Internal Structure Of Material Research Articles

Terminal ballistic and static impactive loading on thick concrete target

The rigid projectile penetration into thick concrete targets was studied through static deep indentation and terminal ballistic tests with small-diameter projectiles. This work aims to investigate the correlation between indentation and penetration for concrete. First, ballistic penetration tests were conducted to obtain the dynamic impact test data including depth of penetration (DOP) and crater dimensions. Second, a sequent static deep indentation test on the concrete target was also carried out. The net axial resisting force was calculated from the recorded force-displacement history considering the effect of friction on static indentation. The resistance measurement was in good agreement with the ones from the ballistic tests suggesting that the static deep indentation tests can be used to estimate the target strength parameter R (Forrestal et al. 2003) of penetration resistance. Third, both the penetration and indentation tests were numerically studied by using the recently developed Lattice Discrete Particles Model (LDPM). LDPM is a discrete model built upon the internal structure of materials at mesoscale with inter-particle constitutive laws accounting for tensile cohesive fracture between aggregates, strain hardening in compression and compaction due to pore collapse. Numerical simulations of the penetration tests were validated by comparing the numerical results with the experimentally recorded DOP and crater damage contour. Moreover, the indentation simulation well captured the force-displacement curve with friction subtracted. Finally, the correlation between the penetration resisting force and static indentation load was further validated by extensive numerical simulations.

Investigating the Phase-Morphology of PLLA-PCL Multiblock Copolymer / PDLA Blends Cross-linked Using Stereocomplexation

ABSTRACTThe macroscale function of multicomponent polymeric materials is dependent on their phase-morphology. Here, we investigate the morphological structure of a multiblock copolymer consisting of poly(L-lactide) and poly(ε-caprolactone) segments (PLLA-PCL), physically cross-linked by stereocomplexation with a low molecular weight poly(D-lactide) oligomer (PDLA). The effects of blend composition and PLLA-PCL molecular structure on the morphology are elucidated by AFM, TEM and SAXS. We identify the formation of a lattice pattern, composed of PLA domains within a PCL matrix, with an average domain spacing d0 = 12 – 19 nm. The size of the PLA domains were found to be proportional to the block length of the PCL segment of the copolymer and inversely proportional to the PDLA content of the blend. Changing the PLLA-PCL / PDLA ratio caused a shift in the melt transition Tm attributed to the PLA stereocomplex crystallites, indicating partial amorphous phase dilution of the PLA and PCL components within the semicrystalline material. By elucidating the phase structure and thermal character of multifunctional PLLA-PCL / PDLA blends, we illustrate how composition affects the internal structure and thermal properties of multicomponent polymeric materials. This study should facilitate the more effective incorporation of a variety of polymeric structural units capable of stimuli responsive phase transitions, where an understanding the phase-morphology of each component will enable the production of multifunctional soft-actuators with enhanced performance.

Solving Material Mechanics and Multiphysics Problems of Metals with Complex Microstructures Using DAMASK—The Düsseldorf Advanced Material Simulation Kit

Predicting process–structure and structure–property relationships are the key tasks in materials science and engineering. Central to both research directions is the internal material structure. In the case of metallic materials for structural applications, this internal structure, the microstructure, is the collective ensemble of all equilibrium and nonequilibrium lattice imperfections. Continuum models to derive process–structure and structure–property relationships are based on two ingredients: 1) quantitative state variables that capture the essential features of the material's state and 2) kinetic equations for the state that describe its evolution under load. Successful models, that is, models that are of practical use, depend on state variables and corresponding evolution laws that are sufficiently representative for the microstructure and that are able to describe the phenomena of interest. The development of software tools capable to integrate these different aspects to get a holistic view of process–structure–property relationships requires joint efforts from specialists in different disciplines and a long‐term perspective. The Düsseldorf Advanced Material Simulation Kit (DAMASK) is such a tool. In this overview article published on the occasion of Advanced Engineering Materials' 20th anniversary, some representative application examples which demonstrate how DAMASK can be used to study metallic microstructures at different length scales are presented.

