This 3D Printed Microscope Bends for 50nm Precision

Exploiting the flexibility of plastic, a group of researchers has created a 3D printable microscope with sub-micron accuracy. By bending the supports of the microscope stage, they can manipulate a sample with surprising precision. Coupled with commonly available M3 bolts and stepper motors with gear reduction, they have reported a precision of up to 50nm in translational movement. We’ve seen functionality derived from flexibility before but not at this scale. And while it’s not a scanning electron microscope, 50nm is the size of a small virus (no, not that kind of virus).

OpenFlexure has a viewing area of 8x8x4mm, which is impressive when the supports only flex 6°. But, if 256 mm3 isn’t enough for you, fret not: the designs are all Open Source and are modeled in OpenSCAD just begging for modification. With only one file for printing, no support material, a wonderful assembly guide and a focus on PLA and ABS, OpenFlexure is clearly designed for ease of manufacturing. Optics are equally interesting. Using a Raspberry Pi Camera Module with the lens reversed, they achieve a resolution where one pixel corresponds to 120nm.

The group hopes that their microscopes will reach low-resource parts of the world, and it seem that the design has already started to spread. If you’d like to make one for yourself, you can find all the necessary files up on GitHub.

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Objectifier: Director of Domestic Technology

book-example[Bjørn Karmann]’s Objectifier is a device that lets you control domestic objects by allowing them to respond to unique actions or behaviour, using machine learning and computer vision. The Objectifier can turn on a table lamp when you open a book, and turn it off when you close the book. Switch on the coffee maker when you place the mug next to the pot, and switch it off when the mug is removed. Turn on the belt sander when you put on the safety glasses, and stop it when you remove the glasses. Charge the phone when you put a banana in front of it, and stop charging it when you place an apple in front of it. You get the drift — the possibilities are endless. Hopefully, sometime in the (near) future, we will be able to interact with inanimate objects in this fashion. We can get them to learn from our actions rather than us learning how to program them.

The device uses computer vision and a neural network to learn complex behaviours associated with your trigger commands. A training mode, using a phone app, allows you to train it for the On and Off actions. Some actions require more human effort in training it — such as detecting an open and closed book — but eventually, the neural network does a fairly good job.

The current version is the sixth prototype in the series and [Bjørn] has put in quite a lot of work refining the project at each stage. In its latest avatar, the device hardware consists of a Pi Zero, a Raspberry-Pi camera module, an SMPS power brick, a relay block to switch the output, a 230 V plug for input power and a 230 V socket outlet for the final output. All the parts are put together rather neatly using acrylic laser cut support pieces, and then further enclosed in a nice wooden enclosure.

On the software side, all of the machine learning part is taken care of using “Wekinator” — a free, open source software that allows building musical instruments, gestural game controllers, computer vision or computer listening systems using machine learning. The computer vision is handled via Processing. All the code is wrapped using openframeworks, with ml4A providing apps for working with machine learning.

All of the above is what we could deduce looking at the pictures and information on his blog post. There isn’t much detail about the hardware, but the pictures are enough to tell us all. The software isn’t made available, but maybe this could spur some of you hackers into action to build another version of the Objectifier. Check out the video after the break, showing humans teaching the Objectifier its tricks.

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Squirrel Café To Predict The Weather From Customer Data

Physicist and squirrel gastronomer [Carsten Dannat] is trying to correlate two critical social economical factors: how many summer days do we have left, and when will we run out of nuts. His research project, the Squirrel Café, invites squirrels to grab some free nuts and collects interesting bits of customer data in return.

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Hackaday Prize Entry: An Internet Of Things Microscope

For their entry into the Citizen Scientist portion of the Hackaday Prize, the folks at Arch Reactor, the St. Louis hackerspace, are building a microscope. Not just any microscope – this one is low-cost, digital, and has a surprisingly high magnification and pretty good optics. It’s the Internet of Things Microscope, and like all good apparatus for Citizen Scientist, it’s a remarkable tool for classrooms and developing countries.

