I am 32 years old and from Ramat Gan. I recently got married in a beautiful celebration with friends and family. I have a BSc in electrical and electronics engineering from Tel Aviv University, and I am almost finished with my master’s degree. I also love sports, and exercising helps me balance my type 1 diabetes.

I have been working at Nova for about five and a half years and currently, work as a system engineering team lead as part of the Elipson project. I started at Nova in 2017 as a student in the CTO team during the first stages of the project. At the time, we could only imagine that it was possible to make RAMAN technology commercially viable–one that could work outside of the lab and create exceptional value and benefits for our customers.

What exactly do you do as part of your job?

I manage a team of system engineers, and we are expected to be experts on the Nova Elipson system. We are responsible for developing new features for the system, improving its stability, making sure it works well according to customer’s requirements and solving the challenges that the service team brings to our table. In addition, we support all the other entities that work on the product, hardware, optics, and software, as well as the service people and product managers.

When additional customer needs arise, we come up with concepts for solutions, prepare and perform feasibility analyses for them, and eventually create requirements documentation for the hardware or software teams, defining what they need to develop.

How do you manage to maintain the level of enthusiasm after being here for five and a half years?

Simply put, my work keeps me engaged and interested. Over the years, everything here has been very dynamic. The project matured and moved departments, and I matured and moved with it and eventually got promoted. This type of environment suits my personality and character. I like change, and things here change all the time—the perfect fit for me.

When I started working at Nova as a bachelor’s student in electrical engineering, I worked in the CTO team on the Nova Elipson project. It actually started as a prototype, and then we progressed to the alpha and beta stages, eventually producing it as a live commercial product.

Today we are already at an advanced stage, and the production and service teams are operating more or less independently. So, the challenges I face are constantly changing, creating the dynamic environment I enjoy.

You mentioned sports earlier. You have another line of work that is related to this, right?

That is true! Before I started working at Nova,  between my military service and college, I was looking for a job, and my girlfriend (now my wife) suggested that I sign up for a basketball refereeing course. I liked the idea, but then I realized that I was more interested in soccer refereeing because it’s a sport that I live and breathe and am incredibly enthusiastic about. I completed a course, and at the beginning of my soccer-referring journey, I refereed games for young children aged 10-12. I gradually progressed to my position today as an assistant referee in the Israeli Premier League and a FIFA international assistant referee in Europe.

Since I have had diabetes since childhood, regular physical activity helps me balance my sugar levels. At every game, I have candies in my pocket in case my blood sugar levels drop.

And what are your goals for the future in this field?

I aspire to reach the top, as I’ve always aspired to reach the highest level in everything I do.

My ambition is to continue improving and working as a referee in the leading games in the Israeli Premier League and advance as far as possible in Europe.

Amazing! Do you see yourself at some point working only in this field?

No! I really enjoy this combination of the two worlds together, which are the two worlds I really like. I think the variety helps me succeed in both of them separately. Being a football referee and working as an engineer at Nova reinforce each other. At the most basic level, when I have a bad day, either at work at Nova or refereeing a bad game, I tell myself that I have the other job to cheer me up. That reminds me everything will be fine.

Being a referee also keeps me fit, which contributes to my health. On the other hand, working at Nova helps to keep my mind sharp. It allows me to constantly learn new things and evolve as a professional in the field of science, engineering, and technology, so it also keeps both my mind and body sharp.

How do you deal with having to travel a lot?

Both of my careers require travel, and this year was a little complex as I needed to travel quite a bit for Nova and for soccer.

On one occasion, I had a series of three flights to games in Europe, and then I flew to the USA on behalf of Nova. After that, I only wanted a little time to rest without traveling. But in the end, it’s an interesting experience. I get to experience new places and meet interesting people, so it is for the best. At Nova, they support my second career, so I’m able to combine both my passions.

How do your friends react to you being a soccer referee?

Everyone is very supportive and encouraging, and I really appreciate it.

Occasionally people recognize me from the stands or I get a close-up on TV during games, and then I immediately receive lots of supportive calls and messages. It’s funny because, in practice, I’m not part of the game–in my opinion, I’m a function of the game. My goal is to keep the game fair, honest, and professional.

