Innovating with AM in Quantum Technologies
Interview with Manolis Papastavrou
Co-Founder & Computational Design Lead – Metamorphic
At CDFAM Berlin, Metamorphic will be presenting a recent project QTEAM, to design an ultra-high vacuum chamber for a space-based gravimeter to undertake quantum physics experiments using computational design and additive manufacturing.
Sure, it sounds like part of the plot from 3 Body Problem cut for time (even their accents), but is in fact a real collaborative project between Metamorphic, RAL Space, Torr Scientific and The University of Nottingham
Metamorphic is a UK based computational design consultancy founded by Manolis Papastavrou and Laurence Coles that we featured in a previous interview for CDFAM.
Could you begin by telling us about the project you’ll be presenting at CDFAM Berlin?
Project QTEAM is a collaborative project between Metamorphic, RAL Space, Torr Scientific and The University of Nottingham that seeks to unlock the potential of Additive Manufacturing in quantum technology, demonstrating its suitability for intricate, high-performance components that are vital for the next generation of quantum devices.
The project was co-funded by Innovate UK as part of the Industrial Strategy Challenge Fund strand to commercialise quantum technologies.
One of the main project outputs is an AM ultra-high vacuum chamber that sits at the heart of a space-based gravimeter. Current lab-based quantum systems are bulky and power-intensive, which poses significant challenges to their practical deployment in the field.
Our approach leverages AM to create compact, lightweight and power-efficient quantum devices, which hold immense potential for applications in areas such as precision navigation and timing, gravitational field sensing etc. that are crucial to aerospace and defence.
As Metamorphic, we have developed novel computational design methods to automate and accelerate the design of bespoke UHV systems for the quantum industry; due to increased complexity, their design can be time consuming and prone to errors when employing conventional CAD tools. This approach has also allowed for optimising the design to achieve a substantial reduction in weight (50%) compared to RAL’s existing quantum gravimeter design.
What led Metamorphic to engage in projects involving quantum technology and additive manufacturing, given your experience with emerging technologies and connections to Nottingham University’s physics group?
Metamorphic was founded on a firm belief that additive manufacturing can unlock opportunities for innovation and our focus ever since has been on unearthing its potential across various technological fronts, beyond the well-established automotive and aerospace sectors.
We had experience working with Nottingham University’s quantum physics group in previous roles and had some understanding of the challenges and unique requirements of this emerging technology sector. At quantum events, we would often see devices built by physicists that, while technically impressive, they’d tend to be over spec’d; this understandably stems from a focus on achieving greater performance and proving the physics, however such systems are usually not suitable for practical applications outside a lab setting. Their design is also guided by traditional manufacturing techniques, which limits how creative physicists can be with the arrangement of all the different subsystems (i.e. optics, electromagnetic coils, imaging etc.).
QTEAM was born out of this question: “What would quantum devices look like if physicists had more design freedom through the use of Additive Manufacturing?”
What unique approach and skills does your team bring to this challenge, which the researchers were unable to address on their own?
Our unique approach lies in how we blend our expertise with other teams to help them turn concepts that originate from fundamental research into working prototypes. We both have PhDs and possess a diverse skill set, which help us bridge the gap between scientific research and engineering design.
In this project, we started from building an understanding of the science behind cold atom gravimeters and how researchers traditionally approach their design and manufacturing, which took the form of workshops. As part of this activity, we gathered requirements and looked at existing designs to understand the technical challenges and what has or hasn’t worked well in the past.
Most importantly though, we educated our collaborators in computational design methods and showed them how these are used to leverage the design freedom that AM has to offer. This is the part where you get lots of ideas flying around, as they realise that they can get closer to their original vision of the device without the constraints imposed by traditional manufacturing techniques.
…Suddenly, some of these ‘crazy’ ideas they may have had in the past become possible! Our role is to help them turn this vision into reality with our expertise in DfAM, mechanical engineering and computational design methods.
How has Grasshopper been instrumental in the design process, particularly in optimizing internal structures and lattices for rigidity and thermal management?
The design of ultra-high vacuum components for quantum devices can be a very time-consuming process due to high complexity. As we mentioned earlier, there is a large number of peripherals mounted on the chambers, such as optics, electromagnetic coils, cameras, ion pumps etc which need to be arranged in such way that they don’t obstruct or influence each other while being packed in the smallest volume possible for portability. Changing or offsetting a single port, may require the entire arrangement to be reassessed and altered to accommodate this small change.
Computational design and specifically Grasshopper allows us to iterate faster by feeding this information into an algorithm; the algorithm finds the optimal placement of ports and generates every time a complex minimal surface and external lattice that joins them.
