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Jumpstart your understanding of advanced chemical imaging & tomography with our three-day course organised with the University of Manchester. Learn about the fundamental principles, current instrumentation, and how these approaches are applied using the scattering and spectroscopic methods with emphasis on X-ray diffraction computed tomography (XRD-CT).
The course includes a 1 day introduction to scientific programming and machine learning with python (optional) and 2 days covering data collection and data analysis including demonstrations of CT data analysis workflows using exemplar real life data provided by us. This course is ideally suited (but not limited) to students and users wanting to understand the exciting potential of advanced CT / chemical imaging methods in their research programs.
£900 + VAT 2-day course Academic/RTO/Micro company: 30th April – 01 May 2024
£1,200 + VAT 3-day course Academic/RTO/Micro company: 29th April – 01 May 2024
£1,200 + VAT 2-day course Industry: 30th April – 01 May 2024
£1,500 + VAT 3-day course Industry: 29th April – 01 May 2024
Travel and Contact Information
Rutherford Appleton Laboratory Visitors Centre – Hamilton Room
Fermi Avenue Harwell Campus
Tel: 01235 567497
We were so thrilled to have Sciad Communications and Cambridge FilmWorks at the Research Complex at Harwell, Rutherford Appleton Laboratory today to talk to us about receiving the Royal Society of Chemistry Horizon Sir George Stokes Prize. We spoke about our work on the development and application of X-ray diffraction computed tomography to image and identify structure-activity relationships within functional materials and devices.
Congratulations to our PhD student Hongyang Dong who has passed his viva!
Hongyang has finished his PhD at the Chemistry department in UCL! He holds MSc degrees in Scientific Computing and a BSc in Physics from UCL. His involvement spans various computing and spectroscopic projects, such as “Developing an intelligent chemical reaction generator” and “Time-correlated single-photon counting (TCSPC) on fluorescence analysis.” Additionally, he completed internships investigating Quadrotor UAV Flight Attitude Control Systems. Hongyang’s PhD entitled “Machine Learning-Based High-Throughput Processing of Chemical Imaging Data” concentrates on employing AI and machine learning for high-throughput chemical imaging data analysis. Proficient in multiple programming languages (Python, C++, Java, C, R), he possesses expertise in high-performance computing and diverse machine learning techniques.
The Faraday Institution 2023 Conference was held on the 11th-13th September 2023 with over 500 delegates attending. One of the highlights of the event was the poster sessions and we are delighted to share Dr. Stephen Price was one of the winners of a poster prize.
The judges said Dr. Price’s poster “Probing the hierarchical structure of secondary LiNO2 cathode particles with nano-focussed XRD-CT” demonstrated strong collaborative research across academia, central facilities and industry with clear articulation of methods and results.
Congratulations to Finden intern Abigail Eddie who received a Highly Commended from The Faraday Institution for her #FUSE2023 poster.
She completed an internship under the supervision of our Senior Scientist Dr Steve Price, Dr Beth Johnston and Dr Innes McClelland from the University of Sheffield.
Abigail’s FutureCat project focused on chemical imaging of battery cathode materials. She took part in adapting scripts in Python to automate the analysis of the X-Ray Diffraction-Computed Tomography (XRD-CT) data of an LiNiO2 cathode. The programs written proved to reliably and efficiently extract crystallographic information and physical parameters from the sample. Reducing the time spent on data processing will allow faster research and development into new battery materials.
Finden’s latest work working with VITO, National Institute of Chemistry Slovenija and UCL Chemistry has been published in a new paper by Clément Jacquot “A multi-scale study of 3D printed Co-Al2O3 catalyst monoliths versus spheres” in Chemical Engineering Journal Advances (open access).
