A rectangular black box is shown, connected to a coil of fiber-optic wire. Out of the end of the fiber, purple light is emitted. A label in the lower right corner says "405nm Singlemode Light Source".

Building A Fiber-Coupled Laser Source For Precision Optics

Laser diodes are convenient light sources, but for precise optical work their often-elliptical beam profile leaves something to be desired. One way to get around this is to couple the beam into a single-mode optical fiber, which then emits a circular Gaussian beam from the other end. For more advanced experiments, therefore, [Diffraction Limited] built this fiber-coupled laser source.

The simplest approach is to place the fiber directly against a light source, but this results in most of the light missing the three-micron fiber core. Optical fibers have an acceptance cone, and only light approaching from within this cone is coupled into the fiber. The design therefore uses an aspheric lens to focus light from the laser diode down to a tiny point matching the diameter of the fiber core, creating a cone of incoming light narrower than the acceptance cone.

The body of the laser source was CNC machined out of brass, with the laser-diode press-fit in one end. The lens stands in front of the diode, and was glued in place so that its focal point was just above the end of a mounting pin for the glass fiber. Positioning and fixing the fiber in place was the biggest challenge; [Diffraction Limited] could use the micro-manipulator from a previous video to position the fiber, but the UV-set glue used to fix it in place shrinks during curing, pulling it out of position. To deal with this, two set screws under the mounting pin allowed its position to be adjusted slightly after gluing. As expected, adhesive shrinkage meant that the completed source initially produced no light, but after the set screws were adjusted, the beam appeared.

For more on fiber-coupled lasers, check out [Les Wright]’s work. If you don’t have access to an aspheric lens, an anti-bumping bead could be a reasonable alternative.

A grey box surrounding a circular red component is mounted on an aluminium extrusion frame. The circular red face has a protrusion extending from it with a white ball bearing at the tip.

Building A Micrometer-Level Displacement Sensor With 3D Printed Parts

Every experienced machinist knows the value of taking regular measurements. If one works carefully and checks dimensions frequently, it’s possible to make a part much more precise than could be made by relying on the machine’s accuracy alone. In a similar vein, it’s possible to make a measuring device out of comparatively crude parts, as long as their behavior is well understood. Related to both principles is [BubsBuilds]’s displacement sensor, which uses a 3D printed frame but reaches precision better than two micrometers.

Admittedly the printed parts aren’t the source of the sensor’s precision, that comes from an opto-interrupter. This design has a central stylus, one end of which contacts the object under measurement. The other end flattens to a knife-edge blade, which fits between the diodes of the opto-interrupter. As the stylus point is pressed in, the blade blocks off more light from reaching the photodiode, creating an output signal proportional to displacement. To keep the stylus from twisting or moving side-to-side, two flat, circular flexures hold the stylus in the center of a cylindrical housing.

[Bubs] printed several flexure variations to see how well they resisted and permitted various torques and forces, and a symmetrical flexure design proved best for his purposes. Once the sensor was assembled, he tested it against the measurements recorded by a laser confocal displacement sensor. This design was an update from a previous version, and it improved in a few regards: the non-linearity had decreased, and the repeatability was now better than two microns, though the range had been halved. Significantly, though, it’s now much easier to mount, making this an actually practical tool.

If, however, this doesn’t fit your needs, there are many other ways to build a linear displacement sensor, ranging from capacitive to magnetostrictive. On the manual side of things, we’ve also covered a comparison of calipers.

Continue reading “Building A Micrometer-Level Displacement Sensor With 3D Printed Parts”

An AI-generated diagram of the coffee-making process is shown. A filter holds a basket of coffee grounds, which are contained in a paper filter. An ultrasonic transducer vibrates the basket.

Brewing Espresso With Ultrasonic Assistance

There are as almost as many kinds of coffee as there are of coffee drinkers, with each method for preparing the beverage appealing to a different kind of palate: moka pots, filter coffee, pour-over coffee, French presses, cold brews, espresso, and more produce their own unique flavours by extracting different compounds from the grounds to different degrees. Now, a new method has joined the throng: ultrasonic-assisted extraction, which can produce even an espresso at room temperature.

