#223 Kai Beckmann: Why Next-Gen Chips Are Critical for AI's Future

This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more. NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more. In this episode of the Eye on AI podcast, we explore the cutting-edge world of semiconductor innovation and its role in the future of artificial intelligence with Kai Beckmann, CEO of Merck KGaA. Kai takes us on a journey into the heart of semiconductor manufacturing, revealing how next-generation chips are driving the AI revolution. From the complex process of creating advanced chips to the increasing demands of AI on semiconductor technology, Kai shares how Merck is pioneering materials science to unlock unprecedented levels of computational power. Throughout the conversation, Kai explains how AI's growth is reshaping the semiconductor industry, with innovations like edge AI, heterogeneous integration, and 3D chip architectures pushing the boundaries of performance. He highlights how Merck is using artificial intelligence to accelerate material discovery, reduce experimentation cycles, and create smarter, more efficient processes for the chips that power everything from smartphones to data centers. Kai also delves into the global landscape of semiconductor manufacturing, discussing the challenges of supply chains, the cyclical nature of the industry, and the rapid technological advancements needed to meet AI's demands. He explains why the semiconductor sector is entering the "Age of Materials," where breakthroughs in materials science are enabling the next wave of AI-driven devices. Like, subscribe, and hit the notification bell to stay tuned for more episodes! Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A. I. Twitter: https://twitter.com/EyeOn_AI (00:00) Introduction (02:48) Merck KGaA (05:21) Foundations of Semiconductor Manufacturing (07:57) How Chips Are Made (09:24) Exploring Materials Science (13:59) Growth and Trends in the Semiconductor Industry (15:44) Semiconductor Manufacturing (17:34) AI's Growing Demands on Semiconductor Tech (20:34) The Future of Edge AI (22:10) Using AI to Disrupt Material Discovery (24:58) How AI Accelerates Innovation in Semiconductors (27:32) Evolution of Semiconductor Fabrication Processes (30:08) Advanced Techniques: Chiplets, 3D Stacking, and Beyond (32:29) Merck's Role in Global Semiconductor Innovation (34:03) Major Markets for Semiconductor Manufacturing (37:18) Challenges in Reducing Latency and Energy Consumption (40:21) Exploring New Conductive Materials for Efficiency

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  AI boom is defined by building capacity in data centers for training large language models. Current application is more you use a web interface, you do chat GPT and use the large language model. What is still to come is edge AI. I mean, you can put a AI chip on a smartphone, take the latest iPhone, and then you can do inference on the AI models right on your end device. You don't need to transfer data like crazy up and down the cloud.

• 0:27Craig S. Smith?

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• 1:06Craig S. Smith?

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• 1:49Craig S. Smith?

  That's netsuite, N-E-T-S-U-I-T-E, dot com slash eyeonai, E-Y-E-O-N-A-I. All run together to get the CFO's Guide to AI and Machine Learning. The guide is free to you at netsuite.com/eyeonai. Netsuite dot com slash eyeonai. I generally start by having you introduce yourself and how you became CEO of the electronics business of Mark KGAA.

• 2:29Craig S. Smith?

  In Darmstadt, Germany. And then we'll talk about material science and semiconductors and and all of the businesses that you have that impact artificial intelligence.

• 2:48Speaker 00

  Yeah, Greg, thanks a lot for for having me on the podcast. So my name is Kai Beckmann. So I started now company already more than thirty five years ago. I'm a computer scientist by training. I I did a minor on microelectronics. So the interest for for semiconductors is kind of deeply rooted in in myself. I then had opportunities to work in all areas of our company in IT. I was leading HR. I was in the countries running our our businesses in Singapore and Malaysia. Healthcare business, life science business, performance material business. And then I entered the executive board some

• 3:33Speaker 00

  meanwhile thirteen years thirteen years ago. And being in charge of a number of what we call group functions, HR procurement, our major production side, our headquarters side, as well as as many other functions. And then seven years ago, I was asked to take over performance materials, performance materials business, which we have then rebranded a while ago as electronics, based on our transformation away from a materials business to an integrated solution provider for the electronics industry and specifically for the semiconductor industry.

• 4:12Craig S. Smith?

