Underwater robots face many challenges, not least of which is how to move around. ZodiAq is a prototype underwater soft robot (link is to research paper) that takes an unusual approach to this problem: multiple flexible appendages. The result is a pretty unconventional-looking device that can not only get around effectively, but can do so without disturbing marine life.

ZodiAq sports a soft flexible appendage from each of its twelve faces, but they aren’t articulated like you might think. Despite this, the device can crawl and swim.

Each soft appendage is connected to a motor, which rotates the attached appendage. This low-frequency but high-torque rotation, combined with the fact that each appendage has a 45° bend to it, has each acting as a rotor. Rotation of the appendages acts on the surrounding fluid, generating thrust. When used together in the right way, these appendages allow the unit to move in a perfectly controllable manner.

This locomotion method is directly inspired by the swimming gait of bacterial flagella, which the paper mentions are regarded as the only example of a biological “wheel”.

How fast can it go? The prototype covers a distance of two body lengths every fifteen seconds. True, it’s no speed demon compared to a propeller, but it doesn’t disturb marine life or environments as it moves around. This method of movement has a lot going for it. It’s adaptable and doesn’t use all twelve appendages at once; so there’s redundancy built in. If some get damaged or go missing, it can still move, just slower.

ZodiAq‘s design strikes us as a very accessible concept, should any aspiring marine robot hackers wish to give it a shot. We’ve seen other highly innovative and beautiful underwater designs as well, like body-length undulating fins and articulated soft arms.

We do notice that since it lacks a “front” — it might be a challenge to decide how to mount something like a camera. If you have any ideas, share them in the comments.

[Antoine Pirrone] and [Grégoire Passault] are making a DIY miniature re-imagining of Disney’s BDX droid design, and while it’s still early, there is definitely a lot of progress to see. Known as the Open Duck Mini v2 and coming in at a little over 40 cm tall, the project is expected to have a total cost of around 400 USD.

Bipedal robots are uncommon, and back in the day they were downright rare. One reason is that the state of controlled falling that makes up a walking gait isn’t exactly a plug-and-play feature.

Walking robots are much more common now, but gait control for legged robots is still a big design hurdle. This goes double for bipeds. That brings us to one of the interesting things about the Open Duck Mini v2: computer simulation of the design is playing a big role in bringing the project into reality.

It’s a work in progress but the repository collects all the design details and resources you could want, including CAD files, code, current bill of materials, and links to a Discord community. Hardware-wise, the main work is being done with very accessible parts: Raspberry Pi Zero 2W, fairly ordinary hobby servos, and an BNO055-based absolute orientation IMU.

So, how far along is the project? Open Duck Mini v2 is already waddling nicely and can remain impressively stable when shoved! (A “testing purposes” shove, anyway. Not a “kid being kinda mean to your robot” shove.)

Check out the videos to see it in action, and if you end up making your own, we want to hear about it, so remember to send us a tip!

We’ve seen plenty of motor projects, but [Jeremy]’s DIY Tubular Linear Motor is a really neat variety of stepper motor in a format we certainly don’t see every day. It started as a design experiment in making a DIY reduced noise, gearless actuator and you can see the result here.

Here’s how it works: the cylindrical section contains permanent magnets, and it slides back and forth through the center of a row of coils depending on how those coils are energized. In a way, it’s what one would get by unrolling a typical rotary stepper motor. The result is a gearless (and very quiet) linear actuator that controls like a stepper motor.

While a tubular linear motor is at its heart a pretty straightforward concept, [Jeremy] found very little information on how to actually go about making one from scratch. [Jeremy] acknowledges he’s no expert when it comes to motor design or assembly, but he didn’t let that stop him from iterating on the concept (which included figuring out optimal coil design and magnet spacing and orientation) until he was satisfied. We love to see this kind of learning process centered around exploring an idea.

We’ve seen DIY linear motors embedded in PCBs and even seen them pressed into service as model train tracks, but this is the first time we can recall seeing a tubular format.

Watch it in action in the short video embedded below, and dive into the project log that describes how it works for added detail.

As everyone knows, no matter how many drill bits one owns, one inevitably needs a size that isn’t on hand. Well, if you ever find yourself needing to drill a hole that’s precisely 13 mm, here’s a trick from [AvE] to keep in mind for doing it with a 1/2″ bit. It’s a hack that only works in certain circumstances, but hey, it just may come in handy some day.

