Mysterious Files PH

Paper as a substrate for electronic circuits is not very common, but promising for flexible circuits with low cost and easy recyclability. That said, paper is not an easy material to work with when printing traces, as the cellulose material is both absorbent and irregular, limiting the resolution and accuracy of so-called papertronics. Even when using higher-quality paper with wax-based masks this resulted in poor resolution issues, so [Zahra Rafiee] et al. opted to approach the problem from the other direction, by using hydrophobic parchment paper as the base combined with a laser.

The nice thing about the inks used with papertronics that they aren’t just traces, but can also be functional elements like resistors, which is also demonstrated in the paper. The channels for the inks are created using a 50 Watt CO₂ laser, which etches away the silicone coating on the parchment paper. The achieved resolution in the article is around 250 µm for line widths and 300 µm line spacing, which is much better than that for wax-based alternatives.

Providing conductivity in the inks was PEDOT:PSS, which, when mixed with dimethyl sulfoxide (DMSO), creates resistors. Capacitors can be printed by creating interlocking PEDOT:PSS ‘fingers’, with a Poly Vinyl Alcohol (PVA) based gel overlaid as electrolyte. These combinations were used to create RC low- and high-pass filters.

The degradation of these papertronic circuits was also tested, with them buried in soil under typical conditions. Only the silicone coating was rather immune to degradation. Since silicone is considered chemically and biologically inert, it’s claimed to not be an issue. For situations where such easy decomposition is not desirable, encapsulation with polydimethylsiloxane (PDMS) is offered as an option.

Avian Visitors is a lovely project by [Teddy Warner] that uses a Raspberry Pi and microphone to keep track of which birds have been visiting your home, and creates a colorful illustration of recent visitors on top of it all.

It reports on a web interface of its own making, but what really takes things to a new level is an optional, stylish E-Ink panel that shows the last 24 hours’ worth of visitors at a glance in a collage.

The key to identification is BirdNET (GitHub here), a deep learning classifier from Cornell that can reliably identify and classify more than 11,000 species worldwide based on sound alone.

Based on that information, the system pulls bird images from a reference set for the region and creates a collage representing the breadth and frequency of visitors in a single image. The larger the image of a bird, the more frequently it was heard.

That’s a cool project, but [Teddy] took things one step further by setting up a color E-Ink display to show a running summary of all the avian visitors the system identifies. [Teddy] has a knack for leveraging projects into wall-mounted art, as we saw with his generative art wall plotter.

Got ideas of your own? Avian Visitors even has options for sending the latest detection to Home Assistant or over MQTT, allowing automation triggers based on specific bird species. If you decide to try it out and put your own spin on it, be sure to let us know by sending us a tip!

The GitHub repository for Avian Visitors has everything you need to get set up, and the basic system needs little more than a Raspberry Pi and a USB microphone. There’s a build video embedded just below, so give it a shot if you want to get a better idea of what birds come visiting.

If you’ve ever worked with produce, you might know about grading. In addition to deciding if, say, a strawberry is good or not, they also have to sort them by color. Turns out, you don’t care if one package of berries is a bit redder than another, but you do care if one package has too much color variation. [Pmalfa31] applied an ESP32 and machine learning to grading tomatoes.

The system knows in advance if you are processing standard tomatoes or cherry tomatoes and uses two different sets of learned data depending on which you select. The program receives raw data from an optical sensor and then processes it to remove empty belt images, compute statistical information, and group readings for a single fruit together.

One thing we liked was the program’s heuristic checking of validity. It knows the approximate size of the tomato, so the code notes if the fruit seems too big for a cherry tomato or too small for a standard tomato. This reduces, but doesn’t eliminate, miscategorizations.

The code is a stack hog, so the program has to request a much larger stack. If you want to try it yourself, there is a simulator on the web available, so you don’t even need any hardware or tomatoes to try it.

Computers have lots of uses on a modern farm.

As someone who disassembles and repairs hardware, [Aad] eventually ended up with a huge collection of mixed bolts and screws. This led to creating the automatic bolt and screw sorting system you see here, although in a way it is just a proof of concept. Bolts and screws happen to be a useful application for now, but the system is capable of sorting just about any small objects.

Mixed pieces go onto a large conveyor belt, shown on the right. This feeds a few screws at a time down a chute, where they roll onto an illuminated platform.

Above the lit platform is a camera, and machine vision is used to detect the size and shape and orientation of each screw. A robotic gripper on a gantry picks the screws up one by one — separating them first if they happened to clump together — and places each in a drop-off cart. The cart drops the object into a receptacle with its brethren, making sure similar ones are grouped together. Watch it in action in the video, embedded below the page break.

It’s a great build that shows fancy components aren’t necessary for good results. Servos and steppers are controlled with an ESP32-WROOM board, and a piezo sensor detects screws falling off the conveyor. Some of you may have noticed a repurposed Ultimaker 3D printer serving as the bulk of the system, its hot end having been replaced with a gripper that can raise and lower. The overhead camera is an ESP32-CAM adapted to accept M12 lenses so it can focus on the platform.

There’s one more feature worth mentioning — the system also has the ability to measure the weight of a picked object by placing it onto a moveable inspection platform, which can optionally put it under a USB microscope for a closer look. Everything is controlled by a nearby PC, so there’s a lot of flexibility built into the system.