 

 

Performing these measurements in the semiconductor fab, rather than in a cost-and-time intensive laboratory setting, provides faster results, which reduces scrap and improves yield.

First, what is the Nova Metrion®? 

The Metrion® is a SIMS tool. SIMS stands for Secondary Ion Mass Spectrometry, a technique widely used in the semiconductor industry to study material composition and depth profiling of semiconductor wafers at the atomic level. To accomplish this feat Metrion determines the concentration of various chemical species vs. distance from the surface of an IC wafer film by sputtering the surface of the wafer, capturing and analyzing the secondary ions.

Conventionally, SIMS equipment has only been available in metrology laboratories that specialize in measuring and characterizing semiconductor devices. In keeping with Nova’s ‘lab to fab’ philosophy, the Nova Metrion® has been intentionally designed to be used in-line in high-volume manufacturing (HVM).

Let’s examine the Metrion SIMS process in more detail.

Metrion SIMS uses an oxygen primary ion beam to sputter a small area on the surface of a silicon wafer. As this primary ion beam sputters through the material on the wafer film, secondary ions are ejected from the surface and are collected and analyzed by a mass spectrometer, which sorts the ions based on tiny differences in their weight.  The Metrion’s mass spectrometer utilizes multiple detectors to sort the ions, and the raw data is displayed in a compositional profile showing counts of the secondary ions versus the time frame in which they are detected.  Using film analysis software that is built into the Metrion process recipes, the data is quantified, converting counts into concentration and collection time into depth for each measured species.

Another key feature of Metrion is the ability to create maps of entire 300mm wafers with as few as 5 measurement points.   These wafer contour maps provide a useful visual representation of within-wafer and wafer-to-wafer uniformity differences.

The numerical data from Metrion is collected and automatically uploaded to the factory host computer where it can be used by fab technical personnel to tune their semiconductor manufacturing processes through a complex mathematical technique called Statistical Process Control. This technique can generate insights that allow users to optimize costs, time, and product yield. By using Metrion as a prevention-based real-time quality control measure, fab personnel can detect trends or changes in their manufacturing process before these result in non-conforming products or scrap. 

Why is semiconductor material composition so important?

As the requirements for modern electronic equipment become more complex, semiconductor chips and therefore the films built onto silicon wafers must become more complex as well. Two important types of semiconductors that vary significantly in composition and structure are logic semiconductors (used in data processing) and memory semiconductors (used in data storage). SIMS measurements performed by Metrion can help identify problems with both logic and memory production processes.

Let’s review how Metrion treats both logic and memory structures built onto wafers.

Logic structures for data processing are challenging to implement on silicon. In particular, the uniformity of the SiGe epitaxial layer is critical (epitaxy is the deposition of a thin layer of single-crystal material, in this case, a compound of silicon and germanium onto the surface of a silicon wafer). Besides SiGe epitaxy and residue control, other semiconductor composition priorities for logic chips include the precise control of dopant concentration, reactor matching, and process excursion prevention.

Semiconductor memory structures have generated significant manufacturer interest to control contamination and identify unwanted chemical residues that could reduce yield. Here, the power of SIMS to detect contamination throughout the entire device, and not just at the surface, is key. Other important SIMS functions include semiconductor material composition and thickness measurements, to improve device function.

By looking at potential diffusion, Metrion users can anticipate problems with barrier layers and source/ drain function. The deposition uniformity within wafers and from wafer to wafer is also important because this affects downstream fabrication processes. Insights in these areas provided by SIMS help to improve device performance, reduce scrap, and increase yield.

These are the main advantages of SIMS, which is used widely in metrology labs.   However, lab SIMS turnaround time is too long, meaning that the data coming from the lab SIMS measurements takes too long to translate into manufacturing process control improvements, which puts many wafers at risk. Let’s look at this in more detail.

For a lab SIMS service provider, turnaround on wafer measurements can take up to two weeks.  For an in-house metrology lab at a semiconductor production facility turnaround could be as short as one day, depending on the number of samples to be measured.  However, time-to-results at such a producer lab could suffer if the production team required a quick result. Also, if the producer lab tool goes down, SIMS results could take months to obtain. One solution is to integrate a SIMS tool such as Metrion directly into the semiconductor production line, something it would be impossible to do with a lab tool. 