TomoGAN: low-dose synchrotron x-ray tomography with generative adversarial networks: discussion

Synchrotron-based x-ray tomography is a noninvasive imaging technique that allows for reconstructing the internal structure of materials at high spatial resolutions from tens of micrometers to a few nanometers. In order to resolve sample features at smaller length scales, however, a higher radiation dose is required. Therefore, the limitation on the achievable resolution is set primarily by noise at these length scales. We present TomoGAN, a denoising technique based on generative adversarial networks, for improving the quality of reconstructed images for low-dose imaging conditions. We evaluate our approach in two photon-budget-limited experimental conditions: (1) sufficient number of low-dose projections (based on Nyquist sampling), and (2) insufficient or limited number of high-dose projections. In both cases, the angular sampling is assumed to be isotropic, and the photon budget throughout the experiment is fixed based on the maximum allowable radiation dose on the sample. Evaluation with both simulated and experimental datasets shows that our approach can significantly reduce noise in reconstructed images, improving the structural similarity score of simulation and experimental data from 0.18 to 0.9 and from 0.18 to 0.41, respectively. Furthermore, the quality of the reconstructed images with filtered back projection followed by our denoising approach exceeds that of reconstructions with the simultaneous iterative reconstruction technique, showing the computational superiority of our approach.

A novel structure-property relationship model based on machine learning

In materials science, the relationship between the material internal structure and its associated macroscale properties can be used to guide the design of materials. In this study, we constructed an interpretative machine learning (ML) model to capture the structure-property relationship and predict the solid solubility in binary alloy systems. To do this, we used a dataset containing about 1843 binary alloys and corresponding experiment values of solid solubility. We designed a common function to represent the relationship between individual descriptor and solid solubility, and a deep neural network to integrate the multiple functions. The resulting model can correctly predict the solid solubility value than other ML models. What is more, based on this model, it is feasible to analyze the effect of structures on target property.

Industrial applications of computed microtomography (microCT) technique

Microcomputed tomography is a non-invasive and non-destructive essential tool for morphological and topological studies of internal structures of different materials allowing 3D visualizations. Currently, many studies focusing industrial applications using microCT as a tool are being developed. In all applications, microCT proved to be an adequate technique for the characterization of different materials allowing accurate and reliable qualitative and quantitative assessments.

Compositional and structural analysis of Fukushima-derived particulates using high-resolution x-ray imaging and synchrotron characterisation techniques

Both the three-dimensional internal structure and elemental distribution of near-field radioactive fallout particulate material released during the March 2011 accident at the Fukushima Daiichi Nuclear Power Plant is analysed using combined high-resolution laboratory and synchrotron radiation x-ray techniques. Results from this study allow for the proposition of the likely formation mechanism of the particles, as well as the potential risks associated with their existence in the environment, and the likely implications for future planned reactor decommissioning. A suite of particles is analyzed from a locality 2 km from the north-western perimeter of the site – north of the primary contaminant plume in an area formerly attributed to being contaminated by fallout from reactor Unit 1. The particles are shown to exhibit significant structural similarities; being amorphous with a textured exterior, and containing inclusions of contrasting compositions, as well as an extensive internal void volume – bimodal in its size distribution. A heterogeneous distribution of the various elemental constituents is observed inside a representative particle, which also exhibited a Fukushima-derived radiocesium (134Cs, 135Cs and 137Cs) signature with negligible natural Cs. We consider the structure and composition of the particle to suggest it formed from materials associated with the reactor Unit 1 building explosion, with debris fragments embedded into the particles surface. Such a high void ratio, comparable to geological pumice, suggests such material formed during a rapid depressurisation and is potentially susceptible to fragmentation through attrition.

