure and atomic interactions within the composite material. Interfaces between graphene contribute significantly to the thermal conductivity of the composite material. This is even more critical for composite materials where the lateral size of graphene can affect the thermal performance of the composite material significantly. Low thermal boundary resistance and high thermal conductivity can be achieved by introducing the structure of a carbon cross-link network between graphene. The proper combination of graphene with large size and carbon cross-links with high density can lead to a fifty-fold improvement in overall thermal performance for the polymer matrix composite material. The relative position between graphene can be adjusted for the further optimization of interfacial conditions, but with little success in nanoscale thermal reinforcement. The bulk thermal conductivity of graphene nanoribbons has been found to be about 2570 W/m·K at room temperature. The results can provide a theoretical basis for understanding the applied physics of thermal transport at the nanoscale in graphene-based polymer matrix composite materials.