So the first step in making a 13 mm hole is to drill a hole with a 1/2″ bit. That’s easy enough. Once that’s done, fold a few layers of tinfoil over into a small square and lay it over the hole. Then put the drill bit onto the foil, denting it into the hole (but not puncturing it) with the tip, and drill at a slow speed until the foil wraps itself around the bit like a sheath and works itself into the hole. The foil enlarges the drill bit slightly and — as long as the material being drilled cooperates — resizes the hole a tiny bit bigger in the process. The basic idea can work with just about any drill bit.

It’s much easier demonstrated than described, so watch it in action in the video around the 2:40 mark which will make it all very clear.

It’s not the most elegant nor the most accurate method (the hole in the video actually ends up closer to 13.4 mm) but it’s still something worth keeping in the mental toolbox. Just file it away along with laying your 3D printer on its side to deal with tricky overhangs.

[ombates] shares a step-by-step method for making a conductive bio-string from scratch, no fancy equipment required. She demonstrates using it to create a decorative top with touch-sensitive parts, controlling animations on an RGB LED pendant. To top it off, it’s even biodegradable!

The string is an alginate-based bioplastic that can be made at home and is shaped in a way that it can be woven or knitted. Alginate comes primarily from seaweed, and it gels in the presence of calcium ions. [ombates] relies on this to make a goopy mixture that, once extruded into a calcium chloride bath, forms a thin rubbery length that can be dried into the strings you see here. By adding carbon to the mixture, the resulting string is darkened in color and also conductive.

There’s no details on what the actual resistance of a segment of this string can be expected to measure, but while it might not be suitable to use as wiring it is certainly conductive enough to act as a touch sensor in a manner similar to the banana synthesizer. It would similarly be compatible with a Makey Makey (the original and incredibly popular hardware board for turning household objects into touch sensors.)

What you see here is [ombates]’ wearable demonstration, using the white (non-conductive) string interwoven with dark (conductive) portions connected to an Adafruit Circuit Playground board mounted as an LED pendant, with the conductive parts used as touch sensors.

Alginate is sometimes used to make dental molds and while alginate molds lose their dimensional accuracy as they dry out, for this string that’s not really a concern. If you give it a try, visit our tip line to let us know how it turned out!

[Simon] wrote in to let us know about DingPong, his handheld portable Pong console. There’s a bit more to it than meets the eye, however. Consider for a moment that back in the 1970s playing Pong required a considerable amount of equipment, not least of which was dedicated electronics and a CRT monitor. What was huge (in more than one way) in the 70s has been shrunk down to handheld, and implemented almost entirely on modern e-waste in the process.

DingPong is housed in an old video doorbell unit (hence the name) and the screen is a Sony Video Watchman, a portable TV from 1982 with an amazing 4-inch CRT whose guts [Simon] embeds into the enclosure. Nearly everything in the build is either salvaged, or scrounged from the junk bin. Components are in close-enough values, and power comes from nameless lithium-ion batteries that are past their prime but still good enough to provide about an hour of runtime. The paddle controllers? Two pots (again, of not-quite-the-right values) sticking out the sides of the unit, one for each player.

At the heart of DingPong one will not find any flavor of Arduino, Raspberry Pi, or ESP32. Rather, it’s built around an AY-3-8500 “Ball & paddle” (aka ‘Pong’) integrated circuit from 1977, which means DingPong plays the real thing!

We have seen Pong played on a Sony Watchman before, and we’ve also seen a vintage Pong console brought back to life, but we’re pretty sure this is the first time we’ve seen a Sony Watchman running Pong off a chip straight from the 70s. Watch it in action in the video (in German), embedded below.

Cloudflare has gotten more active in its efforts to identify and block unauthorized bots and AI crawlers that don’t respect boundaries. Their solution? AI Labyrinth, which uses generative AI to efficiently create a diverse maze of data as a defensive measure.

This is an evolution of efforts to thwart bots and AI scrapers that don’t respect things like “no crawl” directives, which accounts for an ever-growing amount of traffic. Last year we saw Cloudflare step up their game in identifying and blocking such activity, but the whole thing is akin to an arms race. Those intent on hoovering up all the data they can are constantly shifting tactics in response to mitigations, and simply identifying bad actors with honeypots and blocking them doesn’t really do the job any more. In fact, blocking requests mainly just alerts the baddies to the fact they’ve been identified.

