Founder Interview #1: Quantum Diamonds

PJ: 

Kevin, thanks so much for taking the time today to tell us more about Quantum Diamonds. I think a great way to start this would be for you to take a minute and introduce yourself and Quantum Diamonds. It would be really valuable to hear more about what led you to being a first time founder in such a unique and under-addressed industry such as Quantum Sensing. 

Kevin: 

Yes, so actually, I'm the only non-quantum physicist on the Quantum Diamonds team. I have a pure business background — studied in Germany and then Portugal and Italy. 

And then if you're going through the business world, consulting is always popping up, right? So I joined McKinsey afterwards and did a lot of private equity and M&A work there, and then at some point, as part of their leave program, went to get a PhD here at the Technical University of Munich.

Matt Fleming, our now CTO, at that point, was also doing his PhD in the quantum sensing field. Back then, it was completely unclear where there might be potential use cases, and where there might be an industry application.  But I found it interesting. 

First of all, “quantum”, right? It's very hard even for technical people to grasp: what is quantum? Then this whole diamond part, you use synthetic diamonds to actually do measurements. 

For me, this was like a huge black box, but I wanted to understand it more in detail. So, we teamed up. In the beginning, it was just like an informal chat: What is the market size? What is the pricing? How do you make a business out of sensing, which was at that time just a PhD research project?

Eventually, we filed for a grant from the German government to start a business. We talked to many people in the industry, and at some point found the relevant verticals we wanted to focus on that had some traction already.

Then we did our seed round in December with German and UK VCs leading the round. 

PJ: 

So just now, you mentioned that you had to talk to industry experts to identify where those use cases were. Did you ever come across any “industry experts” who had no idea what you were talking about? That had never heard of quantum sensing? Where, in a sense, it felt like you were kind of running into a wall? Or was it pretty easy for people to understand where the use cases could be, or why it could be impactful? 

Kevin: 

Very good question. I would say most people never heard of it. You know, so really like across industries, it was like, “Okay, it's quantum. Let's listen to it because it sounds innovative, but we haven't looked into this in detail” 

So we always had this conversation where it was essentially: “Okay, this is what we can do in terms of measurements, in terms of resolution and speed and field of view”, and then tried to use that to understand what problems these industries are facing in sensing.

But most people we came across were generally interested because of the Quantum nature but never heard of it {Quantum Sensing}. So I think we never actually reached out to someone who then said, “Ah, yeah, I already know it {Quantum Sensing}. We checked it and it's not relevant or it's relevant”

So it was always a kind of white field. 

PJ: 

That's really interesting. Do you envision that being a barrier to mass adoption in the long term? I would think no —  because it seems obvious that as news about this comes out, as more sensing developments come out, and as more research comes out, it's clear that this is a better method to sense.

But do you think that in the short term, or have you seen in the short term, it's been harder to secure pilot projects or partnerships because people don't know what you're talking about? Is it all more or less of a process of convincing right now? 

Kevin: 

Yeah. So, I would kind of separate it from quantum computing in that sense. 

I think in quantum computing, it's very hard to understand what conventional computers can do versus what can quantum computers do. So, it’s hard to adopt right now, and will likely be hard to adopt for a while. In sensing, it's a bit more linear, I would say.

You have commercial sensors that are there in every car, in every tool that you use. And then we come in and are just far more sensitive and faster in the ways that we can measure. So it's very easy for most people to understand why this is better, and this helps, but I think that the “quantum” part opened the doors.

And when the doors get opened for us, it’s not a conversation of:  “In 10 years we can be better”. This is what we are already good at. So the doors were opened by the innovative quantum aspect, but then we already have something really tangible that would let them implement pilot projects in the immediate short term. 

PJ:

Yeah, really tangible in the absolute immediate moment. Totally agree. 

So, I know that the recent 7 million Euro round was, from what I understand, meant to push you guys towards commercialization. Correct me if I’m wrong there. But if I’m not, how have you seen that capital impact the business? 

