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Although the term “quantum computer” might suggest a miniature, sleek device, the latest incarnations are a far cry from anything available in the Apple Store. In a laboratory just 60 kilometers north of New York City, scientists are running a fledgling quantum computer through its paces — and the whole package looks like something that might be found in a dark corner of a basement. The cooling system that envelops the computer is about the size and shape of a household water heater.

Beneath that clunky exterior sits the heart of the computer, the quantum processor, a tiny, precisely engineered chip about a centimeter on each side. Chilled to temperatures just above absolute zero, the computer — made by IBM and housed at the company’s Thomas J. Watson Research Center in Yorktown Heights, N.Y. — comprises 16 quantum bits, or qubits, enough for only simple calculations.

If this computer can be scaled up, though, it could transcend current limits of computation. Computers based on the physics of the super­small can solve puzzles no other computer can — at least in theory — because quantum entities behave unlike anything in a larger realm.

Quantum computers aren’t putting standard computers to shame just yet. The most advanced computers are working with fewer than two dozen qubits. But teams from industry and academia are working on expanding their own versions of quantum computers to 50 or 100 qubits, enough to perform certain calculations that the most powerful supercomputers can’t pull off.
The race is on to reach that milestone, known as “quantum supremacy.” Scientists should meet this goal within a couple of years, says quantum physicist David Schuster of the University of Chicago. “There’s no reason that I see that it won’t work.”
But supremacy is only an initial step, a symbolic marker akin to sticking a flagpole into the ground of an unexplored landscape. The first tasks where quantum computers prevail will be contrived problems set up to be difficult for a standard computer but easy for a quantum one. Eventually, the hope is, the computers will become prized tools of scientists and businesses.

Attention-getting ideas
Some of the first useful problems quantum computers will probably tackle will be to simulate small molecules or chemical reactions. From there, the computers could go on to speed the search for new drugs or kick-start the development of energy-saving catalysts to accelerate chemical reactions. To find the best material for a particular job, quantum computers could search through millions of possibilities to pinpoint the ideal choice, for example, ultrastrong polymers for use in airplane wings. Advertisers could use a quantum algorithm to improve their product recommendations — dishing out an ad for that new cell phone just when you’re on the verge of purchasing one.

Quantum computers could provide a boost to machine learning, too, allowing for nearly flawless handwriting recognition or helping self-driving cars assess the flood of data pouring in from their sensors to swerve away from a child running into the street. And scientists might use quantum computers to explore exotic realms of physics, simulating what might happen deep inside a black hole, for example.

But quantum computers won’t reach their real potential — which will require harnessing the power of millions of qubits — for more than a decade. Exactly what possibilities exist for the long-term future of quantum computers is still up in the air.

The outlook is similar to the patchy vision that surrounded the development of standard computers — which quantum scientists refer to as “classical” computers — in the middle of the 20th century. When they began to tinker with electronic computers, scientists couldn’t fathom all of the eventual applications; they just knew the machines possessed great power. From that initial promise, classical computers have become indispensable in science and business, dominating daily life, with handheld smartphones becoming constant companions (SN: 4/1/17, p. 18).
Since the 1980s, when the idea of a quantum computer first attracted interest, progress has come in fits and starts. Without the ability to create real quantum computers, the work remained theoretical, and it wasn’t clear when — or if — quantum computations would be achievable. Now, with the small quantum computers at hand, and new developments coming swiftly, scientists and corporations are preparing for a new technology that finally seems within reach.

“Companies are really paying attention,” Microsoft’s Krysta Svore said March 13 in New Orleans during a packed session at a meeting of the American Physical Society. Enthusiastic physicists filled the room and huddled at the doorways, straining to hear as she spoke. Svore and her team are exploring what these nascent quantum computers might eventually be capable of. “We’re very excited about the potential to really revolutionize … what we can compute.”

Anatomy of a qubit
Quantum computing’s promise is rooted in quantum mechanics, the counterintuitive physics that governs tiny entities such as atoms, electrons and molecules. The basic element of a quantum computer is the qubit (pronounced “CUE-bit”). Unlike a standard computer bit, which can take on a value of 0 or 1, a qubit can be 0, 1 or a combination of the two — a sort of purgatory between 0 and 1 known as a quantum super­position. When a qubit is measured, there’s some chance of getting 0 and some chance of getting 1. But before it’s measured, it’s both 0 and 1.

Because qubits can represent 0 and 1 simultaneously, they can encode a wealth of information. In computations, both possibilities — 0 and 1 — are operated on at the same time, allowing for a sort of parallel computation that speeds up solutions.

Another qubit quirk: Their properties can be intertwined through the quantum phenomenon of entanglement (SN: 4/29/17, p. 8). A measurement of one qubit in an entangled pair instantly reveals the value of its partner, even if they are far apart — what Albert Einstein called “spooky action at a distance.”
Such weird quantum properties can make for superefficient calculations. But the approach won’t speed up solutions for every problem thrown at it. Quantum calculators are particularly suited to certain types of puzzles, the kind for which correct answers can be selected by a process called quantum interference. Through quantum interference, the correct answer is amplified while others are canceled out, like sets of ripples meeting one another in a lake, causing some peaks to become larger and others to disappear.

One of the most famous potential uses for quantum computers is breaking up large integers into their prime factors. For classical computers, this task is so difficult that credit card data and other sensitive information are secured via encryption based on factoring numbers. Eventually, a large enough quantum computer could break this type of encryption, factoring numbers that would take millions of years for a classical computer to crack.

Quantum computers also promise to speed up searches, using qubits to more efficiently pick out an information needle in a data haystack.

