Science News April 19

[This is a transcript with references.]

Welcome everyone to this week’s science news. Today we’ll talk about artificial intelligence that rediscovered Kepler’s laws, solar flares in the laboratory, nano-surgery with tiny magnets, a candidate for a strange star, what the new JUICE spacecraft will look for, how much air pollution is avoided by nuclear power, a software that creates 3d models from 2d drawings, an estimate for how much rare earth metals the energy transition will need, and of course the telephone will ring.

A team of machine learning scientists from the U.S. and the UK has developed an artificial intelligence that rediscovered Kepler’s 3rd Law of planetary motion using equations.

The idea to use artificial intelligence to discover natural laws from data is not new and it’s been done before. Using software to extract patterns from data and then extrapolating them is a straightforward application of machine learning. But we’d like to have a neat set of equations that describes the data, and not some big machine learning code that we don’t really know what it does.

In the new work they have now made a big step towards that. They’ve developed an algorithm that works like you expect a theoretical physicist to work. I mean, someone’s gotta do it, right?  This algorithm analyses the data, develops hypotheses, and then tries to find a compact formula to express the hypothesis so that it supports the data.

They fed their program with three real-world data sets: NASA’s fact sheet on planets from our own solar system, NASA’s data from the solar-system TRAPPIST-1, and records of the orbits of five binary stars.

The program then tried different mathematical relations between the input parameters – addition, subtraction, multiplication, square roots and so on – and checked how well any of those explain the data. It correctly hit on Kepler’s third Law, that’s a relation between the distance between two bodies – the d in the formula here – their mass, that’s m, and their orbital periods, that’s p. The error values were impressively small.

They called their method AI-Descartes, after the French mathematician René Descartes who championed logical deduction as a scientific method. The system also correctly reproduced Langmuir’s Nobel-Prize-winning work on gas molecules, and Einstein’s law of relativistic time-dilation. Albert is shocked.

Physicists at Caltech have simulated solar flares in the laboratory.

Solar flares are huge and violent outbursts of plasma from the surface of the sun. They emit x-rays and streams of highly energetic particles. Most of those particles are charged, and if they hit Earth, they can damage satellites and electronic devices and even disrupt electrical grids.  Just exactly how solar flares happen is unclear. We know it’s got something to do with the magnetic fields forming arcs that twist and then rip apart, but the exact mechanism has remained a mystery. Trouble is, it’s difficult to do experiments on the surface of the sun.

So, these physicists set out to replicate the plasma arcs in somewhat smaller versions and then prod them into releasing radiation. Here is the setup. They applied high voltage to gas to create multiple strands of ionized plasma loops. The plasma is guided by the magnetic flux tubes much like on the surface of the sun.

The loops become braided which is also believed to happen on the sun. With enough current, a bulge appears in a strand, it lengthens and thins out and then snaps. At that point, the voltage drops because resistance increases. The energy of the whole circuit gets dumped into this area of high resistance, accelerating the plasma, and producing a burst of x-rays. They compared this to observations of a solar flare in 2011 and found a similar sequence of events. You see, if you have a PhD in physics, you’ll even get paid for violent outbursts.

A team of scientists from Canada and China has developed a method to conduct nanosurgery on brain cancer using tiny magnets.

Basically, the method infiltrates cancer cells with carbon nanotubes. It then uses a magnet to rotate the nanotubes which destroys the cells from within. The team worked on mice that had been injected with cells of glioblastoma, a type of cancer that is notorious for being aggressive and often resistant to chemotherapy. It’s the deadliest form of brain cancer. The median survival rate for someone diagnosed with it is 15 months.

Once the mice had developed tumours, the team injected the nanoparticles. The particles were coated with an antibody that’s attracted to a protein in the cancer cell, so the cells absorbed them. It’s sort of a Trojan Horse approach, inviting the enemy inside.

A day later, the researchers put the mice in a rotating magnetic field – at 20 milli Teslas and 20 Hertz – for 30 minutes.They repeated this every two days, five times in total. You can see the difference it made for the tumours here in the diagram. The tumour on the left hasn’t been treated with the magnet. It is more than 10 square millimetres. On the right, the tumour has been treated. It is about 3 square millimetres.

The process worked on all types of glioblastomas, including those that had become resistant to chemotherapies. It's a precision treatment that could potentially be adapted for other cancers, but please don’t try it at home.

A team of Brazilian astronomers may have found an example of a strange star, and, no, it’s not that one woman in Hollywood who isn’t on a diet.

A strange star is a ball of hot plasma that isn’t just weird, is contains strange quarks. The neutrons and protons that atomic nuclei are made of usually contain only up and down quarks, because those are the lightest ones. But if the temperature and pressure are high enough, strange quarks will also be produced. Researchers have searched extensively for evidence of strange quark matter over the past couple of decades, including in compact stars.

This potential strange star is a little more than 8 thousand light years away in the constellation Scorpius. It’s inside the remains of a supernova and estimated to be between two thousand and six thousand years old.  t was examined recently by a team of astrophysicists in Tübingen, Germany. They expected it to be a neutron star because those are quite commonly born within supernovae.

A supernova explosion leaves behind a lot of matter that collapses under its own gravitational pull. This forces electrons into the atomic nuclei, where they turn protons into neutrons. So far, we believe we understand what’s happening. But no one really knows just what all this nuclear matter does.

