Liu Jia

Credit: Unsplash/CC0 Public Domain

Vertical cavity surface emitting lasers (VCSELs) present the basis for large data rate optical interconnects in data centers. Presently VCSELs have replaced edge-emitting lasers for distances below 500 m due to their advantages such as on-wafer test possibility. The demand for VCSELs and in particular, arrays has most recently significantly increased due to the trend for wavelength multiplexing in data centers and the development of automobile applications like short-range LIDAR.

A recent study published in IEEE Xplore and by the Bimberg Chinese-German Center for Green Photonics, Changchun Institute of Optics, Fine Mechanics and Physics (CIOMP) of the Chinese Academy of Sciences reported progress on novel multi-aperture VCSELs (patented). The development of multi-aperture VCSELs leads to performance advantages such as larger temperature roll-over, larger output power, and larger f3dB (the decisive parameter determining the bit rate of communication). This design was recently presented for the first time at ISLC 2021 in Potsdam, Germany.

The novel design is based on fabricating variable shape oxidized apertures from multiple etched blind holes of any geometric arrangements. After oxidation, the blind holes are filled with metal. The metal-filled blind holes efficiently remove heat from the device and allow low resistance current injection to the active area. Hence the device can operate across a wide range of temperatures and higher frequencies. One mesa may contain one or more emitters still matched to a 50 μm diameter fiber. Moreover, the novel MAVs fabrication process is compatible with the present semiconductor manufacturing infrastructure foundry.

Novel multi-aperture VCSEL demands a complete redesign to realize the final device. Classical VCSELs with a narrow oxide aperture show single-mode emission at discrete wavelength, resulting in small output power. Novel multi-aperture VCSEL design with n number of apertures can produce n number single-mode emission at the same discrete wavelength with n times the output power, lower operating temperature of the active area, larger f3dB, compared with the classical VCSEL design.

Another significant advantage of the novel design is single-mode emission with much increased output power, thereby extending the single-mode communication distance up to a kilometer. Tuning the aperture shape away from a circular shape will result in polarized emission.

Most importantly, single-mode or multi-mode multi-aperture VCSELs will exhibit smaller series resistance (compared with present classical VCSEL). Therefore, it will be easy to drive by novel high-speed CMOS driver circuits. The module's energy consumption is much lower, which is an essential step towards green photonics.

Explore further Optimizing of VCSEL photon lifetime for minimum energy consumption at varying bit rates

More information: Ahamed Mansoor et al, Multi-aperture VCSELs: high power, low resistance, single mode, 2021 27th International Semiconductor Laser Conference (ISLC) (2021). Ahamed Mansoor et al, Multi-aperture VCSELs: high power, low resistance, single mode,(2021). DOI: 10.1109/ISLC51662.2021.9615903

Vertical cavity surface emitting lasers (VCSELs) present the basis for large data rate optical interconnects in data centers. Presently VCSELs have replaced edge-emitting lasers for distances below 500 m due to their advantages such as on-wafer test possibility. The demand for VCSELs and in particular, arrays has most recently significantly increased due to the trend for wavelength multiplexing in data centers and the development of automobile applications like short-range LIDAR.

Researchers propose multi-aperture vertical cavity surface emitting lasers of varying size and shape

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Whispering-gallery-mode (WGM) cavities represent an intriguing platform for intensely enhancing light-matter interaction. It lays the foundations for ultra-low threshold lasers, ultra-sensitive sensing, nonlinear optics and quantum photonics. The conventional WGM cavity is composed of homogeneous materials with a constant refractive index both in the core and cladding. The light field is confined in the cavity through the total internal reflection (TIR) and enhanced through constructive interference. The ultrahigh-Q factor has been realized in various dielectric WGM cavities with a large mode volume (V) and angular momentum.

