Does Hot Water Freeze Faster Than Cold? Debate Continues Over The Mpemba Effect

Does hot water freeze faster than cold water? On its face this idea seems like it should be ridiculously simple to test, and even easier to intuit, but this question has in fact had physicists arguing for decades.

Erasto Mpemba’s observations initiated decades of research into the Mpemba effect: whether a liquid (typically water) which is initially hot can freeze faster than the same liquid which begins cold.

There’s a name for the phenomenon of something hot freezing faster than something cold: the Mpemba effect,  named for Erasto Mpemba (pictured above) who as a teenager in Tanzania witnessed something strange in high school in the 1960s. His class was making ice cream, and in a rush to secure the last available ice tray, Mpemba skipped waiting for his boiled milk-and-sugar mixture to cool to room temperature first, like everyone else had done. An hour and a half later, his mixture had frozen into ice cream whereas the other students’ samples remained a thick liquid slurry.

Puzzled by this result, Mpemba asked his physics teacher what was going on. He was told “You were confused. That cannot happen.” Mpemba wasn’t convinced by that answer, and his observations ultimately led to decades of research.

What makes this question so hard to nail down? Among many of the issues complicating exactly how to measure such a thing is that water frankly has some odd properties; it is less dense as a solid, and it is also possible for its solid and liquid phases to exist at the same temperature. Also, water in the process of freezing is not in equilibrium, and how exactly things act as they relax into equilibrium is a process for which — physics-wise — we lack a good theory. Practically speaking, it’s also a challenge how to even accurately and meaningfully measure the temperature of a system that is not in equilibrium.

But there is experimental evidence showing that the Mpemba effect can occur, at least in principle. How this can happen seems to come down to the idea that a hot system (having more energy) is able to occupy and explore more configurations, potentially triggering states that act as a kind of shortcut or bypass to a final equilibrium. In this way, something that starts further away from final equilibrium could overtake something starting from closer.

But does the Mpemba effect actually exist — for example, in water — in a meaningful way? Not everyone is convinced, but if nothing else, it has sure driven a lot of research into nonequilibrium systems.

Why not try your own hand at investigating the Mpemba effect? After all, working to prove someone wrong is a time-honored pastime of humanity, surpassed only in popularity by the tradition of dismissing others’ findings, observations, or results without lifting a finger of your own. Just remember to stick to the scientific method. After all, people have already put time and effort into seriously determining whether magnets clean clothes better than soap, so surely the Mpemba effect is worth some attention.

A portable water quality monitor

Monitoring Water Quality Using Lots Of Sensors And Machine Learning

Despite great progress over the past century, more than a billion people still don’t have access to clean drinking water today. Much of the water on Earth’s surface is polluted, but it’s not always easy to tell a dirty stream from a clean one. Professional kit for water analysis can be expensive, which is why [kutluhan_aktar] decided to design a portable, internet-connected water pollution monitor.

A bowl of water with several sensors immersed in it, and a blue box connected to them
Calibrating the system using a bowl of clean water.

There is no single parameter that determines the quality of a water sample, so the pollution monitor has no less than five different sensors. These can determine the oxidation-reduction potential (a chemical indicator), the pH (acidity), total dissolved solids (mainly salts), turbidity (suspended particles) and temperature. To combine all these numbers into a simple “yes/maybe/no” indicator, [kutluhan] trained a neural network with data gathered from a large number of places around his hometown.

This neural network runs on an Arduino MKR GSM 1400 module. While not a typical platform for AI applications, the neural network runs just fine on it thanks to the Neuton framework, a software plaform designed to run machine learning applications on microcontroller systems like the Arduino. It also has a GSM/3G modem, allowing it to report the measured water quality to a central database.

All of this is housed in a 3D-printed enclosure that makes the whole setup easy to carry and operate in any location. Collecting data across a wide area should help to locate sources of pollution, and hopefully contribute to an improvement in water quality for everyone. Here at Hackaday we love citizen science initiatives like this: previously we’ve featured projects to measure things as varied as air quality and ocean waves.

An OpenBikeSensor

OpenBikeSensor Measures Close Calls

Cycling is fun, healthy, and good for the environment. But unfortunately it’s not always the safest of activities, as inconsiderate drivers can be a significant hazard to cyclists. Several countries, including Germany, France, and Belgium have introduced legislation mandating a minimum passing distance of at least 1.5 meters between cars and bikes. Enforcing such a rule is tricky however, and without accurate data on average passing distances it’s hard to know how many drivers are following it.

