Day: May 6, 2025

Optical Contact Bonding: Where The Macro Meets The Molecular

May 6, 2025 by 19 Comments

If you take two objects with fairly smooth surfaces, and put these together, you would not expect them to stick together. At least not without a liberal amount of adhesive, water or some other substance to facilitate a temporary or more permanent bond. This assumption gets tossed out of the window when it comes to optical contact bonding, which is a process whereby two surfaces are joined together without glue.

The fascinating aspect of this process is that it uses the intermolecular forces in each surface, which normally don’t play a major role, due to the relatively rough surfaces. Before intermolecular forces like Van der Waals forces and hydrogen bonds become relevant, the two surfaces should not have imperfections or contaminants on the order of more than a few nanometers. Assuming that this is the case, both surfaces will bond together in a way that is permanent enough that breaking it is likely to cause damage.

Although more labor-intensive than using adhesives, the advantages are massive when considering that it creates an effectively uninterrupted optical interface. This makes it a perfect choice for especially high-precision optics, but with absolutely zero room for error.

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Improving Flying Drones By Mimicking Flying Squirrels

May 6, 2025 by 12 Comments

With the ability to independently adjust the thrust of each of their four motors, quadcopters are exceptionally agile compared to more traditional aircraft. But in an effort to create an even more maneuverable drone platform, a group of South Korean researchers have studied adding flying squirrel tech to quadcopters. Combined with machine learning, this is said to significantly increase the prototype’s agility in an obstacle course.

Flying squirrels (tribe Pteromyini)) have large skin flaps (patagium) between their wrists and ankles which they use to control their flight when they glide from tree to tree, along with their fluffy squirrel tail. With flights covering up to 90 meters, they also manage to use said tail and patagium to air brake, which prevents them from smacking with bone jarring velocities into a tree trunk.

By taking these principles and adding a similar mechanism to a quadcopter for extending a patagium-like membrane between its rotors, the researchers could develop a new controller (thrust-wing coordination control, TWCC), which manages the extending of the membranes in coordination with thrust from the brushless motors. Rather than relying on trial-and-error to develop the controller algorithms, the researchers trained a recurrent neural network (RNN) which was pre-trained prior to first flights using simulation data followed by supervised learning to refine the model.

During experiments with obstacle avoidance on a test-track, the RNN-based controller worked quite well compared to a regular quadcopter. A disadvantage is of course that the range of these flying squirrel drones is less due to the extra weight and drag, but if one were to make flying drones that will perch on surfaces between dizzying feats of agility in the air, this type of drone tech might just be the ticket.

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Hardware Built For Executing Python (Not Pythons)

May 6, 2025 by 42 Comments

Lots of microcontrollers will accept Python these days, with CircuitPython and MicroPython becoming ever more popular in recent years. However, there’s now a new player in town. Enter PyXL, a project to run Python directly in hardware for maximum speed.

What’s the deal with PyXL? “It’s actual Python executed in silicon,” notes the project site. “A custom toolchain compiles a .py file into CPython ByteCode, translates it to a custom assembly, and produces a binary that runs on a pipelined processor built from scratch.” Currently, there isn’t a hard silicon version of PyXL — no surprise given what it costs to make a chip from scratch. For now, it exists as logic running on a Zynq-7000 FPGA on a Arty-Z7-20 devboard. There’s an ARM CPU helping out with setup and memory tasks for now, but the Python code is executed entirely in dedicated hardware.

The headline feature of PyXL is speed. A comparison video demonstrates this with a measurement of GPIO latency. In this test, the PyXL runs at 100 MHz, achieving a round-trip latency of 480 nanoseconds. This is compared to MicroPython running on a PyBoard at 168 MHz, which achieves a much slower 15,000 nanoseconds by comparison. The project site claims PyXL can be 30x faster than MicroPython based on this result, or 50x faster when normalized for the clock speed differences.

Python has never been the most real-time of languages, but efforts like this attempt to push it this way. The aim is that it may finally be possible to write performance-critical code in Python from the outset. We’ve taken a look at Python in the embedded world before, too, albeit in very different contexts.

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