Instead of blocking requests, Cloudflare goes in the other direction and creates an all-you-can-eat sprawl of linked AI-generated content, luring crawlers into wasting their time and resources as they happily process an endless buffet of diverse facts unrelated to the site being crawled, all while Cloudflare learns as much about them as possible.

That’s an important point: the content generated by the Labyrinth might be pointless and irrelevant, but it isn’t nonsense. After all, the content generated by the Labyrinth can plausibly end up in training data, and fraudulent data would essentially be increasing the amount of misinformation online as a side effect. For that reason, the human-looking data making up the Labyrinth isn’t wrong, it’s just useless.

It’s certainly a clever method of dealing with crawlers, but the way things are going it’ll probably be rendered obsolete sooner rather than later, as the next move in the arms race gets made.

Do you like high-detail 3D models intended for resin printing, but wish you could more easily print them on a filament-based FDM printer? Good news, because [Jacob] of Painted4Combat shared a tool he created to make 3D models meant for resin printers — the kind popular with tabletop gamers — easier to port to FDM. It comes in the form of a Blender add-on called Resin2FDM. Intrigued, but wary of your own lack of experience with Blender? No problem, because he also made a video that walks you through the whole thing step-by-step.

3D models intended for resin printing aren’t actually any different, format-wise, from models intended for FDM printers. The differences all come down to the features of the model and how well the printer can execute them. Resin printing is very different from FDM, so printing a model on the “wrong” type of printer will often have disappointing results. Let’s look at why that is, to better understand what makes [Jacob]’s tool so useful.

Rafts and a forest of thin tree-like supports are common in resin printing. In the tabletop gaming scene, many models come pre-supported for convenience. A fair bit of work goes into optimizing the orientation of everything for best printed results, but the benefits don’t carry directly over to FDM.

For one thing, supports for resin prints are usually too small for an FDM printer to properly execute — they tend to be very thin and very tall, which is probably the least favorable shape for FDM printing. In addition, contact points where each support tapers down to a small point that connects to the model are especially troublesome; FDM slicer software will often simply consider those features too small to bother trying to print. Supports that work on a resin printer tend to be too small or too weak to be effective on FDM, even with a 0.2 mm nozzle.

To solve this, [Jacob]’s tool allows one to separate the model itself from the support structure. Once that is done, the tool further allows one to tweak the nest of supports, thickening them up just enough to successfully print on an FDM printer, while leaving the main model unchanged. The result is a support structure that prints well via FDM, allowing the model itself to come out nicely, with a minimum of alterations to the original.

Resin2FDM is available in two versions, the Lite version is free and an advanced version with more features is available to [Jacob]’s Patreon subscribers. The video (embedded below) covers everything from installation to use, and includes some general tips for best results. Check it out if you’re interested in how [Jacob] solved this problem, and keep it in mind for the next time you run across a pre-supported model intended for resin printing that you wish you could print with FDM.

[Simon Willison] has put together a list of how, exactly, one goes about using a large language models (LLM) to help write code. If you have wondered just what the workflow and techniques look like, give it a read. It’s full of examples, strategies, and useful tips for effectively using AI assistants like ChatGPT, Claude, and others to do useful programming work.

It’s a very practical document, with [Simon] emphasizing realistic expectations and the importance of managing context (both in terms of giving the LLM direction, as well as the model’s context in terms of being mindful of how much the LLM can fit in its ‘head’ at once.) It is useful to picture an LLM as a capable and obedient but over-confident programming intern or assistant, albeit one that never gets bored or annoyed. Useful work can be done, but testing is crucial and human oversight simply cannot be automated away.

Even if one has no interest in using LLMs to help in writing production code, there’s still a lot of useful work they can do to speed up the process of software development in general, especially when learning. They can help research options, interactively explore unfamiliar codebases, or prototype ideas quickly. [Simon] provides useful strategies for all these, and more.

If you have wondered how exactly glorified chatbots can meaningfully help with software development, [Simon]’s writeup hopefully gives you some new ideas. And if this is is all leaving you curious about how exactly LLMs work, in the time it takes to enjoy a warm coffee you can learn how they do what they do, no math required.