Researchers propose and demonstrate an optical black hole cavity based on transformation optics

In recent years, heterogeneous computing has emerged as the vital way to increase computers' performance and energy efficiency by combining diverse hardware devices, such as Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs). The rationale behind this trend is that different parts of an application can be offloaded from the main CPU to diverse devices, which can efficiently execute these parts as co-processors. FPGAs are a subset of the most widely used co-processors, typically used for accelerating specific workloads due to their flexible hardware and energy-efficient characteristics. These characteristics have made them prevalent in a broad spectrum of computing systems ranging from low-power embedded systems to high-end data centers and cloud infrastructures. However, these hardware characteristics come at the cost of programmability. Developers who create their applications using high-level programming languages (e.g., Java, Python, etc.) are required to familiarize with a hardware description language (e.g., VHDL, Verilog) or recently heterogeneous programming models (e.g., OpenCL, HLS) in order to exploit the co-processors' capacity and tune the performance of their applications. Currently, the above-mentioned heterogeneous programming models support exclusively the compilation from compiled languages, such as C and C++. Thus, the transparent integration of heterogeneous co-processors to the software ecosystem of managed programming languages (e.g. Java, Python) is not seamless. In this paper we rethink the engineering trade-offs that we encountered, in terms of transparency and compilation overheads, while integrating FPGAs into high-level managed programming languages. We present a novel approach that enables runtime code specialization techniques for seamless and high-performance execution of Java programs on FPGAs. The proposed solution is prototyped in the context of the Java programming language and TornadoVM; an open-source programming framework for Java execution on heterogeneous hardware. Finally, we evaluate the proposed solution for FPGA execution against both sequential and multi-threaded Java implementations showcasing up to 224x and 19.8x performance speedups, respectively, and up to 13.82x compared to TornadoVM running on an Intel integrated GPU. We also provide a break-down analysis of the proposed compiler optimizations for FPGA execution, as a means to project their impact on the applications' characteristics.

Transparent Compiler and Runtime Specializations for Accelerating Managed Languages on FPGAs

Scientists have predicted that by 2040, almost 50 percent of the world's electric power will be used in computing. What's more, this projection was made before the sudden explosion of generative AI. The amount of computing resources used to train the largest AI models has been doubling roughly every 6 months for more than the past decade. At this rate, by 2030 training a single artificial-intelligence model would take one hundred times as much computing resources as the combined annual resources of the current top ten supercomputers. Simply put, computing will require colossal amounts of power, soon exceeding what our planet can provide.

One way to manage the unsustainable energy requirements of the computing sector is to fundamentally change the way we compute. Superconductors could let us do just that.

Superconductors offer the possibility of drastically lowering energy consumption because they do not dissipate energy when passing current. True, superconductors work only at cryogenic temperatures, requiring some cooling overhead. But in exchange, they offer virtually zero-resistance interconnects, digital logic built on ultrashort pulses that require minimal energy, and the capacity for incredible computing density due to easy 3D chip stacking.

Are the advantages enough to overcome the cost of cryogenic cooling? Our work suggests they most certainly are. As the scale of computing resources gets larger, the marginal cost of the cooling overhead gets smaller. Our research shows that starting at around 10
16 floating-point operations per second (tens of petaflops) the superconducting computer handily becomes more power efficient than its classical cousin. This is exactly the scale of typical high-performance computers today, so the time for a superconducting supercomputer is now.
At Imec, we have spent the past two years developing superconducting processing units that can be manufactured using standard CMOS tools. A processor based on this work would be one hundred times as energy efficient as the
most efficient chips today, and it would lead to a computer that fits a data-center's worth of computing resources into a system the size of a shoebox.The Physics of Energy-Efficient Computation
Superconductivity—that superpower that allows certain materials to transmit electricity without resistance at low enough temperatures—was discovered back in 1911, and the idea of using it for computing has been around
since the mid-1950s. But despite the promise of lower power usage and higher compute density, the technology couldn't compete with the astounding advance of CMOS scaling under Moore's Law. Research has continued through the decades, with a superconducting CPU demonstrated by a group at Yokohama National University as recently as 2020. However, as an aid to computing, superconductivity has stayed largely confined to the laboratory.

