SES AI Q4 2023 Earnings Call Transcript

Quartr
Provided by Quartr
February 26, 2024

There are 7 speakers on the call.

Operator

Good afternoon, ladies and gentlemen. Thank you for joining today's SCS AI Corporation Q4 2023 Lender Call. My name is Tia, and I will be your moderator for today's call. All lines will be muted during the presentation portion of the call with an opportunity for questions and answers at the end. It is my pleasure to pass the call over to Cal Peckelton, Chief Legal Officer.

Operator

Please proceed.

Speaker 1

Thank you. Hello, everyone, and welcome to our conference call covering our Q4 2023 results and financial guidance for 2024. Joining me today are Chiqiao Hu, Founder and Chief Executive Officer and Jing Nialis, Chief Financial Officer. We issued our shareholder letter just after 4 p. M.

Speaker 1

Today, which provides a business update as well as our financial results. You'll find a press release with a link to our shareholder letter and today's conference call webcast in the Investor Relations section of our website at ses.ai. Before we get started, this is a reminder that the discussion today may contain forward looking information or forward looking statements within the meaning of applicable securities legislation. These statements are based on our predictions and expectations as of today. Such statements involve certain risks, assumptions and uncertainties, which may cause our actual or future results and performance to be materially different from those expressed or implied in these statements.

Speaker 1

The risks and uncertainties that could cause our results to differ materially from our current expectations include, but are not limited to, those detailed in our latest earnings release and in our SEC filings. This afternoon, we will review our business as well as our results for the quarter. With that, I'll pass it over to Qi Chao.

Speaker 2

Thanks, Kyle. Good afternoon, everyone. We posted a thorough shareholder letter on our website, which provides all the details for the quarter, the year and our 2024 outlook. Now I want to make our time more efficient with a more focused conversation. There are 3 key points that I believe you should take away from SCS AI's results and outlook.

Speaker 2

First, we became the world's 1st to enter into automotive B Sample joint development with a major automaker for lithium metal. This is a major milestone in the commercialization of lithium metal battery technology for automotive applications. In 2024, our focus will be delivering on our EV B Sample joint development. 2nd, in addition to EV, we have also identified urban air mobility or UAN as an exciting application for lithium metal. The high energy density and high power density of lithium metal really enables UAM.

Speaker 2

UAM is a natural stepping stone to EV for lithium metal. 3rd, to ensure practical safety, especially as we prepare for C sample and commercial deployment, we are doubling down on the use of AI to monitor battery health and predict incident. Our lithium metal large cell avatar AI prediction accuracy increased from just 60% in 2022 to 92% in 2023. And this year, our target is 95%. Ultimately, we want to achieve near 100% safety guarantee for EV and UAN.

Speaker 2

Now I'll talk more about 2023 accomplishments. 2023 was a great year for us. We took a massive step toward commercialization of our lithium metal technology for automotive applications. We signed the world's 1st automotive B Sample joint development agreement for lithium metal batteries with a major automaker. No one has gotten this far with lithium metal batteries for EV application.

Speaker 2

This is a giant leap in the commercialization of lithium metal technology for automotive applications. Our 3 JDA partners, GM, Hyundai and Honda, continue to be very supportive and push aggressively in EV. Hounde recently just became the 2nd largest EV maker in the U. S. It's significant to note that 2 of the key milestones for entering into B Sample development include practical safety and manufacturability.

Speaker 2

We'll share more details around these two accomplishments. The first one, practical safety. Achieving Hazard Level 5 for large 50 ampoureand100 ampoure lithium metal cells was a combination of improved safety in materials as well as improvements in cell design and engineering. In fact, we achieved greater safety related breakthroughs in cell engineering than in material chemistry. This was intentional because by having minimal changes to material chemistry and by focusing on cell design and engineering, we didn't have to sacrifice cell performance and energy density.

Speaker 2

We recruited the world's top cell engineering talent and created designs that are still based on lithium ion, so they can be manufactured at scale, but are unique for lithium metal and can address safety related challenges. We won't go into details about these cell design and engineering improvements since they are our newest trade secrets, but these new designs, engineering and process improvements are being incorporated into our new B Sample cells. With regard to manufacturability, we operated 3 A Sample lines last year. It's important to highlight that we built more large automotive lithium metal cells per month in just one line in 2023 than during all of 2022. This was made possible thanks to significant improvements in white with thin lithium metal anode production and anode electro punching and stacking.

