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Michael Pitcher

Publications and source records attributed to Michael Pitcher.

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Upcycling solar glass into Ce-doped oxyfluorides: spectroscopic and crystallization properties

Oxyfluorides containing up to 80 wt% recycled glass from end-of-life solar panels have been investigated. Reduced processing temperature and high transparency have shown that the material has potential for optical applications. In this work, cerium-doped samples were investigated. Spectroscopic study reveals the presence of Ce$^{3+}$, and luminescence from these ions and oxygen-deficient centers was detected. Raman demonstrated that cerium affects the glass network by promoting polymerization. In turn, thermal analysis indicated some changes in the crystallization events between 500-800 $^o$ C, which were confirmed by in situ X-ray powder diffraction measurements. Crystallization of fluorite, xonotlite, and combeite was confirmed, while other phases give minor contributions to the XRD patterns. Cerium addition reduced the formation of xonotlite, mainly above 700 $^o$ C. The potential applications of the material and the further studies required are discussed.

cond-mat.mtrl-sci

PySlyde: A Lightweight, Open-Source Toolkit for Pathology Preprocessing

The integration of artificial intelligence (AI) into pathology is advancing precision medicine by improving diagnosis, treatment planning, and patient outcomes. Digitised whole-slide images (WSIs) capture rich spatial and morphological information vital for understanding disease biology, yet their gigapixel scale and variability pose major challenges for standardisation and analysis. Robust preprocessing, covering tissue detection, tessellation, stain normalisation, and annotation parsing is critical but often limited by fragmented and inconsistent workflows. We present PySlyde, a lightweight, open-source Python toolkit built on OpenSlide to simplify and standardise WSI preprocessing. PySlyde provides an intuitive API for slide loading, annotation management, tissue detection, tiling, and feature extraction, compatible with modern pathology foundation models. By unifying these processes, it streamlines WSI preprocessing, enhances reproducibility, and accelerates the generation of AI-ready datasets, enabling researchers to focus on model development and downstream analysis.

q-bio.QM