When you think of ‘classroom microscope’, you’re probably thinking about a pile of old optics sitting in the back of a storage closet. These microscopes are purely optical, without the ability to take digital pictures. The glass is good, but you’re not going to get a scanning stage when you’re dealing with 30-year-old gear made for a classroom full of sticky-handed eighth graders.

The Internet of Things Microscope includes a scanning stage that moves across the specimen on the X and Y axes, stitching digital images together to create a very large image. That’s a killer feature for a cheap digital microscope, and the folks at Arch Reactor are doing this with a few cheap stepper motors and stepper motor drivers.

The rest of the electronics are built around a Raspberry Pi, Raspberry Pi camera (which recently got a nice resolution upgrade), and a some microscope eyepieces and objectives. Everything else is 3D printed, making this a very cheap and very accessible microscope that has some killer features.

Raspberry Pi Zero now with Camera Support, Still Only $5

The latest version (1.3) of everyone’s favorite $5 computer now sports a frequently requested feature: a camera connector. The Pi Zero will now use the same economical camera modules available for the full-sized Raspberry Pi units.

The price of the Pi Zero is unchanged at $5, but there is a small catch. While the Raspberry Pi camera modules themselves will work just fine on the Pi Zero, the usual camera cable they come with will not. The Pi Zero’s camera cable connector is a little smaller than the ones on the full-grown Pi, so it needs a special cable to interface the camera modules to the slightly smaller connector found on the Pi Zero.

This should be good news. The new connector has appeared because another production run is ramping up. Logic points to greater availability of the $5 wonder board, but we’re still not holding our breath.

Adafruit Pi Zero camera cable
Pi Zero with camera module connector cable. [Image source: Adafruit]
With the Pi Zero now able to use camera modules, perhaps camera-based Pi projects like these digital binoculars or time-lapse camera rigs can now get even smaller.

[via Engadget]

PiNoculars – A Farseeing Pi Camera

The Raspberry Pi camera provides a 5 megapixel resolution with still images of up to 2592 x 1944 and multiple video modes including 2592 x 1944 at 15 frames per second. With it being mounted on a small board it is ideal for using in hacks. [Josh Williams] mounted the camera on the lens of binoculars to capture some startling images, including this squirrel.

The camera is installed on a custom, laser cut mount that fastens to one eyepiece of the binoculars. The Pi itself is mounted above the binoculars. An LCD touch screen from Adafruit allows [Josh] to select the image and adjust the focus. Snapping pictures is done using either the touch screen or switches that come with the screen.

The Instructable [Josh] wrote is extremely detailed and includes two different ways of mounting the Pi on the binoculars. The quick and dirty method just straps on with tape. The highly engineered method delves into Inkscape to design a plywood mount that is laser cut. For portable operation, [Josh] uses one of the ubiquitous battery packs meant for USB charging.

Basic setup of the Pi and camera are in a video after the break.

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Raspberry Pi Laser Beam Profiler

[Anthony] at UCLA needed to verify the shape of a laser beam. Commercial units for this, as you would expect, are expensive. But a Raspberry Pi with a Pi Noir camera easily handles the task. Not only is the use of the Pi cool but so is the task – they are using lasers to cool molecules to study quantum effects. The Pi camera without the IR filter captures a wide bandwidth making it suitable for use with non-visible lasers. [Anthony] captures the beam along two axes and plots both curves on the LCD touchscreen. That data, based on the pictures, is also available on a host PC. All this in a super compact package with a 7″ touch screen display.

One reason I find this fascinating is I did something similar 1977 at the University of Rochester Laboratory for Laser Energetics. My project was measuring the energy cross-section of a laser beam. The research goal of the Laboratory was the study of inertial confinement laser fusion. While [Anthony] uses an entire camera my project was limited to a 1 dimensional array of charge coupled devices (CCD). The output went to a Tektronix storage terminal and was printed on thermal paper for reference. He uses Python running on the target system. My work used a Z80 development system the size of a tower PC to write my program in assembly language which was then executed on a single board computer. We’ve come a long way. My code is long gone but you can get [Anthony’s] on GitHub.