Qubits can be made using a variety of materials, including ions, silicon or superconductors, which conduct electricity without resistance. Unfortunately, none of these technologies allow for a computer that will fit easily on a desktop. Though the computer chips themselves are tiny, they depend on large cooling systems, vacuum chambers or other bulky equipment to maintain the delicate quantum properties of the qubits. Quantum computers will probably be confined to specialized laboratories for the foreseeable future, to be accessed remotely via the internet.

Going supreme
That vision of Web-connected quantum computers has already begun to Quantum computing is exciting. It’s coming, and we want a lot more people to be well-versed in itmaterialize. In 2016, IBM unveiled the Quantum Experience, a quantum computer that anyone around the world can access online for free.
With only five qubits, the Quantum Experience is “limited in what you can do,” says Jerry Chow, who manages IBM’s experimental quantum computing group. (IBM’s 16-qubit computer is in beta testing, so Quantum Experience users are just beginning to get their hands on it.) Despite its limitations, the Quantum Experience has allowed scientists, computer programmers and the public to become familiar with programming quantum computers — which follow different rules than standard computers and therefore require new ways of thinking about problems. “Quantum computing is exciting. It’s coming, and we want a lot more people to be well-versed in it,” Chow says. “That’ll make the development and the advancement even faster.”

But to fully jump-start quantum computing, scientists will need to prove that their machines can outperform the best standard computers. “This step is important to convince the community that you’re building an actual quantum computer,” says quantum physicist Simon Devitt of Macquarie University in Sydney. A demonstration of such quantum supremacy could come by the end of the year or in 2018, Devitt predicts.

Researchers from Google set out a strategy to demonstrate quantum supremacy, posted online at arXiv.org in 2016. They proposed an algorithm that, if run on a large enough quantum computer, would produce results that couldn’t be replicated by the world’s most powerful supercomputers.

The method involves performing random operations on the qubits, and measuring the distribution of answers that are spit out. Getting the same distribution on a classical supercomputer would require simulating the complex inner workings of a quantum computer. Simulating a quantum computer with more than about 45 qubits becomes unmanageable. Supercomputers haven’t been able to reach these quantum wilds.

To enter this hinterland, Google, which has a nine-qubit computer, has aggressive plans to scale up to 49 qubits. “We’re pretty optimistic,” says Google’s John Martinis, also a physicist at the University of California, Santa Barbara.

Martinis and colleagues plan to proceed in stages, working out the kinks along the way. “You build something, and then if it’s not working exquisitely well, then you don’t do the next one — you fix what’s going on,” he says. The researchers are currently developing quantum computers of 15 and 22 qubits.

IBM, like Google, also plans to go big. In March, the company announced it would build a 50-qubit computer in the next few years and make it available to businesses eager to be among the first adopters of the burgeoning technology. Just two months later, in May, IBM announced that its scientists had created the 16-qubit quantum computer, as well as a 17-qubit prototype that will be a technological jumping-off point for the company’s future line of commercial computers.
But a quantum computer is much more than the sum of its qubits. “One of the real key aspects about scaling up is not simply … qubit number, but really improving the device performance,” Chow says. So IBM researchers are focusing on a standard they call “quantum volume,” which takes into account several factors. These include the number of qubits, how each qubit is connected to its neighbors, how quickly errors slip into calculations and how many operations can be performed at once. “These are all factors that really give your quantum processor its power,” Chow says.

Errors are a major obstacle to boosting quantum volume. With their delicate quantum properties, qubits can accumulate glitches with each operation. Qubits must resist these errors or calculations quickly become unreliable. Eventually, quantum computers with many qubits will be able to fix errors that crop up, through a procedure known as error correction. Still, to boost the complexity of calculations quantum computers can take on, qubit reliability will need to keep improving.

Different technologies for forming qubits have various strengths and weaknesses, which affect quantum volume. IBM and Google build their qubits out of superconducting materials, as do many academic scientists. In superconductors cooled to extremely low temperatures, electrons flow unimpeded. To fashion superconducting qubits, scientists form circuits in which current flows inside a loop of wire made of aluminum or another superconducting material.

Several teams of academic researchers create qubits from single ions, trapped in place and probed with lasers. Intel and others are working with qubits fabricated from tiny bits of silicon known as quantum dots (SN: 7/11/15, p. 22). Microsoft is studying what are known as topological qubits, which would be extra-resistant to errors creeping into calculations. Qubits can even be forged from diamond, using defects in the crystal that isolate a single electron. Photonic quantum computers, meanwhile, make calculations using particles of light. A Chinese-led team demonstrated in a paper published May 1 in Nature Photonics that a light-based quantum computer could outperform the earliest electronic computers on a particular problem.

One company, D-Wave, claims to have a quantum computer that can perform serious calculations, albeit using a more limited strategy than other quantum computers (SN: 7/26/14, p. 6). But many scientists are skeptical about the approach. “The general consensus at the moment is that something quantum is happening, but it’s still very unclear what it is,” says Devitt.

Identical ions
While superconducting qubits have received the most attention from giants like IBM and Google, underdogs taking different approaches could eventually pass these companies by. One potential upstart is Chris Monroe, who crafts ion-based quantum computers.
On a walkway near his office on the University of Maryland campus in College Park, a banner featuring a larger-than-life portrait of Monroe adorns a fence. The message: Monroe’s quantum computers are a “fearless idea.” The banner is part of an advertising campaign featuring several of the university’s researchers, but Monroe seems an apt choice, because his research bucks the trend of working with superconducting qubits.

Monroe and his small army of researchers arrange ions in neat lines, manipulating them with lasers. In a paper published in Nature in 2016, Monroe and colleagues debuted a five-qubit quantum computer, made of ytterbium ions, allowing scientists to carry out various quantum computations. A 32-ion computer is in the works, he says.

Monroe’s labs — he has half a dozen of them on campus — don’t resemble anything normally associated with computers. Tables hold an indecipherable mess of lenses and mirrors, surrounding a vacuum chamber that houses the ions. As with IBM’s computer, although the full package is bulky, the quantum part is minuscule: The chain of ions spans just hundredths of a millimeter.