To bring this technology out of the lab and toward a scalable design that stands a chance of being competitive in the real world, we had to change our approach here at Imec. Instead of inventing a system from the bottom up—that is, starting with what works in a physics lab and hoping it is useful—we designed it from the top down—starting with the necessary functionality, and working directly with CMOS engineers and a full-stack development team to ensure manufacturability. The team worked not only on a fabrication process, but also software architectures, logic gates, and standard-cell libraries of logic and memory elements to build a complete technology.

The foundational ideas behind energy-efficient computation, however, have been developed as far
back as 1991. In conventional processors, much of the power consumed and heat dissipated comes from moving information among logic units, or between logic and memory elements rather than from actual operations. Interconnects made of superconducting material, however, do not dissipate any energy. The wires have zero electrical resistance, and therefore, little energy is required to move bits within the processor. This property of having extremely low energy losses holds true even at very high communication frequencies, where losses would skyrocket ordinary interconnects.

Further energy savings come from the way logic is done inside the superconducting computer. Instead of the transistor, the basic element in superconducting logic is the Josephson-junction.

A Josephson junction is a sandwich—a thin slice of insulating material squeezed between two superconductors. Connect the two superconductors, and you have yourself a Josephson-junction loop.

Under normal conditions, the insulating "meat" in the sandwich is so thin that it does not deter a supercurrent—the whole sandwich just acts as a superconductor. However, if you ramp up the current past a threshold known as a critical current, the superconducting "bread slices" around the insulator get briefly knocked out of their superconducting state. In this transition period, the junction emits a tiny voltage pulse, lasting just a picosecond and dissipating just 2 x 10
-20 joules, a hundred-billionth of what it takes to write a single bit of information into conventional flash memory.

A single flux quantum develops in a Josephson-junction loop via a three-step process. First, a current just above the critical value is passed through the junction. The junction then emits a single-flux-quantum voltage pulse. The voltage pulse passes through the inductor, creating a persistent current in the loop. A Josephson junction is indicated by an x on circuit diagrams. Chris Philpot

The key is that, due to a phenomenon called
magnetic flux quantization in the superconducting loop, this pulse is always exactly the same. It is known as a "single flux quantum" (SFQ) of magnetic flux, and it is fixed to have a value of 2.07 millivolt-picoseconds. Put an inductor inside the Josephson-junction loop, and the voltage pulse drives a current. Since the loop is superconducting, this current will continue going around the loop indefinitely, without using any further energy.

Logical operations inside the superconducting computer are made by manipulating these tiny, quantized voltage pulses. A Josephson-junction loop with an SFQ's worth of persistent current acts as a logical 1, while a current-free loop is a logical 0.

To store information, the Josephson-junction-based version of SRAM in CPU cache, also uses single flux quanta. To store one bit, two Josephson-junction loops need to be placed next to each other. An SFQ with a persistent current in the left-hand loop is a memory element storing a logical 0, whereas no current in the left but a current in the right loop is a logical 1.

Designing a superconductor-based data center required full-stack innovation. Imec's board design contains three main elements: the input and output, leading data to the room temperature world, the conventional DRAM, stacked high and cooled to 77 kelvins, and the superconducting processing units, also stacked, and cooled to 4 K. Inside the superconducting processing unit, basic logic and memory elements are laid out to perform computations. A magnification of the chip shows the basic building blocks: For logic, a Josephson-junction loop without a persistent current indicates a logical 0, while a loop with one single flux quantum's worth of current represents a logical 1. For memory, two Josephson junction loops are connected together. An SFQ's worth of persistent current in the left loop is a memory 0, and a current in the right loop is a memory 1. Chris Philpot
Progress Through Full-Stack Development

To go from a lab curiosity to a chip prototype ready for fabrication, we had to innovate the full stack of hardware. This came in three main layers: engineering the basic materials used, circuit development, and architectural design. The three layers had to go together—a new set of materials requires new circuit designs, and new circuit designs require novel architectures to incorporate them. Codevelopment across all three stages, with a strict adherence to CMOS manufacturing capabilities, was the key to success.