Espresso is normally made by forcing hot water through tightly-packed, finely-ground coffee beans, quickly producing a concentrated extraction. Its one of the hardest kinds of coffee to consistently make well, since the outcome is influenced by everything from grind size and packing density to temperature, pressure, and more. Ultrasonic agitation helps here by creating cavitation bubbles, which form shock waves as they collapse, breaking open the bean structure and producing small, strong jets of water. The experimental apparatus was built into a modified espresso machine. An ultrasonic transducer delivers vibrations to the basket containing the room-temperature slurry of coffee grounds for two or three minutes.

To quantify the results, the researchers analysed total dissolved solids, extraction yield, pH, colour, volatile components, and caffeine and chlorogenic acid contents. By varying ultrasonic power and grind size, the extraction yield and dissolved solids could be adjusted to closely match traditional espresso or cold-brew coffee. The other metrics had no significant differences, and a survey of 100 coffee drinkers found no preference between this and traditional espresso. When the drinkers tried the cold-brew coffees, they preferred the version made with ultrasonic assistance. The experiment succeeded in its goal of reducing energy consumption: the ultrasonic-assisted coffee took about a quarter as much energy to make.

If you still prefer a more traditional approach, we’ve covered some beautiful espresso machines before, including one made out of motorcycle engine parts.

A drone is shown flying above some trees and a building. A pink cloud of dots appears above the drone, and a purple cloud below the drone. Grey crosshairs are to the right of the drone.

Seeing The World In Radio Waves With The QuadRF

Although the basic principle of radio direction finding is easy to understand (measure the phase difference between different antennas, then calculate the angle of arrival from this difference), the radio hardware to actually implement this has historically been hard for hackers to access. The QuadRF project aims to change this by building a phase-coherent four-channel SDR which makes direction mapping easy (GitHub repository).

The QuadRF uses two boards: one to receive and pre-process radio waves, and a Raspberry Pi 5 for additional processing. The RF board has four patch antennas, each capable of either transmitting or receiving in the 4.9 GHz to 6.0 GHz range, with switchable right- or left-hand polarization. For on-device processing, it uses a Lattice ECP5 FPGA, which uses two MIPI cables to connect to the camera and display interfaces on the Raspberry Pi. These form a very high-speed data exchange, and after further processing, the Pi can pass data on over Ethernet or Wi-Fi. Individual QuadRF boards can connect together in a lattice grid to form larger phased arrays.

The QuadRF’s software shows off its real strength: it’s compatible with standard programs like GNU Radio, but it also hosts a few of its own programs. The most striking of these is an “RF camera” which scans its entire frequency range at 30 fps, tracking the direction of detected signals and visualizing them on a spatial plot. When overlaid on a camera feed, this plot lets one easily see the radio signals emitted from electronics; as an example, the creators tracked a drone in flight, even distinguishing the two radio transmitters on the drone.

This isn’t the first multi-antenna SDR we’ve seen, though this is the first that could transmit. It’s important to be careful, though: some applications of this kind of hardware run afoul of arms regulations.

Thanks to [Swake] for the tip!

A selection of materials sits on a counter. There is a fluorescent light bulb, two papers stained with dyes, and a few other pieces of paper with no obvious staining.

Building Your Own X-Ray Detector Screen

Fluoroscopy is probably the best-known method of X-ray imaging: an X-ray beam passes through the subject to be imaged, and the transmitted X-rays illuminate a phosphor screen. Dense objects, such as metal or bone, cast a shadow on the screen, which provides a real-time image of the subject’s interior. Already having access to X-ray sources, [MarcellF]’s next step was to investigate common phosphor materials, then synthesize his own.

Most common materials that fluoresce under ultraviolet light showed no activity under X-rays: fluorescein, quinine, UV fluorescent paint, and common fluorescent minerals emitted no noticeable glow under 80 kV X-ray stimulation. However, strontium aluminate phosphors did fluoresce well, with a strong afterglow, as did the phosphors in a fluorescent light bulb, some LEDs, and an electroluminescent panel. The electroluminescent panel, which used a zinc sulfide phosphor, was almost as bright as the gadolinium oxysulfide screen from a CT scanner’s detector and had no noticeable afterglow.