  Can I just say, just for listeners who who might be confused? Merck G G A A is is a German company. And it it was founded by Jacob Merck, I think, in the in the late seventeen centuries or Friedrich Jacob Merck.

• 4:36Craig S. Smith?

  And and that company then split eventually between the Merck that Americans know, which is the big pharmaceuticals company. And and your company. So there are two separate companies. I think Americans can easily get confused by that.

• 4:56Speaker 00

  Absolutely. And thanks for thanks for explaining that. So we have a more than 350 years history as the kind of Germany headquartered company. And so we operate in three different businesses. We operate in in healthcare, we operate in life sciences, as well as in electronics, covering a broad spectrum of of different different industries and different yeah, technologies and and science.

• 5:21Craig S. Smith?

  Is yeah, can you tell tell me about the work that you do that that is foundational to semiconductors?

• 5:30Speaker 00

  Yeah, as I said, our roots are in chemistry, our roots are in biology, our roots are in physics. And if you combine physics and chemistry, then you easily kind of reach the field of of materials, specialty materials for the electronics electronics industry. And since we started the transformation towards electronics, we combine different parts into one into our portfolio, different parts across different technology steps, manufacturing steps of making a semiconductor from delivery systems in a sub fab that make chemistry gases available to the tools to materials across the full production cycle of semiconductors

• 6:14Speaker 00

  from patterning to to cleans to generalization, thin film materials, specialty gases. And so we we offer a full spectrum, including with the latest acquisition of Unity SC, including metrology instruments for hydrogenous integration, which is very important of new technology required to enhance the performance and the capability of of semiconductor.

• 6:40Craig S. Smith?

  In the semiconductor manufacturing process, can you can you is that too complicated to walk? Us through and tell us where in the process these marked products come into play.

• 6:57Speaker 00

  Yes, that's a great point. So typically you start with like a blank wafer, a wafer that doesn't come from us. There are other companies who who supply silicon wafer and then you start processing the wafer. So you start kind of patterning structures on a wafer. This is a lithography step. I mean, you use light and in today's world, extreme ultraviolet light to create in a photo lithography step, structures. Then with that kind of you wash off the unexposed parts of that. You then build structures on that with thin film deposition on a wafer.

• 7:38Speaker 00

  And you you you start planarizing structures in order to get an even surface. You deposit materials to get kind of charged areas on a on a device positively or negatively. And then with that, you build these semiconductor transistors on a on a on a chip. And and with that, then with these steps, more than a thousand, meanwhile, in in most advanced technologies, more than a thousand steps. You build these enormously complex devices that can probably host more than a hundred billion transistors on one chip in structure sizes that go that go well down to two nanometers scale.

• 8:20Speaker 00

  And that's kind of a technology which has advanced over the past years dramatically. In a way, the the level of complexity, the level of performance has been accomplished. And you need specialty materials to to create these highly, highly complex and differentiated devices. That's the way we want if you want a kind of a pretty, pretty kind of visual number. So if if you take our materials and our technologies, our equipment and our instruments. So and if you try to identify in a in a normal retail store, electronic devices in a retail store.

• 8:59Speaker 00

  Whether they have been exposed to our equipment or materials, there's a greater than ninety-nine percent probability that any electronic device, TV, handphone, computer, cars, what have you, has been, has been made with the help of our materials, tools and, and equipment.

• 9:19Craig S. Smith?

  And in terms of materials, that's, those are layers on the sub, the silicon substrate that, that you're building up as you, as you create the, what's the most common of those materials, or the most heavily used?

• 9:38Speaker 00

  When, when I started doing that at, at university, and you had a handful of materials that you could use to, to make a semiconductor, and of course silicon is the base material, and you, you have created silicon, silicon oxide layers for insulation, you have used aluminum for, for, for conducting, conducting layers, and that's basically kind of the set of materials, and you needed a couple of solvents to, to wash stuff off the surface, and that's about it. Meanwhile, we use eighty percent of the non-radioactive periodic table of elements to make semiconductors, eighty percent. There's not much left, correct, on, on, let's say, advancing technology.

• 10:23Speaker 00

  There's a, there's a famous quote, it was used publicly in many instances by, by Pat Gelsinger, CEO of Intel, who said, "We're not gonna stop innovating semiconductors until we have exploited the full periodic table of elements." This is music to my team's ears. So of course, for, for chemists, that is like the message that drives them to the next level of, of, of excitement and performance, and this is what like feeds their, their brain for, for making better semiconductors tomorrow.