At the materials level, we had to step away from the previous lab-favorite superconducting material: niobium. While niobium is easy to model and behaves very well under predictable lab conditions, it is very difficult to scale down. Niobium is sensitive to both process temperature and its surrounding materials, so it is not compatible with standard CMOS processing. Therefore, we switched to the related compound niobium titanium nitride for our basic superconducting material. Niobium titanium nitride can withstand temperatures used in CMOS fabrication without losing its superconducting capabilities, and it reacts much less with its surrounding layers, making it a much more practical choice.

The basic building block of superconducting logic and memory is the Josephson junction. At Imec, these junctions have been manufactured using a new set of materials, allowing the team to scale down the technology without losing functionality. Here, a tunneling electron microscope image shows a Josephson junction made with alpha-silicon insulator sandwiched between niobium titanium nitride superconductors, achieving a critical dimension of 210 nanometers. Imec

Additionally, we employed a new material for the meat layer of the Josephson-junction sandwich—amorphous, or alpha, silicon. Conventional Josephson-junction materials, most notably aluminum oxide, didn't scale down well. Aluminum was used because it "wets" the niobium, smoothing the surface, and the oxide was grown in a well-controlled manner. However, to get to the ultrahigh densities that we are targeting, we would have to make the oxide too thin to be practically manufacturable. Alpha silicon, in contrast, allowed us to use a much thicker barrier for the same critical current.

We also had to devise a new way to power the Josephson junctions that would scale down to the size of a chip. Previously, lab-based superconducting computers used transformers to deliver current to their circuit elements. However, having a bulky transformer near each circuit element is unworkable. Instead, we designed a way to deliver power to all the elements on the chip at once by creating a resonant circuit, with specialized capacitors interspersed throughout the chip.

At the circuit level, we had to redesign the entire logic and memory structure to take advantage of the new materials' capabilities. We designed a
novel logic architecture that we call pulse-conserving logic. The key requirement for pulse-conserving logic is that the elements have as many inputs as outputs and that the total number of single flux quanta is conserved. The logic is performed by routing the SFQs through a combination of Josephson-junction loops and inductors to the appropriate outputs, resulting in logical ORs and ANDs. To complement the logic architecture, we also redesigned a compatible Josephson-junction-based SRAM.

Lastly, we had to make architectural innovations to take full advantage of the novel materials and circuit designs. Among these was cooling conventional silicon DRAM down to 77 kelvins and designing a glass bridge between the 77-K section and the main superconducting section. The bridge houses thin wires that allow communication without thermal mixing. We also came up with a way of stacking chips on top of each other and are developing vertical superconducting interconnects to link between circuit boards.
A Data Center the Size of a Shoebox
The result is a superconductor-based chip design that's optimized for AI processing. A zoom in on one of its boards reveals many similarities with a typical 3D CMOS system-on-chip. The board is populated by computational chips: We call it a superconductor processing unit (SPU), with embedded superconducting SRAM, DRAM memory stacks, and switches, all interconnected on silicon interposer or on glass-bridge advanced packaging technologies.

But there are also some striking differences. First, most of the chip is to be submerged in liquid helium for cooling to a mere 4 K. This includes the SPUs and SRAM, which depend on superconducting logic rather than CMOS, and are housed on an interposer board. Next, there is a glass bridge to a warmer area, a balmy 77 K that hosts the DRAM. The DRAM technology is not superconducting, but conventional silicon cooled down from room temperature, making it more efficient. From there, bespoke connectors lead data to and from the room-temperature world.

Davide Comai

Moore's law relies on fitting progressively more computing resources into the same space. As scaling down transistors gets more and more difficult, the semiconductor industry is turning toward
3D stacking of chips to keep up the density gains. In classical CMOS-based technology, it is very challenging to stack computational chips on top of each other because of the large amount of power, and therefore heat, that is dissipated within the chips. In superconducting technology, the little power that is dissipated is easily removed by the liquid helium. Logic chips can be directly stacked using advanced 3D integration technologies resulting in shorter and faster connections between the chips, and a smaller footprint.

