For the past two years, quantum sensing technology specialist Richard Norte (Department of Precision Microsystems Engineering) has been working intensively with machine learning expert Miguel Bessa (Department of Materials Science & Engineering) - a collaboration that has led to a real breakthrough in science: âWeâve been able to experimentally demonstrate the worldâs best vibration isolation at the micro-scale which has exciting implications for next-generation technologies like ultra-sensitive sensing, non-GPS navigation and quantum Internet.â
Mechanical resonators
Working together as part of the Faculty of Mechanical, Maritime and Materials Engineeringâs (3mE) Cohesion Projects initiative, Norte and Bessa set out to produce new types of sensors that could measure weak forces like gravity and dark matter. These forces are notoriously hard to measure because the sensors - mechanical resonators - need to be very well isolated from outside vibrations. âThe only way to isolate resonators from surrounding thermal ânoiseâ right now is to put them in very large, extremely expensive refrigerators, each costing about half a million Euros, so if you want to have a whole network of resonators, each with their own âfridge, that becomes very expensive. But if one can attain high levels of vibration isolation on a microchip working at room temperature, then one can really start to unlock a lot of groundbreaking technologies.â
Weâve basically made the most vibration-isolated object ever made and we did it with a design that was really simple.
Machine learning
At a certain point Norte felt that his background in nano- and microchip technology could only get him so far: âIf I look at all the research that Iâve done in the past, itâs all been me sitting there going âWell I think this would work - letâs go and try it and painstakingly testing all these different designs⊠But then I realised maybe machine learning could help me over this experimental loop that I constantly find myself in â that maybe machine learning could be used to augment our creative possibilities.â
So Norte sent an email to Bessa: âIâm more of a computational person. Iâm into machine learning, Artificial Intelligence, and I try to apply AI to designing new materials or new structures either at the very small or the very large scale.â
Bessa describes Norte as the ideal partner because âhe can develop nanoscale devices that very few people can and that allows the AI to be very creative.â This means that instead of the researchers having ideas and then controlling everything in the process, the researchers try to delegate at least part of the tasks to machine-learning algorithms and optimisation algorithms. âSo when Richard reached out and told me about these applications â and I have to be honest I knew very little about photonics and phononics â he was very patient with me. Eventually, I realised that these structures are governed by conventional mechanical principles but due to their size being so extreme they start behaving more quantum mechanically. Once Richard and I found a common language to communicate without the jargon of the field, we were ready to tackle the intended challenge: can machine learning and optimisation techniques really help in this context?â
Spider webs
However, they still needed a good initial concept design. Then after months of hard work learning something about each otherâs fields of expertise, inspiration hit - âpartly as a result of staring into dusty corners during corona lockdown,â jokes Norte. Spider webs! âWe realised that nature has been evolving vibrational sensors over millions of years. And if you look at a spider web, itâs designed to sense very small vibrations while also blocking out other things like the wind from the trees or other environmental noise.â
So the team asked a specific machine learning algorithm called Bayesian Optimisation to come up with a really good design based on the basic geometry of a spider web, and this threw up something totally unexpected: âWe saw that there was some kind of torsional vibration in some of the outer threads of the web construction,â says Bessa, âand that was actually not something weâd thought about. So this was really an outcome of the exploration by the algorithm.â
World record
With this new insight, the teamâs post-doctoral researcher, Dongil Shin, was able to come up with simulations that mimic the experiments very closely. âAnd excitingly, when we did the simulations, the algorithm said âyou can break the world record on one of the properties, a so-called Quality Factor, integral to this particular design,â says Bessa. âAccording to the algorithm, our simulation had a Quality Factor of 2 billion - much larger than anything we could find in the literature and with a design that was far simpler than anything proposed previously.â
Validation
But would the results found in the simulations hold up in practical experiments? This challenge was taken on by PhD student Andrea Cupertino, who built the web-inspired resonator using ultra-thin ceramics from materials often used on microchips, and then tested the new design in the lab. âIt was far from easy,â says Bessa, âand it took a while to make sure that all the experimental conditions were similar to the simulation but eventually it was validated, it was real! And so the AI really did help.â
âAnd the cool thing about this design is that itâs able to produce great isolation with a minimalist geometry,â adds Norte, âso now we can make these devices really easily, very cheaply and you donât need fridges because it can all be done at room temperature.â
Cohesion Project
Both Bessa and Norte are convinced that this breakthrough was the result of collaboration between scientists from very different disciplines: âSometimes when youâre not in the field youâre like OK letâs do that and put this together and youâre done but it took us two years - really two years - to achieve our goal even using a fairly simple algorithm. The experimental technique was also very well known by Richard so it was truly the symbiosis between these two different worlds that produced something really quite nice.â
âAnd I gained a new intuition out of this,â adds Norte âa new way of looking at things and thatâs much simpler than I could have ever imagined. We thought we were going to come up with some super-complicated design and it ended up being this incredibly simple idea and that I think is the power of AI, the machine learning algorithms.â

Dr. Richard Norte