Scientists in laser goggles tend to the whole setup. The foreign nature of the equipment explains why ion technology for quantum computing hasn’t taken off yet, Monroe says. So he and colleagues took matters into their own hands, creating a start-up called IonQ, which plans to refine ion computers to make them easier to work with.

Monroe points out a few advantages of his technology. In particular, ions of the same type are identical. In other systems, tiny differences between qubits can muck up a quantum computer’s operations. As quantum computers scale up, Monroe says, there will be a big price to pay for those small differences. “Having qubits that are identical, over millions of them, is going to be really important.”

In a paper published in March in Proceedings of the National Academy of Sciences, Monroe and colleagues compared their quantum computer with IBM’s Quantum Experience. The ion computer performed operations more slowly than IBM’s superconducting one, but it benefited from being more interconnected — each ion can be entangled with any other ion, whereas IBM’s qubits can be entangled only with adjacent qubits. That interconnectedness means that calculations can be performed in fewer steps, helping to make up for the slower operation speed, and minimizing the opportunity for errors.
Early applications
Computers like Monroe’s are still far from unlocking the full power of quantum computing. To perform increasingly complex tasks, scientists will have to correct the errors that slip into calculations, fixing problems on the fly by spreading information out among many qubits. Unfortunately, such error correction multiplies the number of qubits required by a factor of 10, 100 or even thousands, depending on the quality of the qubits. Fully error-corrected quantum computers will require millions of qubits. That’s still a long way off.

So scientists are sketching out some simple problems that quantum computers could dig into without error correction. One of the most important early applications will be to study the chemistry of small molecules or simple reactions, by using quantum computers to simulate the quantum mechanics of chemical systems. In 2016, scientists from Google, Harvard University and other institutions performed such a quantum simulation of a hydrogen molecule. Hydrogen has already been simulated with classical computers with similar results, but more complex molecules could follow as quantum computers scale up.

Once error-corrected quantum computers appear, many quantum physicists have their eye on one chemistry problem in particular: making fertilizer. Though it seems an unlikely mission for quantum physicists, the task illustrates the game-changing potential of quantum computers.

The Haber-Bosch process, which is used to create nitrogen-rich fertilizers, is hugely energy intensive, demanding high temperatures and pressures. The process, essential for modern farming, consumes around 1 percent of the world’s energy supply. There may be a better way. Nitrogen-fixing bacteria easily extract nitrogen from the air, thanks to the enzyme nitrogenase. Quantum computers could help simulate this enzyme and reveal its properties, perhaps allowing scientists “to design a catalyst to improve the nitrogen fixation reaction, make it more efficient, and save on the world’s energy,” says Microsoft’s Svore. “That’s the kind of thing we want to do on a quantum computer. And for that problem it looks like we’ll need error correction.”

Pinpointing applications that don’t require error correction is difficult, and the possibilities are not fully mapped out. “It’s not because they don’t exist; I think it’s because physicists are not the right people to be finding them,” says Devitt, of Macquarie. Once the hardware is available, the thinking goes, computer scientists will come up with new ideas.

That’s why companies like IBM are pushing their quantum computers to users via the Web. “A lot of these companies are realizing that they need people to start playing around with these things,” Devitt says.

Quantum scientists are trekking into a new, uncharted realm of computation, bringing computer programmers along for the ride. The capabilities of these fledgling systems could reshape the way society uses computers.

Eventually, quantum computers may become part of the fabric of our technological society. Quantum computers could become integrated into a quantum internet, for example, which would be more secure than what exists today (SN: 10/15/16, p. 13).

“Quantum computers and quantum communication effectively allow you to do things in a much more private way,” says physicist Seth Lloyd of MIT, who envisions Web searches that not even the search engine can spy on.

There are probably plenty more uses for quantum computers that nobody has thought up yet.

“We’re not sure exactly what these are going to be used for. That makes it a little weird,” Monroe says. But, he maintains, the computers will find their niches. “Build it and they will come.”

An expectant mom might want to think twice about quenching her thirst with soda.

The more sugary beverages a mom drank during mid-pregnancy, the heavier her kids were in elementary school compared with kids whose mothers consumed less of the drinks, a new study finds. At age 8, boys and girls weighed approximately 0.25 kilograms more — about half a pound — with each serving mom added per day while pregnant, researchers report online July 10 in Pediatrics.
“What happens in early development really has a long-term impact,” says Meghan Azad, an epidemiologist at the University of Manitoba in Canada, who was not involved in the study. A fetus’s metabolism develops in response to the surrounding environment, including the maternal diet, she says.

The new findings come out of a larger project that studies the impact of pregnant moms’ diets on their kids’ health. “We know that what mothers eat during pregnancy may affect their children’s health and later obesity,” says biostatistician Sheryl Rifas-Shiman of Harvard Medical School and Harvard Pilgrim Health Care Institute in Boston. “We decided to look at sugar-sweetened beverages as one of these factors.” Sugary drinks are associated with excessive weight gain and obesity in studies of adults and children.

Rifas-Shiman and colleagues included 1,078 mother-child pairs in the study. Moms filled out a questionnaire in the first and second trimesters of their pregnancy about what they were drinking — soda, fruit drinks, 100 percent fruit juice, diet soda or water — and how often. Soda and fruit drinks were considered sugar-sweetened beverages. A serving was defined as a can, glass or bottle of a beverage.

When the children of these moms were in elementary school, the researchers assessed the kids using several different measurements of obesity. They took kids’ height and weight to calculate body mass index and performed a scanning technique to determine total fat mass, among other methods.