The thing is now that the total mass of the object determines the gravitational pull and that, together with the rotation determines what the matter does. For matter to form a neutron star, you need a certain minimum mass, otherwise you get a white dwarf

This weird new star, named XMMU with a long number, falls short of the mass required for a neutron star, with a mass of just about three quarters the mass of our sun, but its radius is too small for it to be a white dwarf. However, if it was a strange star, then it should be cooler because this strange quark matter radiates more efficiently. It’s marked in red on this graph. The researchers now say that it could be that the strange quarks have formed pairs which makes them radiate less efficiently again.

On the question of why the star’s mass is so low, the team suggests that the collapse of the supernova could have produced a detonation that would force the star to shed a lot of its outer core in a neutrino-driven wind, and that would fit with theoretical models.

So, it’s far from confirmation. It’s more a way of trying to make an unwilling observation fit to a cherished hypothesis.

Mr Wayne, thanks for calling in.

Bat news? Yes, I do have some bat news this week.

Scientists discovered two bat skeletons in western Wyoming and they’re believed to be the oldest ever at 52 point 5 million years!

No, they didn’t leave a last will. Why are you asking. Hello?

The JUICE spacecraft took off last week to head to Jupiter and some of its moons. Unfortunately, the mess that is English pronunciation hides the fact that there’s ICE in JUICE. The acronym sort of stands for Jupiter Icy Moons Explorer. It’s a mission of the European Space Agency that will look at three of the icy moons Galileo discovered in 1609, the so-called Galilean moons.

They’re not terrifically interested in Io, the one on the left. But they’re keenly interested in the other three: Europa, Ganymede and Callisto.

The mission is a real push to find another habitable planet and signs of past life within our own solar system. Not on Jupiter, because however gorgeous it looks, it’s known for its toxic gases, crushing pressures and doesn’t even have a stable surface. But those three moons are promising. They have icy crusts, seem to have magnetic fields, and are believed to have salty oceans underneath the ice that might host life.

Ganymede is especially interesting. These are images taken by the Juno mission in 2021. It’s not just the biggest moon in the solar system with a radius slightly less than half that of Earth. It also has a magnetic field, likely produced by a molten iron core. And while a magnetic field is not a prerequisite for life, it wouldn’t hurt, because it means the moon could have an atmosphere and protection from galactic radiation.

However, it’ll take about 8 years for JUICE to get to Jupiter, so we’ll have to be patient for a bit longer.

Scientists from Cornell University and Switzerland have made an estimate of how much of five rare metals will be needed to transition to electric vehicles by 2050, when the world is supposed to be at net zero.

They looked at forty eight countries which host sixty one percent of the world’s population, including the U.S., China, and India. These countries have all pledged to electrify transportation. The European Union has banned the sale of new petrol and diesel cars from 2035. And the U.S. wants to follow suit.

The authors of this paper assume that vehicle ownership of all types will keep growing, particularly in China and India, reaching two point three nine billion in the 48 countries by 2050, almost three times more than in 2010.

But like hydrogen fuel cells, electric vehicles need a lot of metals, and not all of them are abundant on Earth. That includes lithium, nickel, cobalt, manganese and the six platinum group metals.

As the climate crisis pushes countries to ditch combustion engines, the demand for these metals will skyrocket.

Take lithium. The research estimate that the need for that metal will rise more than two thousand nine hundred percent if forty per cent of the vehicles on the road in those countries is electrical by 2050. If all vehicles are electrical, then the rise is more than seven thousand per cent.

It’s similar for each of the other metals, the numbers are staggering.

The authors say the biggest immediate problems are lithium, cobalt and nickel. It’s not just that supply will run short, it’s also that some of the biggest metal deposits are in political unstable countries. Chile, Congo, Indonesia, Brazil, Argentina and South Africa.   

And this doesn’t take into account the problem that the existing electric grids won’t be able to power that many cars. But that’s another story that we shall talk about another time.

A team of computer scientists at Carnegie Mellon University in Pittsburgh has developed a machine-learning tool that can turn a rough sketch into a virtual 3D model.

It’s been trained on a lot of images of 3-D objects, including cars, cats and human faces. It takes a sketch and tries to combine it with what it’s learned, creating a computer model that can be rotated in three dimensions.

Here’s how it makes 3D faces from 2D sketches.  You can control the model in real time. It can for example create cats and cars, from label maps and simple sketches.

Or you can draw the 2D outline and then fold it into a 3D car.

Hi Elon,

No, no it’s a great car. We’ve put the soup cans together with the cereal boxes to grow one, too.

Love you too.

A group of American researchers has calculated how much air pollution would be caused by phasing out nuclear power in the United States and how many deaths that would cause.

The study comes at a time when many countries are grappling with what to do about nuclear power. Trying to decarbonize the economy and cope with gas shortages resulting the war in Ukraine and switching off nuclear power seems a bit too much too fast.

But different countries go different paths. The U.K. is ramping up nuclear power. Germany has just this weekend shut down its remaining three nuclear power plants, part of a pledge made after the Fukushima nuclear accident in 2011.

For this new study, the authors coupled an energy grid optimization model with a chemical transport model and then laid it over population density maps across the U.S. The energy grid model calculates the cheapest types of available energy that would fill in power needs, hour by hour, region by region.

They discovered that just shutting down nuclear, means more fossil fuels. No surprise there. In fact, that’s what has happened in Germany with the earlier shut downs of nuclear plants – a shift to coal and importing electricity.  An additional 5200 Americans would die from pollution in the first year in this first scenario.

You can see it represented in the increase in red on the maps on the right of the screen. The people affected would disproportionately be Black Americans because they are more likely to live near fossil fuel plants. Increasing renewables can prevent that from happening, but the authors point out that this needs to be a planned transition and not just shutting nuclear off leaving the rest to the market.

So, yeah. Keep on dusting those solar panels.