Popular Science has an excellent article on how Josephine Cochrane transformed how dishes are cleaned by inventing an automated dish washing machine and obtaining a patent in 1886. Dishwashers had been attempted before, but hers was the first with the revolutionary idea of using water pressure to clean dishes placed in wire racks, rather than relying on some sort of physical scrubber. The very first KitchenAid household dishwashers were based on her machines, making modern dishwashers direct descendants of her original design.

It wasn’t an overnight success. Josephine faced many hurdles. Saying it was difficult for a woman to start a venture or do business during this period of history doesn’t do justice to just how many barriers existed, even discounting the fact that her late husband was something we would today recognize as a violent alcoholic. One who left her little money and many debts upon his death, to boot.

She was nevertheless able to focus on developing her machine, and eventually hired mechanic George Butters to help create a prototype. The two of them working in near secrecy because a man being seen regularly visiting her home was simply asking for trouble. Then there were all the challenges of launching a product in a business world that had little place for a woman. One can sense the weight of it all in a quote from Josephine (shared in a write-up by the USPTO) in which she says “If I knew all I know today when I began to put the dishwasher on the market, I never would have had the courage to start.”

But Josephine persevered and her invention made a stir at the 1893 World’s Fair in Chicago, winning an award and mesmerizing onlookers. Not only was it invented by a woman, but her dishwashers were used by restaurants on-site to clean tens of thousands of dishes, day in and day out. Her marvelous machine was not yet a household device, but restaurants, hotels, colleges, and hospitals all saw the benefits and lined up to place orders.

Early machines were highly effective, but they were not the affordable, standard household appliances they are today. There certainly existed a household demand for her machine — dishwashing was a tedious chore that no one enjoyed — but household dishwashing was a task primarily done by women. Women did not control purchasing decisions, and it was difficult for men of the time (who did not spend theirs washing dishes) to be motivated about the benefits. The device was expensive, but it did away with a tremendous amount of labor. Surely the price was justified? Yet women themselves — the ones who would benefit the most — were often not on board. Josephine reflected that many women did not yet seem to think of their own time and comfort as having intrinsic value.

Josephine Cochrane ran a highly successful business and continued to refine her designs. She died in 1913 and it wasn’t until the 1950s that dishwashers — direct descendants of her original design — truly started to become popular with the general public.

Nowadays, dishwashers are such a solved problem that not only are they a feature in an instructive engineering story, but we rarely see anyone building one (though it has happened.)

We have Josephine Cochrane to thank for that. Not just her intellect and ingenuity in coming up with it, but the fact that she persevered enough to bring her creation over the finish line.

[Ken Shirriff] has been sharing a really low-level look at Intel’s Pentium (1993) processor. The Pentium’s architecture was highly innovative in many ways, and one of [Ken]’s most recent discoveries is that it contains a complex circuit — containing around 9,000 transistors — whose sole purpose is to multiply specifically by three. Why does such an apparently simple operation require such a complex circuit? And why this particular operation, and not something else?

Let’s back up a little to put this all into context. One of the feathers in the Pentium’s cap was its Floating Point Unit (FPU) which was capable of much faster floating point operations than any of its predecessors. [Ken] dove into reverse-engineering the FPU earlier this year and a close-up look at the Pentium’s silicon die shows that the FPU occupies a significant chunk of it. Of the FPU, nearly half is dedicated to performing multiplications and a comparatively small but quite significant section of that is specifically for multiplying a number by three. [Ken] calls it the x3 circuit.

Why does the multiplier section of the FPU in the Pentium processor have such specialized (and complex) functionality for such an apparently simple operation? It comes down to how the Pentium multiplies numbers.

Multiplying two 64-bit numbers is done in base-8 (octal), which ultimately requires fewer operations than doing so in base-2 (binary). Instead of handling each bit separately (as in binary multiplication), three bits of the multiplier get handled at a time, requiring fewer shifts and additions overall. But the downside is that multiplying by three must be handled as a special case.

[Ken] gives an excellent explanation of exactly how all that works (which is also an explanation of the radix-8 Booth’s algorithm) but it boils down to this: there are numerous shortcuts for multiplying numbers (multiplying by two is the same as shifting left by 1 bit, for example) but multiplying by three is the only one that doesn’t have a tidy shortcut. In addition, because the result of multiplying by three is involved in numerous other shortcuts (x5 is really x8 minus x3 for example) it must also be done very quickly to avoid dragging down those other operations. Straightforward binary multiplication is too slow. Hence the reason for giving it so much dedicated attention.