• 10:54Craig S. Smith?

  And, and who are your principal clients in the semiconductor industry? Is it obviously TSMC and, but, or are they component suppliers to the big foundries?

• 11:08Speaker 00

  So everyone who makes a semiconductor is on our client list. We have done a precise analysis. We took the top 100 companies who make semiconductors, and each one of them is on our client list, each one of them. And of course, typically, these are companies who have fabs, so not the fab-less companies. Of course, they give their manufacturing to foundries, companies who operate fabs. In some instances, the tool companies can be customers too, so they offer them fully packaged solutions to our fab customers. But mainly, it is the semiconductor industry,

• 11:52Speaker 00

  which is on our client list.

• 11:55Craig S. Smith?

  Yeah, and I have to ask, you know, I've spent a lot of my life in China, so I follow the China story. Are you guys restricted under the export controls to sell to China? Or do your materials fall outside of that?

• 12:16Speaker 00

  Certainly, we are restricted, and we follow those restrictions very tightly and clearly. So we operate under all these global rules and special national rules. I think we have to, of course, understand there is we serve the display market as well, and 70% of global display real estate, so all display surface is produced in China, 70%. So there is almost 70% of smartphones, TVs, automotive displays, they all come from China. So this is, of course, the lion's share of our activities in China for China.

• 12:58Craig S. Smith?

  Yeah, and in the business generally, is it the display business or the semiconductor business or something else that's the bulk of your business?

• 13:07Speaker 00

  The bulk is semiconductor, clearly. The majority, the vast majority, and of our, what we call electronics core, because we have put one part of our business, the Surface Solutions business, is... For sale and this has been been already assigned deal and it's been carved out. So of what we call electronics core, the rest is already eighty percent is facing the semiconductor industry. And only then twenty percent is left for for the display industry.

• 13:33Craig S. Smith?

  Yeah, so you you guys have a really wonderful overview of the semiconductor industry, right? Where is it growing? Is it growing everywhere? Is it? I mean, famously, TSMC and Intel are building big fabs in in the United States. Where is it growing right now?

• 14:01Speaker 00

  Any semiconductor industry is probably one of the most fascinating industries. And if anyone has any problems with blood pressure to work in a cyclical industry, maybe it's not a good, not a good advice. So it's going up and down. It's like if you take my thirty five years, if you take an average, it's like four good years. And then we'll be four bad quarters. This is the typical, the typical cause of of things. And it's always been like this. Now, meanwhile, it's getting a bit more complicated because different technologies have different cycles. And they're not fully in sync like they were in the past. And this is why at any given point in time, there are some businesses, of course, beautifully developing and others are a bit more, a bit more behind.

• 14:43Speaker 00

  In the current setup, of course, artificial intelligence drives a lot of growth in the semiconductor industry. And this is still predominantly focused on on on training large language models. And the GPUs and the boards used in in in data center applications. This is driving a lot of growth as we speak. But other technologies meanwhile are catching up slowly as well. But it's not anymore like as nice of a wave that you could you could monitor. It's more like many waves on top of one another. So this, the industry is a bit more kind of spread out in terms of recovery than it was in the past.

• 15:26Craig S. Smith?

  That cyclical nature previously was was that tied to simply inventory piling up? And then getting used and piling up, or was it tied to some?

• 15:40Craig S. Smith?

  Some other cycle in the economy.

• 15:43Speaker 00

  Yeah, if you look over a larger period of time, then predominantly it's driven by the the fact that these fabs can run either fully utilized or they will be stopped, lines will be stopped. And there is no such thing as a fifty percent utilization typically in a simplified way, just a quite a simplified picture. So it means they run hundred percent and you create some point inventory and you feel maybe it now it's time to stop producing, I need to deplete my inventory and then it goes, comes all over again. That is the simplified picture. Of course, you can still find that in memory where the products are a bit more commoditized, you find it less and less in logic where the products are much more specialized on

• 16:28Speaker 00

  for different, different customers. So this is why the picture is not anymore as it was in the past, you know, the cycles in the early two thousands where even the, the logic part, the, the CPUs for desktop computing were kind of almost commoditized, maybe the wrong word, but they were more replaceable than, than they are today. So in, in those times, it was piling up inventory and then depleting inventory again, this created the cycles. And it's still the situation that these fabs can run either kind of on a, on a full utilization or you better stop them because you're just burning cash.