We suppose that once all the screws and bolts in a shop are sorted, it only makes sense to sort all the nuts. Are there other objects besides screws and bolts that would be useful to sort with a system like this? If you have any ideas, don’t keep them to yourself! [Aad] would love to hear your comments and ideas, so share them below.

Having a fully automated cotton candy vending machine in your possession is a great thing, but not if you do not have full access to its software. With [Block’s Retro Repairs] getting ghosted by the manufacturer on regaining account access to the machine he bought used for $300, there was little left but to try and break into the system.

We previously covered the journey in getting the vending machine back into a state where it’d actually reliably produce cotton candy again, a process which is quite tedious and temperamental. After a lot of fiddling with sensors and temperature settings this was fixed, but still left the issue that as a vending machine it should allow the owner to set prices and such. Sadly this could only be done remotely via a special account, which access to had been left with the previous owner.

Despite the very custom exterior, the vending machine runs what is effectively an Android system, consisting of an industrial computer board wired into a lot of stepper drivers and other control boards. To the extreme delight of everyone involved, it was possible to access the Ct Terminal application with adb and its product database on the device’s storage. Unfortunately writing back a changed database file didn’t change anything in the UI, so for a few months the project languished.

After nearly bricking the system and ending up factory resetting the control software including temperatures, it actually improved the performance of the machine and produced cotton candy, so that was one win. Ultimately the solution was to modify the original app, but a combination of weak coding skills and the app being in Chinese  led him to use free LLM coding chatbots to assist here.

This resulted in a custom settings menu being added with the ability to modify pricing, no need for online access any more and a very nice cotton candy vending machine for the private arcade where presumably friends and family can enjoy cheap or even free cotton candy. Finally having the machine sealed against ant intrusion was also a major improvement.

When the Chernobyl Nuclear Power Plant’s #4 reactor experienced an extreme criticality event on that infamous day in 1986, the resulting steam explosion and lack of any kind of containment building meant that parts of the core were scattered throughout the site. In an extensive update to the original 2023 video, the [Chornobyl Family] covers the mad scramble to design robots to perform on-the-ground measurements, and ultimately remove all this debris for safe disposal.

This essentially took the form of a hackathon, involving teams from all over the USSR and allied nations, creating the most diverse range of robots that 1980s Soviet technology and later Western technology could muster.

Many of these robots didn’t perform very well, or at all, mostly due to the bypassing of any kind of testing before deployment. Especially at the beginning of the clean-up the robots were being pushed into the high-radiation zones as soon as they were finished, with not only mechanical issues being a problem, but also with e.g. inaccurate radiation measurements by the RR-1 robot, that overstated measurements by more than a factor of ten. Meanwhile the RR-2 and RR-3 were too top-heavy and after deployment by helicopter simply tipped over. Eventually manual measurements proved to be faster and safer.

Early debris removal robots like the TR-1A were rather simplistic, with successive generations of robots over the next weeks and months improving on it. The use of a combustion engine instead of batteries provided to be a boon, as combustion engines are far less affected by radiation.

The BAER Beloyarets used an airport cart as the basis, with its electronics relying on vacuum tube technology and relays, with an internal combustion engine. This proved to be one of the most reliable designs and it’s been largely preserved on display in the Chornobyl Exclusion Zone, with many others of these robots also being on display around the nuclear plant or in the city of Chornobyl.

Overall an absolutely dizzying number of robotic designs were invented on the spot, adapted from existing designs or repurposed for operation in a high-radiation zone. Eventually bulldozer designs like the STR-1 helped to push radioactive debris off the roofs into containers, massively reducing the radioactive contamination of the area.

The fact that following #4’s RUD the other three RBMK units were able to keep operating safely without risks to its operators, and with the zone now safe for tourists, is a real testament to the success of the worst hackathon imaginable. Many of the lessons learned are relevant today, including during the decommissioning of Fukushima Daiichi’s melted-down cores.

Given that the no doubt totally sustainable build-out of data centers has sent both solid state and magnetic hard drive prices soaring, though, [WNY Over The Air] decided to take a look back at optical disks — specifically the high-density BDXL disks — and see how they do hosting the music library for his Plex server, among other things.

Price wise, well, it’s going to vary depending where you are in the world and exactly when you look. But Blu-ray pricing is looking competitive to hard drives again, and that even goes for the long-lasting, archival-quality “M-disks” that are supposed to last 1000 years in ideal conditions. Of course if you’re playing with LLM Agents, having your precious data on a Write Once Read Many medium like Blu-ray also has the advantage of keeping the agent from wiping it out, which [WNY] takes pains to point out.

That might be obvious, but what’s less obvious is that once the disk has had its metadata queued by his media-streaming Plex server the M-disk is plenty fast enough for streaming music with no noticeable lag. That load time does happen every time you load in a fresh disk, but how often would you be swapping out 100 GB of songs? Even with lossless formats like FLAC, that’s a few thousand tracks. If you’ve already got a Blu-ray drive and are hard up for storage, it might make sense right now to move your music to an optical disk while waiting for drive pries to normalize.

The window where this makes financial sense might not last long, and we’ll be back to wondering where to store our data. All we can say is that’s probably not going to be audio tape, as cool as a reel-to-reel would look in the server room.