Speaker 2

We made the right decision to move lithium metal anode production in house. We were able to resolve issues associated with tear, wrinkle and powders much more efficiently. By consistently producing a large quantity of large automotive lithium metal cells, we generated a large amount of data that we fed our health monitoring and incident prediction avatar AI model. Prior to 2023, our avatar AI prediction accuracy was 60%. By the end of 2023, we are pleased to announce that we achieved 92%.

Speaker 2

This is important progress. The combination of greater number of cells and greater number of quality control checkpoints per cell was instrumental to the training of our Avatar AI model, making that more accurate. Our training data increased 10x from 2022 to 2023. We are confident that with more data training and advancement in AI model, we will achieve 95% incident prediction this year and eventually reach near 100% safety guarantee. In 2023, we also laid the foundation for using AI for future roadmap electrolyte development.

Speaker 2

The goal is to build a roadmap for future generations of liquid metal. Now switching to our 2024 plans. We expect to make further progress in automotive commercialization of lithium metal in 2024, and we will focus full steam on our EV B Sample JDA. We plan to further boost our cell engineering and process development efforts. We'll continue to improve cell practical safety and manufacturability.

Speaker 2

We plan to build and operate these sample lines with our JDA partners, potentially one at our own facility and another at our JDA partners' facility. These these sample lines will incorporate our latest cell design and engineering as well as manufacturing process improvements. These b sample lines will also have our latest production quality control plan. We will increase from about 600 checkpoints to about 1500 checkpoints later this year, including more imaging based checkpoints such as x-ray, ultrasound, CT and vision. All of these will be fully integrated with our Avatar AI model.

Speaker 2

This means the amount of training data for AI model will significantly increase in both quantity and quality. We expect our Avatar AI prediction accuracy to reach 95% for large automotive sales by end of this year. Avatar AI can reach near 100% incident prediction with sufficient data training. This is very different from today's lithium ion quality data, which are still largely based on traditional statistical analysis And the manufacturing data are decoupled from real world vehicle data and very basic models are used to predict incidents. That's why we still have lithium ion battery incidents that cost 1,000,000,000 of dollars in recall.

Speaker 2

Our Avatar AI applies a far more advanced AI model that is pre trained on both lithium metal and lithium ion data, and we have access to a comprehensive set of material chemistry data, manufacturing quality data and real world vehicle data. We can achieve near 100% safety guarantee. This near 100% safety guarantee is extremely important for automotive applications and is only possible with advanced avatar AI. On the use of AI for roadmap electrolytevelopment, our amazing team of human scientists and AI scientists will work together to systematically study electrolyte chemical structures from public and internal database. We're very excited to report that we will commission our new electrolyte foundry in Massachusetts to focus exclusively on high throughput synthesis and testing of both human and AI generated electrolyte solvent and salt chemical structures.

Speaker 2

This is a super exciting area. Some pharmaceutical companies have already demonstrated promising signals using similar approach. However, we are the very first to go this deep in the battery industry and the signals are very inviting. We know we can accelerate the screening of novel Elachiflight candidates. Now let's see if we can use AI to develop a new Elachiflight that's better than the best ever human developed one.

Speaker 2

While we focus on automotive commercialization of current generation of lithium metal, this will help us build a robust road map of future generations of lithium metal. In addition to the EV market, we identified urban air mobility, UAN, as a promising and exciting market that is about to take off, especially when powered by high energy density lithium metal batteries. It's significant to note that B Sample for EV is equivalent to commercial production for UAN. For UAN, the energy density and power density of current lithium ion batteries are too low and that results in short flight time and limited payload and number of passengers, making the current UAN business non economical. Lithium metal with about 60% higher energy density will change all that and make UAM a profitable business.

Speaker 2

The leading UAM companies have been waiting for a lithium metal company that can produce high quality, large automotive grade cells. And 2024 will be a key year for the battery design in and qualification. And 2025, we'll see demo flights in major cities such as Seoul, New York City and Abu Dhabi. This is perfect timing for us. We will convert 1 of our ASAMPLE lines in South Korea to produce exclusively UAM cells.