Continue reading “Building Your Own X-Ray Detector Screen”

A boiling flask is mounted in a heating manted, with a tube leading from it to a U-shaped tube. From here, the tube continues to a bottle of yellow fluid, from which another tube emerges. A flame is emitted from this last tube.

Building A Desktop Catalytic Cracker

Although crude oil contains a vast diversity of hydrocarbons, a comparatively small number of these make up the bulk of demand for oil. Cracking solves this mismatch: most of the demand is for light, short-carbon-chain molecules, so a cracker breaks down long-chain hydrocarbons into lighter, more commercially-valuable chemicals. This is usually done in massive industrial plants, but as [Markus Bindhammer] showed, it’s possible even in a tabletop apparatus.

There are several methods of cracking, but [Markus] used catalytic fluid cracking: a feedstock high in alkanes (hydrocarbons containing fully saturated carbon-carbon bonds) is heated in the presence of a catalyst, whereupon its long alkane chains split to form alkenes (hydrocarbons with a carbon-carbon double bond) with the loss of a hydrogen molecule. In [Markus]’s setup, a heating mantle heated a boiling flask containing paraffin oil and an amorphous silica-alumina catalyst. Vapors from this flask passed through a condenser tube and a bottle of bromine water, then escaped through a flashback arrestor. Bromine reacts far more readily with alkenes than with alkanes, so the disappearance of its characteristic yellow color would visually indicate the production of alkenes.

To avoid unwanted oxidation, [Markus] purged the cracker with argon before using it. While running the cracker, a flammable mixture of light hydrocarbons and hydrogen escaped from the flask of bromine water. The yellow color of bromine disappeared, and two phases formed: one aqueous, and a lighter phase of hydrocarbons and brominated hydrocarbons. The hot side of the reactor did not survive well; the catalyst turned black with coke, and the heating mantel’s cover fused to the boiling flask. However, the reaction undoubtedly succeeded: while a pool of normal paraffin oil wouldn’t ignite, the cracked oil lit easily.

To go the other way, from small molecules to larger hydrocarbon chains, [Markus] has also used the Fischer-Tropsch process.

Continue reading “Building A Desktop Catalytic Cracker”

Three brown pancakes are sitting in a frying pan.

Optimizing Pancakes From Chemical Principles

Although parents and teachers like to point out the deep link between cooking and chemistry, most people don’t deliberately apply any chemical principles beyond acid/base reactions to their recipes. Not so [Ben Kazez]: he’s written a thorough exploration of the chemical journey to the perfect pancake, and made a calculator for others to use with their own ingredients.

The goal is to optimize the pancakes along four dimensions: interior texture (light and smooth), a tangy flavour, rise, and a crisp, brown exterior layer. The tang comes from residual acids, and since lactic acid produces the best taste, dairy-based acid sources (such as Greek yoghurt or buttermilk) are preferable. Acids also react with baking soda to release carbon dioxide, making them a part of one of the four rising agents. The other three are carbon dioxide released when double-acting baking powder is heated, steam released from the batter, and air bubbles stabilized by egg white foam.

Dairy products, besides contributing acid, also provide a protein structure to keep the interior smooth. In a normal wheat-heavy pancake, two proteins (glutenin and gliadin) interact to form tough strands of gluten. Fats bind to hydrophobic amino acids in these proteins and shorten the gluten chains, hence the name shortening. Adding ricotta cheese also replaces some of this gluten network with a smoother structure of previously-denatured dairy proteins. Dairy products also contribute to the Maillard reaction between reducing sugars (such as lactose, glucose, and fructose) and amino acids, which causes the browning of the pancake’s surface. Besides being brown, the surface should be crisp; since amylose, found in corn starch, forms a brittle, glassy, crackly network when dehydrated, corn starch was added.

The result is a set of chemical equations which can be tuned to create perfect pancakes, combined in the calculator. This summary doesn’t do justice to the depth of the research here; [Ben] also investigated optimal batter resting times, fermentation, cooking fats, cooking surfaces, and spatula properties. If all this has you interested in more about dairy proteins, check out our article on cheesemaking.

Featured image: “Buttermilk pancakes from a recipe by Darina Allen” by [Didym].