3.46 Ga Apex chert 'microfossils' reinterpreted as mineral artefacts produced during phyllosilicate exfoliation

We acknowledge the facilities, scientific and technical assistance of the Australian Microscopy & Microanalysis Research Facility at: Centre for Microscopy Characterisation and Analysis, The University of Western Australia; Electron Microscopy Unit, The University of New South Wales. These facilities are funded by the Universities, State and Commonwealth Governments. DW was funded by the European Commission and the Australian Research Council (FT140100321). This is ARC CCFS paper number XXX. We acknowledge Martin van Kranendonk, Owen Green, Cris Stoakes, Nicola McLoughlin, the late John Lindsay and the Geological Survey of Western Australia for fieldwork assistance, Thomas Becker for assistance with Raman microspectroscopy, Anthony Burgess from FEI for the preparation of one of the TEM wafers, and Russell Garwood, Tom Davies, Imran Rahman & Stephan Lautenschlager for training and advice on the SPIERS and AVIZO software suites. We thank Chris Fedo and an anonymous reviewer for comments that improved the manuscript.Peer reviewedPostprin

Concurrent Multiscale Computing of Deformation Microstructure by Relaxation and Local Enrichment with Application to Single-Crystal Plasticity

This paper is concerned with the effective modeling of deformation microstructures within a concurrent multiscale computing framework. We present a rigorous formulation of concurrent multiscale computing based on relaxation; we establish the connection between concurrent multiscale computing and enhanced-strain elements; and we illustrate the approach in an important area of application, namely, single-crystal plasticity, for which the explicit relaxation of the problem is derived analytically. This example demonstrates the vast effect of microstructure formation on the macroscopic behavior of the sample, e.g., on the force/travel curve of a rigid indentor. Thus, whereas the unrelaxed model results in an overly stiff response, the relaxed model exhibits a proper limit load, as expected. Our numerical examples additionally illustrate that ad hoc element enhancements, e.g., based on polynomial, trigonometric, or similar representations, are unlikely to result in any significant relaxation in general

Structural Material Property Tailoring Using Deep Neural Networks

Advances in robotics, artificial intelligence, and machine learning are ushering in a new age of automation, as machines match or outperform human performance. Machine intelligence can enable businesses to improve performance by reducing errors, improving sensitivity, quality and speed, and in some cases achieving outcomes that go beyond current resource capabilities. Relevant applications include new product architecture design, rapid material characterization, and life-cycle management tied with a digital strategy that will enable efficient development of products from cradle to grave. In addition, there are also challenges to overcome that must be addressed through a major, sustained research effort that is based solidly on both inferential and computational principles applied to design tailoring of functionally optimized structures. Current applications of structural materials in the aerospace industry demand the highest quality control of material microstructure, especially for advanced rotational turbomachinery in aircraft engines in order to have the best tailored material property. In this paper, deep convolutional neural networks were developed to accurately predict processing-structure-property relations from materials microstructures images, surpassing current best practices and modeling efforts. The models automatically learn critical features, without the need for manual specification and/or subjective and expensive image analysis. Further, in combination with generative deep learning models, a framework is proposed to enable rapid material design space exploration and property identification and optimization. The implementation must take account of real-time decision cycles and the trade-offs between speed and accuracy

BSP-fields: An Exact Representation of Polygonal Objects by Differentiable Scalar Fields Based on Binary Space Partitioning

The problem considered in this work is to find a dimension independent algorithm for the generation of signed scalar fields exactly representing polygonal objects and satisfying the following requirements: the defining real function takes zero value exactly at the polygonal object boundary; no extra zero-value isosurfaces should be generated; C1 continuity of the function in the entire domain. The proposed algorithms are based on the binary space partitioning (BSP) of the object by the planes passing through the polygonal faces and are independent of the object genus, the number of disjoint components, and holes in the initial polygonal mesh. Several extensions to the basic algorithm are proposed to satisfy the selected optimization criteria. The generated BSP-fields allow for applying techniques of the function-based modeling to already existing legacy objects from CAD and computer animation areas, which is illustrated by several examples

Two-phase flow and oxygen transport in the perforated gas diffusion layer of proton exchange membrane fuel cell

Liquid water transport in perforated gas diffusion layers (GDLs)is numerically investigated using a three-dimensional (3D)two-phase volume of fluid (VOF)model and a stochastic reconstruction model of GDL microstructures. Different perforation depths and diameters are investigated, in comparison with the GDL without perforation. It is found that perforation can considerably reduce the liquid water level inside a GDL. The perforation diameter (D = 100 μm)and the depth (H = 100 μm)show pronounced effect. In addition, two different perforation locations, i.e. the GDL center and the liquid water break-through point, are investigated. Results show that the latter perforation location works more efficiently. Moreover, the perforation perimeter wettability is studied, and it is found that a hydrophilic region around the perforation further reduces the water saturation. Finally, the oxygen transport in the partially-saturated GDL is studied using an oxygen diffusion model. Results indicate that perforation reduces the oxygen diffusion resistance in GDLs and improves the oxygen concentration at the GDL bottom up to 101% (D = 100 μm and H = 100 μm)

Review of the Synergies Between Computational Modeling and Experimental Characterization of Materials Across Length Scales

With the increasing interplay between experimental and computational approaches at multiple length scales, new research directions are emerging in materials science and computational mechanics. Such cooperative interactions find many applications in the development, characterization and design of complex material systems. This manuscript provides a broad and comprehensive overview of recent trends where predictive modeling capabilities are developed in conjunction with experiments and advanced characterization to gain a greater insight into structure-properties relationships and study various physical phenomena and mechanisms. The focus of this review is on the intersections of multiscale materials experiments and modeling relevant to the materials mechanics community. After a general discussion on the perspective from various communities, the article focuses on the latest experimental and theoretical opportunities. Emphasis is given to the role of experiments in multiscale models, including insights into how computations can be used as discovery tools for materials engineering, rather than to "simply" support experimental work. This is illustrated by examples from several application areas on structural materials. This manuscript ends with a discussion on some problems and open scientific questions that are being explored in order to advance this relatively new field of research.Comment: 25 pages, 11 figures, review article accepted for publication in J. Mater. Sc