• 17:05Craig S. Smith?

  Yeah, although given the, the advance of, of AI and the demand, generative AI and the man, demand for GPUs and the shortage in GPUs, it seems that, that inventory buildup is, is for the foreseeable future not going to be a problem. Is that right? That is a pretty steady demand.

• 17:34Speaker 00

  Yeah, still bear in mind that AI is in terms of percentage of all devices, semiconductor devices produced in the world is still a fairly low percentage. We are still talking about a fraction of a percent. So that's why it doesn't really move the needle in terms of overall capacity inventory yet. In terms of value, we are already reaching 10% of AI-related semiconductor devices, which of course includes not only the data center devices. It includes as well kind of edge AI devices like yeah, processors on a smartphone, processors on a, on a, on a, for, for mobile computing at large.

• 18:14Speaker 00

  So this is the broader spectrum, 10% of the value equals somewhere 0.1, 0.2% of the devices manufactured.

• 18:23Craig S. Smith?

  How do you see that developing? Because certainly demand AI is going to spread. And are you guys, is that triggering any, any sort of shift in your production? Or triggering any sort of research for, for new materials that can be applied?

• 18:46Speaker 00

  I think the first thing it does, the kind of the AI boom that we see is it requires more sophisticated chips. That's what it, what it does in the first place. So, and, and more sophisticated by an order of magnitude, not just by a small margin. More complex architectures, smaller structure sizes, even what we call heterogeneously integrated semiconductor devices. It means you take chiplets and kind of glue them together in order to increase performance and, and packaging density. So that's of course, again, a dimension that helps kind of accelerating our contribution to, to the industry. That's the first, the first thing.

• 19:29Speaker 00

  The second thing is with the current, yeah.

• 19:34Speaker 00

  AI boom is defined by by building capacity in data centers for training large language models. Then the the the current application is more you use a web interface, you do chat G P T and and use the large language model. What is still to come is edge AI. I mean, you put a a AI chip on on a smartphone, take the latest iPhone, you you have that functionality on the iPhone already, but of course, the percentage of market share is not not huge yet. And then you can do inference on the AI models right on your end device. You don't need to transfer data like crazy up and down the the cloud. You can do that inference on your device.

• 20:17Speaker 00

  You mean, things like Microsoft Copilot, for example, on a laptop computer can be done right on your on on your laptop computer with kind of a a C P U, G P U that you have in order to do the inference. That is the next level of of of AI use cases, and I think we will all see that coming. One could ask, what is the killer app? What will what will make that happen? We shall see. There's a lot being done around visualizing data, analyzing data, text analysis, of course, is a big deal there as well. Picture editing is an important area as well.

• 21:01Speaker 00

  Information research is an important part. I I would suspect that a lot of these applications will be more and more compelling in their in their use case, that demand for compute power, edge AI, compute power on your end device will be increasing.

• 21:19Craig S. Smith?

  Yeah, so you see your your business growing dramatically, I guess, in the next ten years.

• 21:26Speaker 00

  Yeah, we just upgraded our our capital market guidance, midterm guidance, based on those trends. Yes, I think we do have quite some confidence in in the industry picking up on driven by AI, the increased complexity of the chips, as well as the the sheer volume. Over the next, over the next couple of years, absolutely.

• 21:47Craig S. Smith?

  Yeah, and you guys develop new materials. Is, can you talk about what you're doing there? And, and obviously, AI is being applied to material science and discovering new materials. Do you guys use AI in your, in your research?

• 22:10Speaker 00

  Great point. That's an amazing point. Of course, we, we enable AI and we use AI to enable us. So it's a kind of a full, full circle of things.