Of the 1,078 kids in the study, 272, or 25 percent, were considered overweight or obese based on their BMI. Moms who drank at least two servings of sugar-sweetened beverages per day during the second trimester had children most likely to fall in this group. Other measurements of obesity were also highest for these kids. Children’s own sugary beverage drinking habits did not alter the results, the scientists say.

The research can’t say moms’ soda sips directly caused the weight gain in her kids. But based on this study and other work, limiting sugary drinks during pregnancy “is probably a good idea,” Azad says. There’s no harm in avoiding them, “and it looks like there may be a benefit.” Her advice is to drink water instead.

DNA might reveal how dogs became man’s best friend.

A new study shows that some of the same genes linked to the behavior of extremely social people can also make dogs friendlier. The result, published July 19 in Science Advances, suggests that dogs’ domestication may be the result of just a few genetic changes rather than hundreds or thousands of them.

“It is great to see initial genetic evidence supporting the self-domestication hypothesis or ‘survival of the friendliest,’” says evolutionary anthropologist Brian Hare of Duke University, who studies how dogs think and learn. “This is another piece of the puzzle suggesting that humans did not create dogs intentionally, but instead wolves that were friendliest toward humans were at an evolutionary advantage as our two species began to interact.”

Not much is known about the underlying genetics of how dogs became domesticated. In 2010, evolutionary geneticist Bridgett vonHoldt of Princeton University and colleagues published a study comparing dogs’ and wolves’ DNA. The biggest genetic differences gave clues to why dogs and wolves don’t look the same. But major differences were also found in WBSCR17, a gene linked to Williams-Beuren syndrome in humans.
Williams-Beuren syndrome leads to delayed development, impaired thinking ability and hypersociability. VonHoldt and colleagues wondered if changes to the same gene in dogs would make the animals more social than wolves, and whether that might have influenced dogs’ domestication.

In the new study, vonHoldt and colleagues compared the sociability of domestic dogs with that of wolves raised by humans. Dogs typically spent more time than wolves staring at and interacting with a human stranger nearby, showing the dogs were more social than the wolves. Analyzing the genetic blueprint of those dogs and wolves, along with DNA data of other wolves and dogs, showed variations in three genes associated with the social behaviors directed at humans: WBSCR17, GTF2I and GTF2IRD1. All three are tied to Williams-Beuren syndrome in humans.
“It’s fascinating that a handful of genetic changes could be so influential on social behavior,” vonHoldt says.

She and colleagues propose that such changes may be closely intertwined with dog domestication. Previous hypotheses have suggested that domestication was linked dogs’ development of advanced ways of analyzing and applying information about social situations, a way of thinking assumed to be unique to humans. “Instead of developing a more complex form of cognition, dogs appear to be engaging in excessively friendly behavior that increases the amount of time they spend near us and watching us,” says study coauthor Monique Udell, who studies animal behavior at Oregon State University in Corvallis. In turn, she says, that gives dogs “the opportunities necessary for them to learn about our behavior and what maximizes their success when living with us.”

The team notes, for instance, that in addition to contributing to sociability, the variations in WBSCR17 may represent an adaptation in dogs to living with humans. A previous study revealed that variations in WBSCR17 were tied to the ability to digest carbohydrates — a source of energy wolves would have rarely consumed. Yet, the variations in domestic dogs suggest those changes would help them thrive on the starch-rich diets of humans. Links between another gene related to starch digestion in dogs and domestication, however, have recently been called into question (SN Online: 7/18/17).

The other variations, the team argues, would have predisposed the dogs to be hypersocial with humans, a trait that humans would then have selected for as dogs were bred over generations.

Robots are branching out. A new prototype soft robot takes inspiration from plants by growing to explore its environment.

Vines and some fungi extend from their tips to explore their surroundings. Elliot Hawkes of the University of California in Santa Barbara and his colleagues designed a bot that works on similar principles. Its mechanical body sits inside a plastic tube reel that extends through pressurized inflation, a method that some invertebrates like peanut worms (Sipunculus nudus) also use to extend their appendages. The plastic tubing has two compartments, and inflating one side or the other changes the extension direction. A camera sensor at the tip alerts the bot when it’s about to run into something.

In the lab, Hawkes and his colleagues programmed the robot to form 3-D structures such as a radio antenna, turn off a valve, navigate a maze, swim through glue, act as a fire extinguisher, squeeze through tight gaps, shimmy through fly paper and slither across a bed of nails. The soft bot can extend up to 72 meters, and unlike plants, it can grow at a speed of 10 meters per second, the team reports July 19 in Science Robotics. The design could serve as a model for building robots that can traverse constrained environments.

This isn’t the first robot to take inspiration from plants. One plantlike predecessor was a robot modeled on roots.

Tsutomu Miyasaka was on a mission to build a better solar cell. It was the early 2000s, and the Japanese scientist wanted to replace the delicate molecules that he was using to capture sunlight with a sturdier, more effective option.

So when a student told him about an unfamiliar material with unusual properties, Miyasaka had to try it. The material was “very strange,” he says, but he was always keen on testing anything that might respond to light.
Other scientists were running electricity through the material, called a perovskite, to generate light. Miyasaka, at Toin University of Yokohama in Japan, wanted to know if the material could also do the opposite: soak up sunlight and convert it into electricity. To his surprise, the idea worked. When he and his team replaced the light-sensitive components of a solar cell with a very thin layer of the perovskite, the illuminated cell pumped out a little bit of electric current.