It is also straightforward to stack multiple boards of 3D superconducting chips on top of each other, leaving only a small space between them. We modeled a stack of 100 such boards, all operating within the same cooling environment and contained in a 20- by 20- by 12-centimeter volume, roughly the size of a shoebox. We calculated that this stack can perform 20 exaflops (in
BF16 number format), 20 times the capacity of the largest supercomputer today. What's more, the system promises to consume only 500 kilowatts of total power. This translates to energy efficiency one hundred times as high as the most efficient supercomputer today.

So far, we've scaled down Josephson junctions and interconnect dimensions over three succeeding generations. Going forward, Imec's road map includes tackling 3D superconducting chip-integration and cooling technologies. For the first generation, the road map envisions the stacking of about 100 boards to obtain the target performance of 20 exaflops. Gradually, more and more logic chips will be stacked, and the number of boards will be reduced. This will further increase performance while reducing complexity and cost.
The Superconducting Vision
We don't envision that superconducting digital technology will replace conventional CMOS computing, but we do expect it to complement CMOS for specific applications and fuel innovations in new ones. For one, this technology would integrate seamlessly with quantum computers that are also built upon superconducting technology. Perhaps more significantly, we believe it will support the growth in AI and machine learning processing and help provide cloud-based training of big AI models in a much more sustainable way than is currently possible.

In addition, with this technology we can engineer data centers with much smaller footprints. Drastically smaller data centers can be placed close to their target applications, rather than being in some far-off football-stadium-size facility.

Such transformative server technology is a dream for scientists. It opens doors to online training of AI models on real data that are part of an actively changing environment. Take potential robotic farms as an example. Today, training these would be a challenging task, where the required processing capabilities are available only in far-away, power-hungry data centers. With compact, nearby data centers, the data could be processed at once, allowing an AI to learn from current conditions on the farm

Similarly, these miniature data centers can be interspersed in energy grids, learning right away at each node and distributing electricity more efficiently throughout the world. Imagine smart cities, mobile health care systems, manufacturing, farming, and more, all benefiting from instant feedback from adjacent AI learners, optimizing and improving decision making in real time.

How to Put a Data Center in a Shoebox

Laser Launch into Orbit

[This is a transcript of the video embedded below. Some of the explanations may not make sense without the animations in the video.]

"Battery's almost empty. Connect to a power source." Why do we still not have wireless power? That's what we'll talk about today.

Wireless power would have many benefits. First, it'd get rid of all those different plugs. We'd also no longer have to crawl around on airport floors and fight over the only two available outlets. And if you don't have to plug and unplug your things constantly, that's one piece less that can break. It could power devices that can't easily be reached, such as medical implants or robots used in contaminated areas. It'd also be much easier to make devices waterproof, though I'm afraid even with wireless power it'll still be difficult to dry your hair underwater.
So why don't we have wireless power already? The problem is fairly basic. Power is energy transferred per time, and energy travels locally. This means if you want to get energy from one place to another, it has to travel at least one path between these two places. If you have a cable, then the energy goes along that path, except for some unavoidable losses mostly due to heat. If you don't have a cable, well, then you have to find some other way to get the energy where you want it to go. That leaves you with two options.

You either generously splatter energy into all directions and hope that some of it arrives at the intended destination. That's like filling up your car tank not with a hose, but instead by parking it next to a gasoline sprinkler. Sure, it'll work if you wait long enough, but it's extremely wasteful.

The other thing you can do is to focus the energy at a particular target. This will be much more efficient, but now you have a focused beam that can deposit energy into anything that gets in the way, like walls, trees, or humans. That isn't good. Maybe we could put some kind of shield around that energy so that nothing gets in the way. Like – a cable?
But, but, you may say, we already have wireless chargers. Indeed, wireless charging exists, but it currently works only over short distances. This is called "near-field" wireless power transfer. In these systems the power does not travel freely through space but can be extracted near a source, though the power you can extract that way drops quickly with the distance to the source.

