Making a monumental scientific breakthrough is really kind of its own reward. Even so, it’s always nice to get extra recognition in the form of unexpected money. For the 347 scientists around the world who made history when they captured the first image of a black hole, the event itself is pretty sweet. The cake of notoriety recently gained some icing, because the group has been awarded a $3 million Breakthrough Prize.
The prize, known as “the Oscars of science”, was created eight years ago with the goal of furthering scientific advancements in the areas of physical science, mathematics, and life science. Created by tech investor Yuri Milner, the Breakthrough Prize is funded by other deep-pocketed notables like Sergey Brin and the Zuckerbergs. This year’s theme is “seeing the invisible”. Prizes will also be awarded for discoveries toward non-opioid pain relievers and the study of neuro-degenerative disorders.
Each of the black hole imaging scientists will receive $8,645.53 when the prize is awarded in a televised ceremony on November 3rd, which is going down at NASA’s Ames Research Center in Mountain View, CA. In lieu of parading all 347 scientists across the stage, [Shep Doeleman] of the Harvard-Smithsonian Center for Astrophysics and Director of the Event Horizon Telescope project, will accept the award on their behalf.
What exactly are black holes, and how did they come about? Explore their origins with [Will Sweatman] in this feature from 2018.
Black hole wire frame CC0 Public Domain via Phys.org
Black hole image via NASA
Over the years many people have made an air quality monitor station, usually of some configuration which measures particulates (PM2.5 & PM10). Some will also measure ozone (O3), but very few will meet the requirements that will allow one to calculate the Air Quality Index (AQI) as used by the EPA and other organizations. [Ryan Kinnett]’s project is one of those AQI-capable stations.
The AQI requires the measurement of the aforementioned PM2.5 (µg/m3), PM10 (µg/m3) and O3 (ppb), but also CO (ppm), SO2 (ppb) and NO2 (ppb), all of which has to be done with specific sensitivities and tolerances. This means getting sensitive enough sensors that are also calibrated. [Ryan] found a company called Spec Sensors who sell sensors which are pretty much perfect for this goal.
Using Spec Sensor’s Ultra-Low Power Sensor Modules (ULPSM) for ozone, nitrogen-dioxide, carbon monoxide and sulfur dioxide, a BME280 for air temperature, pressure and relative humidity, as well as a Plantower PMS5003 laser particle counter and an ADS1115 ADC, a package was created that fit nicely alongside an ESP8266-based NodeMCU board, making for a convenient way to read out these sensors. The total one-off BOM cost is about $250.
The resulting data can be read out and the AQI calculated from them, giving the desired results. Originally [Ryan] had planned to take this sensor package along for a ride around Los Angeles, to get more AQI data than the EPA currently provides, but with the time it takes for the sensors to stabilize and average readings (1 hour) it would take a very long time to get the readings across a large area.
Ideally many of such nodes should be installed in the area, but this would be fairly costly, which raises for [Ryan] the question of how one could take this to the level of the Air Quality Citizen Science project in the LA area. Please leave your thoughts and any tips in the comments.
For serious data collection with weather sensors, a solar shield is crucial. The shield protects temperature and humidity sensors from direct sunlight, as well as rain and other inclement weather, without interfering with their operation. [Mare] managed to create an economical and effective shield for under three euros in materials.
It began with a stack of plastic saucers intended for the bottom of plant pots. Each of these is a lot like a small plate, but with high sides that made them perfect for this application. [Mare] cut the bottom of each saucer out with a small CNC machine, but the cut isn’t critical and a hand tool could also be used.
Three threaded rods, nuts, and some plastic spacers between each saucer yields the assembly you see here. When mounted correctly, the sensors on the inside are protected from direct exposure to the elements while still allowing airflow. As a result, the readings are more accurate and stable, and the sensors last longer.
The top of the shield is the perfect place to mount a UV and ambient light sensor board, and [Mare] has a low-cost DIY solution for that too. The sensor board is covered by a clear glass dish on top that protects the board without interfering with readings, and an o-ring seals the gap.
3D printing is fantastic for creating useful components, and has been instrumental in past weather station builds, but projects like these show not everything needs to be (nor should be) 3D printed.
Olive oil at its finest quality is a product that brings alive the Mediterranean cuisine of which it is a staple. Unfortunately for many of us not fortunate enough to possess our own olive grove, commercial olive oils are frequently adulterated, diluted with cheaper oils such as canola. As consumers we have no way of knowing this, other than the taste being a bit less pronounced. Food standards agencies use spectrophotometers to check the purity of oils, and [Daniel James Evans] has created such a device using a Raspberry Pi.