Speaker 2

This will incorporate our latest production quality control plan and be fully integrated with Avatar AI. This line just outside of Seoul will have all the quality and engineering improvements of our B Sample lines, but dedicated to UAM lithium metal cells, modules and Avatar AI development and production. So our 2024 goals will include 3. First is focus on EV B Sample. We will work with our B Sample joint development partners to build and operate new B Sample lines.

Speaker 2

We will improve manufacturing quality control plan from 600 to 1500 checkpoints. 2nd is shipped UAM cells. Our UAM cells will be our 1st commercial products. We will build a dedicated UAM lithium metal line and ship the 1st batch of cells to our UAM customers. 3rd is improved Avatar AI incident prediction accuracy.

Speaker 2

Our ultimate goal is near 100% safety guarantee for EV and UAM applications. In 2024, our goal is 95%. We will finish pre training our Avatar AI with EVA sample data and train with new EVB sample and UAN cell data. These are challenging, but exciting goals. Progress in EVB sample development and shipping the 1st batch of UAN cells will represent major progress in the commercialization of lithium metal batteries for EV and UAM applications.

Speaker 2

Achieving 95% incident prediction accuracy for Avatar AI will represent a major milestone towards the ultimate goal of near 100% safety guarantee, which will be critical for real world safety. In future roadmap material development, we're building an AI super scientist. In cell design and engineering, we're building an AI super engineer. In manufacturing quality and real world health monitoring and incident prediction, we're building Avatar AI. And this information can be used in our supply chain and sustainability management, so we reduce cost and CO2 footprint and built a new supply chain for our EV and UAM customers.

Speaker 2

At SCS AI, our mission is to power a new era of electric transportation on land and in air with lithium metal batteries. As we build more automotive large capacity lithium metal cells, generate more data, expand to B Sample and prepare for C Sample and commercial production, AI becomes an increasingly integral part of both material development and battery health monitoring and incident prediction. Lithium metal not only leads to longer range and more passengers, but near 100% safety guarantee and accelerated roadmap technology development. We realized that we are building more than just a battery company, but the beginning of a super intelligent AI for electric transportation. With that, I'll pass to our Chief Financial Officer, Jin Nialis, for financial update.

Speaker 3

Thank you, Qichao. Good afternoon, everyone. Today, I will cover our Q4 and full year 2023 financial results and discuss our operating and capital budget for 2024. In the Q4, our operating expenses were $17,900,000 down slightly from the same period last year. Stock based compensation expense was $4,400,000 in the quarter.

Speaker 3

We reported research and development expenses of $7,400,000 Our gross R and D spending in the 4th quarter was $16,200,000 which includes $8,800,000 that was billed to our OEM customers and is treated as contra R and D expense. Our G and A expenses were $10,600,000 For the full year 2023, cash used in operations was $56,400,000 and capital expenditures were $15,800,000 We ended 2023 with $332,000,000 in liquidity. Our strong balance sheet will support the company as we maintain on track to achieve our commercialization milestones. For the full year 2024, we expect cash usage from operations to be in the range of $90,000,000 to $100,000,000 and capital expenditures in the range of $20,000,000 to 30,000,000 dollars We expect total cash usage for the year in the range of $110,000,000 to 130,000,000 dollars Priorities for 2024 spending are to attract top talents to support the strategic goals Qichao laid out earlier, Build production capacities to deliver lithium metal cells to our EV and UAN partners and invest in the use of AI for electrolyte material discovery as we stay at the forefront of battery material science innovation. We are very thankful for all the support we have received from our customers, partners and shareholders.

Speaker 3

With that, I will hand the call back to the operator to open up for questions.

Operator

We will now begin the Q The first question comes from the line of Winnie Dong with Deutsche Bank. Please proceed.

Speaker 4

Hi. Thank you so much for taking my questions. First is a clarification. It seems like you're now targeting 2 b sample lines. I just want to clarify if this is for 1 JDM partner or if it's like 2.

Speaker 4

I think you've sort of hinted at that in the battery day. And then if you can also remind us what we could anticipate in the B sample process and any time line on with this when it could potentially conclude? Thank you.