Enter OpenBikeSensor, an open-source hardware and community science project designed to gather exactly this information. Currently in its prototype phase, it aims to make a simple bike-mounted sensor that measures the lateral distance to any passing vehicles. The resulting data is collected online to generate maps highlighting danger zones, which can ultimately be used by city planners to improve cycling infrastructure.

The hardware is based around a set of ultrasonic sensors that measure the lateral distance to any large object. A GPS module keeps track of the bike’s location, while an ESP32 reads out the data and stores it onto an SD card. The user interface consists of a handlebar-mounted display that shows the system’s status. There’s also a button that the user needs to press any time they are passed by a vehicle: this will trigger a measurement and log the location. Once back home, the user can connect the OpenBikeSensor to their WiFi network and download their trip data.

The initial results look promising, and any project that gets people cycling and tinkering with electronics at the same time is worth looking into. It’s not the first time we’ve seen bike-mounted sensors either: people have designed their own sensors to measure air pollution in South America, or simply their own bike’s speed or tire pressure. Continue reading “OpenBikeSensor Measures Close Calls”

How The Hunga Tonga Volcano Eruption Was Felt Around The World

On the 14th of January, 2022, the Hunga Tonga-Hunga Ha’apai volcano began a gigantic eruption that would go on to peak in ferocity the next day. The uninhabited island volcano would quickly make headlines as the country of Tonga was cut off the world and tsunamis bore out from the eurption zone.

In a volcanic event of this size, the effects can be felt around the world. With modern instruments, they can be properly understood too. Let’s take a look at how the effects of the Hunga Tonga eruption were captured and measured across the globe.

Continue reading “How The Hunga Tonga Volcano Eruption Was Felt Around The World”

Anr air quality sensor mounted on a bike's handlebar

Measuring Air Quality Using Mobile Sensors For The Masses

Poor air quality is a major problem for city dwellers the world over. Dust, smoke, particles and noxious gases from vehicles, industry and agriculture makes many megacities downright hazardous to live in. Pinpointing the source of pollution and developing strategies for mitigation requires accurate data on pollutant levels, but obtaining these numbers is not always easy.

Enter CanAirIO, a citizen science project that aims to gather air quality data from around the world by putting sensors into the hands of as many people as possible. Its team has developed two different sensor nodes for this purpose: an indoor one that can measure CO2, and a mobile one that can measure particulate matter (PM) levels. Both versions are powered by an ESP32 microcontroller that reads out the air quality sensors and connects to the Internet using WiFi or BlueTooth. The data can then be shared online to create detailed maps showing local variations in air quality.

The design of the sensor nodes is fully open-source, allowing anyone with basic electronic skills to build them. The sensors are a Sensirion SCD30 for CO2 measurement and an SPS30 for PM levels. The mobile version comes with a neat 3D-printed enclosure that can be mounted on a bike’s handlebar, enabling the user to quickly gather data around their neighbourhood. A mobile app simplifies setting up the sensors and sharing the data.

The project has already been successful in gathering detailed data in the city of Bogotá, Colombia, and will no doubt prove useful in many other pollution hotspots around the world. We’ve seen similar community efforts to monitor air pollution and even radiation in various places, both showing how relatively simple devices can help to make a difference in people’s wellbeing. Continue reading “Measuring Air Quality Using Mobile Sensors For The Masses”

Astro Pi Mk II, The New Raspberry Pi Hardware Headed To The Space Station

Back in 2015, European Space Agency (ESA) astronaut Tim Peake brought a pair of specially equipped Raspberry Pi computers, nicknamed Izzy and Ed, onto the International Space Station and invited students back on Earth to develop software for them as part of the Astro Pi Challenge. To date, more than 50,000 young people have had their code run on one of the single-board computers; making them arguably the most popular, and surely the most traveled, Raspberry Pis in the solar system.

While Izzy and Ed are still going strong, the ESA has decided it’s about time these veteran Raspberries finally get the retirement they’re due. Set to make the journey to the ISS in December aboard a SpaceX Cargo Dragon, the new Astro Pi MK II hardware looks quite similar to the original 2015 version at first glance. But a peek inside its 6063-grade aluminium flight case reveals plenty of new and improved gear, including a Raspberry Pi 4 Model B with 8 GB RAM.

