Lifeboat Foundation

Scientists have studied this ebb and flow for centuries, but only began understanding its effects on our planet at the dawn of the space age in the mid-20th century. Now it is clear that around solar maximum the sun is more likely to bombard Earth with charged particles that damage satellites and power grids. The solar cycle also plays a minor role in climate, as variations in irradiance can cause slight changes in average sea-surface temperatures and precipitation patterns. Thus, a better understanding of the cycle’s physical drivers is important for sustainable living on Earth.

Yet scientists still lack a model that perfectly predicts the cycle’s key details, such as the exact duration and strength of each phase. “I think the solar cycle is so stable and clear that there is something fundamental that we are missing,” says Ofer Cohen, a solar physicist at the University of Massachusetts Lowell. One obstacle to figuring it out, he says, is that crucial details of the apparent mechanisms behind the cycle—such as the sun’s magnetic field—are largely hidden from our view. But that might be about to change.

Tim Linden, an astronomer at The Ohio State University, and his colleagues recently mapped how the sun’s high-energy glow dances across its face over time. They found a potential link between these high-energy emissions, the sun’s fluctuating magnetic field and the timing of the solar cycle. This, many experts argue, could open a new window into the inner workings of our nearest, most familiar star.

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When electronics need their own power sources, there are two basic options: batteries and harvesters. Batteries store energy internally, but are therefore heavy and have a limited supply. Harvesters, such as solar panels, collect energy from their environments. This gets around some of the downsides of batteries but introduces new ones, in that they can only operate in certain conditions and can’t turn that energy into useful power very quickly.

New research from the University of Pennsylvania’s School of Engineering and Applied Science is bridging the gap between these two fundamental technologies for the first time in the form of a “metal-air scavenger” that gets the best of both worlds.

This metal-air scavenger works like a battery, in that it provides power by repeatedly breaking and forming a series of chemical bonds. But it also works like a harvester, in that power is supplied by energy in its environment: specifically, the chemical bonds in metal and air surrounding the metal-air scavenger.

The synthesis of plastic precursors, such as polymers, involves specialized catalysts. However, the traditional batch-based method of finding and screening the right ones for a given result consumes liters of solvent, generates large quantities of chemical waste, and is an expensive, time-consuming process involving multiple trials.

Ryan Hartman, professor of chemical and biomolecular engineering at the NYU Tandon School of Engineering, and his laboratory developed a lab-based “intelligent microsystem” employing machine learning, for modeling chemical reactions that shows promise for eliminating this costly process and minimizing environmental harm.

In their research, “Combining automated microfluidic experimentation with machine learning for efficient polymerization design,” published in Nature Machine Intelligence, the collaborators, including doctoral student Benjamin Rizkin, employed a custom-designed, rapidly prototyped microreactor in conjunction with automation and in situ infrared thermography to study exothermic (heat generating) polymerization—reactions that are notoriously difficult to control when limited experimental kinetic data are available. By pairing efficient microfluidic technology with machine learning algorithms to obtain high-fidelity datasets based on minimal iterations, they were able to reduce chemical waste by two orders of magnitude and catalytic discovery from weeks to hours.

Wind power surged worldwide in 2019, but will it sustain? More than 340,000 wind turbines generated over 591 gigawatts globally. In the U.S., wind powered the equivalent of 32 million homes and sustained 500 U.S. factories. What’s more, in 2019 wind power grew by 19 percent, thanks to both booming offshore and onshore projects in the U.S. and China.

A study by Cornell University researchers used supercomputers to look into the future of how to make an even bigger jump in wind power capacity in the U.S.

“This research is the first detailed study designed to develop scenarios for how wind energy can expand from the current levels of seven percent of U.S. electricity supply to achieve the 20 percent by 2030 goal outlined by the U.S. Department of Energy National Renewable Energy Laboratory (NREL) in 2014,” said study co-author Sara C. Pryor, a professor in the Department of Earth and Atmospheric Studies, Cornell University. Pryor and co-authors published the wind power study in Nature Scientific Reports, February 2020.

Most of the pieces of Elon Musk’s Master Plan, Part Deux are already in place. Tesla’s mass-market cars, the Model 3 and Model Y, have already been released. The Solar Roof is finally seeing a ramp. And the release of a feature-complete version of the company’s Full Self-Driving suite seems to be drawing closer.

For Tesla’s Full Self-Driving suite to be feature-complete, the electric car maker would need to master inner-city driving. FSD already works for highway driving with Navigate on Autopilot with automatic lane changes. But when it comes to inner-city streets, Full Self-Driving still has some ways to go. Fortunately, if Tesla’s v10.2 2020.12.5 release is any indication, it appears that more and more aspects of city driving are becoming recognized by the company’s neural networks.

Designer Michal Bonikowski’s concept is probably four or five generations ahead of the current mode of thinking, but Bonikowski told Robb Report that he was inspired by the recent Maveric concept by Airbus. “That aircraft’s unique design helps reduce drag while providing more cabin space,” he said. “I have been thinking a lot about this lately, and wondered what could happen if a big company would like to create an electric plane.”

Scientists have engineered a mutant enzyme that converts 90 percent of plastic bottles back to pristine starting materials that can then be used to produce new high-quality bottles in just hours. The discovery could revolutionize the recycling industry, which currently saves about 30 percent of PET plastics from landfills, reported Science Magazine.

Elon Musk has revealed the reason behind Tesla’s cabin-facing camera that has been in the Model 3 for years without being used.

When Tesla launched the Model 3, it equipped the vehicle with a standard cabin-facing camera located in the rearview mirror.

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