What is the value of inline SIMS?

Laboratory SIMS systems only measure coupons, not full wafers.   Wafers must be broken into coupons resulting in scrap.  A single point is measured on each coupon.  A SIMS expert is required to manually set up each measurement and to analyze the data point by point. This whole process can take days (or weeks as just discussed).

Nova Metrion®, on the other hand, measures whole wafers and is fully automated.  Metrion fits seamlessly into the production line,  accepting wafers from the fab’s automated transport system, loading them into the Metrion measurement chamber, measuring the wafers, providing full profile data and wafer mapping, and automatically uploading the data to the factory host.  All this can be done within minutes. The real advantage of an inline Metrion SIMS system, then, is that the shorter time to data results in tighter process control and improved yield.

Figure 2 illustrates this point. In a fab with 50,000 wafer starts per month, and a turnaround time for SIMS data of 2 hours, less than 200 valuable wafers will be placed at risk. But if it takes 24 hours to get the SIMS data back from a lab, the number of wafers at risk increases dramatically to 1600. The key point here is that the faster the time to obtain results with Metrion SIMS the more wafers are saved and therefore more money is saved by improving yield.

Figure 1: Wafers at Risk by Hour for 50K Wafer Starts per Month (WSPM)

Not all the wafers have to be scrapped, so let’s imagine a scenario where there is a 3% yield loss due to some problem in the manufacturing process and, further, that this problem is identified by SIMS.

How much would a 3% increase in yield save a fab in one day?  Would it save the fab $500, $5,000 or $50,000? (our assumptions are that the fab has 50,000 wafer starts per month and the cost per wafer is $1,000) The answer is that a 3% yield increase could save a fab $7,500 in a single day, a significant amount.

Now let’s imagine that a catastrophic event occurs where all of the wafers at a certain process step are lost, or if  50% of the wafers in a deposition step are lost. That’s going to have a huge financial impact.  

Why can’t these savings be achieved by inline metrology today?

There are in-line solutions available, such as LEXES (Low energy Electron Induced X-ray Emission Spectrometry), Ellipsometry, 4-point probe, and XRD (X-Ray Defraction).  But these techniques have to be correlated. In other words, no single metrology option exists that will provide a comprehensive picture of what is happening on the wafer.

Nova Metrion® can replace these in-line metrology options because it performs direct measurements of material composition through the entire wafer stack.  Metrion also produces full wafer maps of thickness and uniformity based on several points across a wafer. Additionally, the data is automatically uploaded to the factory host for statistical process control.  

What makes Nova Metrion® unique?

The Nova Metrion® includes several key features that make it well-suited for high-volume manufacturing.   For example, Metrion uses an oxygen ion beam, which is fast, contamination-free, and safe for use in production.

Metrion uses multiple ion detectors, which enable multiple chemical species to be measured simultaneously. It also delivers superior depth resolution and higher data density.

Additionally, Metrion utilizes multiple modes of operation to detect a broad range of species through complex stacks, including dielectric layers.

To reduce the impacted measurement area on a wafer, Metrion utilizes a small, die-sparing raster zone, enabling SIMS measurements on product wafers without damaging valuable dies.

Lastly, the Metrion is fully automated. Offering much more than automated wafer handling Metrion has built-in film analysis recipes, recipe management, factory host communication, and compatibility with automated wafer transport.

Why is contamination from SIMS a concern?

The ultimate goal for Metrion is to measure product wafers and then feed those same wafers back into the production process, without impacting yield.

A contamination study using a Nova VeraFlex® XPS system was recently completed. The goal was to determine if Germanium ions redeposit on the surface of a wafer as a result of a SIMS measurement.

While the XPS system did pick up Germanium in the sidewall of the crater produced on the wafer surface by the SIMS primary ion beam (which is what we would expect because we’re exposing some of the SiGe layer on the edges of the crater), there was no Germanium detected in any of the other locations, including the crater center.

The conclusion from this test was that no Germanium ions were redeposited on the wafer surface during the SIMS measurement. Therefore, the Metrion did not cause any contamination and should be considered safe to use on product wafers.

What is the meaning of full automation?