There are a variety of ways this can be done with alternating currents, that is the stuff that comes out of your wall outlet. The simplest and also the oldest method is inductive power transfer.

Inductive power transfer uses two coils – one transmitter and one receiver – very close to each other, that's usually millimeters to centimeters. If an alternating current goes through the transmitter coil it creates an oscillating magnetic field. The same field then also passes through the receiving coil, where it induces another alternating current. So you've moved some power from the one coil to the other.
This is currently the most common method of wireless power transfer. It's used for example to recharge electric toothbrushes and shavers and things like that. With this method, the power transferred increases with frequency but decreases with distance between the coils. That's because the larger the distance, the less of the magnetic field from the transmitter coil reaches the receiving coil. In practice this means that the two coils have to be right next to each other.
There are several variations of this method, for example magnetic resonant power transfer. In this case you add capacitors to both circuits. They then have a preferred resonance frequency at which the power transfer is more efficient. This method also works over somewhat larger distances than the inductive transfer, up to a few times the size of the coils. This method is often used for wireless phone chargers.

But let's be honest this isn't what we're looking for. We want our phone to magically recharge while we're queuing for coffee, right? And for this we need far-field wireless power transfer.

The most obvious way to get this done is by sending energy with electromagnetic waves that travel freely. It's like radio, except you don't want to transmit the sound signal, but the energy.

This too is an old technology. Already on 1964, the American engineer William Brown did a series of experiments in which he powered a small helicopter for hours using microwaves.
Microwaves, guess what, are also used in microwave ovens. Those ovens are shielded for a reason, the reason being that you don't want this energy to bounce around in your kitchen. Before microwave ovens became consumer products, they were used in scientific laboratories and often didn't have shields. And that had some interesting consequences, which I learned from Tom Scott's video about unfreezing hamsters. Yes, hamsters. Here's how James Lovelock recalls thes e first microwave ovens.

"In the course of the experiments, while we were building it, the thing was running open and the radiation was bouncing all around the room. And the light bulbs would light up without warning. The filaments just had the same wavelength as the radiation and it would absorb it and light up. And the pound notes were the funniest ones, they'd catch fire because the metal strip inside was just about the wavelength of the magnetron."

If you haven't watched Tom's video, you should, I swear you won't regret it. But don't forget to come back.

So, yes, you can use electromagnetic radiation for wireless power transfer, but most of us don't want things in our vicinity to catch fire every now and then. This means this technology can really only be used at small power. But at small power it is being used already.

Samsung, for example, has produced a TV remote that is powered by energy extracted from your home Wireless. Another example that you have probably all seen are RFID security tags. The abbreviation stands for radio frequency identification. They are powered by another device that serves as a reader. The power transferred in those examples is typically a micro Watt. This isn't remotely enough to charge your phone, which needs some million times more.
At this point you may be wondering why not just extract energy from all that radiation which is in the air already? Indeed, there's a group at Georgia Tech which has developed a receiver that grabs energy of the 5G network, again that's not much, some microwatts, but at distances up to 180 meters from a network antenna.

If you want to transfer more power without setting things on fire, you have to find a way to focus power transfer smartly. This isn't all that easy with electromagnetic waves. They tend to spread out into many directions, and that reduces the amount of energy that arrives at the target. You could use lasers, but again there's the issue that things might get in the way. Also, lasers are themselves not exactly power efficient.
However, the intensity of the radiation drops with 1/R^2 in the far field only if you're far away from all antennas, not if you are close by, or actually inside, an array of antennas. Then the intensity may drop far less.
The start-up Ossia makes use of this. Their system is called Cota. It's an array of about 60 times 60 centimeter size with a few hundred tiny antennas. They emit radiation in the frequency range of several GHz, so that's somewhat higher than the frequency used in a typical home wireless. The system can detect the position of your phone or other devices and then focus a signal to only that position, instead of wasting energy by emitting it everywhere.

