Lifeboat Foundation

In nature, wood, shells, and other structural materials are lightweight, strong, and tough. Significantly, these materials are made at the ambient temperature in the local environment – not at the high temperatures at which human-made structural materials are generally processed. Similar materials are difficult to make synthetically. In a review article in Nature Materials, a team of scientists assessed the common design motifs of a range of natural structural materials and determined what it would take to design and fabricate structures that mimic nature. They considered the remaining challenges to include the need for comprehensive characterization of strength and toughness to identify underlying multiscale mechanisms.

This comprehensive assessment provides new inspiration and understanding of design principles that may lead to more efficient synthetic approaches for advanced, lightweight structural materials for transportation, buildings, batteries, and energy conversion.

In the natural world, many of the structural materials (wood, shells, bones, etc.) are hybrid materials made up of simple constituents that are assembled at ambient temperatures and often have remarkable properties. Even though the constituent materials generally have poor intrinsic properties, the superior extrinsic properties of the hybrid materials are the result of the arrangement of hard and soft phases in complex hierarchical architectures, with dimensions spanning from the nanoscale to the macroscale. The resulting materials are lightweight and usually show interesting combinations of strength and toughness, even though these two key structural properties tend to be mutually exclusive. It is relatively easy to make materials that are strong or tough, but difficult to make materials that are both.

New light has been shed on the formation of increasingly precious rare earth elements (REEs) by researchers from Trinity College Dublin. They accomplished this by creating synthetic rocks and testing their responses to varying environmental conditions. REEs are used in many electronic devices and green energy technologies, including everything from smartphones to electric vehicles.

The findings, just published on September 19 in the journal Global Challenges, have implications for recycling REEs from electronic waste, designing materials with advanced functional properties, and even for finding new REE deposits hidden around the globe.

Dr. Juan Diego Rodriguez-Blanco, Associate Professor in Nanomineralogy at Trinity and an iCRAG (SFI Research Centre in Applied Geosciences) Funded Investigator, was the principal investigator of the work. He said:

Scientists have discovered a mineral stronger than a diamond called lonsdaleite. The mineral, which has been theorized about for years, was recently found in Africa after meteorites landed in the region. It’s also believed to exist on Earth in some form, though scientists are unsure how much is available on our planet.

Amid the festivities at its fall 2022 GTC conference, Nvidia took the wraps off new robotics-related hardware and services aimed at companies developing and testing machines across industries like manufacturing. Isaac Sim, Nvidia’s robotics simulation platform, will soon be available in the cloud, the company said. And Nvidia’s lineup of system-on-modules is expanding with Jetson Orin Nano, a system designed for low-powered robots — plus a new platform called IGX.

Isaac Sim, which launched in open beta last June, allows designers to simulate robots interacting with mockups of the real world (think digital re-creations of warehouses and factory floors). Users can generate datasets from simulated sensors to train the models on real-world robots, leveraging synthetic data from batches of parallel, unique simulations to improve the model’s performance.

It’s not just marketing bluster, necessarily. Some research suggests that synthetic data has the potential to address many of the development challenges plaguing companies attempting to operationalize AI. MIT researchers recently found a way to classify images using synthetic data, and nearly every major autonomous vehicle company uses simulation data to supplement the real-world data they collect from cars on the road.

This novel technology can be built in many ways, even like a snake.

The National Renewable Energy Laboratory (NREL) has revealed a breakthrough technology with wave energy. The lab claims that with this new technology, electricity can be produced from waves and even from clothes, and cars.

NREL — which specializes in the research and development of renewable energy, energy efficiency, energy systems integration, and sustainable transportation — has already taken out the patent of its unique distributed embedded energy converter technologies (DEEC-Tec).

Continue reading “NREL’s newly patented technology will generate electricity from ocean waves, lab claims” »

Circa 2019 face_with_colon_three

“You could train your particular ‘tongue’ to know what one of these whiskies ‘tasted’ like, so that when the fake stuff came along it could identify it and when the real stuff came along it could confirm that it was the real stuff,” said Dr Alasdair Clark, the lead author of the research from the University of Glasgow.

Clark said the technology could be incorporated into a small, portable device and have a wide range of applications, from identifying poisons to environmental monitoring of rivers.

Continue reading “Scientists develop ‘artificial tongue’ to detect fake whiskies” »

Electric vehicles have often been hailed as the future. Major motoring companies are aiming to produce nothing but electric vehicles in the future, and some aspire to hit that target by the end of the decade. Cars that are traditionally seen as so-called gas guzzlers — like pickup trucks, muscle cars, and hummers — all have electric equivalents. Governments, including the one running the United States, are improving infrastructure, offering tax incentives, and enacting policies aimed at getting more electric vehicles on the road. And modern-day industrial icons like Elon Musk, who obviously has a vested interest in the electric car’s success, constantly promote the concept. Musk recently published a tweet that likened internal combustion engines to the steam engine — an archaic method of producing mechanical power.

The loss of life would be equivalent to six planes, each carrying 200 passengers, killing everyone on board, every year.

Reducing air pollution from road transport will save thousands of lives and improve the health.

In our published research we evaluated the costs and benefits of a rapid transition. In one scenario, Australia matches the pace of transition of world leaders such as Norway. The modeling estimates this would save around 24,000 lives by 2042. Over time, the resulting greenhouse emission reductions would almost equal Australia’s current total annual emissions from all sources.

Continue reading “Rapid adoption of electric vehicles could save money and avoid 24,000 deaths over 20 years” »

A team at Los Alamos National Laboratory has developed a novel approach for comparing neural networks that looks within the “black box” of artificial intelligence to help researchers understand neural network behavior. Neural networks recognize patterns in datasets; they are used everywhere in society, in applications such as virtual assistants, facial recognition systems and self-driving cars.

“The artificial intelligence research community doesn’t necessarily have a complete understanding of what neural networks are doing; they give us good results, but we don’t know how or why,” said Haydn Jones, a researcher in the Advanced Research in Cyber Systems group at Los Alamos. “Our new method does a better job of comparing neural networks, which is a crucial step toward better understanding the mathematics behind AI.”

Jones is the lead author of the paper “If You’ve Trained One You’ve Trained Them All: Inter-Architecture Similarity Increases With Robustness,” which was presented recently at the Conference on Uncertainty in Artificial Intelligence. In addition to studying network similarity, the paper is a crucial step toward characterizing the behavior of robust neural networks.