Kevin: 

Ya, so I would say it’s still a little bit early, right? So we are just getting started with hiring some people, but I think where we could see a lot of traction come from this is in our testing as a service, as we call it. 

We have our own labs here now, fully equipped with different measurement systems. So, integrated circuits and some chemistry probes are being sent from companies that want to do this next-generation testing. We don’t yet have a fully standalone product that we can ship to a chip manufacturer, but we can do these tests in house already, and that’s something really tangible that we can work with for now. 

PJ: 

Got it — and how far away do you guys think you are from having a product you can ship out to allow customers to conduct tests on their own? 

Kevin: 

Right now we’re working with a contract manufacturer to integrate the sensors into what you can think of as a kind of microscope, and we hope to install the first one in the fall at one of the research institutes in Germany. 

PJ: 

Awesome, congratulations. Moving back to the sensors —  you said it best, it’s kind of a black box, right? I can tell you, even after twenty plus hours of researching just to understand what quantum sensing is, what an NV center is, why you would use diamonds, so on and so forth, it’s still a little confusing even to me. 

With that, I think it would be really beneficial if you could give your take and reasoning on why NV centers are the best for this type of sensing, and why you chose to focus on diamonds as your solid state qubits. 

Kevin:

Yep. So, we didn’t do a huge comparison and benchmarking of alternative quantum sensing technologies, actually. 

We started from the side of: what are NV centers good at, and what problems out there could they address? 

So we came more from the technology point of view, which I would say, in entrepreneurship, is sometimes the wrong approach. But we looked at NV centers first to see what they were really good at in order to find our market. 

NV centers can do ultra precise measurements of magnetic fields in a relatively high field of view, up to a couple of millimeters squared. Plus, they’re non-destructive, so you can look into more complex architectures in whatever use case. So, it really comes down to those small features. 

Then we looked at the different fields that might require that. So, thinking about chemistry, biology, or semiconductor manufacturing, you always have to do precise measurements. In the best case, these need to be at the nanometer scale. And then speed also plays a role. So, we can do these types of measurements with NV centers, and it only takes a fraction of a second to do so. The rest is post processing. 

Then, at some point, we really thought about, you know, where do you need a very high precision but very fast measurement? That’s what led us to talk to the semiconductor manufacturers, and we heard from them that as they continue to produce these more complex chips, with more complex architectures, they’ll need technology that allows them to do non destructive testing to see that all the different components work reliably. 

It was at that point where we really saw a customer problem and a clear technology roadmap to solve it. 

PJ: 

Got it. Really interesting, and you’re right, pretty unconventional, but I guess that’s why you guys are one of the only companies doing this type of work. 

I would love if you could tell me more about the process — from procurement of the diamonds through to creation of the sensors, what are the steps involved there? Are you guys growing the diamonds in house and creating the NV centers? Procuring diamonds that already have that imperfection? What’s that look like? 

Kevin: 

So, we’re honestly not 100% decided on supply chain yet. The typical approach, from the research perspective, is to buy synthetic diamond material from companies like Element 6, which is one of the biggest names in the industry. 

Their diamonds are electronic grade, so very, very high purity. And then you can basically just implement the NV centers by shooting a nitrogen atom into the crystal lattice, taking out the neighboring atoms, and putting it into an annealing oven. In the oven, the nitrogen and the vacancy kind of just find themselves, and form together to create the NV center. So that’s one way of doing it. 

But you can also do it in the growth phase. If you think about a synthetic diamond, you have a growth chamber where you just shoot all of the carbon atoms in, and you can directly include NV centers into the growth process. That would be the second way of doing it. 

Right now, we’re investigating both, and they both have their pros and cons. I think the big value add is not actually creating the NV centers, but interpreting, and reading them out. When you do wide field imaging —  say you have a 4x4mm diamond — you take a picture, and then have to do analysis to transform the fluorescence of the magnetic field for every single pixel. This is a huge post-processing effort, and this is where, to our understanding, the value add lies. 

A picture doesn’t mean anything. But if you have that magnetic field data, then you can say “oh, this is a short in the semiconductor”, for example. This is where the magic happens. 

