Toggle light / dark theme

Extension of laser beam structures promises new laser applications. Exploration of how beam structures change during nonlinear frequency conversion processes has drawn increasing interest in recent years. Nonlinear conversion is an excellent route for structured beam generation and represents a growing, hybrid field for researchers in nonlinear optics and laser technology, as well as the emerging area of light-field regulation technology.

For structured and nonlinear frequency conversion, researchers have considered both intracavity oscillation and external cavity spatial modulation. To achieve flexible outputs, spatial light modulators can be used to obtain structured beams both inside and outside the cavity. But this is an indirect, inefficient method. Intracavity nonlinear frequency generation of structured beams offers a direct, efficient method that has only rarely been investigated, until recently.

Inside a laser cavity, an effect known as “transverse mode locking” (TML) enables the direct generation of the vortex beams or optical vortices from a laser cavity. It is known that both solid-state microchip lasers and VCSELs can produce quite similar outputs of TML beam patterns under large Fresnel number pumping conditions. The complex transverse patterns formed by the TML effect, commonly composed of different basic modes with different weight coefficients and different locking phases, make for abundant spatial information in fundamental frequency modes. Nonlinear frequency conversion of these directly generated TML beams is of great interest, but not yet well studied.

Scanning electron microscopes are one of those niche instruments that most of us don’t really need all the time, but would still love to have access to once in a while. Although we’ve covered a few attempts at home-builds before, many have faltered, except this project over on Hackday. IO by user Vini’s Lab, which appears to be still under active development. The principle of the SEM is pretty simple; a specially prepared sample is bombarded with a focussed beam of electrons, that is steered in a raster pattern. A signal is acquired, using one of a number of techniques, such as secondary electronics (SE) back-scattered electrons (BSE) or simply the transmitted current into the sample. This signal can then be used to form an image of the sample or gather other properties.

The project is clearly in the early stages, as the author says, it’s a very costly thing to build, but already some of the machined parts are ready for assembly. Work has started on the drive electronics for the condenser stigmata lens. This part of the instrument takes the central part of the rapidly diverging raw electron beam that makes it through the anode, and with a couple of sets of octopole coil sets, and an aperture or two, selects only the central portion of the beam, as well as correcting for any astigmatism in the beam. By adjusting the relative currents through each of the coils, a quadrupole magnetic field is created, which counteracts the beam asymmetry.

Scanning control and signal acquisition are handled by a single dedicated card, which utilises the PIO function of a Raspberry Pi Pico module. The Pico can drive the scanning operation, and with an external FTDI USB3.0 device, send four synchronised channels of acquired sample data back to the host computer. Using PCIe connectors and mating edge connectors on the cards, gives a robust and cost effective physical connection. As can be seen from the project page, a lot of mechanical design is complete, and machining has started, so this is a project to keep an eye on in the coming months, and possibly years!

“This is an answer to a huge demand we’ve had from a number of customers who wanted access to this platform but were limited because of the platform they’re on,” Richard Kerris, Nvidia’s Omniverse VP, said to reporters this week.

Omniverse Cloud is in early access now, and Nvidia is taking applications for it.

Next, Nvidia announced Omniverse OVX, a computing system designed specifically to meet the needs of massive simulations — or industrial digital twins.

Rice University researchers have tested a tiny lensless microscope called Bio-FlatScope, capable of producing high levels of detail in living samples. The team imaged plants, hydra, and, to a limited extent, a human.

A previous iteration of the technology, FlatCam, was a lensless device that channeled light through a mask and directly onto a camera sensor, aimed primarily outward at the world at large. The raw images looked like static, but a custom algorithm translated the raw data into focused images.

The device described in current research looks inward to image micron-scale targets such as cells and blood vessels inside the body, and even through skin. The technology combines a sophisticated phase mask to generate patterns of light that fall directly onto the chip, the researchers said. The mask in the original FlatCam looked like a barcode and limited the amount of light that passes through to the sensor.

There’s been a lot of focus on how both Intel and AMD are planning for the future in packaging their dies to increase overall performance and mitigate higher manufacturing costs. For AMD, that next step has been V-cache, an additional L3 cache (SRAM) chiplet that’s designed to be 3D die stacked on top of an existing Zen 3 chiplet, tripling the total about of L3 cache available. Today, AMD’s V-cache technology is finally available to the wider market, as AMD is announcing that their EPYC 7003X “Milan-X” server CPUs have now reached general availability.

As first announced late last year, AMD is bringing its 3D V-Cache technology to the enterprise market through Milan-X, an advanced variant of its current-generation 3rd Gen Milan-based EPYC 7,003 processors. AMD is launching four new processors ranging from 16-cores to 64-cores, all of them with Zen 3 cores and 768 MB L3 cache via 3D stacked V-Cache.