• 22:21Speaker 00

  So the, the, the way, of course, we need to, to, to identify new molecules, new precursors that are used for, for, for making chips, requires typically a lot of experiments, where you check whether this precursor does what it's supposed to do. Can you synthesize it? Is it, is it stable enough? Does it have the, the properties that you, that you need? And with AI, we can reduce the number of necessary experiments quite drastically. So in a recent talk, I have explained that kind of out of hundred different potential target molecules, we can remove ninety-nine

• 23:01Speaker 00

  just based on, on AI and just synthesize one for the next level of testing. And then this next level of testing, that's another capability that we have built over the past, over the past five years, that we, in, in the past, we have provided then this kind of synthesized molecule to a tool company or to a semiconductor fab in order to test the electrical properties. Meanwhile, we have the same capability within our, our own premises. It's called Intermolecular. It's a, it's, it's a facility that's based in the Silicon Valley in San Jose. And so we then can do electrical combinatorial testing of that material on a wafer

• 23:45Speaker 00

  in a, in a transistor structure. And with that, reduce the cycle of, of these refinements of our material.

• 23:54Speaker 00

  Drastically in the past, we talked about one to two years and now we are in the in in weeks on a week scale. That's of course a huge benefit, less experiments and faster cycle time is quite exciting. Of course, a pretty natural question that I typically get is then is it do our chemists like that? Because if they do less experiments, do they lose their jobs? I think it's the opposite because our chemists and I've talked to many of them, they they like to do successful experiments. They don't like to do experiments that fail and we remove the experiments that fail by artificial intelligence.

• 24:33Craig S. Smith?

  Yeah, and and that pace of discovery, is that resulting in new products for you guys?

• 24:42Speaker 00

  Absolutely. It is then identifying new material opportunities for our customers, which they invalidate in their processes, which then feeds novel technologies that is then implemented by our customers.

• 24:58Craig S. Smith?

  Yeah, I'm just curious. So when you synthesize a new molecule and you send it to to California, in what form is that sent? Is that, I don't know, is it a vial of liquid? Is it a roll of sheet? Is it a block of solid material? Or is it just some formula?

• 25:30Speaker 00

  So it could be all of the above, except the formula. So it's either it could be a liquid, a gas, or a powder, a solid material, and it's shipped in, of course, containers, small containers that keep that intact and ensure safety for transportation. But it's the way how we handle these materials. Yeah, absolutely.

• 25:50Craig S. Smith?

  Yeah. And then when you validated it, you put it into production for for for yeah, for semiconductor fabs. And how often do you come out with new materials for semiconductor?

• 26:10Craig S. Smith?

  Fabrication.

• 26:11Speaker 00

  It's pretty tough to give you a precise number because overall our product list probably has a couple of thousand different, different, different materials, material combinations, molecules, formulations, and it's quite a frequent event that new process step requires new formulation, a new precursor for our customers. So it's not just once a year, it happens quite frequently. Not everything will be then adapted for mass production, but still it's a pretty normal, if not daily, process.

• 26:48Craig S. Smith?

  Wow. And do you see the semiconductor fabrication process changing, you know, in the next 10 years? I mean, I don't know if it's been the focus, but from my point of view, from a journalist's point of view, the focus has been on, you know, smaller and smaller gate sizes, as you said, down to 2 nanometer. Is it going to continue miniaturizing? Or are there gains to be had through other parts of the process, maybe through materials?

• 27:31Speaker 00

  Yeah, that's a great point. So, you know, when I was at university, the end of the 80s of the last century, and already many people speculated, is Moore's law over? That was, you know, quite a while ago. And so maybe half jokingly, we have said there's maybe like a derived Moore's law that the number of people declaring Moore's law being over doubles every other year. So that's maybe...

• 28:02Speaker 00

  I didn't get a trademark for that, so it's free to use.

• 28:08Speaker 00

  Certainly not called Beckmann's law, I can tell you. But so the dimension, the focus was on what we call shrink. So getting the tachryphary to create smaller structures. And everything else was auxiliary to making a semiconductor over a couple of decades, over about three decades now. And of course, we are touching limits. There may be physical limits, but more importantly, there are economic limits to that, where it simply doesn't scale financially properly. And this is where then additional methods are being used.

• 28:48Speaker 00

  And probably the most novel way of doing it is the current trend, especially in the area of AI, around heterogeneous integration. So you build chiplets and then you put these chiplets together in a certain way in order to better scale your performance on the chip. And with that, if you take, you know, Nvidia's H1 hopper, I think we're talking about more than 200 billion transistors, not on a single die, however, on this system. And you can almost glue stacks of memory very close to your GPU to reduce distances

• 29:32Speaker 00

  for data transfer, because data transfer is still the part of the whole compute with the highest energy consumption and the highest impact on latency. So that is then a system, I think especially called that CoVOS. This is a chip on wafer on substrate, which is then the next level of densification of transistors, like three dimensions plus all these different capabilities to make even more complicated chips happen.

• 30:04Craig S. Smith?

  Yeah. And where do your materials come into play in that, in the glue or in the?

• 30:13Speaker 00

  In the thin film materials needed to build the structures on the chip, in the planarization that helps to create even even layers in the doping, to dope the conducting layers, transistor parts of that. It is required as well as for patterning steps. It's required are tools for delivering the chemistry. It's required for the chromatology instruments that help to measure the precision of the 3D stacking that is done for the integration. So everywhere, literally everywhere.

• 30:54Craig S. Smith?

  I have to ask because I've interviewed Andrew Feldman at Cerebrus a couple of times, which is another strategy. Instead of chiplits, stacking chiplits, they're laying it all out on a wafer scale engine. Do you work with them as well?

• 31:15Speaker 00

  We work in the early development with many different partners in order to identify new technologies. Of course, for us, the value is then in mass production with the big foundries. This is where the value sits. But there's lots of different technologies in the early days on like wafer scale, as you explained, at the genes integration, which is already in mass production. And we talk about neuromorphic computing architecture that is maybe a bit further out, that bring compute and storage much closer together in order to do the brain-like way of computing data.

• 31:58Speaker 00

  And of course, far out things like quantum computing. We work with PsyQuantum in Silicon Valley as well in identifying materials for qubits in future. So there's things that are near term and things that are really far out. And we try to cover in a meaningful way different phases of the lifecycle. But the focus, of course, is on what is very close to mass production and helps our customers to scale today's technologies.

• 32:27Craig S. Smith?

  So you guys are sort of the hidden...

• 32:33Craig S. Smith?

  Uh hand behind a lot of semiconductor manufacturing or semiconductor development. Is is uh how how large is your organization and and uh? Yeah, I mean, how many chemists and engineers do you have working for you?

• 32:54Speaker 00

  Maybe we've put ourselves like on a slogan that we have used for a couple of years that we are kind of the company behind the companies advancing digital living. That has like a really encouraged the team to do what it does. So is we take pride of making our customers successful. So if we feel there's something great coming out of our customers' pipeline and we were an integral part of making that happen. I think it creates a lot of pride in the in the organization. Overall, our company is more than sixty two thousand people globally. The electronics sector is is in seven thousand people.

• 33:33Speaker 00

  And overall, our company employs in in all kinds of R and D and R and D related functions, more than six thousand people, six thousand R and D. Researchers driving science, technology across different domains from chemistry, biology, physics, engineering, computer science, data science. As well, so highly science based, science based company ever since its its its its foundation more than three hundred fifty years ago.

• 34:02Craig S. Smith?

  Yeah, and where are your biggest markets?

• 34:05Speaker 00

  That's basically where our customers are. So in the in the current environment, there is a lot in the in Asian countries, South Korea, Japan. In regions like like Taiwan, in of course, United States is amongst our largest geographies. Europe in the in the electronics industry is a bit lagging behind. I see that with yeah, quite some sadness as a as a European citizen. And we try to catch up. However, we do have great research centers over here such as IMAC, such as. Lady, a very important research centers for the global semiconductor industry.

• 34:49Speaker 00

  So we are basically where our customers are.

• 34:52Craig S. Smith?

  Yeah, and the semiconductor industry in Europe. Are there fabs being built right now?

• 35:03Speaker 00

  We do have already a number of highly specialized fabs in Europe of companies like Infineon, like STMicro, like NXP. And of course fabs operated by companies like Global Foundries, like Intel of course in Ireland as well. And I've just visited in summer kind of the groundbreaking of the so-called ESMC fab, which is a joint venture between companies like TSMC, NXP, Infineon and Bosch.

• 35:41Craig S. Smith?

  Is there anything I haven't touched on that you want to say?