The company claims that their system should be able to deliver 2 to 3 Watts at one meter distance, 1 Watt at 2 meters, and 10 to 50 miliwatt across 10 meters.

For comparison, a USB-3 port, which you most likely currently charge your phone with, delivers up to 4.5 Watts. So this isn't so bad, but still really only good to power small devices like maybe alarm clocks and other things you don't use. Also, the machine consumes between 40 and 60 Watts, which is roughly half the power consumption of a typical fridge, so not exactly energy efficient.

This technology was approved for sale and use in the USA already in 2019, and a few months ago it was also approved in the UK and the EU. The company says that Walmart is piloting the system in some distribution centers for inventory tracking and asset management, and Toyota is testing its viability to replace some wiring in cars, where it could power sensors and make it easier to replace them. These are all cases where you need really small amounts of power.

There are now a number of other companies with similar products, for example Energos whose system is called Watt-Up, and GuRu. The GuRu system operates at somewhat higher frequencies, at 24 GHz, which they claim makes it easier to miniaturizing the device.

I had a run-in with some guys who worked on wireless power about 15 years ago because they claimed in their product description that the electromagnetic energy "tunnels" from one place to another. If you've followed my blog for a really, really long time, you may remember this.

The reason I picked on this "tunneling" description is that I was afraid it may raise the impression you can somehow avoid the need for energy to go from one place to another with quantum something. This is not the case. Energy doesn't just jump from one place to another, and quantum mechanics doesn't change anything about this. For all I know that start-up no longer exists.
But referring to quantum something to attract customers hasn't gone entirely out of fashion. There is a new wireless power company now, technovatar, which says on their website that they use neither electric nor magnetic fields but instead "transfer energy through energy quantization" which is "based on the creation of energy structures in space". I have no idea what that means. They also claim their system does not use "any of existing methods of energy transfer". So I guess this means they sell a non-existing method of energy transfer.

Some of you may also remember that a few years ago there was a lot of buzz around wireless power transfer by ultrasound. The idea is that you convert electric energy into sound, transmit that sound, and then convert it back. You *can do that and it *does work, but of course this too doesn't solve the problem that the energy has to somehow get from one place to another, and if you get in the way, some of that energy might be deposited into your body.
This company was called "u-Beam" and at the time and it made quite a few headlines. But in 2016, the entire engineering team left the company, and a former employee wrote a series of blog posts explaining that the technology did not work. He wrote: "While in theory [uBeam] may be possible in limited cases, the safety, efficiency, and economics of it mean it is not even remotely practical." The company still exists, though it's been renamed to SonicEnergy. It seems like wireless power by ultrasound isn't going to become reality any time soon, maybe not ever.

There are however several technologies under development that might soon improve the efficiency of wireless power transfer and make the transfer more stable.

For example, in 2018 a group of researchers published a paper in PRL in which they proposed a way to improve the absorption of wireless power by a method of self-tuning called "Coherently enhanced wireless power transfer". It's basically a feedback loop that allows the system to adapt to reflections in the environment. A further step forward was made in 2020 by researchers from Stanford University. They developed a circuit that can adapt wireless power transfer to a moving source at times less than a millisecond. This drastically reduces loss and improves efficiency.
And near-field wireless power systems can be improved with metamaterials. Metamaterials are engineered to have desired responses to electromagnetic fields, sometimes also in the optical part of the spectrum. They can therefore much enhance the efficiency of the system. There's a lot more to say about metamaterials. Let me know in the comments if you would be interested in a video on metamaterials specifically.

It looks like wireless power technology slowly gets going, but there's already a new problem on the horizon. Wireless power might do away with the plugs, but the receiver has to be embedded inside the device. And unless everybody agrees on some standard receiver, which seems incredibly unlikely going by past experience, we're going to see a lot of devices that won't work in a room with another sender.

Personally I clearly think the way to go is tiny flying robots that deliver charge to your phone by crawling inside. Now I just need a catchy name and a website and soon I'll be rich and famous. Until this happens, please don't forget to like this video and subscribe.