AMD’s Milan-X processors are an upgraded version of its current 3rd generation Milan-based processors, EPYC 7003. Adding to its preexisting Milan-based EPYC 7,003 line-up, which we reviewed back in June last year, the most significant advancement from Milan-X is through its large 768 MB of L3 cache using AMD’s 3D V-Cache stacking technology. The AMD 3D V-Cache uses TSMC’s N7 process node – the same node Milan’s Zen 3 chiplets are built upon – and it measures at 36 mm², with a 64 MiB chip on top of the existing 32 MiB found on the Zen 3 chiplets.

“Moore’s law could once again get a reprieve, in spite of the naysayers.”


Using graphene and molybdenum disulphide, scientists in China have made a transistor gate with a length of only 0.3 nanometres, equivalent to just one carbon atom, by exploiting the vertical aspect of the device.

In 1959, scientists at Bell Labs invented the metal–oxide–semiconductor field-effect transistor (MOSFET). This led to mass-production of transistors for a wide range of applications – including computer processors. The Intel 4,004, the first commercially produced microprocessor, debuted in 1971 and featured 2,250 transistors on a single chip, using a 10,000 nm (10 µm) fabrication process.

Since that time, the MOSFET has become the most widely manufactured device in history. Thanks to vast improvements in miniaturisation, the latest processors now contain 114 billion transistors, making them 50 million times more powerful than the Intel 4004.

If you’re anything like us you’ve been keeping a close eye on the development of RISC-V: an open standard instruction set architecture (ISA) that’s been threatening to change the computing status quo for what seems like forever. From its humble beginnings as a teaching tool in Berkeley’s Parallel Computing Lab in 2010, it’s popped up in various development boards and gadgets from time to time. It even showed up in the 2019 Hackaday Supercon badge, albeit in FPGA form. But getting your hands on an actual RISC-V computer has been another story entirely. Until now, that is.

Clockwork has recently announced the availability of the DevTerm R-01, a variant of their existing portable computer that’s powered by a RISC-V module rather than the ARM chips featured in the earlier A04 and A06 models. Interestingly the newest member of the family is actually the cheapest at $239 USD, though it’s worth mentioning that not only does this new model only include 1 GB of RAM, but the product page makes it clear that the RISC-V version is intended for experienced penguin wranglers who aren’t afraid of the occasional bug.

Beyond the RISC-V CPU and slimmed down main memory, this is the same DevTerm that our very own [Donald Papp] reviewed earlier this month. Thanks to the modular nature of the portable machine, this sort of component swapping is a breeze, though frankly we’re impressed that the Clockwork team is willing to go out on such a limb this early in the product’s life. In our first look at the device we figured at best they would release an updated CPU board to accommodate the Raspberry Pi 4 Compute Module, but supporting a whole new architecture is a considerably bolder move. One wonders that other plans they may have for the retro-futuristic machine. Perhaps a low-power x86 chip isn’t out of the question?

Circa 2021


It is now possible to grow and culture human brain tissue in a device that costs little more than a cup of coffee. With a $5 washable and reusable microchip, scientists can watch self-organising brain samples, known as brain organoids, growing in real time under a microscope.

The device, dubbed a “microfluidic bioreactor”, is a 4-by-6-centimetre chip that includes small wells in which the brain organoids grow. Each is filled with nutrient-rich fluid that is pumped in and out automatically, like the fluids that flush through the human brain.

Using this system, Ikram Khan at the Indian Institute of Technology Madras in Chennai and his colleagues at the Massachusetts Institute of Technology (MIT) have now reported the growth of a brain organoid over seven days. This demonstrates that the brain cells can thrive inside the chip, says Khan.

And going forward, we’ll do this with far more knowledge of what we’re doing, and more control over the genes of our progeny. We can already screen ourselves and embryos for genetic diseases. We could potentially choose embryos for desirable genes, as we do with crops. Direct editing of the DNA of a human embryo has been proven to be possible — but seems morally abhorrent, effectively turning children into subjects of medical experimentation. And yet, if such technologies were proven safe, I could imagine a future where you’d be a bad parent not to give your children the best genes possible.

Computers also provide an entirely new selective pressure. As more and more matches are made on smartphones, we are delegating decisions about what the next generation looks like to computer algorithms, who recommend our potential matches. Digital code now helps choose what genetic code passed on to future generations, just like it shapes what you stream or buy online. This might sound like dark science fiction, but it’s already happening. Our genes are being curated by computer, just like our playlists. It’s hard to know where this leads, but I wonder if it’s entirely wise to turn over the future of our species to iPhones, the internet and the companies behind them.

Discussions of human evolution are usually backward looking, as if the greatest triumphs and challenges were in the distant past. But as technology and culture enter a period of accelerating change, our genes will too. Arguably, the most interesting parts of evolution aren’t life’s origins, dinosaurs, or Neanderthals, but what’s happening right now, our present – and our future.