Speaker 2

Yes, Winnie, so last year we announced 1 B Sample and then so one and then we are preparing 1 B Sample line for that B Sample JDA. And then we are working with at least one other OEM carmaker to potentially sign a second P sample JDA. And this is why we are preparing a second line. And then later this year, we might end up having 2 B Sample lines and operate 2 B Sample lines. And then in terms of timing, we expect the B Sample development will take about 18 months, so this year, 2024 and until mid next year.

Speaker 4

Got it. Thank you so much. And then I think some of us may not be entirely familiar with the UAMS application and then the developmental process. Then you mentioned on the call that B sample is actually equivalent to commercial production on that front. So I was wondering if you can maybe elaborate a little bit more on that and potentially disclose how many E related partners are you actually working with currently?

Speaker 4

Thanks.

Speaker 2

Yes. Yes, that's a good question. So with EV, you have this sort of cliff basically after B sample and then C sample and then you have to get to at least 10 gigawatt hours, basically from less than 1 gigawatt hour all the way to 10 gigawatt hour. And then if you don't have more than 10 gigawatt hour, then it's really hard for you to get any meaningful commercial contract. But then for UAM, it's different because UAM is actually still in the process of ramping up.

Speaker 2

And then several companies in the UAM, their volume currently are small. We're talking about single digit number of aircrafts per year. So that's actually a very good opportunity for us because then our B sample line, even a fully optimized A sample line, we can produce at least 1,000 cells per month and 1,000 cell is about 2 aircrafts worth of batteries. So per month and obviously considering yields, all that stuff, we can make 1 to 2 aircrafts worth of batteries. That's not very meaningful for EV, but then for UAM, it's actually very meaningful.

Speaker 2

And then we're able to supply to them not only for testing, but then later for FAA qualification, certification as well as commercial because EV is already a big market, which we continue to focus on and that is still the core focus. But then UAN because it's a small market and then it's just ramping up, we can actually ramp up our battery capacity along with UAN ramp up.

Speaker 4

Okay. That's very helpful. And then maybe on the CapEx spending of $20,000,000 to $30,000,000 $1,000,000 for this year, I was wondering if you can delineate how much of that goes into automotive versus UAM? I think also for 2023, you've ended the year with quite a bit lower CapEx than targeted. So, I guess, what do you think you have spent?

Speaker 4

And then if you can also comment on maybe like the capital efficiency and what's driving the much lower spending, that would be helpful. Thank you.

Speaker 3

Yes. Thank you, Winnie.

Speaker 2

I think you'll call it. Okay. Yes, go ahead,

Speaker 3

Jia. So to answer your first question, of this year's guidance, most of the cash is on the EB sample lines. We are going to spend some money to change one of our current e sample lines to be dedicated UAM lines, but that portion of the CapEx is a relatively small portion of the overall CapEx spending. And your second question on last year's lower spending than our guidance, Most of the lower spending is due to just cost control and both on the G and A and some R and D aspect to try to be very prudent with our cash. So a lot of the OpEx part of the saving is permanent.

Speaker 3

And then on the CapEx side, we were pushing out some of the PO process for the B Simple line that Qichao talked about. So that was a timing issue that was pushed out from last year to this year. So we're placing the PO. We're still going through the vendor evaluation process and we'll place the PO for the B Sample line this year. So it's partially timing, but largely permanent reduction on the cost.

Speaker 3

Cal, please feel free to add.

Speaker 2

Yes, Winnie, so the focus is definitely on automotive. And then most of the CapEx this year will be on the building and operation of 2 B Sample lines later this year. And then for UAM, basically, we're just taking an old A Sample line and then converting that to UAM. But the focus, all the development, all the new stuff will definitely take place on the automotive B Sample lines.

Speaker 4

Got it. Thank you so much for taking my questions.

Speaker 1

Operator, are there any further questions on the in the queue?

Operator

Excuse me. Can you hear me?

Speaker 1

Can hear you now. Yes.

Speaker 3

Yes. I can. Yes. We will take the

Operator

next question coming from the line of Sean Severson with Water Tire Research. Please proceed. There are no additional questions at this time. I will pass it back to Cal Pinkleton for any additional remarks.