PJ: 

Got it. What kind of tech are you all using to interpret those pictures? Are you integrating any AI into that process? 

Kevin: 

So what we do is kind of a two-step process. One is transforming the pixel data into magnetic field information. That’s powered by proprietary algorithms that we took from our co-founder’s PhD. But then, once you have that, you can leverage regular post-processing image comparison for each layer. 

Then, of course, machine learning comes back into play when, for example, you see a defect in a chip ten times, and see how they impact the magnetic fields. Then it’s relatively straightforward through different algorithms to identify that defect based on the magnetic field data. A lot of value lies in that analytics layer. 

PJ:  

Awesome. So I want to go back to the process for one second. You said you’re testing two different processes and methods of NV creation — are there significant differences between the two in terms of cost and scalability? 

Kevin: 

In terms of price, they’re pretty similar. Maybe a 10% difference plus or minus. The main challenge, in general, is which is easier to implement. 

On the one hand, you have this synthetic diamond, and you implant it. But the main challenge is that, at some point, you want the NV center to be homogenously integrated into the entire chip. 

If you use the growth process, you can very precisely target where you want to implant the NV center, but if you just shoot them in, you have to optimize a ton of different parameters. What is the speed? What is the angle? How long do you have to put them into the oven? So implantation is definitely more complex, but it’s also much faster when compared to growing your own diamonds. 

PJ: 

Let’s switch now to the use cases for Quantum Diamonds. I know one of your co-founders, Dr. Liu, thinks medical diagnostics is the most interesting potential use case for this tech. I’d be really interested to hear what yours is. 

Kevin: 

That’s a very big question. I would say, in the long term, I think the most attractive right now is within semiconductor testing. Right now we work with a lot of semiconductor clients in a lab environment. It’s a lot of R&D work. So this is a small field where we’re already making a large impact, and it’s not bound by any regulatory constraints. 

In the long term, I would say the entire health care industry and use case if highly attractive. If you think about drug development, enzyme screening, all of these biological chemical processes that are sometimes limited by the number of samples you can look at —  we’re really excited about using this technology to do high throughput drug development and screening. 

So, you take these diamonds and then have, I don’t know, a thousand different drugs you want to observe, and you can see in real-time how they behave. This obviously comes with a lot of regulatory implications, though. You can’t just put anything into a biolab without approval. 

PJ: 

Awesome. I think I mentioned it before, but one has to think that if you guys are right in your thesis that this technology is that much better than any other sensing technique in the market, then it’s right to assume that at some point there will either be more early stage competitors entering the market or that a larger incumbent will begin to develop a competitive solution. What’s Quantum Diamond’s plan to stay ahead? 

Kevin: 

Yeah, another good question. So we think that there’s a pretty steep learning curve that we are on right now that others just can’t catch up with. So, if you think about the way we talk to semiconductor people now, we’re well on our way to understanding their problems in great detail. We’ve built this analytics layer specifically to learn from every chip we test or every enzyme we screen. 

I think that because we’ve got this head start, it’s simply impossible to catch up. Even if you put a lot of resources into accelerating the process. Then, of course, if we can really make a difference in one or two of these verticals, then being bought by one of the big players in the field is a definite possibility. 

But we’re pretty confident that even beyond that possibility, we can go to these different verticals and be a highly functioning and successful standalone company, regardless of any other competitors entering the market. 

PJ: 

Alright, last one. Corny question to wrap it up. What’s next for Quantum Diamonds? 

Kevin: 

Yeah, so we’re just about to hire a couple of more people, roughly 20, which is a good number to do the really hardcore R&D. Then it’s really about launching the first product and bringing it to market. Though we’re operational in Germany right now, that’s not where the main market opportunity lies. So we’ll spend a lot of time in Asia and the US with these new resources to understand in more detail what’s needed in terms of product roadmap and product development. 

PJ:

Awesome. Thanks so much, Kevin, for your time. Really illuminating stuff, and I’m excited to see where you guys end up.