Full automation means more than just wafer handling with an EFEM (Equipment Front End Module) transfer system. It includes pattern recognition to locate a specific measurement area on a pattern wafer,  wafer transport, tool recipe management, and factory host communication for statistical process control.  These built-in standard features enable Metrion to be used by a trained operator, rather than an experienced SIMS scientist in a laboratory setting running the film analysis on the tool.

The Nova applications team develops what are called recipes in the Metrion system.  Those recipes include the film analysis and quantification, which can be set up to run automatically by the trained operator simply and quickly.

Lastly, we have automated tuning and calibration as discussed in the previous section.

All of these things equal full automation.

What is the value of full automation offered by Metrion?

It is true that fully automated systems like Metrion cost more than manual lab SIMS systems, with higher maintenance costs as well.

However, a common misconception is that capital equipment expenses and maintenance costs are the biggest drivers of ownership costs.  Rather, the largest components of the entire cost to own a metrology tool like Metrion are consumables costs and uptime.

Fully automated systems have much higher availability than manual systems, usually 90% or higher.  Manual systems typically have 50% or even lower availability.

And these are generous assumptions because of the manual adjustments required to set up a lab SIMS, including beam alignment, magnet settings, and switching between oxygen and cesium sources.   These manual procedures, taken together with manual film analysis, can take two to four days on a lab SIMS, resulting in significant tool downtime.  A fully automated system such as the Nova Metrion® has much higher availability.

We still need to factor in labor costs.

The Metrion has lower labor costs than manual laboratory systems because SIMS experts are not required to run the system. Also, the automated recipe management means that measurement jobs can be set up to run on their own.  An expert operator is not needed to attend the tool 100% of the time.

The Metrion sample measurement recipes can be loaded remotely through the factory host.  And the numerical data resulting from the measurements is automatically uploaded to the factory host upon completion of a job.

Compared to a manual laboratory SIMS, then, the Metrion demonstrates higher productivity.

So, what does this mean? It means that the Metrion potentially has a 20% lower cost of ownership compared to laboratory SIMS systems. With such advantages, it is clear why semiconductor fabrication facilities could benefit from Nova Metrion® SIMS.   

How does Nova Metrion® achieve better depth resolution than lab SIMS and why is it important?

Now we’re going to review some of the data we have generated with the Metrion to explain its technical advantages.

Lab SIMS typically have a single detector.  To collect data on multiple species during a single data acquisition run, the detectors must undergo a mass switching cycle.  This means that some data will be missed because data can only be collected on one species at a time.

Metrion detectors monitor the species of interest continuously during the acquisition, resulting in higher data density and better depth resolution.

Why is a small analysis area important?

Recall that the goal for Metrion is to measure product wafers inline.  For this to be viable in HVM, Metrion must be able to measure within a 50µm x 50µm² metrology pad or scribe line.  This die-sparing SIMS measurement strategy limits damage to the wafer and preserves as much of the wafer as possible so that usable die can be built on the remaining surface.  Minimizing the analysis area also reduces the data acquisition time.

By comparison, the minimum measurement area for most lab SIMS is 150µm x 150µm². Therefore, measurement runs take longer than with Metrion, data acquisition times are longer, and damage to the on-wafer die can occur. All these add to the total cost of ownership.

Summary: Why is the Metrion important?

Metrion provides wafer-level SIMS data that semiconductor manufacturers can rely on for high-volume manufacturing SPC. Metrion provides fully automated hardware and measurement sequences, with recipe-driven to support 300mm wafers. HVM worthy, Metrion provides convenient fab connectivity for SPC. Metrion offers high throughput, accuracy, and repeatability with a robust algorithm suite for material information analysis.

Metrion is only one part of Nova’s growing product portfolio.  The critical metrics that all fabs must monitor include composition and thickness, homogeneity, uniformity, as well as strain, and crystallinity.  Along with Metrion, Nova offers a full suite of products for materials metrology to quantify these metrics. The Nova VeraFlex® system is optimized for composition and thickness measurements, Elipson was designed to measure strain and crystallinity, and Metrion measures materials composition, uniformity, and thickness.

