Three-dimensional morphological modelling of concrete using multiscale Poisson polyhedra.

This paper aims at developing a random morphological model for concrete microstructures. A 3D image of concrete is obtained by microtomography and is used in conjunction with the concrete formulation to build and validate the model through morphological measurements. The morphological model is made up of two phases, corresponding to the matrix, or cement paste and to the aggregates. The set of aggregates in the sample is modelled as a combination of Poisson polyhedra of different scales. An algorithm is introduced to generate polyhedra packings in the continuum space. The latter is validated with morphological measurements.

Ultra-Low Thermal Conductivity and Improved Thermoelectric Performance in Tungsten-Doped GeTe.

Compared to SnTe and PbTe base materials, the GeTe matrix exhibits a relatively high Seebeck coefficient and power factor but has garnered significant attention due to its poor thermal transport performance and environmental characteristics. As a typical p-type IV-VI group thermoelectric material, W-doped GeTe material can bring additional enhancement to thermoelectric performance. In this study, the introduction of W, Ge1-xWxTe (x = 0, 0.002, 0.005, 0.007, 0.01, 0.03) resulted in the presence of high-valence state atoms, providing additional charge carriers, thereby elevating the material's power factor to a maximum PFpeak of approximately 43 µW cm-1 K-2, while slightly optimizing the Seebeck coefficient of the solid solution. Moreover, W doping can induce defects and promote slight rhombohedral distortion in the crystal structure of GeTe, further reducing the lattice thermal conductivity κlat to as low as approximately 0.14 W m-1 K-1 (x = 0.002 at 673 K), optimizing it to approximately 85% compared to the GeTe matrix. This led to the formation of a p-type multicomponent composite thermoelectric material with ultra-low thermal conductivity. Ultimately, W doping achieves the comprehensive enhancement of the thermoelectric performance of GeTe base materials, with the peak ZT value of sample Ge0.995W0.005Te reaching approximately 0.99 at 673 K, and the average ZT optimized to 0.76 in the high-temperature range of 573-723 K, representing an increase of approximately 17% compared to pristine GeTe within the same temperature range.

Nanochitin and Nanochitosan: Chitin Nanostructure Engineering with Multiscale Properties for Biomedical and Environmental Applications.

Nanochitin and nanochitosan (with random-copolymer-based multiscale architectures of glucosamine and N-acetylglucosamine units) have recently attracted immense attention for the development of green, sustainable, and advanced functional materials. Nanochitin and nanochitosan are multiscale materials from small oligomers, rod-shaped nanocrystals, longer nanofibers, to hierarchical assemblies of nanofibers. Various physical properties of chitin and chitosan depend on their molecular- and nanostructures; translational research has utilized them for a wide range of applications (biomedical, industrial, environmental, and so on). Instead of reviewing the entire extensive literature on chitin and chitosan, here, recent developments in multiscale-dependent material properties and their applications are highlighted; immune, medical, reinforcing, adhesive, green electrochemical materials, biological scaffolds, and sustainable food packaging are discussed considering the size, shape, and assembly of chitin nanostructures. In summary, new perspectives for the development of sustainable advanced functional materials based on nanochitin and nanochitosan by understanding and engineering their multiscale properties are described.

Multiscale characterization and micromechanical modeling of crop stem materials.

An essential prerequisite for the efficient biomechanical tailoring of crops is to accurately relate mechanical behavior to compositional and morphological properties across different length scales. In this article, we develop a multiscale approach to predict macroscale stiffness and strength properties of crop stem materials from their hierarchical microstructure. We first discuss the experimental multiscale characterization based on microimaging (micro-CT, light microscopy, transmission electron microscopy) and chemical analysis, with a particular focus on oat stems. We then derive in detail a general micromechanics-based model of macroscale stiffness and strength. We specify our model for oats and validate it against a series of bending experiments that we conducted with oat stem samples. In the context of biomechanical tailoring, we demonstrate that our model can predict the effects of genetic modifications of microscale composition and morphology on macroscale mechanical properties of thale cress that is available in the literature.

Multiscale Toughening Mechanisms in Biological Materials and Bioinspired Designs.

Biological materials found in Nature such as nacre and bone are well recognized as light-weight, strong, and tough structural materials. The remarkable toughness and damage tolerance of such biological materials are conferred through hierarchical assembly of their multiscale (i.e., atomic- to macroscale) architectures and components. Herein, the toughening mechanisms of different organisms at multilength scales are identified and summarized: macromolecular deformation, chemical bond breakage, and biomineral crystal imperfections at the atomic scale; biopolymer fibril reconfiguration/deformation and biomineral nanoparticle/nanoplatelet/nanorod translation, and crack reorientation at the nanoscale; crack deflection and twisting by characteristic features such as tubules and lamellae at the microscale; and structure and morphology optimization at the macroscale. In addition, the actual loading conditions of the natural organisms are different, leading to energy dissipation occurring at different time scales. These toughening mechanisms are further illustrated by comparing the experimental results with computational modeling. Modeling methods at different length and time scales are reviewed. Examples of biomimetic designs that realize the multiscale toughening mechanisms in engineering materials are introduced. Indeed, there is still plenty of room mimicking the strong and tough biological designs at the multilength and time scale in Nature.

Materials Knowledge Systems in Python - A Data Science Framework for Accelerated Development of Hierarchical Materials.

There is a critical need for customized analytics that take into account the stochastic nature of the internal structure of materials at multiple length scales in order to extract relevant and transferable knowledge. Data driven Process-Structure-Property (PSP) linkages provide systemic, modular and hierarchical framework for community driven curation of materials knowledge, and its transference to design and manufacturing experts. The Materials Knowledge Systems in Python project (PyMKS) is the first open source materials data science framework that can be used to create high value PSP linkages for hierarchical materials that can be leveraged by experts in materials science and engineering, manufacturing, machine learning and data science communities. This paper describes the main functions available from this repository, along with illustrations of how these can be accessed, utilized, and potentially further refined by the broader community of researchers.

Extraction of Process-Structure Evolution Linkages from X-ray Scattering Measurements Using Dimensionality Reduction and Time Series Analysis.

The rapid development of robust, reliable, and reduced-order process-structure evolution linkages that take into account hierarchical structure are essential to expedite the development and manufacturing of new materials. Towards this end, this paper lays a theoretical framework that injects the established time series analysis into the recently developed materials knowledge systems (MKS) framework. This new framework is first presented and then demonstrated on an ensemble dataset obtained using small-angle X-ray scattering on semi-crystalline linear low density polyethylene films from a synchrotron X-ray scattering experiment.