A Framework for the Systematic Design of Segmentation Workflows

Segmentation of microscopy images is an essential step in most experimental studies of process–structure–property relationships in advanced materials. Currently employed segmentation approaches require the user to identify and string together a sequence of algorithms (and codes) into customized workflows that need extensive tweaking and optimization (often accomplished through repeated trials) for producing the most reliable results for each set of images. Recent advances in materials characterization instruments have significantly increased the throughput and variety of microscopy images that could be generated in the efforts to document and understand the material internal structure. There is a critical need for a guiding framework for the systematic design of segmentation workflows that can eventually lead to fully automated segmentation workflows. In this work, we propose one such modular framework consisting of five sequential steps that is applicable to segmentation of a broad variety of microscopy images. Each step is designed to accomplish a specific subtask in the overall segmentation using available functions in popular software packages. Furthermore, the modular nature of the framework allows the user to explore alternate functions in each step, while systematically comparing their relative efficacies. We describe this new segmentation framework in this paper and demonstrate its value through case studies involving a variety of microstructures.

Evaluation of internal structure of self-contracting auxetic rubber material by finite element analysis

Evaluation of internal structure of self-contracting auxetic rubber material by finite element analysis

Beam characterization for neutron imaging after installation of the external collimator at TRR-1/M1

The neutron imaging facility at Thai Research Reactor-1/Modification 1 (TRR-1/M1), located at Thailand Institute of Nuclear Technology (Public Organization) has been improved for non-destructive characterization of internal structure of materials. The aims are to study the beam characteristic after an installation of the external collimator, and to optimize the exposure condition for a new setup. The neutron imaging setup was modified to increase the L/D ratio. As a consequence of the extended distance from the beam port to the sample position, an external collimator was installed to focus the neutron beam since 2018. Moreover, a new sample holder was installed to support sample rotation and translations with increased stability. The experiment was performed at the TRR-1/M1 reactor with 1 MW-reactor power. The neutron beam at the 8-inches south beam port of the TRR-1/M1 was evaluated in terms of beam homogeneity and the relationship between the grayscale value and image quality obtained from a CCD camera. The present performance of the neutron imaging system was tested with an ASTM standard sample, called sensitivity indicator. The results are shown in terms of image contrast and sharpness.

Internal nanocrystalline structure and stiffness alterations of electrospun polycaprolactone-based mats after six months of in vitro degradation. An atomic force microscopy assay

Biodegradable electrospun nanofibrous scaffolds for bone tissue engineering applications have been extensively studied as they can provide attractive open-worked architecture resembling natural extracellular matrix, with tunable physical and mechanical properties enhancing positive cellular response. For this purpose, electrospun mats were tested in terms of morphology, mechanical and physical properties, degradation kinetics and related phenomena occurring in micro- and nanoscale. However, detailed description of internal nanostructures of electrospun mats and their changes related to in vitro degradation is still missing. In this manuscript, we report qualitative and quantitative evaluation of internal lamellar nanostructure of electrospun fibrous scaffolds made of pristine polycaprolactone and composite with polymeric matrix and nanoceramic (hydroxyapatite) filler during in vitro degradation. Morphological and mechanical studies performed with an atomic force microscope were followed by scanning electron microscope imaging and X-Ray diffraction. The results suggest degradation-dependent alteration of both organization and thickness of nano-scaled lamellas recorded with atomic force microscope. Moreover, changes of the material's internal structure were followed by enhanced stiffness and higher crystallinity of electrospun fibers.

Metasurface-Based Molecular Biosensing Aided by Artificial Intelligence.

Molecular spectroscopy provides unique information on the internal structure of biological materials by detecting the characteristic vibrational signatures of their constituent chemical bonds at infrared frequencies. Nanophotonic antennas and metasurfaces have driven this concept towards few-molecule sensitivity by confining incident light into intense hot spots of the electromagnetic fields, providing strongly enhanced light-matter interaction. In this Minireview, recently developed molecular biosensing approaches based on the combination of dielectric metasurfaces and imaging detection are highlighted in comparison to traditional plasmonic geometries, and the unique potential of artificial intelligence techniques for nanophotonic sensor design and data analysis is emphasized. Because of their spectrometer-less operation principle, such imaging-based approaches hold great promise for miniaturized biosensors in practical point-of-care or field-deployable applications.

Improvement in quantitative phase mapping by a hard x-ray microscope equipped with a Lau interferometer

X-ray phase contrast imaging offers a complementary modality next to conventional absorption. To reveal internal structures of soft materials in high resolution, an X-ray phase imaging microscope has been developed by installing a Lau interferometer into a commercially available ZEISS Xradia 800 Ultra-nano computed tomography X-ray microscope. On this system, a twin phase image is once generated through measurements of interference fringes. In order to produce a quantitative X-ray phase map, the twin phase image should be treated by deconvolution. However, conventional deconvolution results showed a reduction in image quality due to noise and artifacts. Therefore, we propose and evaluate the performance of an iterative deconvolution method. The results show that the proposed deconvolution method does not affect spatial resolution, increases the signal to noise ratio compared to that of the twin phase image, and is capable of imaging complex structures.

Wood–Moisture Relationships Studied with Molecular Simulations: Methodological Guidelines

This paper aims at providing a methodological framework for investigating wood polymers using atomistic modeling, namely, molecular dynamics (MD) and grand canonical Monte Carlo (GCMC) simulations. Atomistic simulations are used to mimic water adsorption and desorption in amorphous polymers, make observations on swelling, mechanical softening, and on hysteresis. This hygromechanical behavior, as observed in particular from the breaking and reforming of hydrogen bonds, is related to the behavior of more complex polymeric composites. Wood is a hierarchical material, where the origin of wood-moisture relationships lies at the nanoporous material scale. As water molecules are adsorbed into the hydrophilic matrix in the cell walls, the induced fluid–solid interaction forces result in swelling of these cell walls. The interaction of the composite polymeric material, that is the layer S2 of the wood cell wall, with water is known to rearrange its internal material structure, which makes it moisture sensitive, influencing its physical properties. In-depth studies of the coupled effects of water sorption on hygric and mechanical properties of different polymeric components can be performed with atomistic modeling. The paper covers the main components of knowledge and good practice for such simulations.

FIB-SEM Three-Dimensional Tomography for Characterization of Carbon-Based Materials

A review on the recent advances of the three-dimensional (3D) characterization of carbon-based materials was conducted by focused ion beam-scanning electron microscope (FIB-SEM) tomography. Current studies and further potential applications of the FIB-SEM 3D tomography technique for carbon-based materials were discussed. The goal of this paper is to highlight the advances of FIB-SEM 3D reconstruction to reveal the high and accurate resolution of internal structures of carbon-based materials and provide suggestions for the adoption and improvement of the FIB-SEM tomography system for a broad carbon-based research to achieve the best examination performances and enhance the development of innovative carbon-based materials.

Effect of carbonization temperature on the grindability of carbonaceous material produced from different coals

Carbonization experiments were conducted on four kinds of sub‐bituminous coal particles at a temperature range of 450–1200 °C. The effect of treating temperature on the grindability of produced carbonaceous materials was investigated, and its mechanism was analyzed through various means. Results show that the grindability of all coals, whether caking or slightly‐caking, exhibit the same variation trend with an increase in carbonization temperature. Moreover, the entire process can be divided into four stages. (1) After the most intense devolatilization stage, the grindability of carbonaceous material exhibited different degrees of increase compared with that of raw coal because of the development of a pore structure. (2) The first significant decrease in the grindability occurred from the plastic stage to the complete resolidification of the coal matrix. (3) After the aromatic polycondensation stage accompanied by a large amount of H2 release, the coal molecular structure became compact, such that the grindability of semi‐coke considerably decreased again. (4) At high temperatures, the coal matrix underwent graphitization, which changed semi‐coke to coke. The molecular structure of coal became ordered, and the grindability decreased again. The analysis shows that a change in the internal chemical structure of carbonaceous material has a much more pronounced effect on grindability than a change in its pore structure, except in the first stage. The constant compaction and regularization of the coal molecular structure continued happening throughout the entire process and play a decisive role in the change in grindability.

