Since the beginning of the industrial age, material performance and design have been in the midst of innovation of many disruptive technologies. Today's electronics, space, medical, transportation, and other industries are enriched by development, design and deployment of composite, heterogeneous and multifunctional materials. As a result, materials innovation is now considerably outpaced by other aspects from component design to product cycle. In this article, we review predictive nonlinear theories for multiscale modeling of heterogeneous materials. Deeper attention is given to multiscale modeling in space and to computational homogenization in addressing challenging materials science questions. Moreover, we discuss a state-of-the-art platform in predictive image-based, multiscale modeling with co-designed simulations and experiments that executes on the world's largest supercomputers. Such a modeling framework consists of experimental tools, computational methods, and digital data strategies. Once fully completed, this collaborative and interdisciplinary framework can be the basis of Virtual Materials Testing standards and aids in the development of new material formulations. Moreover, it will decrease the time to market of innovative products.

Pathogen infection leads to defence induction as well as to changes in carbohydrate metabolism of plants. Salicylic acid and oxylipins are involved in the induction of defence, but it is not known if these signalling molecules also mediate changes in carbohydrate metabolism. In this study, the effect of application of salicylic acid and the oxylipins 12-oxo-phytodienoic acid (OPDA) and jasmonic acid on photosynthesis was investigated by kinetic chlorophyll fluorescence imaging and compared with the effects of infection by virulent and avirulent strains of Pseudomonas syringae. Both pathogen strains and OPDA caused a similar change in fluorescence parameters of leaves of Arabidopsis thaliana. The response to OPDA appeared faster compared with that to the pathogens and persisted only for a short time. Infiltration with jasmonic acid or salicylic acid did not lead to a localized and distinct fluorescence response of the plant. To capture the faint early symptoms of the plant response, a novel algorithm was applied identifying the unique fluorescence signature-the set of images that, when combined, yield the highest contrast between control and infected leaf segments. Unlike conventional fluorescence parameters, this non-biased approach indeed detected the infection as early as 6 h after inoculation with bacteria. It was posssible to identify distinct fluorescence signatures characterizing the early and late phases of the infection. Fluorescence signatures of both infection phases were found in leaves infiltrated with OPDA.

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In this paper, we present a systematic approach for characterization and reconstruction of statistically optimal representative unit cells of polydisperse particulate composites. Microtomography is used to gather rich three-dimensional data of a packed glass bead system. First-, second-, and third-order probability functions are used to characterize the morphology of the material, and the parallel augmented simulated annealing algorithm is employed for reconstruction of the statistically equivalent medium. Both the fully resolved probability spectrum and the geometrically exact particle shapes are considered in this study, rendering the optimization problem multidimensional with a highly complex objective function. A ten-phase particulate composite composed of packed glass beads in a cylindrical specimen is investigated, and a unit cell is reconstructed on massively parallel computers. Further, rigorous error analysis of the statistical descriptors (probability functions) is presented and a detailed comparison between statistics of the voxel-derived pack and the representative cell is made.

This article focuses on computational multiscale methods for the mechanical response of nonlinear heterogeneous materials. After a short historical note, a brief overview is given of some recent activities in the field, with a particular focus on nonlinear homogenization methods. The two‐scale nonlinear computational homogenization (CH) scheme for mechanics is presented, along with details on representative unit cell aspects and statistics. Model performance is advocated through a decoupled implementation and multiscale schemes based on the nonuniform transformation field analysis. High‐performance parallel multiscale implementations of the CH scheme are addressed in more detail.

Localized infection of a plant can be mapped by a sequence of images capturing chlorophyll fluorescence transients in actinic light. Choice of the actinic light protocol co-determines fluorescence contrast between infected leaf segment and surrounding healthy tissue. Frequently, biology cannot predict with which irradiance protocol, in which fluorescence image of the sequence, and in which segment of the image there will be the highest contrast between the healthy and infected tissue. Here, we introduce a new technique that can be applied to identify the combination of chlorophyll fluorescence images yielding the highest contrast. The sets of the most contrasting images vary throughout the progress of the infection. Such specific image sets, stress-revealing fluorescence signatures, can be found for the initial and late phases of the infection. Using these signatures, images can be divided into segments that show tissue in different infection phases. We demonstrate the capacity of the algorithm in an investigation of infection of the model plant Arabidopsis thaliana by the bacterium Pseudomonas syringae. We show that the highest contrast is found with transients elicited by fluctuating, harmonically modulated irradiance with long periods.

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Plasmopara viticola is an economically important pathogen of grapevine. Early detection of P. viticola infection can lead to improved fungicide treatment. Our study aimed to determine whether chlorophyll fluorescence (Chl-F) imaging can be used to reveal early stages of P. viticola infection under conditions similar to those occurring in commercial vineyards. Maximum (F(V)/F(M)) and effective quantum yield of photosystem II (I broken vertical bar(PSII)) were identified as the most sensitive reporters of the infection. Heterogeneous distribution of F(V)/F(M) and I broken vertical bar(PSII) in artificially inoculated leaves was associated with the presence of the developing mycelium 3 days before the occurrence of visible symptoms and 5 days before the release of spores. Significant changes of F(V)/F(M) and I broken vertical bar(PSII) were spatially coincident with localised spots of inoculation across the leaf lamina. Reduction of F(V)/F(M) was restricted to the leaf area that later yielded sporulation, while the area with significantly lower I broken vertical bar(PSII) was larger and probably reflected the leaf parts in which photosynthesis was impaired. Our results indicate that Chl-F can be used for the early detection of P. viticola infection. Because P. viticola does not expand systemically in the host tissues and the effects of infection are localised, Chl-F imaging at high resolution is necessary to reveal the disease in the field