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International audience; ConspectusThe chemical study of materials from natural history and cultural heritage, which provide information for art history, archeology, or paleontology, presents a series of specific challenges. The complexity of these ancient and historical materials, which are chemically heterogeneous, the product of alteration processes, and inherently not reproducible, is a major obstacle to a thorough understanding of their making and long-term behavior (e.g., fossilization). These challenges required the development of methodologies and instruments coupling imaging and data processing approaches that are optimized for the specific properties of the materials. This Account discusses how these characteristics not only constrain their study but also open up specific innovative avenues for providing key historical information. Synchrotron methods have extensively been used since the late 1990s to study heritage objects, in particular for their potential to provide speciation information from excitation spectroscopies and to image complex heritage objects and samples in two and three dimensions at high resolution. We examine in practice how the identification of key intrinsic chemical specificities has offered fertile ground for the development of novel synchrotron approaches allowing a better stochastic description of the properties of ancient and historical materials. These developments encompass three main aspects: (1) The multiscale heterogeneity of these materials can provide an essential source of information in the development of probes targeting their multiple scales of homogeneity. (2) Chemical alteration can be described in many ways, e.g., by segmenting datasets in a semiquantitative way to jointly inform morphological and chemical transformation pathways. (3) The intrinsic individuality of chemical signatures in artifacts triggers the development of specific strategies, such as those focusing on weak signal detection. We propose a rereading of the advent of these new methodologies for analysis and characterization and examine how they have led to innovative strategies combining materials science, instrument development, history, and data science. In particular, we show that spectral imaging and the search for correlations in image datasets have provided a powerful way to address what archeologists have called the uncertainty and ambiguity of the material record. This approach has implications beyond synchrotron techniques and extends in particular to a series of rapidly developing approaches that couple spectral and spatial information, as in hyperspectral imaging and spatially resolved mass spectrometry. The preeminence of correlations holds promise for the future development of machine learning methods for processing data on historical objects. Beyond heritage, these developments are an original source of inspiration for the study of materials in many related fields, such as environmental, geochemical, or life sciences, which deal with systems whose alteration and heterogeneity cannot be neglected.

Hydrophobic properties were conferred to a high-lignin-content Kraft pulp by a laccase-catalysed treatment in the presence of lauryl gallate (LG). The treatment resulted in a two-fold increase in contact angle and conferred water absorption resistance to the pulp. Kappa number was increased, indicating that some phenolic compounds were incorporated in the pulp. A control treatment with LG alone did not affect water absorption, demonstrating that laccase was essential to attain these new properties. The loss of hydrophobicity after an acetone Soxhlet extraction highlighted that adsorbed acetone-soluble compounds played a key role in the properties. GC-FID and HPSEC-UV analysis of the acetone extract indicated the formation of dodecanol and different phenolic oligomers. SEM images showed the treatment-induced changes in the fibre network. Additional experiments with various reaction times and reactant concentrations highlighted the role of LG oxidation products in the introduction of absorption resistance. (C) 2013 Elsevier B.V. All rights reserved.