This study demonstrates the characteristics of two model packing configurations: 3D printed (3DP) catalyst monoliths on the one hand, and their conventional counterparts, packed beds of spheres, on the other. Cobalt deposited on alumina is selected as a convenient model system for this work, due to its wide spread use in many catalytic reactions. 3DP constructs were produced from alumina powder impregnated with cobalt nitrate while the alumina spheres were directly impregnated with the same cobalt nitrate precursor. The form of the catalyst, the impregnation process, as well as the thermal history, were found to have a significant effect on the resulting cobalt phases. Probing the catalyst bodies in situ by XRD-CT indicated that the level of dispersion of identified Co phases (Co3O4 reduced to CoO) across the support is maintained under reduction conditions. The packed bed of spheres exhibits a non-uniform distribution of cobalt phases, including a core-shell morphology with an average crystallite size of 10–14 nm across the sphere, while the 3DP monolith exhibits a uniform distribution of cobalt phases with an average crystallite size of 5–12 nm upon reduction from Co3O4 to CoO. Computational Fluid Dynamics (CFD) modelling was carried out to develop digital twins and assess the effect of the geometry of both configurations on the pressure drop and velocity profiles. Finally, the activity of both Cobalt-based catalyst geometries was assessed in terms of their conversion, selectivity and turn over frequencies under model multiphase (selective oxidation) reaction conditions, which showed that the desired 3D printed monolithic geometries can offer distinct advantages to the reactor design.
To read the full paper visit https://doi.org/10.1016/j.ceja.2023.100538
We are thrilled to receive this Sir George Stokes Prize prize for the development and application of X-ray diffraction computed tomography to image and identify structure-activity relationships within functional materials and devices. Thank you so much to Royal Society of Chemistry and all our collaborators. The prize recognised the work Finden has done in advancements of X-ray diffraction computed tomography (XRD-CT) and related chemical imaging methods like pair distribution function computed tomography (PDF-CT) or multimodal-CT through collaborations with academic and industrial partners.
Professor Andrew Beale said on winning, “We hope that eventually, these techniques will move from particle accelerators into the laboratory, and ultimately into the medical field. There, they have the potential to bring about improvements in the health sector, as well as the performance of materials.”
Read more about the prize at https://www.rsc.org/prizes-funding/prizes/2023-winners/the-xrd-ct-pioneers/
Read more about Finden’s work:
We’re thrilled to share that our Chemical Imaging and Tomography training course in collaboration with The University of Manchester was an incredible success!
Over the course of just two days, our expert instructors guided a group of enthusiastic learners through a comprehensive overview of this cutting-edge technology. The feedback we received was overwhelmingly positive, with many remarking on the new skills and insights they gained.
From the basics of chemical imaging to the intricacies of X-Ray scattering tomography, our participants gained a solid understanding of the field. In addition, our participants were introduced to XRD-CT data processing and analysis using Python, a powerful tool for interpreting chemical imaging data. By the end of the course, they had developed a strong foundation for applying these skills in their own research and work.
Thank you to all of our amazing participants for making this course such a resounding success, and we can’t wait to see the work you’ll accomplish with your newfound knowledge and skills!
We’re committed to staying at the forefront of this rapidly evolving industry, and we’re excited to continue sharing our expertise with all of you.
Finden Ltd has been selected to feature in the ESRF – The European Synchrotron 2022 Highlights. Former Finden employee Dr. Dorota Matras’s work can be found on page 148 (Full paper at https://lnkd.in/ek6aUS-t). Many thanks to the ESRF ID31 team, Marta Mirolo, Isaac Martens and Jakub Drnec, for their help with this experiment!
The research work was a collaboration with UCL Chemistry. Read more about our work at ESRF – The European Synchrotron during 2022 at https://esrf.fr/Apache_files/Highlights/2022/#/page/0.
We are proud to announce Finden Ltd have been awarded a grant to take part in research on structured unconventional reactors for CO2-free methane catalytic cracking as part of the STORMING EU project.
STORMING EU will develop breakthrough and innovative structured reactors heated using renewable electricity, to convert fossil and renewable CH4 into CO2-free H2 and highly valuable carbon nanomaterials for battery applications.
Finden are performing X-ray characterisation of the catalysts used for methane to nanostructures and hydrogen formation. This will involve spectroscopy and scattering on powders as well as X-ray imaging of structured reactors. Finden will be supporting a new PhD student Antonia Bobitan in research on this project.
More information about the STORMING EU project can be found at https://storming-project.eu