[Ken] goes into considerable detail on how exactly this is done, and it involves carry lookaheads as a key element to saving time. He also points out that this specific piece of functionality used more transistors than an entire Z80 microprocessor. And if that is not a wild enough idea for you, then how about the fact that the Z80 has a new OS available?

Lucid dreaming is the state of becoming aware one is dreaming while still being within the dream. To what end? That awareness may allow one to influence the dream itself, and the possibilities of that are obvious and compelling enough that plenty of clever and curious people have formed some sort of interest in this direction. Now there are some indications that VR might be a useful tool in helping people achieve lucid dreaming.

The research paper (Virtual reality training of lucid dreaming) is far from laying out a conclusive roadmap, but there’s enough there to make the case that VR is at least worth a look as a serious tool in the quest for lucid dreaming.

One method of using VR in this way hinges on the idea that engaging in immersive VR content can create mild dissociative experiences, and this can help guide and encourage users to perform “reality checks”. VR can help such reality checks become second nature (or at least more familiar and natural), which may help one to become aware of a dream state when it occurs.

Another method uses VR as a way to induce a mental state that is more conducive to lucid dreaming. As mentioned, engaging in immersive VR can induce mild dissociative experiences, so VR slowly guides one into a more receptive state before falling asleep. Since sleeping in VR is absolutely a thing, perhaps an enterprising hacker with a healthy curiosity in lucid dreaming might be inspired to experiment with combining them.

We’ve covered plenty of lucid dreaming hacks over the years and there’s even been serious effort at enabling communication from within a dreaming state. If you ask us, that’s something just begging to be combined with VR.

[Nicholas LaBonte] shows off a Cyberdeck Handheld that demonstrates just how good something can look when care and attention goes into the design and fabrication. He wanted to make something that blended cyberpunk and nautical aesthetics with a compact and elegant design, and we think he absolutely succeeded.

On the inside is a Raspberry Pi and an RTL-SDR. The back of the unit is machined from hardwood, and sports a bronze heat sink for the Raspberry Pi. The front has a prominent red PSP joystick for mouse input and a custom keyboard. The keyboard is especially interesting. On the inside it’s a custom PCB with tactile switches and a ATmega32U4 running QMK firmware — a popular choice for DIY keyboards — and presents to the host as a regular USB HID device.

How did he make those slick-looking keys? It’s actually a single plate that sits between the front panel and the switches themselves. [Nicholas] used a sheet of polymer with a faux-aluminum look to it and machined it down, leaving metal-looking keys with engraved symbols as tabs in a single panel. It looks really good, although [Nicholas] already has some ideas about improving it.

On the right side is the power button and charging port, and astute readers may spot that the power button is where a double-stack of USB ports would normally be on a Raspberry Pi 5. [Nicholas] removed the physical connectors, saving some space and connecting the USB ports internally to the keyboard and SDR.

As mentioned, [Nicholas] is already full of ideas for improvements. The bronze heat sink isn’t as effective as he’d like, the SDR could use some extra shielding, and the sounds the keyboard ends up making could use some work. Believe it or not, there’s still room to spare inside the unit and he’d maybe like to figure out a way to add a camera, GPS receiver, or maybe a 4G modem. We can’t wait! Get a good look for yourself in the video, embedded below.

Holography is about capturing 3D data from a scene, and being able to reconstruct that scene — preferably in high fidelity. Holography is not a new idea, but engaging in it is not exactly a point-and-shoot affair. One needs coherent light for a start, and it generally only gets touchier from there. But now researchers describe a new kind of holographic camera that can capture a scene better and faster than ever. How much better? The camera goes from scene capture to reconstructed output in under 30 milliseconds, and does it using plain old incoherent light.

The new camera is a two-part affair: acquisition, and calculation. Acquisition consists of a camera with a custom electrically-driven liquid lens design that captures a focal stack of a scene within 15 ms. The back end is a deep learning neural network system (FS-Net) which accepts the camera data and computes a high-fidelity RGB hologram of the scene in about 13 ms.  How good are the results? They beat other methods, and reconstruction of the scene using the data looks really, really good.