Creating and supporting such a complex and extensive product portfolio requires a substantial team effort. For example, the Metrion product team, comprised of scientists, engineers, production experts, and support personnel spent many hours together to make Metrion a success. And customers appreciate the effort.

In the second part of this blog post, we explore some widely applicable use cases where Metrion solved critical customer wafer fab issues successfully.

Give us a little background about yourself

I’m Ayelet Sapirstein, an algorithm developer at Nova. I joined the company six months ago after working at several startups in the field of computer vision and machine learning. I have a bachelor’s in math and computer science from Ben Gurion University and a master’s degree in computer science from the Hebrew University, Jerusalem.

From your background, it sounds like Nova is a bit of a change for you professionally

Yes, I agree. I feel like I made a huge leap professionally when I joined Nova. The majority of algorithm experts here have a background in physics, actually, most of them have a Ph.D. in physics, and that was a challenge for me at first. But now, I can see that there are numerous benefits to my background in computer science, and I contribute fresh new perspectives to the team. I quickly learned that each field of expertise has its advantages.

Working with people who studied physics and the way it’s applied to physical products is a big difference from my training, and I’m intrigued by it.

What helped you feel welcome?

The team! Everyone here is so supportive.  My onboarding mentor helped me immensely during my transition to this new role which made me feel comfortable as a new member of the Nova team.

During the onboarding process, I was introduced to each of my team members, as well as to other teams. I received both a personal and professional introduction. This was helpful, giving me a full picture of how each person fit into the larger Nova puzzle.  Because of these introductions early on, I had a good grasp on how everything and everyone was connected, so I felt more confident determining who I should turn to when I needed my questions answered. Learning about each team member’s unique point of view on the product, technology, challenges, and solutions also gave me a broad organizational and functional perspective, which supported my acclimation at Nova.

So now that you’re six months in, how do you feel about working at Nova?

The first thing that struck me is that the algorithm team is comprised of almost 50% women. I’m inspired daily by so many women in my team. It’s refreshing to work with people I really appreciate both on a professional and personal level. This is real girl power, and I have a lot of role models here, which is something you don’t always see, especially in the science and tech fields.

What would you say is your superpower?

My creativity, especially through art. For example, I once completed a series of paintings that I called: Portrait of a Mathematician. The paintings applied the mathematical theorems that mathematicians developed. It actually started out as a joke. I took a drawing class where we were given an exercise to draw something without taking our hands off the page. There’s a mathematical theorem called the Euler method, which basically says which line drawings you can create using each edge of the graph only once. With this method in mind, I thought, “well, I can create a painting analysis by thinking ahead, planning, and drawing something in one line.” So, I made a portrait of this mathematician using one continuous line, meaning I never took my hand off the page.

After I successfully completed this painting, I thought about other mathematicians I could draw by applying their theorems. And that’s how I started. And when I posted my work on Facebook, my friends suggested ideas, and I created several additional portraits.

One day I saw a call for mathematical drawings for an exhibition, and I sent in my work. The curators of the exhibition saw it and told me how I can improve them and make them more suitable for the exhibition. So, I worked on upgrading them and they were exhibited!

That is amazing!  

Yes. And then I even created a lecture about it.

Have you been painting since childhood or is it something you picked up over the years? 

It’s something I picked up when I was around 27 years old after I took a course. My parents encouraged us to take up science and sports. They didn’t really encourage us to pursue the arts at all, so I had never really done it. I was pretty much taught that you either have talent or you don’t. But then, from the people around me I learned that it’s a bit more complicated than that. They showed me that to be a successful artist, you have to work at it, and it’s not about being born gifted. I started with a drawing class, and I realized very quickly that I wanted to draw my ideas instead of trying to copy reality, so it evolved into creating illustrations.

Talent is not something that is innate or that you’re necessarily born with. You can learn things and enhance your skills. Practice is the key to getting better. This is an approach I’m trying to embrace in all I do, as it represents a growth mindset.

What are you working on now?

I’m involved in a project that pairs elementary school students with illustrators. The students make up a monster–they either draw it or compose a description of the monster, and then the illustrator draws the monster. I’m now working on a monster, and I’m looking forward to meeting the kid creator. 

As a child, did you know that you would study computer science, or did you have other dreams?  