The result, reported in 2009 in the Journal of the American Chemical Society, piqued the interest of other scientists, too. The perovskite’s properties made it (and others in the perovskite family) well-suited to efficiently generate energy from sunlight. Perhaps, some scientists thought, this perovskite might someday be able to outperform silicon, the light-absorbing material used in more than 90 percent of solar cells around the world.
Initial excitement quickly translated into promising early results. An important metric for any solar cell is how efficient it is — that is, how much of the sunlight that strikes its surface actually gets converted to electricity. By that standard, perovskite solar cells have shone, increasing in efficiency faster than any previous solar cell material in history. The meager 3.8 percent efficiency reported by Miyasaka’s team in 2009 is up to 22 percent this year. Today, the material is almost on par with silicon, which scientists have been tinkering with for more than 60 years to bring to a similar efficiency level.
“People are very excited because [perovskite’s] efficiency number has climbed so fast. It really feels like this is the thing to be working on right now,” says Jao van de Lagemaat, a chemist at the National Renewable Energy Laboratory in Golden, Colo.

Now, perovskite solar cells are at something of a crossroads. Lab studies have proved their potential: They are cheaper and easier to fabricate than time-tested silicon solar cells. Though perovskites are unlikely to completely replace silicon, the newer materials could piggyback onto existing silicon cells to create extra-effective cells. Perovskites could also harness solar energy in new applications where traditional silicon cells fall flat — as light-absorbing coatings on windows, for instance, or as solar panels that work on cloudy days or even absorb ambient sunlight indoors.

Whether perovskites can make that leap, though, depends on current research efforts to fix some drawbacks. Their tendency to degrade under heat and humidity, for example, is not a great characteristic for a product meant to spend hours in the sun. So scientists are trying to boost stability without killing efficiency.

“There are challenges, but I think we’re well on our way to getting this stuff stable enough,” says Henry Snaith, a physicist at the University of Oxford. Finding a niche for perovskites in an industry so dominated by silicon, however, requires thinking about solar energy in creative ways.

Leaping electrons
Perovskites flew under the radar for years before becoming solar stars. The first known perovskite was a mineral, calcium titanate, or CaTiO3, discovered in the 19th century. In more recent years, perovskites have expanded to a class of compounds with a similar structure and chemical recipe — a 1:1:3 ingredient ratio — that can be tweaked with different elements to make different “flavors.”

But the perovskites being studied for the light-absorbing layer of solar cells are mostly lab creations. Many are lead halide perovskites, which combine a lead ion and three ions of iodine or a related element, such as bromine, with a third type of ion (usually something like methylammonium). Those ingredients link together to form perovskites’ hallmark cagelike pyramid-on-pyramid structure. Swapping out different ingredients (replacing lead with tin, for instance) can yield many kinds of perovskites, all with slightly different chemical properties but the same basic crystal structure.

Perovskites owe their solar skills to the way their electrons interact with light. When sunlight shines on a solar panel, photons — tiny packets of light energy — bombard the panel’s surface like a barrage of bullets and get absorbed. When a photon is absorbed into the solar cell, it can share some of its energy with a negatively charged electron. Electrons are attracted to the positively charged nucleus of an atom. But a photon can give an electron enough energy to escape that pull, much like a video game character getting a power-up to jump a motorbike across a ravine. As the energized electron leaps away, it leaves behind a positively charged hole. A separate layer of the solar cell collects the electrons, ferrying them off as electric current.

The amount of energy needed to kick an electron over the ravine is different for every material. And not all photon power-ups are created equal. Sunlight contains low-energy photons (infrared light) and high-energy photons (sunburn-causing ultraviolet radiation), as well as all of the visible light in between.

Photons with too little energy “will just sail right on through” the light-catching layer and never get absorbed, says Daniel Friedman, a photovoltaic researcher at the National Renewable Energy Lab. Only a photon that comes in with energy higher than the amount needed to power up an electron will get absorbed. But any excess energy a photon carries beyond what’s needed to boost up an electron gets lost as heat. The more heat lost, the more inefficient the cell.
Because the photons in sunlight vary so much in energy, no solar cell will ever be able to capture and optimally use every photon that comes its way. So you pick a material, like silicon, that’s a good compromise — one that catches a decent number of photons but doesn’t waste too much energy as heat, Friedman says.

Although it has dominated the solar cell industry, silicon can’t fully use the energy from higher-energy photons; the material’s solar conversion efficiency tops out at around 30 percent in theory and has hit 20-some percent in practice. Perovskites could do better. The electrons inside perovskite crystals require a bit more energy to dislodge. So when higher-energy photons come into the solar cell, they devote more of their energy to dislodging electrons and generating electric current, and waste less as heat. Plus, by changing the ingredients and their ratios in a perovskite, scientists can adjust the photons it catches. Using different types of perovskites across multiple layers could allow solar cells to more effectively absorb a broader range of photons.

Perovskites have a second efficiency perk. When a photon excites an electron inside a material and leaves behind a positively charged hole, there’s a tendency for the electron to slide right back into a hole. This recombination, as it’s known, is inefficient — an electron that could have fed an electric current instead just stays put.

In perovskites, though, excited electrons usually migrate quite far from their holes, Snaith and others have found by testing many varieties of the material. That boosts the chances the electrons will make it out of the perovskite layer without landing back in a hole.

“It’s a very rare property,” Miyasaka says. It makes for an efficient sunlight absorber.

Some properties of perovskites also make them easier than silicon to turn into solar cells. Making a conventional silicon solar cell requires many steps, all done in just the right order at just the right temperature — something like baking a fragile soufflé. The crystals of silicon have to be perfect, because even small defects in the material can hurt its efficiency. The need for such precision makes silicon solar cells more expensive to produce.

Perovskites are more like brownies from a box — simpler, less finicky. “You can make it in an office, basically,” says materials scientist Robert Chang of Northwestern University in Evanston, Ill. He’s exaggerating, but only a little. Perovskites are made by essentially mixing a bunch of ingredients together and depositing them on a surface in a thin, even film. And while making crystalline silicon requires temperatures up to 2000° Celsius, perovskite crystals form at easier-to-reach temperatures — lower than 200°.

