Now that my students are wrapping up their summer research activities, it’s time to share some of my new designs. This one is inspired by my students – they wanted to design and 3D print keychains – and Rozenn’s request to have name tags for our plants.
Read on to see how I designed these, which involved a little bit of magic for the swash ornament.
I wrote this piece for a Wolfram technology blog a while back. It’s a bit Mathematica centric for that reason. The blog got delayed, then the editor left the company, then the new editor blew off the piece and I got tired of waiting, so here it is.
Not so long ago…
In 2012, the Raspberry Pi Foundation released the Raspberry pi, an affordable, credit-card sized computer originally designed to help younger students learn programming. It peels away the black-box of computers and exposes users to the fascinating world of how software controls hardware that control sensors that interact with the user’s surroundings. The computer science community refers to this idea as physical computing. As an Analytical Chemist, I call it a scientific instrument. Since much of my research and teaching deals with scientific instrumentation, the Raspberry Pi has turned out to be an excellent platform for exploring new ways to make measurements.
I am teaching Mandy to sing (sort of). Here’s Mandy playing along to Carol of the Bells in what may be the worlds “first” Periodic Table spectrum visualizer. Now, before we blow up the Twitter sphere with allegations that Mandy belongs on the Top Ten List of Most Infamous Lip Syncing incidents, I’m not claiming that this is live. Mandy wasn’t designed to do real-time spectrum analysis (she’s a Periodic Table, after all) but I wanted to see if some geeky visualizations would be possible. So, I created my own version of Carol of the Bells (written in Sonic-Pi) and then analyzed the audio file using Mathematica, which has a neat function, SpectrogramArray, that provides easy access to the frequencies in an audio file. I then binned the frequencies into 118 buckets – one for each element on the periodic table, and converted the intensities into colors (blue for high amplitude, red for low amplitude). I probably should have thought a bit more about which elements should display which frequencies, but time was running short so I simply made the heavier elements have the lower frequencies. In any case – enjoy.
The staff over at the Wolfram Community have recognized Mandy – the bright Periodic Table as one of their Staff Picks. The forum post, which can be viewed here, highlights how Mathematica was used in various parts of the project. In the design phase, Mathematica was used to create the layout of the periodic table, which then could be exported to Inkscape/Adobe Illustrator for final processing of an image that could be recognized by the laser cutter. The curated data provided by the Wolfram platform is used to create the trends, and I used some notebook Manipulate commands to visualize the RGB-LED output for (rapid) rapid prototyping. The actual operation of Mandy uses a Python-based speech recognition script that calls on Mathematica to communicate to the Arduino controlling all of the LEDs. (Yes, this is an ‘everything but the kitchen sink’ project.)
About six months ago, I started working on a project I like to call my piece de resistance. It combines a number of maker skills that I’ve learned over the past few years. I call her Mandy, and she’s a laser-cut periodic table that has a bunch of three-color LEDS, an Arduino that controls the individually addressable LEDs, and a Raspberry Pi that stores information about the elements. To make it stand out from being “just another bright periodic table”, I added a voice activation component, so Mandy is able to display different periodic trends at your verbal command!
I’m getting ready to move to a different part of the country, so I do not have time to provide more information about Mandy. In the meanwhile, I created a teaser-trailer for your (OK, my) personal enjoyment.
Happy #RealTimeChem week everybody. What, you don’t know what it is? Neither did I, untill I happened to read about it over at Compound Interest . (You guessed it, I’ve got lots of grading to do so I’m procrastinating again.) Since the theme this year centers on the four new elements that have been added to the periodic table, and I have an affinity for the table and all its secrets, I thought it might be fun to take advantage of the periodic properties of the table and predict some of the characteristics of the new elements.
Wolfram’s Mathematica can run on a $5 Raspberry Pi zero. While it may be painfully slow, it does open up opportunities to use Mathematica in low-power, remote-sensing applications. This blog post is a first in a series highlighting the design challenges I’ve encountered (and in some cases overcome) building Mathematica on Pi (MoP) devices. (Hey, I think I just created a new acronym.)
The Go! Link from Vernier Software & Technology (Vernier), is a USB adapter for their proprietary sensors which also provides some basic features such as a buffer, sensor auto-identification and raw voltage reading conversion. Vernier provides a software development kit which allows programmers to use Go! devices in their own systems. Since Wolfram’s Mathematica software became available on the Raspberry Pi, I have been thinking about how one can build a flexible sensor system using Vernier’s products and based on the inexpensive computer and the powerful data analysis and visualization tools of Mathematica. This project isn’t new, and my earlier attempts were highlighted on the Raspberry Pi blog and I recently announced a previous version of this software package. What I’m presenting now is a more user-friendly system that makes data collection easy through the device driver framework incorporated into Mathematica.
GoIOLink is the flagship component of a project I call VernierPiLink which seeks to provide a variety of Vernier-sensor-Raspberry-Pi integration resources. It relies on VS&T’s Go!Link USB adapter to perform the physical connection between an analog Vernier sensor and the Raspberry Pi. On the software side, I am using the Go! I/O software development kit also from VS&T and the Wolfram Language which comes free (for non-commercial use) on the Raspberry Pi.
In the previous iteration of my website, I had some details about installing the Vernier Go software development kit on the Raspberry Pi and then using Mathematica to visualize the results. Here is an updated set of instructions which is a little more straightforward.