The Next Stage Of The Solar Boom Is Already Underway

solar boom

“Every five days, the sun provides the Earth with as much energy as all proven supplies of oil, coal, and natural gas,” reports Singularity Hub in a powerful summation of the potential power of solar energy. “If humanity could capture just one 6,000th of Earth’s available solar energy, we’d be able to meet 100 percent of our energy needs.”

The attempt to harness one of the most abundant clean energy resources–sunlight–has been a long and historied endeavor, starting all the way back in the Industrial Revolution when French scientist Alexandre Edmond Becquerellar first discovered that a solar cell had the ability to convert sunlight into electricity through the photovoltaic effect in 1839. While it took a long time before we had the technology to make a commercial solar cell, in the United States, solar power has received government support for nearly 50 years. So why hasn’t solar power–clean, renewable, and overabundant–taken over our energy landscape?

For a long time, solar power was simply too expensive–it just couldn’t compete with the cheap cost and relative ease of fossil fuels, around which the entire energy industry was already built, with negligible exceptions. But now, solar power is cheaper than ever, with this year’s average price per watt of solar energy clocking in at just $3. In fact, solar (and wind power) are now cheaper than coal in most countries in the world. And the really great news is that they’re going to keep getting even cheaper.

This is in large part thanks to the fact that we are in the midst of a solar tech revolution. “Today,” reports Singularity Hub, “we are riding a tremendous wave of advancements in both solar panel efficiency and novel methods of expanding surface area coverage.”

At the forefront of this movement is a startup called Heliogen, which is backed by clean energy enthusiast, technocrat, and – as luck would have it – billionaire Bill Gates that is pushing solar power efficiency to new heights with the implementation of Artificial Intelligence. “Heliogen has created a system that will concentrate solar energy at temperatures as high as 1832 degrees Fahrenheit (1000 degrees Celsius) and replace the use of fossil fuels in industrial tasks such as producing cement and steel,” reports the International Business Times. This is achieved with the use of an AI-based computer system which is able to “align a set of large mirrors that will reflect solar energy on a single target. The accuracy of this system is what makes it possible to generate not just huge amounts of solar energy, but even control the output to make it comparable with the immediate power boost that happens with burning fossil fuels.”

This incredible concentration and efficiency falls in line with the current trend in solar energy, which is how to address one of the sector’s biggest obstacles: land area use. “Traditionally, solar energy-generating plants have been deployed on swathes of out-of-eyesight farmland, or on the roofs of self-powered homes and commercial properties. Yet critics point to land area use as the single greatest barrier to widespread solar adoption,” writes Singularity Hub. “Over the next decade, however, solar panels will be installed almost ubiquitously across urban and semi-urban areas, embedded in our infrastructure, transparent surfaces, and potentially even transit vessels.”

The Bill Gates-backed Heliogen model is still in its early stages of development and the groundbreaking AI technology still has a long way to go before it comes to market, but it is not the only revolution in solar energy currently underway. In fact, the sector is absolutely bursting with innovation as scientists and investors respond to the urgent need to cut carbon emissions and offset our dependence on fossil fuels with alternative energy like solar.

Just this month, a team of scientists at MIT unveiled that they have developed a new protective coating for advanced solar cells with huge possible implications. While a protective covering might not be the sexiest tech innovation, it is a hugely important one, making our existing solar technology more efficient and more resilient. As reported by Phys.org, “MIT researchers have improved on a transparent, conductive coating material, producing a tenfold gain in its electrical conductivity. When incorporated into a type of high-efficiency solar cell, the material increased the cell’s efficiency and stability.”

This is an especially important breakthrough due to the fact that the material currently used in the solar sector to coat the solar cells has a lot of shortcomings. “The material most widely used today for such purposes is known as ITO, for indium titanium oxide, but that material is quite brittle and can crack after a period of use.” The new and improved coating developed by MIT is a high-performing, flexible organic polymer known as PEDOT, which is “deposited in an ultrathin layer just a few nanometers thick, using a process called oxidative chemical vapor deposition (oCVD). This process results in a layer where the structure of the tiny crystals that form the polymer are all perfectly aligned horizontally, giving the material its high conductivity.”