Seeking stability
In many ways, perovskites have become even more promising solar cell materials over time, as scientists have uncovered exciting new properties and finessed the materials’ use. But no material is perfect. So now, scientists are searching for ways to overcome perovskites’ real-world limitations. The most pressing issue is their instability, van de Lagemaat says. The high efficiency levels reported from labs often last only days or hours before the materials break down.

Tackling stability is a less flashy problem than chasing efficiency records, van de Lagemaat points out, which is perhaps why it’s only now getting attention. Stability isn’t a single number that you can flaunt, like an efficiency value. It’s also a bit harder to define, especially since how long a solar cell lasts depends on environmental conditions like humidity and precipitation levels, which vary by location.

Encapsulating the cell with water-resistant coatings is one strategy, but some scientists want to bake stability into the material itself. To do that, they’re experimenting with different perovskite designs. For instance, solar cells containing stacks of flat, graphenelike sheets of perovskites seem to hold up better than solar cells with the standard three-dimensional crystal and its interwoven layers.

In these 2-D perovskites, some of the methylammonium ions are replaced by something larger, like butylammonium. Swapping in the bigger ion forces the crystal to form in sheets just nanometers thick, which stack on top of each other like pages in a book, says chemist Aditya Mohite of Los Alamos National Laboratory in New Mexico. The butylammonium ion, which naturally repels water, forms spacer layers between the 2-D sheets and stops water from permeating into the crystal.
Getting the 2-D layers to line up just right has proved tricky, Mohite says. But by precisely controlling the way the layers form, he and colleagues created a solar cell that runs at 12.5 percent efficiency while standing up to light and humidity longer than a similar 3-D model, the team reported in 2016 in Nature. Although it was protected with a layer of glass, the 3-D perovskite solar cell lost performance rapidly, within a few days, while the 2-D perovskite withered only slightly. (After three months, the 2-D version was still working almost as well as it had been at the beginning.)

Despite the seemingly complex structure of the 2-D perovskites, they are no more complicated to make than their 3-D counterparts, says Mercouri Kanatzidis, a chemist at Northwestern and a collaborator on the 2-D perovskite project. With the right ingredients, he says, “they form on their own.”

His goal now is to boost the efficiency of 2-D perovskite cells, which don’t yet match up to their 3-D counterparts. And he’s testing different water-repelling ions to reach an ideal stability without sacrificing efficiency.

Other scientists have mixed 2-D and 3-D perovskites to create an ultra-long-lasting cell — at least by perovskite standards. A solar panel made of these cells ran at only 11 percent efficiency, but held up for 10,000 hours of illumination, or more than a year, according to research published in June in Nature Communications. And, importantly, that efficiency was maintained over an area of about 50 square centimeters, more on par with real-world conditions than the teeny-tiny cells made in most research labs.

A place for perovskites?
With boosts to their stability, perovskite solar cells are getting closer to commercial reality. And scientists are assessing where the light-capturing material might actually make its mark.

Some fans have pitted perovskites head-to-head with silicon, suggesting the newbie could one day replace the time-tested material. But a total takeover probably isn’t a realistic goal, says Sarah Kurtz, codirector of the National Center for Photovoltaics at the National Renewable Energy Lab.

“People have been saying for decades that silicon can’t get lower in cost to meet our needs,” Kurtz says. But, she points out, the price of solar energy from silicon-based panels has dropped far lower than people originally expected. There are a lot of silicon solar panels out there, and a lot of commercial manufacturing plants already set up to deal with silicon. That’s a barrier to a new technology, no matter how great it is. Other silicon alternatives face the same limitation. “Historically, silicon has always been dominant,” Kurtz says.
For Snaith, that’s not a problem. He cofounded Oxford Photo-voltaics Limited, one of the first companies trying to commercialize perovskite solar cells. His team is developing a solar cell with a perovskite layer over a standard silicon cell to make a super-efficient double-decker cell. That way, Snaith says, the team can capitalize on the massive amount of machinery already set up to build commercial silicon solar cells.
A perovskite layer on top of silicon would absorb higher-energy photons and turn them into electricity. Lower-energy photons that couldn’t excite the perovskite’s electrons would pass through to the silicon layer, where they could still generate current. By combining multiple materials in this way, it’s possible to catch more photons, making a more efficient cell.

That idea isn’t new, Snaith points out: For years, scientists have been layering various solar cell materials in this way. But these double-decker cells have traditionally been expensive and complicated to make, limiting their applications. Perovskites’ ease of fabrication could change the game. Snaith’s team is seeing some improvement already, bumping the efficiency of a silicon solar cell from 10 to 23.6 percent by adding a perovskite layer, for example. The team reported that result online in February in Nature Energy.

Rather than compete with silicon solar panels for space on sunny rooftops and in open fields, perovskites could also bring solar energy to totally new venues.

“I don’t think it’s smart for perovskites to compete with silicon,” Miyasaka says. Perovskites excel in other areas. “There’s a whole world of applications where silicon can’t be applied.”

Silicon solar cells don’t work as well on rainy or cloudy days, or indoors, where light is less direct, he says. Perovskites shine in these situations. And while traditional silicon solar cells are opaque, very thin films of perovskites could be printed onto glass to make sunlight-capturing windows. That could be a way to bring solar power to new places, turning glassy skyscrapers into serious power sources, for example. Perovskites could even be printed on flexible plastics to make solar-powered coatings that charge cell phones.

That printing process is getting closer to reality: Scientists at the University of Toronto recently reported a way to make all layers of a perovskite solar cell at temperatures below 150° — including the light-absorbing perovskite layer, but also the background workhorse layers that carry the electrons away and funnel them into current. That could streamline and simplify the production process, making mass newspaper-style printing of perovskite solar cells more doable.

