Self-similar mesostructure evolution of the growing mollusc shell reminiscent of thermodynamically driven grain growth.

Significant progress has been made in understanding the interaction between mineral precursors and organic components leading to material formation and structuring in biomineralizing systems. The mesostructure of biological materials, such as the outer calcitic shell of molluscs, is characterized by many parameters and the question arises as to what extent they all are, or need to be, controlled biologically. Here, we analyse the three-dimensional structure of the calcite-based prismatic layer of Pinna nobilis, the giant Mediterranean fan mussel, using high-resolution synchrotron-based microtomography. We show that the evolution of the layer is statistically self-similar and, remarkably, its morphology and mesostructure can be fully predicted using classical materials science theories for normal grain growth. These findings are a fundamental step in understanding the constraints that dictate the shape of these biogenic minerals and shed light on how biological organisms make use of thermodynamics to generate complex morphologies.

Semantic integration of diverse data in materials science: Assessing Orowan strengthening.

This study applies Semantic Web technologies to advance Materials Science and Engineering (MSE) through the integration of diverse datasets. Focusing on a 2000 series age-hardenable aluminum alloy, we correlate mechanical and microstructural properties derived from tensile tests and dark-field transmission electron microscopy across varied aging times. An expandable knowledge graph, constructed using the Tensile Test and Precipitate Geometry Ontologies aligned with the PMD Core Ontology, facilitates this integration. This approach adheres to FAIR principles and enables sophisticated analysis via SPARQL queries, revealing correlations consistent with the Orowan mechanism. The study highlights the potential of semantic data integration in MSE, offering a new approach for data-centric research and enhanced analytical capabilities.