Even with the incredible advances currently being made in the solar energy sector, there is still much more room for improvement. As Singularity Hub reports, “while the efficiency of current run-of-the-mill solar panels still hovers around 16-18 percent, traditional silicon solar panels have only reached half of their theoretical efficiency potential. And new materials science breakthroughs are now on track to double this theoretical constraint, promising cheap, efficient, and abundant solar energy.”

Every advance in the efficiency and ease of solar power production carries major real-world implications, getting us closer to being able to meet the emission cutting goals set by the Paris climate accord. In order to avoid the climate tipping point towards catastrophic climate change, most of the world’s known fossil fuel reserves will have to remain in the ground. This means that the need to develop a clean energy sector that is able to compete economically and logistically with oil and gas is imperative and urgent. However, as OilPrice reported earlier this year,  and investment is “The No.1 Bottleneck For Clean Energy Tech.” The only thing standing between us and a solar-powered world is a few more Bill Gates or a whole lot more civil, political, and private sector support. SOURCE

This robot can sort recycling by giving it a squeeze

The robot, called RoCycle, uses pincers to pick through garbage and identify what materials each bit contains. It could help reduce how much waste gets sent to landfill.

Image of recycling robot sorting various items into bins
JASON DORFMAN, MIT CSAIL

Greasy pizza box, takeaway coffee cup, plastic yogurt pot—are they trash or recycling? What can and can’t be recycled is often confusing, not least because the answer depends on the facilities at your local waste processing plant. In many plants, grease-soaked cardboard or cups lined with polyethylene cannot be recycled and thus head for landfill—often taking a batch of other recycling with them.

One US waste processing company has reported that 25% of all recycling it receives is so contaminated it must be sent straight to landfills. Meanwhile, the amount of household waste rejected for recycling in England increased by 84% between 2011-2012 and 2014-2015, according to government figures. And it’s about to get worse. Much of the world’s waste is sold to China for recycling. But last month China introduced stricter standards for the amount of contamination it will accept: anything more that 0.5% impure will go in the ground.

That’s why the way we sort waste needs to get much better. Many large recycling centers already use magnets to pull out metals, and air filters to separate paper from heavier plastics. Even so, most sorting is still done by hand. It’s dirty and dangerous work.

So Lillian Chin and her colleagues at the Computer Science and Artificial Intelligence Lab at MIT have developed a robot arm with soft grippers that picks up objects from a conveyor belt and identifies what they are made from by touch. MORE

Machine learning is making pesto even more delicious

Researchers at MIT have used AI to improve the flavor of basil. It’s part of a trend that is seeing artificial intelligence revolutionize farming.

What makes basil so good? In some cases, it’s AI.

Machine learning has been used to create basil plants that are extra-delicious. While we sadly cannot report firsthand on the herb’s taste, the effort reflects a broader trend that involves using data science and machine learning to improve agriculture.

The researchers behind the AI-optimized basil used machine learning to determine the growing conditions that would maximize the concentration of the volatile compounds responsible for basil’s flavor. The study appears in the journal PLOS One today.

The basil was grown in hydroponic units within modified shipping containers in Middleton, Massachusetts. Temperature, light, humidity, and other environmental factors inside the containers could be controlled automatically. The researchers tested the taste of the plants by looking for certain compounds using gas chromatography and mass spectrometry. And they fed the resulting data into machine-learning algorithms developed at MIT and a company called Cognizant.

The idea of using machine learning to optimize plant yield and properties is rapidly taking off in agriculture. Last year, Wageningen University in the Netherlands organized an “Autonomous Greenhouse” contest, in which different teams competed to develop algorithms that increased the yield of cucumber plants while minimizing the resources required. They worked with greenhouses where a variety of factors are controlled by computer systems.

Similar technology is already being applied in some commercial farms, says Naveen Singla, who leads a data science team focused on crops at Bayer, a German multinational that acquired Monsanto last year. “Flavor is one of the areas where we are heavily using machine learning—to understand the flavor of different vegetables,” he says.  MORE