Printing perovskite solar cells on glass is also an area of interest for Oxford Photovoltaics, Snaith says. The company’s ultimate target is to build a perovskite cell that will last 25 years, as long as a traditional silicon cell.

The moon had a magnetic field for at least 2 billion years, or maybe longer.

Analysis of a relatively young rock collected by Apollo astronauts reveals the moon had a weak magnetic field until 1 billion to 2.5 billion years ago, at least a billion years later than previous data showed. Extending this lifetime offers insights into how small bodies generate magnetic fields, researchers report August 9 in Science Advances. The result may also suggest how life could survive on tiny planets or moons.
“A magnetic field protects the atmosphere of a planet or moon, and the atmosphere protects the surface,” says study coauthor Sonia Tikoo, a planetary scientist at Rutgers University in New Brunswick, N.J. Together, the two protect the potential habitability of the planet or moon, possibly those far beyond our solar system.

The moon does not currently have a global magnetic field. Whether one ever existed was a question debated for decades (SN: 12/17/11, p. 17). On Earth, molten rock sloshes around the outer core of the planet over time, causing electrically conductive fluid moving inside to form a magnetic field. This setup is called a dynamo. At 1 percent of Earth’s mass, the moon would have cooled too quickly to generate a long-lived roiling interior.
Magnetized rocks brought back by Apollo astronauts, however, revealed that the moon must have had some magnetizing force. The rocks suggested that the magnetic field was strong at least 4.25 billion years ago, early on in the moon’s history, but then dwindled and maybe even got cut off about 3.1 billion years ago.
Tikoo and colleagues analyzed fragments of a lunar rock collected along the southern rim of the moon’s Dune Crater during the Apollo 15 mission in 1971. The team determined the rock was 1 billion to 2.5 billion years old and found it was magnetized. The finding suggests the moon had a magnetic field, albeit a weak one, when the rock formed, the researchers conclude.
A drop in the magnetic field strength suggests the dynamo driving it was generated in two distinct ways, Tikoo says. Early on, Earth and the moon would have sat much closer together, allowing Earth’s gravity to tug on and spin the rocky exterior of the moon. That outer layer would have dragged against the liquid interior, generating friction and a very strong magnetic field (SN Online: 12/4/14).

Then slowly, starting about 3.5 billion years ago, the moon moved away from Earth, weakening the dynamo. But by that point, the moon would have started to cool, causing less dense, hotter material in the core to rise and denser, cooler material to sink, as in Earth’s core. This roiling of material would have sustained a weak field that lasted for at least a billion years, until the moon’s interior cooled, causing the dynamo to die completely, the team suggests.

The two-pronged explanation for the moon’s dynamo is “an entirely plausible idea,” says planetary scientist Ian Garrick-Bethell of the University of California, Santa Cruz. But researchers are just starting to create computer simulations of the strength of magnetic fields to understand how such weaker fields might arise. So it is hard to say exactly what generated the lunar dynamo, he says.

If the idea is correct, it may mean other small planets and moons could have similarly weak, long-lived magnetic fields. Having such an enduring shield could protect those bodies from harmful radiation, boosting the chances for life to survive.

August’s total solar eclipse won’t be the last time the moon cloaks the sun’s light. From now to 2040, for example, skywatchers around the globe can witness 15 such events.

Their predicted paths aren’t random scribbles. Solar eclipses occur in what’s called a Saros cycle — a period that lasts about 18 years, 11 days and eight hours, and is governed by the moon’s orbit. (Lunar eclipses follow a Saros cycle, too, which the Chaldeans first noticed probably around 500 B.C.)

Two total solar eclipses separated by that 18-years-and-change period are almost twins — compare this year’s eclipse with the Sept. 2, 2035 eclipse, for example. They take place at roughly the same time of year, at roughly the same latitude and with the moon at about the same distance from Earth. But those extra eight hours, during which the Earth has rotated an additional third of the way on its axis, shift the eclipse path to a different part of the planet.
This cycle repeats over time, creating a family of eclipses called a Saros series. A series lasts 12 to 15 centuries and includes about 70 or more eclipses. The solar eclipses of 2019 and 2037 belong to a different Saros series, so their paths too are shifted mimics. Their tracks differ in shape from 2017’s, because the moon is at a different place in its orbit when it passes between the Earth and the sun. Paths are wider at the poles because the moon’s shadow is hitting the Earth’s surface at a steep angle.

Predicting and mapping past and future eclipses allows scientists “to examine the patterns of eclipse cycles, the most prominent of which is the Saros,” says astrophysicist Fred Espenak, who is retired from NASA’s Goddard Spaceflight Center in Greenbelt, Md.

He would know. Espenak and his colleague Jean Meeus, a retired Belgian astronomer, have mapped solar eclipse paths from 2000 B.C. to A.D. 3000. For archaeologists and historians peering backward, the maps help match up accounts of long-ago eclipses with actual paths. For eclipse chasers peering forward, the data are an itinerary.

“I got interested in figuring out how to calculate eclipse paths for my own use, for planning … expeditions,” says Espenak, who was 18 when he witnessed his first total solar eclipse. It was in 1970, and he secured permission to drive the family car from southern New York to North Carolina to see it. Since then, Espenak, nicknamed “Mr. Eclipse,” has been to every continent, including Antarctica, for a total eclipse of the sun.

“It’s such a dramatic, spectacular, beautiful event,” he says. “You only get a few brief minutes, typically, of totality before it ends. After it’s over, you’re craving to see it again.”

Speculation is running rampant about potential new discoveries of gravitational waves, just as the latest search wound down August 25.

