Project highlights

  • Work with a ground-breaking new instrument to modernise traditional petrographic techniques in geology and archaeology.
  • Form relationships with academic and industrial partners and build case studies that demonstrate the value of automated image analysis and mass petrography.
  • Establish novel areas of research and new directions for mineralogy and petrology.


Petrography – the optical microscopic analysis of thin sections of materials – is the fastest and most cost-effective tool for investigating the mineralogy and microtexture of rocks, ceramics, and other solid materials. Rock, soil and archaeological thin sections have been studied for over 150 years, with samples in archives around the world. The data produced from petrographic analysis underpins the exploration for and processing of natural resources – including the metals we will need for renewable energy technologies – materials used in construction, and forensic studies of objects both recent and ancient.

Petrographic analysis has traditionally required an appropriate optical microscope, access to the physical thin section samples, and an expert user to classify, measure and interpret the specimen. Samples could be viewed, and thus analysed, only one-at-a-time. Expert users can obtain qualitative data within minutes using a basic microscope, but quantitative analysis is time consuming. However, ground-breaking new optical microscopy technology (see figure) allows multiple sections to be scanned simultaneously to produce high quality images very rapidly. We will pair this advance with computer-based image analysis for classification and quantification, enabling thin section archives and previously-unavailable derived data to be brought into a digital environment.

This PhD will develop a new, highly automated, workflow that will unlock the full value of optical analysis and combine human levels of identification and classification with superhuman levels of speed and reproducibility. These approaches will allow for quantitative and statistically-robust approaches to mineralogy and petrology, and for the rapid development of reference databases for archaeological materials. These in turn unlock the potential for new research in geology, archaeology and material science, with deeper insight into textural and mineralogical diversity of natural and archaeological materials


University of Leicester


  • Dynamic Earth


Project investigator


How to apply


Image Capture – The Zeiss Axio Scan is a recently-developed instrument that offers some inherent advantages over traditional optical microscopes for image capture. It is automated, and can capture multi-channel images from multiple thin sections rapidly. However, there is a need for workflow development, including the standardisation and calibration of images.

Image Analysis – Computer-based image analysis in petrography is often dependent on an expert user “training” an artificial intelligence, which can subsequently automate processes. Within this PhD, you will need to curate training datasets, and investigate the various approaches for image analysis available, with a critical assessment of their suitability for geological and archaeological applications.

Case studies in geology – quantitative analysis supports new directions in petrology. For example, the distribution of crystal sizes in igneous rocks can be used to interpret cooling histories, the mineralogy and fabric of metamorphic rocks can be used to interpret tectonic history, and the mineralogy and fabric of sedimentary rocks can be used to interpret depositional environment and diagenetic evolution. Such interpretation has traditionally been applied to a single specimen, but the mass petrography approach opens up opportunities for analysis of hundreds of samples over much wider field areas.

Case studies in archaeology – the identification of artefacts such as pot sherds depends on petrographic analysis of their components and textures. The ability to produce accessible libraries of both images and quantitative data can enhance the identification and provenancing of artefacts, the techniques used to make them, and hence the spread of people and their technologies.

Training and skills

Project specific training will be provided in equipment use and image analysis. You will have access to undergraduate modules in archaeology and geology that can be used to provide additional context for case studies and applications.  Additional training from external facilities and commercial partners will also be available.

The Open University-run Virtual Microscope ( provides a platform for showcasing thin sections of rocks and providing accessible teaching collections.  Training will be provided in creating and curating specimens.

Partners and collaboration

Dan Smith is a researcher on various projects on mineral resources, including NERC FAMOS and the UKRI Circular Economy Centre for Technology Metals. He uses analytical techniques to improve our understanding of Earth materials – particularly mineral resources from magmatic systems ‒ and how we can more sustainability process them.

Jose Carvajal Lopez is a Lecturer in Historical Archaeology with expertise on archaeological ceramic petrography. He has analysed ceramic sets from Spain, the Balkans and the Persian Gulf and has supervised several PhD and MA students. He uses petrography to assess technology and provenance of ceramic assemblages by understanding and describing their mineralogical and petrological composition and texture.

Clare Warren is a metamorphic petrologist at the Open University with interests in linking petrographical clues at the microscale to tectonic histories on the scale of mountain belts.

Annika Burns is a thin section technician within the School of Geography, Geology and the Environment, with a PhD in thin sections of archaeological sediments and has been a teaching assistant in the micromorphology of archaeological sediments to BSc, MSc and PhD students. She has created methodologies for thin sectioning a wide variety of earth science materials.

Further details

To apply to this project please visit:

Possible timeline

Year 1

Equipment training, preparing initial training libraries, method development of systematic image capture and calibration. Collation of suitable simple samples. Image analysis and quantification of simple specimens.

Year 2

Development of case studies libraries and training data; advanced image analysis. Internship opportunities. Write up and publication of methods and first case studies

Year 3

Further case study development and research applications.  Continued write up and publications.

Further reading

Ye, Z., MingChao, L. and Shuai, H., 2018. Automatic identification and classification in lithology based on deep learning in rock images. Acta Petrologica Sinica, 34(2), pp.333-342.

Berrezueta, E., Domínguez-Cuesta, M.J. and Rodríguez-Rey, Á., 2019. Semi-automated procedure of digitalization and study of rock thin section porosity applying optical image analysis tools. Computers & Geosciences, 124, pp.14-26.

Zeiss Axioscan product page:


As a lab-based project, with flexibility in which samples are utilised for case studies, this project can proceed with very few risks from covid-19 in terms of travel restrictions or access to third-party laboratories. Additional opportunities including work placements and additional training can be scheduled flexibly.  All work at all institutions will be governed by local covid-safe working procedures.