The beefier hardware will no doubt be appreciated by students looking to push the envelope. While the majority of Python programs submitted to the Astro Pi program did little more than poll the current reading from the unit’s temperature or humidity sensors and scroll messages for the astronauts on the Astro Pi’s LED matrix, some of the more advanced projects were aimed at performing legitimate space research. From using the onboard camera to image the Earth and make weather predictions to attempting to map the planet’s magnetic field, code submitted from teams of older students will certainly benefit from the improved computational performance and expanded RAM of the newest Pi.

As with the original Astro Pi, the ESA and the Raspberry Pi Foundation have shared plenty of technical details about these space-rated Linux boxes. After all, students are expected to develop and test their code on essentially the same hardware down here on Earth before it gets beamed up to the orbiting computers. So let’s take a quick look at the new hardware inside Astro Pi MK II, and what sort of research it should enable for students in 2022 and beyond.

Continue reading “Astro Pi Mk II, The New Raspberry Pi Hardware Headed To The Space Station”

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Hackaday Links: March 14, 2021

It’ll be Pi Day when this article goes live, at least for approximately half the globe west of the prime meridian. We always enjoy Pi Day, not least for the excuse to enjoy pie and other disc-shaped foods. It’s also cool to ponder the mysteries of a transcendental number, which usually get a good treatment by the math YouTube community. This year was no disappointment in this regard, as we found two good pi-related videos, both by Matt Parker over at Standup Maths. The first one deals with raising pi to the pi to the pi to the pi and how that may or may not result in an integer that’s tens of trillions of digits long. The second and more entertaining video is a collaboration with Steve Mould which aims to estimate the value of pi by measuring the volume of a molecular monolayer of oleic acid floating on water. The process was really interesting and the results were surprisingly accurate; this might make a good exercise to do with kids to show them what pi is all about.

Remember basic physics and first being exposed to the formula for universal gravitation? We sure do, and we remember thinking that it should be possible to calculate the force between us and our classmates. It is, of course, but actually measuring the attractive force would be another thing entirely. But researchers have done just that, using objects substantially smaller than the average high school student: two 2-mm gold balls. The apparatus the Austrian researchers built used 90-milligram gold balls, one stationary and one on a suspended arm. The acceleration between the two moves the suspended ball, which pivots a mirror attached to the arm to deflect a laser beam. That they were able to tease a signal from the background noise of electrostatic, seismic, and hydrodynamic forces is quite a technical feat.

We noticed a lot of interest in the Antikythera mechanism this week, which was apparently caused by the announcement of the first-ever complete computational model of the ancient device’s inner workings. The team from University College London used all the available data gleaned from the 82 known fragments of the mechanism to produce a working model of the mechanism in software. This in turn was used to create some wonderful CGI animations of the mechanism at work — this video is well worth the half-hour it takes to watch. The UCL team says they’re now at work building a replica of the mechanism using modern techniques. One of the team says he has some doubts that ancient construction methods could have resulted in some of the finer pieces of the mechanism, like the concentric axles needed for some parts. We think our friend Clickspring might have something to say about that, as he seems to be doing pretty well building his replica using nothing but tools and methods that were available to the original maker. And by doing so, he managed to discern a previously unknown feature of the mechanism.

We got a tip recently that JOGL, or Just One Giant Lab, is offering microgrants for open-source science projects aimed at tackling the problems of COVID-19. The grants are for 4,000€ and require a minimal application and reporting process. The window for application is closing, though — March 21 is the deadline. If you’ve got an open-source COVID-19 project that could benefit from a cash infusion to bring to fruition, this might be your chance.

And finally, we stumbled across a video highlighting some of the darker aspects of amateur radio, particularly those who go through tremendous expense and effort just to be a pain in the ass. The story centers around the Mt. Diablo repeater, an amateur radio repeater located in California. Apparently someone took offense at the topics of conversation on the machine, and deployed what they called the “Annoy-o-Tron” to express their displeasure. The device consisted of a Baofeng transceiver, a cheap MP3 player loaded with obnoxious content, and a battery. Encased in epoxy resin and concrete inside a plastic ammo can, the jammer lugged the beast up a hill 20 miles (32 km) from the repeater, trained a simple Yagi antenna toward the site, and walked away. It lasted for three days and while the amateurs complained about the misuse of their repeater, they apparently didn’t do a thing about it. The jammer was retrieved six weeks after the fact and hasn’t been heard from since.