Live X-Ray imaging (LiveX)
Lead Research Organisation:
UNIVERSITY OF OXFORD
Department Name: Materials
Abstract
X-ray imaging techniques are a powerful tool to study the dynamic of metal solidification phenomena, however current analytical tools suffer of two main drawbacks. Firstly, these techniques are currently available only at synchrotrons, which have restricted access. Secondly, the vast and complex data sets generated during time-resolved experiments present profound technical and practical problems for quantification and the extraction of scientific knowledge.
We propose a project to develop an X-ray multi-modal imaging system (LiveX) in which ML will be embedded in the data acquisition procedure and used to interpret raw data in real-time, as they are collected, drastically reducing the complexity and time required for data analysis. The system will be designed to be integrated in existing laboratory X-ray sources and to accept any ML algorithm. Our primary goal will be to develop LiveX as a flexible tool to investigate metal solidification both in a laboratory environment, to carry on fundamental studies without the need of a synchrotron, and for process development in industry. To this end the set up will be coupled with a high temperature furnace and an ML algorithm trained for the investigation of nucleation and growth phenomena during the solidification of aluminium alloys. The instrument will be a world first, providing a unique capability which will foster the establishment of new collaborations and facilitate industrially led research, for which access to synchrotron time is generally difficult. This will benefit our ongoing research on aluminium recycling; the flexibility of the approach will also allow its use in other fields and this will be sought as part of the program.
We propose a project to develop an X-ray multi-modal imaging system (LiveX) in which ML will be embedded in the data acquisition procedure and used to interpret raw data in real-time, as they are collected, drastically reducing the complexity and time required for data analysis. The system will be designed to be integrated in existing laboratory X-ray sources and to accept any ML algorithm. Our primary goal will be to develop LiveX as a flexible tool to investigate metal solidification both in a laboratory environment, to carry on fundamental studies without the need of a synchrotron, and for process development in industry. To this end the set up will be coupled with a high temperature furnace and an ML algorithm trained for the investigation of nucleation and growth phenomena during the solidification of aluminium alloys. The instrument will be a world first, providing a unique capability which will foster the establishment of new collaborations and facilitate industrially led research, for which access to synchrotron time is generally difficult. This will benefit our ongoing research on aluminium recycling; the flexibility of the approach will also allow its use in other fields and this will be sought as part of the program.
Publications


Feng S
(2022)
X-ray Imaging of Alloy Solidification: Crystal Formation, Growth, Instability and Defects.
in Materials (Basel, Switzerland)

Feng S
(2022)
Investigating Metal Solidification with X-ray Imaging
in Metals

Han I
(2023)
Tracking the evolution of hot tears in aluminium alloys using high-speed X-ray imaging
in IOP Conference Series: Materials Science and Engineering

Han I
(2024)
Revealing hot tear formation dynamics in Al-Cu alloys with X-ray radiography
in Acta Materialia

Huang C
(2022)
3D Correlative Imaging of Lithium Ion Concentration in a Vertically Oriented Electrode Microstructure with a Density Gradient
in Advanced Science

Leung C
(2023)
Correlative full field X-ray compton scattering imaging and X-ray computed tomography for in situ observation of Li ion batteries
in Materials Today Energy

Liotti E
(2022)
Probing interdendritic flow and hot tearing during solidification using real time X-ray imaging and droplet tracking
in Acta Materialia
Description | Collaboration with Loughborough University |
Organisation | Loughborough University |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Sharing knowledge sample and data on Aluminium sustainable manufacturing |
Collaborator Contribution | Sharing knowledge sample and data on Aluminium sustainable manufacturing |
Impact | - Obtained a joint EPSRC grant proposal in 2023 |
Start Year | 2022 |