One might wonder what makes this different from, say, a 3D scene captured by a stereoscopic camera, or with an RGB depth camera (like the now-discontinued Intel RealSense). Those methods capture 2D imagery from a single perspective, combined with depth data to give an understanding of a scene’s physical layout.

Holography by contrast captures a scene’s wavefront information, which is to say it captures not just where light is coming from, but how it bends and interferes. This information can be used to optically reconstruct a scene in a way data from other sources cannot; for example allowing one to shift perspective and focus.

Being able to capture holographic data in such a way significantly lowers the bar for development and experimentation in holography — something that’s traditionally been tricky to pull off for the home gamer.

What does one do when frustrated at the lack of affordable, open source portable trackers? If you’re [OG-star-tech], you design your own and give it modular features that rival commercial offerings while you’re at it.

What’s a star tracker? It’s a method of determining position based on visible stars, but when it comes to astrophotography the term refers to a sort of hardware-assisted camera holder that helps one capture stable long-exposure images. This is done by moving the camera in such a way as to cancel out the effects of the Earth’s rotation. The result is long-exposure photographs without the stars smearing themselves across the image.

Interested? Learn more about the design by casting an eye over the bill of materials at the GitHub repository, browsing the 3D-printable parts, and maybe check out the assembly guide. If you like what you see, [OG-star-tech] says you should be able to build your own very affordably if you don’t mind 3D printing parts in ASA or ABS. Prefer to buy a kit or an assembled unit? [OG-star-tech] offers them for sale.

Frustration with commercial offerings (or lack thereof) is a powerful motive to design something or contribute to an existing project, and if it leads to more people enjoying taking photos of the night sky and all the wonderful things in it, so much the better.

[Martin] of [Wintergatan] is on a quest to create the ultimate human-powered, modern marble music machine. His fearless mechanical exploration and engineering work, combined with considerable musical talent, has been an ongoing delight as he continually refines his designs. We’d like to highlight this older video in which he demonstrates how to dynamically regulate the speed of a human-cranked music machine by taking inspiration from gramophones: he uses a flyball governor (or centrifugal governor).

These devices are a type of mechanical feedback system that was invented back in the 17th century but really took off once applied to steam engines. Here’s how they work: weights are connected to a shaft with a hinged assembly. The faster the shaft spins, the more the weights move outward due to centrifugal force. This movement is used to trigger some regulatory action, creating a feedback loop. In a steam engine, the regulator adjusts a valve which keeps the engine within a certain speed range. In a gramophone it works a wee bit differently, and this is the system [Wintergatan] uses.

To help keep the speed of his music machine within a certain narrow range, instead of turning a valve the flyball governor moves a large disk brake. The faster the shaft spins, the harder the brake is applied. Watch it in action in the video (embedded below) which shows [Wintergatan]’s prototype, demonstrating how effective it is.

[Wintergatan]’s marble machine started out great and has only gotten better over the years, with [Martin] tirelessly documenting his improvements on everything. After all, when every note is the product of multiple physical processes that must synchronize flawlessly, it makes sense to spend time doing things like designing the best method of dropping balls.

One final note: if you are the type of person to find yourself interested and engaged by these sorts of systems and their relation to obtaining better results and tighter tolerances, we have a great book recommendation for you.

[JanTec Engineering] was fascinated by the idea of using a 3D printer’s hot end to inject voids and channels in the infill with molten plastic, leading to stronger prints without the need to insert hardware or anything else. Inspiration came from two similar ideas: z-pinning which creates hollow vertical channels that act as reinforcements when filled with molten plastic by the hot end, and VoxelFill (patented by AIM3D) which does the same, but with cavities that are not uniform for better strength in different directions. Craving details? You can read the paper on z-pinning, and watch VoxelFill in (simulated) action or browse the VoxelFill patent.

With a prominent disclaimer that his independent experiments are not a copy of VoxelFill nor are they performing or implying patent infringement, [JanTec] goes on to use a lot of custom G-code (and suffers many messy failures) to perform some experiments and share what he learned.

One big finding is that one can’t simply have an empty cylinder inside the print and expect to fill it all up in one go. Molten plastic begins to cool immediately after leaving a 3D printer’s nozzle, and won’t make it very far down a deep hole before it cools and hardens. One needs to fill a cavity periodically rather than all in one go. And it’s better to fill it from the bottom-up rather than from the top-down.