When I was young, I thought I would be a psychologist when I grew up.

When I was young math came easy for me, yet I did think of studying psychology at college. But then, in my early twenties, I met a friend who studied math, and he encouraged me to do the same. I was intrigued, so I took one math course. This opened a whole new world to me.

I loved the challenge that came with math. There were some difficult problems to solve, and sometimes it would take hours, but then there was an AHA! moment where suddenly things connected, and I cracked the puzzle. The moment it all comes together–that to me is a moment of creative inspiration, and it’s so much fun.

You are a member of the Baot Online community. What part did it play in your life? 

Baot is the largest Israeli community of women software engineers, data scientists, and researchers in the tech industry. Baot offers women developers professional assistance and promotes women developers in their careers. It’s a very authentic approach created and run by women who understand exactly what other women are going through because they were in the same place not long ago.

Baot also helps its members create their own personal and professional brands through writing professional blog posts, attending conferences, and lecturing at conferences around the world. They encourage us to pursue our dreams and provide us with inspiration to create new ones.

I received their support when I was looking to make a career change, and they actually introduced me to Nova, for which I’m grateful. Now it is my turn to pass it on, and I am mentoring women in Baot in their job search.

Computer chips are in the news today because they are in short supply, which is causing widespread global disruptions   Why can’t we just manufacture more chips?

The short answer is that making computer chips is incredibly complicated. Chip fabrication facilities are running full blast, but that still isn’t enough to satisfy the voracious global demand. There are few manufacturers capable of meeting the soaring demand for highly advanced chips, and these suppliers were caught off guard by the massive global pandemic-driven surge in demand for more computer processing power.  With millions of products from cars to smartphones to washing machines reliant on these postage stamp-sized computing powerhouses, entire end-product production lines had to come to a standstill and legions of consumer products became unavailable.

What exactly is a computer chip?

A computer chip is a packaged set of electronic circuits printed onto a thin, circular wafer made of the element silicon, one of the most abundant elements in the earth’s crust. These electronic circuits work with the help of transistors, which serve as tiny switches that turn an electrical current on or off. These operations are the basis for all modern computing.

The first commercially available computer chip was the Intel 4004 microprocessor, released in 1971. It consisted of 2,300 transistors and was one of the first to use silicon gate technology, which made it possible to increase the circuit density fivefold compared to previous computer chips.

By comparison, Intel’s 12th-generation i9-12900K CPU contains 3 billion transistors, each one only 7 nanometers in width (a nanometer is one billionth of a meter). Apple’s M1 Max chip, developed for the MacBook Pro, is even more impressive, containing 114 billion transistors built on the 5-nanometer scale. That’s about one-fourth the size of the smallest viruses- only 50 times larger than a single hydrogen atom!

Computer chips serve a variety of different purposes, but they broadly fall into four categories. There are microprocessors (also known as central processing units or CPUs), memory chips (used for short-term storage of digital data), graphical processing units (GPUs), and commodity integrated circuits (CICs) used in single-purpose appliances such as barcode scanners.

How is a computer chip made?

Silicon is the chief ingredient in all modern computer chips because of its ability to act as either a conductor or an insulator of electrical current.  Silicon is also readily available and extremely cheap, since it is the main ingredient in beach sand.

While we often hear about the ongoing shortage of silicon, what we really mean is the shortage of silicon chips. There are very few manufacturers with the capacity to build silicon chips at the incredibly small nanometer scale, and this production challenge is only growing as these chips get smaller every year while the demand for them continues to explode.

Manufacturing tools like precision lathes and 3D printers can create intricate designs, but they become ineffective beyond micrometer levels of precision. This makes them unsuitable for assembling computer chips.

Because their transistors and interconnections are so small, computer chip manufacture requires a process known as photolithography, which uses light to etch images onto a silicon wafer coated with a photo-resistant material. Once a schematic of the chip has been etched onto the silicon, the etching is filled with various metals and then doped to create transistors. Doping is a process that adds precise levels of impurities such as boron, aluminum, indium, arsenic, or antimony to the silicon to alter its electrical properties and create the minuscule components of a computer chip.