Publicly available logs from astronomical observatories indicate that several telescopes have been zeroing in on one particular region of the sky, potentially in response to a detection of ripples in spacetime by the Advanced Laser Interferometer Gravitational-Wave Observatory, LIGO. These records have raised hopes that, for the first time, scientists may have glimpsed electromagnetic radiation — light — produced in tandem with gravitational waves. That light would allow scientists to glean more information about the waves’ source. Several tweets from astronomers reporting rumors of a new LIGO detection have fanned the flames of anticipation and amplified hopes that the source may be a cosmic convulsion unlike any LIGO has seen before.
“There is a lot of excitement,” says astrophysicist Rosalba Perna of Stony Brook University in New York, who is not involved with the LIGO collaboration. “We are all very anxious to actually see the announcement.”

An Aug. 25 post on the LIGO collaboration’s website announced the end of the current round of data taking, which began November 30, 2016. Virgo, a gravitational wave detector in Italy, had joined forces with LIGO’s two on August 1 (SN Online: 8/1/17). The three detectors will now undergo upgrades to improve their sensitivity. The update noted that “some promising gravitational-wave candidates have been identified in data from both LIGO and Virgo during our preliminary analysis, and we have shared what we currently know with astronomical observing partners.”

When LIGO detects gravitational waves, the collaboration alerts astronomers to the approximate location the waves seemed to originate from. The hope is that a telescope could pick up light from the aftermath of the cosmic catastrophe that created the gravitational waves — although no light has been found in previous detections.

LIGO previously detected three sets of gravitational waves from merging black holes (SN: 6/24/17, p. 6). Black hole coalescences aren’t expected to generate light that could be spotted by telescopes, but another prime candidate could: a smashup between two remnants of stars known as neutron stars. Scientists have been eagerly awaiting LIGO’s first detections of such mergers, which are suspected to be the sites where the universe’s heaviest elements are formed. An observation of a neutron star crash also could provide information about the ultradense material that makes up neutron stars.
Since mid-August, seemingly in response to a LIGO alert, several telescopes have observed a section of sky around the galaxy NGC 4993, located 134 million light-years away in the constellation Hydra. The Hubble Space Telescope has made at least three sets of observations in that vicinity, including one on August 22 seeking “observations of the first electromagnetic counterparts to gravitational wave sources.”

Likewise, the Chandra X-ray Observatory targeted the same region of sky on August 19. And records from the Gemini Observatory’s telescope in Chile indicate several potentially related observations, including one referencing “an exceptional LIGO/Virgo event.”

“I think it’s very, very likely that LIGO has seen something,” says astrophysicist David Radice of Princeton University, who is not affiliated with LIGO. But, he says, he doesn’t know whether its source has been confirmed as merging neutron stars.

LIGO scientists haven’t commented directly on the veracity of the rumor. “We have some substantial work to do before we will be able to share with confidence any quantitative results. We are working as fast as we can,” LIGO spokesperson David Shoemaker of MIT wrote in an e-mail.

Alien megastructures are out. The unusual fading of an oddball star is more likely caused by either clouds of dust or an abnormal cycle of brightening and dimming, two new papers suggest.

Huan Meng of the University of Arizona in Tucson and his colleagues suggest that KIC 8462852, known as Tabby’s star, is dimming thanks to an orbiting cloud of fine dust particles. The team observed the star with the infrared Spitzer and ultraviolet Swift space telescopes from October 2015 to December 2016 — the first observations in multiple wavelengths of light. They found that the star is dimming faster in short blue wavelengths than longer infrared ones, suggesting smaller particles.
“That almost absolutely ruled out the alien megastructure scenario, unless it’s an alien microstructure,” Meng says.

Tabby’s star is most famous for suddenly dropping in brightness by up to 22 percent over the course of a few days (SN Online: 2/2/16). Later observations suggested the star is also fading by about 4 percent per year (SN: 9/17/16, p. 12), which Meng’s team confirmed in a paper posted online August 24 at arXiv.org.

Joshua Simon of the Observatories of the Carnegie Institution for Science in Pasadena, Calif., found a similar dimming in data on Tabby’s star from the All Sky Automated Survey going back to 2006. Simon and colleagues also found for the first time that the star grew brighter in 2014, and possibly in 2006, they reported in a paper August 25 at arXiv.org.

“That’s fascinating,” says astrophysicist Tabetha Boyajian of Louisiana State University in Baton Rouge. She first reported the star’s flickers in 2015 (the star is nicknamed for her) and is a coauthor on Meng’s paper. “We always speculated that it would brighten sometime. It can’t just get fainter all the time — otherwise it would disappear. This shows that it does brighten.”

The brightening could be due to a magnetic cycle like the sun’s, Simon suggests. But no known cycle makes a star brighten and dim by quite so much, so the star would still be odd.
Brian Metzger of Columbia University previously suggested that a ripped-up planet falling in pieces into the star could explain both the long-term and short-term dimming. He thinks that model still works, although it needs some tweaks.

“This adds some intrigue to what’s going on, but I don’t think it really changes the landscape,” says Metzger, who was not involved in the new studies. And newer observations could complicate things further: The star went through another bout of dimming between May and July. “I’m waiting to see the papers analyzing this recent event,” Metzger says.

West German power companies have decided to go ahead with two nuclear power station projects…. Compared with the U.S. and Britain, Germany has been relatively backward in the application of nuclear energy…. The slow German start is only partly the result of restrictions placed upon German nuclear research after the war. — Science News, September 16, 1967

Update
Both East and West Germany embraced nuclear power until antinuclear protests in the 1970s gathered steam. In 1998, the unified German government began a nuclear phaseout, which Chancellor Angela Merkel halted in 2009. The 2011 Fukushima nuclear disaster in Japan caused a rapid reversal. Germany closed eight of its nuclear plants immediately, and announced that all nuclear power in the country would go dark by 2022 (SN Online: 6/1/11). A pivot to renewable energy — wind, solar, hydropower and biomass — produced 188 billion kilowatt-hours of electricity in 2016, nearly 32 percent of German electricity usage.