A spectrophotometer shines white light through a sample to be tested, splits the light up into a spectrum with a prism or diffraction grating, and measures the light level at each point in the spectrum to gain a spectral profile of the sample. Different samples can then be compared by overlaying their profiles and looking at any differences. This build shines the light from an LED through a sample of oil, splits the result with a diffraction grating, and captures the spectrum with a Raspberry Pi camera. Commercial instruments are usually calibrated by co-incidentally sampling a pure sample of the same solvent the test subject is dissolved in, in this case the calibration is done against a sample of pure olive oil. The software requires the user to identify the spectrum in the resulting photograph, before generating a curve.
From a basis of having worked with and maintained spectrophotometers in the distant past we would have expected to see an incandescent bulb rather than an LED for a flatter response, but since this is an oil identifier rather than a finely calibrated laboratory instrument this is probably less of an issue.
Over the years we’ve had quite a few spectrophotometer projects here, this Hackaday Prize entry from 2016 is just one of many.
Air pollution isn’t just about the unsightly haze in major cities. It can also pose a major health risk, particularly to those with vulnerable respiratory systems. A major part of hazardous pollution is particulate matter, tiny solid particles suspended in the air. Particulate pollution levels are of great interest to health authorities worldwide, and [niriho] decided to build a monitoring rig of their own.
Particulate matter is measured by an SDS011 particulate matter sensor. This device contains a laser, and detects light scattered by airborne particles in order to determine the level of particulate pollution in PM2.5 and PM10 ranges. The build makes use of an ESP32 as the brains of the operation, chosen for its onboard networking hardware. This makes remotely monitoring the system easy. Data is then uploaded to a Cacti instance, which handles logging and graphing of the data.
For those concerned about air quality, or those who are distrustful of official government numbers, this build is a great way to get a clear read on pollution in the local area. You might even consider becoming a part of a wider monitoring network!
The concept behind non-line-of-sight (NLOS) imaging seems fairly easy to grasp: a laser bounces photons off a surface that illuminate objects that are within in sight of that surface, but not of the imaging equipment. The photons that are then reflected or refracted by the hidden object make their way back to the laser’s location, where they are captured and processed to form an image. Essentially this allows one to use any surface as a mirror to look around corners.
Main disadvantage with this method has been the low resolution and high susceptibility to noise. This led a team at Stanford University to experiment with ways to improve this. As detailed in an interview by Tech Briefs with graduate student [David Lindell], a major improvement came from an ultra-fast shutter solution that blocks out most of the photons that return from the wall that is being illuminated, preventing the photons reflected by the object from getting drowned out by this noise.
The key to getting the imaging quality desired, including with glossy and otherwise hard to image objects, was this f-k migration algorithm. As explained in the video that is embedded after the break, they took a look at what methods are used in the field of seismology, where vibrations are used to image what is inside the Earth’s crust, as well as synthetic aperture radar and similar. The resulting algorithm uses a sequence of Fourier transformation, spectrum resampling and interpolation, and the inverse Fourier transform to process the received data into a usable image.
This is not a new topic; we covered a simple implementation of this all the way back in 2011, as well as a project by UK researchers in 2015. This new research shows obvious improvements, making this kind of technology ever more viable for practical applications.
Continue reading “Looking Around Corners With F-K Migration”
Hackers often have broad interests across the sciences, of which nuclear topics are no exception. The Geiger counter remains a popular build, and could be a handy tool to have in a time of rising tensions between nuclear powers. [Leonora Tindall] had tinkered with basic units, but wanted a better idea of actual radiation levels in her area. Thus began the build!
The project began by leveraging the Geiger counter kit from the Mighty Ohm. [Leonora] had built one of these successfully, but wished for a visual readout to supplement the foreboding ticking noises from the device. This was achieved by installing a Metro Mini microcontroller along with a 4-character, 14-segment alphanumeric display. This, along with the cardboard enclosure, makes the build look like a prop from an 80s hacker movie. Very fitting for the Cold War-era technology at work.
By using a pre-built kit and upgrading it with display hardware, [Leonora] now has readings at a glance without having to reinvent the wheel and design her own board from scratch. Of course, if you’re thinking of taking on a more complex build, you might consider a scintillation detector instead.