The external lattice has a dual purpose: it provides mechanical rigidity, and acts as a support structure to facilitate the printing (LPBF) process. The user specifies the printing orientation, and the algorithm detects all the overhangs and “grows” an external lattice to support them.
We are in the process of making this smarter, by including thermal FEA that adapts the lattice so that more heat can be extracted during printing from areas that are more likely to experience heat build-up. It would be hard to achieve this with any other tool, since Grasshopper is so versatile, can be easily interfaced with external libraries/ software, an ever-expanding list of plugins and a powerful API.
Does your team utilize only commercially available software, or have you developed proprietary tools as well? If you’ve created your own tools, what specific needs do they meet, and how do they enhance performance compared to standard solutions?
We use whatever tools are most suitable for addressing the technical challenge. For example, we validate our designs with commercial multi-physics simulation tools, or we design mechanical interfaces that require machining with commercial CAD software.
Sometimes, the tools we require are not available commercially, so we develop them ourselves. This is where computational design scripts come into play; they are usually developed for a specific application, but some of their functions or methods can provide solutions to other design problems. Each script is a unique recipe that combines traditional CAD with parametric modelling and form finding. Sometimes FEA and CFD tools are thrown into the mix that are interfaced with optimisation algorithms (i.e. genetic, surrogate modelling etc) to explore a large design space and provide insights into optimal design solutions. In some cases, we incorporate external libraries developed in Python or C# to bring additional functionality into our scripts.
A commercial DfAM tool is unable to match that level of customisation when it comes to such highly complex digital workflows. The majority require the engineer to import geometries that have been designed using conventional CAD software, that are then filled with various types of lattices. However, this approach limits the design freedom that AM has to offer.
We believe that there is a lot to learn from the field of architecture, where they’ve been developing their own computational design tools to balance form, structure and function for more than three decades. Someone could say that at Metamorphic we like to treat objects as buildings.
What advancements or tools do you hope to see developed in the future to further assist your team in supporting your clients?
It would be great to see computational design tools that integrate meshless CFD and provide manufacturability insights for different AM processes. Faster rendering would also be very welcome; we know that nTop have made significant advancements in this area, but it should also become a focus for some of the other tools like Grasshopper (Rhino).
And last but not least: most additively manufactured parts require machining, and if they have been designed entirely with computational design tools, there is no established way of defining machining operations and generating drawings for the machine shop.
How would someone, whether a quantum space physicist or a terrestrial-focused engineer, recognize when it’s the right time to seek Metamorphic’s expertise for solving their engineering challenges?
Metamorphic can be involved at any point during an innovation journey— from conceptualisation where radical new ideas are needed, through to the final stages of a project where optimising a design for manufacturing becomes crucial.
What is common amongst our clients is a desire to redefine the boundaries of what’s possible within their projects.
Quite often they have a vision for a novel component or device that can benefit from the design freedom offered by AM, yet they lack the Design for AM (DfAM) expertise to materialise it. This becomes even more challenging for them if there is additional need for AM process development (they might require for example an exotic metal alloy that is not commercially available at AM service bureaus) or AM is just a step within a larger manufacturing workflow.
Our role is to help them make advancements in their area of interest and unlock opportunities for innovation through design for AM.
What do potential clients need to prepare, in terms of design or manufacturing specifications, to ensure they are ready to engage with Metamorphic effectively?
All this information can be gathered at the start of the project through collaborative workshops. Quite often we question or challenge certain specifications that might be based on dated assumptions or technologies or traditional manufacturing limitation. This approach can provide cost benefits and most importantly lead to breakthroughs that wouldn’t have been discovered by simply adhering to the initial specs.
Do you offer training or software workflows for clients to explore the tools and design collaboratively, or do you deliver a complete engineered solution?
We provide both. We operate as a flexible resource that complements our clients’ teams. So far, we have mainly delivered complete engineered solutions in the form of prototypes that can be tested in a lab environment, but there have been cases where we developed a customised computational design tool so that the client can explore the design space themselves.
Finally, what do you hope attendees will take away from your presentation at CDFAM, and what are you looking to learn from the event?
In presenting at CDFAM, we hope to demonstrate that computational design and AM have a special place in high-tech, high-value applications in a wide range of emerging technology sectors.
We would like to inspire other multi-disciplinary teams by showing the ways in which these tools have been successfully integrated to drive innovation; to get them thinking about their own technical challenges and how these can be addressed with advanced computational design workflows.
As a design engineering consultancy specialising in AM, we are particularly interested in learning about new computational design tools and workflows and how these have been applied in other industry sectors.
By staying up to date, we can continue to enhance our design-to-manufacturing workflows and push the boundaries of what is possible with AM. It’s a unique opportunity for us to engage with leading experts in this field, which could lead to future collaborations that extend our technical capabilities and offering.