Simulation of Uniaxial Deformation of a Ferrogel Sample Exposed by the External Magnetic Field

Ferrogels are magnetoactive composite materials with very soft hydrogel matrix, filled by ferromagnetic particles. This work is devoted to a numerical investigation of magneto-mechanical behaviour of a small sample of ferrogel. Our model is based on a coarse grained molecular dynamics approach: polymeric matrix is emulated by lattice of bead-strings chains and magnetic single-domain particles are considered as rigid spheres and placed in a nodes of the lattice. This model was previously successfully used for a research of equilibrium magnetization of the material. Here we examine of the reaction of ferrogel sample on uniaxial tension in presence of an external magnetic field. Modelling proves that key role in a changes of mechanical response during the magnetization plays an internal structure of material, specifically, the existence of particles aggregates, induced by forces of dipolar magnetic interaction. Also the influence of magnetic anisotropy on a process is considered.

Three-dimensional structure of high-performance heat insulator produced with micro and nano particle alumina

The internal structure of heat insulator materials, which were built by mixing micrometer-size α-alumina with nanometer-size fumed alumina though changing their mixture ratios, was inspected using transmission electron microscopy (TEM) tomography and synchrotron radiation nano-tomography. The heat insulator samples formed by two kinds of alumina phase have high porosity that consist of hierarchical structures of nanometer and micrometer size. From TEM observation, it is found that the porosity was 90.7% in the aggregate of fumed alumina with an average particle diameter of 35 nm whilst the average pore size was 70–80 nm. From observation of synchrotron radiation nano-tomography, it is found that α-alumina particles distribute homogeneously in samples that have fumed alumina phase of more than 50 mass%. The effect of internal microstructure on heat insulator properties were considered by performing a simple heat transfer simulation using image based models prepared from synchrotron radiation nano-tomography images. Similar changes in heat transfer with the experiment were obtained by the simulation. Therefore, it is suggested that the change of heat transfer depending on a mixture ratio of α-alumina and fumed alumina is mainly caused by the internal microstructure, that is, the distribution and connectivity of α-alumina phase within fumed alumina phase.

Direct observation of picosecond melting and disintegration of metallic nanoparticles

Despite more than a century of study, the fundamental mechanisms behind solid melting remain elusive at the nanoscale. Ultrafast phenomena in materials irradiated by intense femtosecond laser pulses have revived the interest in unveiling the puzzling processes of melting transitions. However, direct experimental validation of various microscopic models is limited due to the difficulty of imaging the internal structures of materials undergoing ultrafast and irreversible transitions. Here we overcome this challenge through time-resolved single-shot diffractive imaging using X-ray free electron laser pulses. Images of single Au nanoparticles show heterogeneous melting at the surface followed by density fluctuation deep inside the particle, which is directionally correlated to the polarization of the pumping laser. Observation of this directionality links the non-thermal electronic excitation to the thermal lattice melting, which is further verified by molecular dynamics simulations. This work provides direct evidence to the understanding of irreversible melting with an unprecedented spatiotemporal resolution.

Micro-CT-based micromechanics and numerical homogenization for effective elastic property of ultra-high performance concrete

A computational homogenization model using microstructures obtained from X-ray micro-CT is developed to estimate the porosity-based elastic properties of ultra-high performance concrete under freeze–thaw action. The model is transformed directly from micro-CT which is capable of reflecting realistic distribution of porosity and heterogeneities inside the ultra-high performance concrete. Factors are taken into consideration, including the determination of representative volume element, the position and numbers of representative volume element cubes, fiber orientation, image resolution, applied filter, and pore distribution. The relationship between the material internal structure and freeze–thaw resistance is studied at micro-scale. The volume-averaged homogenization approach is applied to calculate the effective properties of the ultra-high performance concrete which are compared with experimental data. It is demonstrated that the proposed model provides an effective tool to evaluate the elastic properties of the ultra-high performance concrete based on microstructural characterization data.