This photolithography process can be repeated many times to create multiple layers of electronic components on the silicon wafers. Modern chips may have many dozens of layers to fit as many transistors as possible into the smallest possible space. However, there is a tradeoff between the growing number of component layers and the increasing amounts of heat they generate, because too much heat will cause degradation of computing performance.

Once all these layers are complete, the chip must be thoroughly tested to ensure that it conforms to its design requirements. The term Yield refers to the percentage of chips that pass these tests and, as a result, aren’t discarded or downgraded to conform to lower specifications. Depending on the manufacturer, a yield of at least 90% is considered ideal.

After fabrication, the silicon wafers are transformed into usable computer chips. To accomplish this the wafers are sliced into small units called dies, which must then be packaged to create a computer chip. The tiny postage-stamp-sized die are individually attached to a substrate equipped with electrical connections and the entire assembly is then encapsulated. The electrical connections, which come in a variety of types, connect the computer chip to the rest of the computer system once it is installed in a CPU socket, memory slot, or another interface in a computer or other digital device.

Naturally, the entire computer chip manufacturing process must occur in a clean room engineering space, since even the tiniest microscopic contaminants can immediately ruin the chips being produced. After all, the level of precision required is many orders of magnitude smaller than the human eye can perceive.

Which companies make computer chips?

The world’s biggest chip manufacturers are household names like Samsung and Intel, while numerous other companies manufacture embedded chips for myriad other devices, such as smartphones, vehicles, and internet-connected smart tech.

The semiconductor supply chain broadly consists of three main players:

• Integrated device manufacturers (IDMs) design, manufacture, and sell their own computer chips
• “Fabless” semiconductor firms design and sell chips, but outsource manufacturing
• Pure play foundries manufacture only and sell to the IDMs and fabless semiconductor companies

Bill, can you please introduce yourself?

I went to Taiwan University, and I majored in chemical engineering. My thesis for my master’s degree was in a not very well-known field called: Super Critical Fluid. After graduation I began working at TSMC, which is the world’s largest semiconductor factory. Then I moved to another company that specializes in polyester fibers and that was a big change for me. After a few years, I realized that I am much more interested in the semiconductor industry and here I am at Nova.

Why did you choose to join Nova?

Two of my classmates work for Nova and have strongly recommended that I join. I knew that Nova, with 30 years of industry, maintains a young and exciting atmosphere where the people are kind and respectful to each other.

So, it’s very different from my previous company. It’s a different culture because it is a global company with a multicultural atmosphere. I also heard that the well-being activities are real fun. It’s very funny because I haven’t experienced that before in my previous company since they were a more traditional industry and now I am enjoying the attention and treats. My previous employers focused a lot more on work and not life beyond the job, like making friends at work. So it is a refreshing change. 

How was your onboarding experience so far in the few weeks since you joined Nova?

I have been at Nova for four weeks in Taiwan, and on my fifth week, I was sent to Israel for a month of training. I knew this would happen even before I joined and was excited to travel, learn and experience the Nova spirit. 

What Does your training include?

The purpose of the training is to learn about the physical principles of Nova MARS and how to use software to solve the customer’s problem. 

Are you planning to also travel during your stay in Israel?

Yeah, we have gone to the beaches in Tel Aviv where our hotel is located, and we are planning to visit the Dead Sea, Jaffa, and Jerusalem… Also, our colleagues in the service team have already invited us to have dinner with them, which is a very warm welcome. 

What do you do in your after-work activities?

In Taiwan, I like to go to the gym, exercise, and strengthen my body. And I also enjoy mountain climbing on the weekend because there are lots of beautiful mountains. There are about 200-300 mountains that we could climb in Taiwan. I love to do this with my friend, because I like the isolation from the city, from the work. We have no signal on our cell phones when we enter the mountains, and we take care of each other. I also like to train at the gym to get ready for climbing. Those are two of my main hobbies. And the most important thing, I got married last year. 

Oh, congratulations!

thank you!

An engineering failure in a building, whether at the foundations or in a brick in one of its floors, may lead to the collapse of the whole structure. The same is true for the field of computer chips, except that here the physical dimensions are less than one nanometer – a billionth of a meter. When the cost of every manufacturing error is the loss of billions of dollars, even the slightest component irregularity may disable the entire chip, cause tremendous losses, and disrupt a huge variety of products and services. At Nova, an Israeli company that offers leading inline metrology solutions, advanced hardware and sophisticated software are combined to solve this issue.