• 35:48Speaker 00

  If I have kind of left the understanding that materials are now kind of the new dimension of driving performance of semiconductor devices, then probably I've done a good enough job. So some of our customers call it. Meanwhile, this is the age of materials coming from the age of tools, the age of kind of lithography now turning into the age of material to make these amazing devices happen. I think it's very important. Part second is AI, so we use AI and we enable AI. At the same time, it's an important part of driving value and kind of all across different domains that we cover.

• 36:37Speaker 00

  Trying to explain how the technology overall kind of emerges into into new new fields, heterogeneous integration as probably the most important new dimension 3D structures. We talk about memory anyway being in a 3D structure. Meanwhile, logic is more and more turning into 3D transistors, probably there will be 3D logic eventually at some point. So there's there's many different areas that give us kind of reason to be to be optimistic about how technology evolves and how the market opportunity evolves going forward.

• 37:18Craig S. Smith?

  Yeah, well, actually, and that that brought up another question. In stacking or or in, I mean, that was Cerebrus's thesis is that, you know, you you you etch a wafer and then you cut it up into little chips and then you wire all these chips together and it's those connections between the chips that that determine latency because or or contribute to latency because there's a there's a a limit to how quickly they can transfer

• 37:59Craig S. Smith?

  data from, you know, high performance, what is it, high bandwidth memory to the logic, for example. And it seems like that that connection, that the limit on that data transfer would be a materials science problem. Are you guys working on that at all?

• 38:20Speaker 00

  I think there's I think the stacking is one dimension. I think the first step, of course, if if we if we can, we try to have 3D structures on one wafer. This is always the the more efficient part, like in 3D NAND in in storage, there's just layer on layer on layer up to 300, if not more, that are used to store data in in NAND structures. This is one part. And

• 38:47Speaker 00

  This will be explored for DRAM as well, it will be explored for logic, this is a bit further out. If that doesn't work, then of course the next opportunity could be you stack dice, like you just said, you kind of produce a die and then you you you stack these dice and of course the latency is defined still by distance and the distance between distance on a wafer to distance across wafers is orders of magnitude and this is where of course latency and and energy consumption comes comes from. This is where we then look into leakage current, for example, of of conducting conducting structures. So this is where materials properties can help to improve that.

• 39:32Speaker 00

  If you take that example in a in a very simplified way and I try to to make it a simple example, the the conducting lines that are created on a chip, they used to be when I was at university, as I said, aluminum was a a material of choice. Then we saw over time, again, I simplified in in in one in one use case, over time copper was then then used as well for all these these power distribution, still used for kind of backside power distribution or layers on on on top of of the transistors. Then underneath for smaller structures, you knew you used tungsten as a as an important important material.

• 40:13Speaker 00

  But if as you go forward, you see limits coming up in terms of of of the the electrical properties and this is where we now explore moliptonium is the kind of the new kid on the block because it performs better than the traditional materials in in that spectrum. It shows how material innovation helps to solve problems created then by higher densification on a chip. Leakage current is one dimension very important, then of course conductivity overall very important to make high performance chips possible. And then in stacking, you have that, of course, in the third dimension with how do you build these contacts, how we do this through silicon bias, which is the holes that you drill in

• 40:57Speaker 00

  order to build contacts to your to your kind of. Consistor layers or storage layers on a chip and how you package it all together to make it sturdy enough for great performance and improve energy consumption. I hope that makes sense and very simplified way to tell you how the innovation cycles over even a longer period of time take place.

• 41:20Craig S. Smith?

  And I would guess then you're continuing to look for new conducting materials for those connections.

• 41:29Speaker 00

  Absolutely, this is where the kind of the 80% and the remaining 20% of the periodic table of elements comes from by exploring can other materials have better properties in what we try to accomplish on a chip. This is exactly where that comes from, of course, with all questions on cost of making a chip, stability and all different factors that are kind of required to be observed.

• 41:57Craig S. Smith?

  This has been fascinating because it opens up understanding of another dimension in semiconductors. And you guys are a public company?

• 42:10Speaker 00

  We are 70% held by the founder's family, who is now in the 13th generation, holding 70% of our equity and 30% is publicly traded. We are listed on the German DAX index and so this gives us, as we call it, the best of both worlds. So the stability, longevity of a family-owned company with a high involvement of our owner's family as well as transparency and the agility of a publicly listed company. So we have kind of best of, best of both worlds.

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