Extracting Composition And Texture Of Ancient Pigments From Modeling Of Their Spectral Reflectance

Universities and Institutes of France
October 09, 2022
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  • Organisation/Company: Université Grenoble Alpes
  • Research Field: Technology › Materials technology
  • Researcher Profile: First Stage Researcher (R1) Recognised Researcher (R2) Established Researcher (R3) Leading Researcher (R4)
  • Application Deadline: 09/10/2022 00:00 - Europe/Brussels
  • Location: France › Grenoble
  • Type Of Contract: Temporary
  • Job Status: Full-time
  • Offer Starting Date: 01/12/2022
  • We need to reconstruct the knowledge and know-how of ancient societies, to better understand their connection with their environment and their social organization. Prehistoric societies left many cave paintings, using pigments that were applied to the cave walls. Archeologists, chemists, geologists and physicians are working together to identify the composition of these pigments, their geographic origin, as well as the preparation methods that were applied to them. In order to do this, we would need the chemical and mineral composition as well as the physical characteristics of these pigments: the size of the grains, their shape, their distribution. We can extract that information by extracting samples locally, but these sampling are destructive, and we would like to avoid it.

    We can measure without contact, in the laboratory and in the field, the optical properties (absorption, scattering) of the pigments, including the spectral response in the visible and near infra-red ranges, as well as their bi-directional reflectance function. This optical response is connected to the chemical and mineral composition of the pigments and to the shape of the grains. In theory, it should be possible to extract the chemical and physical parameters of the pigments from their optical response. However, we do not have at the moment a physical model that correctly simulates the color variations observed in pictographs.

    Thesis goal:

    Create a physical model that connects the optical properties of the pigments used in cave paintings, and measured in-situ, to their physical and chemical properties: chemical composition of the minerals and binders, granulometry, texture. That model will be based on a physical model of radiative transfer inside the pigment layer.

    Scientific challenges:

  • The pigments used in cave paintings are usually dry powders. We do not currently have a physical model for the reflectance of dry powders, as opposed to suspensions or compact materials.
  • Experiments show that pigments can have different colors with the same chemical and mineral composition, implying that scattering effects are playing a role in the color.

  • We have very few reference materials with well known physical properties and measured spectral response as well as bidirectional reflectance function, for dry powders.

  • We do not have accurate optical constants for the materials (minerals, binders) used in the pigments, and measuring them is challenging.
  • Painting materials are applied on a rock wall. This substrate contributes to the overall reflectance and appearance in some spectral ranges. We will have to remove its contribution.
  • Methodology:

  • Build a corpus of dry mineral powders with known chemical composition and granulometry, and measure their bidirectional reflectance and spectrum in the visible and near infra-red, for a large number of incoming light direction and outgoing observation.
  • Build a physical model for radiative transfer inside granular materials, possibly by adapting existing models.
  • Invert this physical model to extract the characteristics of the materials from the measured spectrum and reflectance. Validate the model using the measures from the first step.
  • Expand the model to mixtures of several minerals simulating natural pigments.
  • Test on actual rock paintings.
  • Possible extensions:

  • Invert the effects of aging, by reconstructing the appearance of the material as it was initially (with more pigments present, possibly a matrix connecting them).
  • Mission:

  • conduct a series of measurements of the bidirectional reflectance spectra of a set of reference minerals and pigments to be used for the inversion of their composition and physical properties.
  • extract a compact model that represents the measured reflectance properties of these minerals.
  • connect the parameters of the model with the known chemical and physical properties of the reference minerals and pigments.
  • extrapolate the model to predict the behavior of the model with other minerals and pigments, validate on other pigments.
  • Main activities :

  • Laboratory measurements of bidirectional reflectance spectra of sets of minerals of different composition and texture, and of typical pigment materials (use one of the IPAG's spectrogonio radiometres).
  • Data reduction and analysis of the laboratory measurements
  • preparation of a set of different mineral powders with different textures
  • characterisation of the materials (composition, grain size distribution, optical properties…)
  • building a reflectance model that corresponds with the measurements.
  • connect the parameters of the model with the known physical and chemical properties of the materials
  • write scientific papers describing the work performed and their results
  • present the results at scientific conferences
  • Funding category: Contrat doctoral

    PHD Country: France

    Offer Requirements Specific Requirements

    The candidate should have good knowledge in optics and numerical modeling. Knowledge or experience in radiative transfer or optical properties of materials will be a plus.

    This project is, by nature, cross-disciplinary. The candidate will have to learn tools and practice from both Computer Graphics and material science. We are looking for a candidate with a strong background in either of the two disciplines, willing to learn the tools and methods of the other discipline.

  • Trade skills/ expertise
  • - Strong knowledge in optics and skills in programming (C/C++) are desirable.

    - English: read, written, spoken

    - Ability to work in an interdisciplinary environment

    - Research methodology

    - Good writing skills

  • Personal skills
  • - Autonomy, rigor, sense of teamwork

    - open-mindedness

    - initiative

    - ability to integrate

    Contact Information
  • Organisation/Company: Université Grenoble Alpes
  • Organisation Type: Public Research Institution
  • Country: France
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