Leading semiconductor manufacturers use Nova’s measurement and monitoring systems, to minimize expensive mistakes in the chip manufacturing process. To support the growing demand for higher computation power and larger memory capacities, the Semiconductor development process is becoming more advanced and complex, requiring the measurement techniques to become increasingly more sophisticated.

“We support companies in the development and manufacturing process, conduct experiments, and use the data provided by the customer to form models,” says Dr. Danny Kandel, VP of Technology in the CTO group. “We are often required to develop unique and innovative metrology solutions, to support the development of new advanced integrated circuits. Since we deal with critically small dimension ranges which are difficult to measure, the measurement techniques must combine hardware, advanced algorithms, and machine learning.”

Dr. Danny Kandel, VP of Technology

Kandel is part of Nova’s CTO division, dealing with future technologies and focuses on the effort to solve future challenges in a rapid manner. Dr. Dror Shafir, VP of New Technology, in the CTO division: “for SSD memory chips, for example, we had to develop an optical technology combined with unique algorithms, able to measure complex signals, filter unnecessary data, and noise, and analyze the input aiming to provide an accurate representation to our customers. New innovative algorithmics, combining the conversion of scientific theories with complex mathematical models, were formed in the development process.

How can machine learning help achieve the best results with unique hardware?

The greatest ideas say Kandel and Shafir, arise when experts in different fields in the company brainstorm together. “Our clients require quick solutions for complex problems, and our way of overcoming these challenges is to get physicists, algorithm developers, and software experts to think together.” This, for example, is the reason why Nova started using machine learning as an alternative to traditional physics computations; “the machine learning applications we have embedded improved hardware performance, dramatically shortened the time required for highly-complex problem solution, and simply took over the market.”

The next step would be combining physics-based and machine-learning-based algorithms. “We have in fact created a new type of algorithm with distinct advantages of accuracy and speed, allowing us to solve problems which used to be unsolvable until recently.”  They both affirm that this innovative and creativity-encouraging approach, is deeply rooted in the company’s DNA: “whenever a team member comes up with a good idea, no matter how crazy or expensive it seems to be, everyone – from the CEO to junior directors – tells them to go for it, and it happened more than once. The potential impact of it is huge.”

Software Takes the Front Seat

Nova’s software group in the Dimensional Metrology division works closely with the algorithm, hardware, and system groups, and uses a wide variety of technologies to support the company’s growing product demand. “On the one hand, we offer traditional technologies that are at the core of Nova’s offering, technologies that we are constantly developing. On the other hand, we are adding top-tech software modules to keep up with the rapid development in our industry,” explains Kenny Krupnik, VP of Software in the Critical Dimensions Division, “We work with a wide variety of technologies and each of our development teams can offer a supplementary solution.”

Nova offers solutions of various types: software-hardware combined products dealing with the physical aspects of the metrology process as well as with robotics and communication, big data management products, tool-fleets management, software, and machine learning. “Historically, the chip market has been hardware-oriented, while Nova has an exceptional strategic approach of leading the market through software,” Krupnik adds. “For example, one of our flagship products, Nova Fit, is a leading machine-learning product that plays a major role in allowing Nova to meet its clients’ most strict measurement requirements. Our goal, producing advanced software solutions which will hasten the company’s growth, has proven itself during recent years, as the profit from these products showed significant growth.”.

Dr. Dror Shafir, VP of New Technology

“The chip industry stands is at the core of every other industry,” Shafir says. He states that the more complex the products get, the more advanced the chip and its manufacturing monitoring solutions must get: “we have to reinvent ourselves every time because we can’t just exploit more of the same thing, it just wouldn’t be enough.” Kandel adds: “if you look for challenges and openness to modern innovations, especially in the algorithmics field, with an open and supportive work environment, you will find it here.” And Krupnik sums up: “unlike most of our competitors, Nova’s size is optimal, producing a great combination of a strong, steadily growing company, with a progressive, family-like organizational culture, which allows personal growth and a never-ending technological experience. Things move fast and it’s a fun environment to work in.”