Speaker 1

Thanks. We did receive a few pre submitted questions by virtue of a questionnaire we made available to investors ahead of the call. And at this stage, we'll take a selected number of the questions which were submitted by investors for our CEO, Chi Chiao Hu. The first question is when will the first commercial battery production be available on the market?

Speaker 2

Yes. I think for UAM, and as we mentioned earlier, UAM is a nice beachhead, a stepping stone to EV. So for UAM, we're targeting first half of twenty twenty five next year. And for EV, we're targeting likely the second half of next year.

Speaker 1

Great. The next question we got from investors ahead of the call is what are the key challenges to scale lithium metal anode in production when it comes to notching and stacking?

Speaker 2

Yes. We actually covered this in previous earnings calls. So the material itself, lithium and especially lithium on copper is quite thin and then quite weak. And if you use conventional processes like laser or metal die punching, you actually don't get very good results. And then you end up with lots of issues like powders or tearing and also making large with very thin lithium foil is also very difficult.

Speaker 2

And then you end up with wrinkles and then we actually worked with several partners and tried different techniques from extrusion, lamination to just coating. And eventually, we actually settled on one process. And then in the early days, we used to have the vendors make it for us, but then we realized it was hard to control the quality. So then we took this in house and then we're able to improve the quality and the product a lot faster.

Speaker 1

Great. And the final question we'll take from the pre submitted questions from investors is, how will you use artificial intelligence to advance battery technology?

Speaker 2

So for us, it's really 2 parts. 1 is to ensure safety. And then anytime you have a new battery technology, especially one that has very high energy density, and then especially you are in B sample and then C sample and then very soon commercial, the consideration around safety becomes quite different. And then we're not talking about just paper safety, but we're talking about can you put this battery inside a car or inside an aircraft and then in actual usage, is it safe? And then also what happens when the worst happens?

Speaker 2

So the use of AI basically by collecting the manufacturing quality data, because also quality is safety, a lot of the issues that happen in quality will directly result in incidents and also collecting actual live vehicle data. Then we can actually predict the incident and then have a very accurate monitoring of the battery health. And then we can actually predict the incidents before that happens. So this becomes really important. And then it's really important to give OEMs the confidence that, yes, it's a new battery technology, yes, it has higher energy density than other battery technologies, but it's actually safe because we can make it safe with the use of this Avatar AI.

Speaker 2

And then the other part is using this for future material development. And then that's when we try to improve performance, cycle life, energy density, safety and then for future road map material development. And this AI really allows us to screen a lot more candidates much faster.

Speaker 1

Excellent. Thanks. I'll turn it back to the operator. Operator, are there any additional questions in queue at this stage?

Operator

Yes. The first question comes from the line of Sean Severson with Watertown Research. Please proceed.

Speaker 5

Hello. Good afternoon, everyone. Try this again. Can you hear me now?

Speaker 1

I can hear you.

Operator

Yes. Hello?

Speaker 2

Yes.

Speaker 5

Okay. Good. All right. Just making sure. Chi Chiao, I was I wanted to talk about the B sample push in 2024.

Speaker 5

And how does that reflect itself in terms of milestones or events over the next 12 to 18 months that are going to be able to provide kind of progress reports and updates. So just trying to understand the news flow and data that comes out of this as you go through this B Sample push?

Speaker 2

Yes. The B Sample itself and entering B Sample itself is a big milestone. It represents a new chemistry lithium metal is no longer in R and D or just early stage engineering development, but it's actually in B sample. And then we are considering a lot from the perspective of the final vehicles. So some of the milestones will include, for example, we are setting up the line then we will begin operating the B Sample lines.

Speaker 2

And then we expect second half of this year, we will have the B Sample lines running. And then in the first half of twenty twenty five, we will have data from the cells coming off the B Sample lines. And then these cells will likely be different from the original designs in terms of product designs. For example, some will have high nickel cathodes for the premium vehicles, some will have LFP cathodes for the economy cars and then also benchmark cost of LFP lithium metal with high nickel lithium ion, just showing that these LFP lithium metal B Sample cells can actually be low cost, but also achieve very high energy density. And then yes, so also in the first half of twenty twenty five, then the quality, the number of quality control points, the incident prediction and then integrating the Speed Sample line with Avatar just showing that the number of cells that we built and the number of quality checkpoints per cell and then the product of the 2, how this increased number of amount of data that we will have access to, how that will help train Avatar and make Avatar more accurate?

Speaker 2

Great. Thank you. So these are the ones that

Speaker 6

are more work.

Speaker 1

So these

Speaker 2

are the ones that are tied together.

Speaker 5

That was kind of my next question was about Avatar and safety as well. How differentiated is this 100% safety goal? When you look at some of the other technologies and batteries out there and we had conversations with OEMs, I mean, is this something that is very unique, you think, to SCS and this goal and to be a realistic goal to achieve versus kind of versus what's out there today for options for OEMs?

Speaker 2

Yes. So the goal obviously is a goal shared by almost all OEMs near 100% safety guarantee. And then this is really important because when you have a car or an aircraft out there, you need to make sure it's safe. So what's unique about SCS is that all this data are actually for lithium metal. And then Avatar AI, any AI that you use is actually quite dependent on the quality of the data.

Speaker 2

And then no one else has the amount of lithium metal data that we do. And the reason actually, we actually don't care about the OEM JDAs. The reason that we build these B Sample lines is to collect more data, is to generate more data. So for us, the B Sample lines are like a mine of data. So no one else has these B Sample lines and then no one else has the quality and the quantity of lithium metal cell data that we do, so that we can use all this data to train this avatar.

Speaker 2

So our data are specific to lithium metal and our avatar is specific to lithium metal. And then so it's unique in the sense that no one else has access to the kind of lithium metal data that we do. So our avatar is most accurate for lithium metal. Now in terms of is this approach unique, it's also unique because even if you look at lithium ion today, most OEMs don't have access to car data, but they won't have access to battery data or most car battery or most battery companies will have access to manufacturing data, but not car data. But then so what you're trying to do is actually integrate the battery manufacturing data with the car data.

Speaker 2

And then this approach is also quite unique. Some larger companies are in the process of doing this, but then because they have a large inertia and then it's quite expensive for them to change so that they have not implemented this approach But so for us, it's unique because we have the highest quality and highest quantity of lithium metal data and also this approach of combining cell manufacturing and also vehicle data.

Speaker 5

Thanks. And my last question is regarding the UAM market and opportunity. Obviously, you seem pretty excited about the opportunities having some commercialization there. Can you help us understand how you think about the market, the development, the commercialization there? I mean, obviously, you're talking about very few units, but going out over the next year or so.

Speaker 5

But why does this make you excited when you look to this as being an important part of SCS's future?

Speaker 2

Yes. So I mean the focus is on EV and all the development that we're doing are not really targeted for UAM, therefore EV. It's just that these batteries actually happen to have very good usage in UAM. And what's exciting about this is there are 2 things. 1 is from the customer perspective.

Speaker 2

So UAM currently, this market doesn't really exist or it's very early stage because without a high energy density, high power density battery, it's not practical. You can only carry 2 people or you can fly 10 minutes, less than 20 minutes. The whole market is not economical. But with lithium metal, so you can carry more people, you can carry more payload and then you can fly for longer, then the business actually becomes more economical. So from the customer's perspective, UAM lithium metal really enables UAM and then that's why it's very exciting.

Speaker 2

And then from our perspective, because once we get designed in, once we go through all the qualification, all the testing, the FAA certification, then this battery this battery pack actually becomes FAA certified. And then you are there, you set the standards for many years to come. So from both the customers' perspective and also our perspective, it's a very good fit. And the volume is small, so we can actually produce using our B Sample lines and also A Sample lines. That's why it's a good fit in terms of the near term.

Speaker 2

Great. Thank you. That's very helpful.

Operator

Thank you. The next question comes from the line of Jed Dorschmeyer with William Blair. Please proceed.

Speaker 6

You have Mark Schuder on for Jed Dorsheimer here today. Qiu Chow, a question for you on the progress of the prismatic cells. That was one of the main takeaways from Battery World. I'm wondering, has there been any more progress there? Any other color on that?

Speaker 6

Anything from the other JDA partners on the prismatic cell?

Speaker 2

Yes. So the prismatic cell, we have made some progress and we plan to update that in second half of this year. And the prismatic cell is actually for 1 of the B Sample JDA partners. So they use the combination of LFP lithium metal in the prismatic format. We have more updates later this year.

Speaker 6

Okay, great. Thank you. Next, switching gears a bit to UAM, you talked about a 60% increase in energy density versus the incumbent. So if I take around 700 watt hours per liter for traditional cells, which is a rough benchmark, are you looking to target over 1100 watt hours per liter for these cells? Is that a target you need for that B sample line that's converting to UAM?

Speaker 2

Right. So the current lithium ion, we're talking about 7 20, 7 50 watts per liter and then 260, 280 watts per kg. So for the UAN cells, we're targeting at least 440 and higher watts per kg and 1100 to 1200 watts per liter. So these will have very high energy density at the cell level.

Speaker 6

Okay. And are there the latest 100 amp hour data was around 8 60 watt hours per liter. So are there what are the puts and takes there? Is that just general materials improvement? Or can you make trade offs versus cycle life to achieve that?

Speaker 2

Right. So the UAM will not use the exact same cell design as the 100 ampouered A Sample cell. So the A Sample and the B Sample EV cells, those are designed for long cycle life and then EV cycling conditions, typically SILVER 3 charge and discharge, 3 hour charge and discharge. But then for UAM, then the cell designs will be different because we're going to target much higher energy density and then the charge and discharge profiles will be different. We're going to use relatively slower charge or battery swapping.

Speaker 2

This is one business model that we are actually discussing with several UAM customers and also the UAM discharge profile. So takeoff, climbs, cruise, design and landing and also the depth of charge and discharge are different. So because of the difference in the UAN mission profile and EV mission profile, we will design the cells differently. So the materials will still be the same, but then for example, cathode loading, thickness of lithium, the cell design will be different.

Speaker 6

Got it. Thank you very much.

Speaker 2

Thank you.

Operator

Thank you. There are no additional questions left at this time. I will hand the back to Cal Pigotton for any closing remarks.

Speaker 1

Thanks. I'll turn it over to Qiu Chow for any closing remarks before we end the call.

Speaker 2

Yes. Thanks, Carl. Yes, so basically, I just want to reiterate the 3 main focus for us. 1 is absolute focus on EV B Sample JDA. We signed the world's first and we expect to sign more later this year.

Speaker 2

So the EV B Sample and B sample lines will be critical to improve our manufacturability and also generate more data. 2nd is we identified UAM as a stepping stone EV and then we're going to deliver the 1st batch of UAM cells this year. And then third is we'll try to achieve near 100% safety prediction. And this year, our goal is 95%. And then we really want to improve the quality and quantity of our lithium metal cell data, both testing data as well as the manufacturing quality data.

Speaker 2

So these are the 3 focus and then I'm really excited about this year. And as we continue to make progress towards commercialization of lithium metal for EV and UAM and also integrate the use of AI as a core part of SCS. Bill? Thanks.

Powered by Quartr

Key Takeaways

  • We achieved the world’s first automotive B Sample joint development agreement for lithium metal batteries with a major automaker, marking a milestone toward EV commercialization and driving focus on delivering EV B Sample lines in 2024.
  • SCS AI has identified urban air mobility (UAM) as a high-growth application for lithium metal, targeting demo flights in major cities by 2025 and converting an existing A Sample line to ship the first UAM cells this year.
  • Our Avatar AI battery health-monitoring system improved incident prediction accuracy from 60% in 2022 to 92% in 2023, with a 2024 target of 95% and the ultimate goal of near 100% safety guarantee for EV and UAM applications.
  • In 2023 we reached Hazard Level 5 safety for large 50–100 Ah cells through cell engineering breakthroughs and significantly ramped up in-house lithium metal anode production to drive manufacturability.
  • SCS AI ended 2023 with $332 million in liquidity and plans $110–130 million of cash usage in 2024 to fund B Sample line build-outs, the dedicated UAM cell line, AI development and talent recruitment.
AI Generated. May Contain Errors.
Earnings Conference Call
SES AI Q4 2023
00:00 / 00:00