He got better performance by modifying his 3D printer’s hot end with an airbrush nozzle, which gave about 4 mm of extra length to work with. This extra long nozzle could reach down further into cavities, and fill them from the bottom-up for better results. Performing the infill injection at higher temperatures helped fill the cavities more fully, as well.

Another thing learned is that dumping a lot of molten plastic into a 3D print risks deforming the print because the injected infill brings a lot of heat with it. This can be mitigated by printing the object with more perimeters and a denser infill so that there’s more mass to deal with the added heat, but it’s still a bit of a trouble point.

[JanTec] put his testing hardware to use and found that parts with infill injection were noticeably more impact resistant than without. But when it came to stiffness, an infill injected part resisted bending only a little better than a part without, probably because the test part is very short and the filled cavities can’t really shine in that configuration.

These are just preliminary results, but got him thinking there are maybe there are possibilities with injecting materials other than the one being used to print the object itself. Would a part resist bending more if it were infill injected with carbon-fibre filament? We hope he does some follow-up experiments; we’d love to see the results.

[James Sharman] designed and built his own 8-bit computer from scratch using TTL logic chips, including a VGA adapter, and you can watch it run a glorious rotating cube demo in the video below.

The rotating cube is the product of roughly 3,500 lines of custom assembly code and looks fantastic, running at 30 frames per second with shading effects from multiple light sources. Great results considering the computing power of his system is roughly on par with vintage 8-bit home computers, and the graphics capabilities are limited. [James]’s computer uses a tile map instead of a frame buffer, so getting 3D content rendered was a challenge.

The video is about 20 seconds of demo followed by a detailed technical discussion on how exactly one implements everything required for a 3D cube, from basic math to optimization. If a deep dive into that sort of thing is up your alley, give it a watch!

We’ve featured [James]’ fascinating work on his homebrew computer before. Here’s more detail on his custom VGA adapter, and his best shot at making it (kinda) run DOOM.

One can 3D print with conductive filament, and therefore plausibly create passive components like resistors. But what about active components, which typically require semiconductors? Researchers at MIT demonstrate working concepts for a resettable fuse and logic gates, completely 3D printed and semiconductor-free.

Now just to be absolutely clear — these are still just proofs of concept. To say they are big and perform poorly compared to their semiconductor equivalents would be an understatement. But they do work, and they are 100% 3D printed active electronic components, using commercially-available filament.

How does one make a working resettable fuse and transistor out of such stuff? By harnessing thermal expansion, essentially.

The conductive filament the researchers used is Electrifi by Multi3D, which is PLA combined with copper micro-particles. A segment printed in this filament is normally very conductive due to the densely-packed particles, but as temperature increases (beginning around 40° C) the polymer begins to soften and undergoes thermal expansion. This expansion separates the copper particles, causing a dramatic increase in electrical resistance as electrical pathways are disrupted. That’s pretty neat, but what really ties it together is that this behavior is self-resetting, and reversible. As long as the PLA isn’t straight up melted (that is to say, avoids going over about 150° C) then as the material cools it contracts and restores the conductive pathways to their original low-resistance state. Neat!

So where does the heat required come from? Simply passing enough current through the junction will do the job. By carefully controlling the size and shape of traces (something even hobbyist filament-based 3D printers are very good at) this effect can be made predictable and repeatable.

The simpler of the two test components uses the resistance spike as a self-resetting fuse. The printed component is designed such that current above a threshold triggers a surge in resistance, preventing damage to some theoretical circuitry downstream. As long as the component is not destroyed by heating it to the point that it melts, it self-resets as it cools.

The transistor is a bit more interesting. By designing two paths so that they intersect each other, one can be used as a control path and the other as a signal path. Applying a voltage to the control path electrically controls the resistance of the signal path, effectively acting as a transistor. Researchers combined these basic transistors into NOT, AND, and OR gates. One is shown here.

This whole system is scalable, low-cost, and highly accessible to just about anyone with some basic equipment. Of course, it has some drawbacks. The switching speed is slow (seconds rather than nanoseconds) and being thermally-driven means power consumption is high. Still, it’s pretty nifty stuff. Check out the research paper for all the nitty-gritty details.

We’ve seen 3D printed triboelectric generators so it’s pretty exciting to now see printed active electronic components. Maybe someday they can be combined?