Laser Additive Manufacturing of Lunar Regolith: Generating Synchrotron X-ray Calibrated Sensors

A fully funded PhD studentship in the Department of Mechanical Engineering

Laser Additive Manufacturing of Lunar Regolith: Generating Synchrotron X-ray Calibrated Sensors for Manufacturing Control and Validating Models for Future Lunar Missions

Key information

Supervisors: Prof Peter D. Lee (UCL), Dr Chu Lun Alex Leung (UCL), Dr Caterina Iantaffi (European Space Agency)
Application deadline: ongoing
Project start date: 01 October 2025
Project duration: 4 years
Studentship funding: Home tuition fees (currently £6,215/year) and maintenance stipend (currently £22,780/year) provided for 3.5 years

PhD project description

Human and robotic exploration of the Moon requires in situ manufacturing, a key component of In Situ Resource Utilisation (ISRU). Additive Manufacturing (AM), or 3D printing, has been identified as a key technology enabler for sustainable and on-demand components manufacturing from local resources.

This project aims to develop and optimise laser-based AM manufacturing methods for fabricating small parts (e.g. drills, solar panels support structures, etc.) with lunar Regolith-based materials. In situ monitoring techniques and Machine Learning (ML) algorithms will be explored to ensure parts quality. Although previous studies have demonstrated that laser powder bed fusion (LPBF) can manufacture lunar Regolith parts (Caprio et al. [1] Additive Manufacturing, 2020; Goulas et al. [2] Additive Manufacturing, 2021), significant challenges remain in fabricating structural parts with consistent properties due to LPBF process complexities and variations in the mineralogical composition of Regolith powders. You will use our unique in situ synchrotron x-ray imaging AM machines to observe real-time laser-Regolith interactions and defect formation, expanding on the preliminary work of Iantaffi et. al who found 5 distinctive processability windows. You will expand on this work experimentally and use your results it to inform and validate multiphysics numerical models of LPBF under lunar-like conditions.

The experimental method for synchrotron x-ray imaging is a well-established approach within the group; however, recent interest in further process optimisation (i.e. dual lasers use for reducing thermal stress), in line monitoring and the exploration of novel Regolith materials has grown due to their potential applications in space manufacturing (Makaya et al., [3] CEAS Space Journal, 2023). For instance, the electro-deoxidation of Regolith materials (Meurisse et al. [4] Planetary and Space Science Journal, 2022) yields a byproduct that may be suitable for printing structural components. The sensors integration will provide data for real-time ML monitoring and process control algorithm development, using the models to extrapolate to lunar conditions.

Starting from the material characterisation, a detailed process map will be conducted to provide below and top melting surface views with different sensors (optical and IR cameras, photodiodes, etc…) providing correlation and calibration information to enable modelling of future lunar experiment missions. After narrowing down the processability window, final assessments will be performed to evaluate the density and mechanical performance of the parts.

Keywords: Additive Manufacturing, Machine Learning, Human and Robotic exploration, Lunar Regolith

Co-funding opportunities

We are in the process of seeking co-funding from the European Space Agency (ESA), through a Discovery idea submission on Open Space Innovation Platform (OSIP). This will provide expert guidance and access to the Advanced Manufacturing Laboratory (AML) in ECSAT.

Person specification

Applicants should ideally have a first-class, or equivalent, undergraduate degree in Chemistry, Physics, Materials Science and Engineering, or a related discipline.
A passion for space research is essential.
Excellent organisational, interpersonal, and communication skills, along with a stated interest in interdisciplinary research, are essential.
Ideally you will have experience in one or more of the following:
- Natural science (e.g. Chemistry and Physics)
- Image analysis
- Matlab and Python programming
- Machine Learning
- Additive manufacturing
- Materials Science and Engineering
Fluency and clarity in spoken English as well as good written English in accordance with UCL English requirements (TOEFL>92 or IELTS>6.5).

Eligibility

Please note that the available funding supports tuition fees at the Home/UK rate (currently £6,215 per year). Students who are eligible to pay fees at the UK rate are welcome to apply (e.g. UK students or EEA or Swiss nationals who are “settled” or “pre-settled” within the UK in accordance with the EU Settlement Scheme). Please refer to our website for further information about Home tuition fee eligibility.

Nationals from one of the 23 ESA member states who are eligible to pay tuition fees at the Overseas rate (currently £33,000 per year) are also welcome to apply, however the tuition fees covered by the studentship will be limited to the Home/UK level. International students will be required to find additional funding for the remaining Overseas tuition fees.

Applicants whose first language is not English are required to meet UCL's English language entry requirements.

Please refer to this webpage for full eligibility criteria: Mechanical Engineering MPhil/PhD

How to apply

Eligible applicants should first contact Prof. Peter Lee (peter.lee@ucl.ac.uk) and Dr Chu Lun Alex Leung (alex.leung@ucl.ac.uk). Please enclose the following documents: