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Finden Ltd have been providing analytical and scientific consultancy services since 2012. Helping businesses across sectors; catalysis, automotive, energy and pharma. Based in Oxfordshire.
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CS01 | Transaction MzQ0MTkxMjMwNWFkaXF6a2N4
Published 04 Nov 2024 03:39
Company registered at Companies House
1 Jul 2025 to 30 Sep 2025
X-ray micro-computed tomography (micro-CT) is a powerful imaging technique used across industries such as energy, automotive, and advanced manufacturing to examine the internal structure of materials and devices. However, imaging certain components---particularly those containing metals---presents significant challenges due to beam hardening. This effect ...
1 May 2023 to 31 Jul 2023
Finden and NPL are working together to develop novel statistical and machine-learning based methods to reduce the noise levels for chemical imaging and tomography datasets. The proposed approaches will result in clearer images with sharper associated spectra/patterns, aiding interpretation and quantification of the data. The approach will be applicable to...
1 Sep 2022 to 31 Aug 2025
no public description
31 Dec 2021 to 31 Mar 2022
Through this project we seek to identify and develop methods to automatically segment complex chemical imaging datasets, e.g. XRD-CT, Raman mapping and other hyperspectral imaging techniques. The goal is to identify the minimum number of unique chemical environments in a dataset, without needing prior knowledge or input as to the expected identity or numb...
1 Jun 2020 to 30 Nov 2020
no public description
1 Apr 2020 to 31 Mar 2021
Our company has developed advanced chemical imaging capabilities which we offer as a service to industry, helping our clients accelerate their R&D. Our imaging approaches yield rich and large datasets that contain an abundance of physico-chemical information. This project will use artificial intelligence approaches to reconstruct X-ray scatter-based chemi...
1 Mar 2020 to 31 Dec 2020
This project will use machine learning approaches to extract physico-chemical information from chemical imaging data. This novel approach will tackle an emerging problem in this field, namely how to automatically identify and extract chemical signals from the rich and ever-larger datasets that it is now possible to collect. There are several features that...
1 Jun 2018 to 30 Nov 2020
"Air pollution is one of today's most concerning problems, causing unacceptable health issues to many people in our societies. This project will strive to deliver materials, and products for easy customer use, that can help tackle this problem for UK and global benefit. The project will take novel technology now emerging from the UK's academic (University...
