In a hunt for more sustainable technologies, researchers are looking further into enabling two-dimensional materials in renewable energy that could lead to sustainable production of chemicals such as ammonia, which is used in fertilizer.

This next generation of low-dimensional materials, called MXenes, catalyzes the production of air into ammonia for foods and transportation for high-efficiency energy fertilizers.

MXenes has a wide range of possibilities that allow for highly flexible chemical compositions, offering significant control over their properties.

For consumers worried about the risks associated with using lithium-ion batteries—which are used in everything from phones to laptops to electric vehicles—Michigan State University has discovered that a natural material found in wood can improve battery safety while also improving the battery’s life.

Chengcheng Fang, assistant professor in the College of Engineering, and Mojgan Nejad, an associate professor in the College of Agriculture and Natural Resources, collaborated to engineer lignin, a natural ingredient of wood that provides support and rigidity, into a thin film separator that can be used inside lithium-ion batteries to prevent short circuits that can cause a fire.

“We wanted to build a better battery,” said Fang. “But we also wanted it to be safe, efficient and sustainable.”

Questions to inspire discussion.

Q: How is Ford trying to shape consumer attitudes towards driving? A: Ford is attempting to convince consumers that driving is an essential life skill rather than a chore, possibly to maintain demand for traditional vehicles.

Q: What message is Ford sending about the future of driving? A: Ford’s CEO suggests that everyone should continue to know how to drive, implying that fully autonomous vehicles are not the immediate future.

Regulatory Approach.

Q: How might Ford be influencing regulators regarding autonomous vehicles? A: Ford may be trying to convince regulators that autonomous vehicles are not significantly safer than human drivers to potentially delay or prevent approval.

Technology Development.

IN A NUTSHELL The Cavorite X7 is the world’s first ‘heli-plane’, offering a revolutionary blend of helicopter and airplane capabilities. Featuring a fan-in-wing design, it achieves vertical takeoff and transitions to high-speed flight seamlessly. With a cargo capacity of up to 1,500 lbs, it serves as an efficient solution for both passenger

The aviation industry witnessed a monumental breakthrough on February 10, 2025, as Boom Supersonic’s XB-1 aircraft accomplished what many experts deemed impossible. Flying over the Mojave Desert at speeds exceeding the sound barrier, the aircraft achieved something unprecedented in aviation history: supersonic flight without generating a sonic boom. This revolutionary achievement has opened new possibilities for the future of air travel.

For decades, the notorious sonic boom has been the Achilles’ heel of supersonic travel. When aircraft exceed the speed of sound (approximately 761 miles per hour at sea level), they create powerful shock waves that culminate in the distinctive thunderous crack heard on the ground. This disruptive phenomenon has historically restricted supersonic flights to ocean routes, as demonstrated by the iconic Concorde.

Boom Supersonic’s XB-1 has changed this narrative through its implementation of Mach cutoff technology. This innovative approach exploits atmospheric conditions to redirect shock waves upward rather than toward the ground. By carefully selecting specific flight altitudes and analyzing atmospheric data, the aircraft effectively minimizes the impact of these pressure waves.

Researchers have demonstrated a new way of attacking artificial intelligence computer vision systems, allowing them to control what the AI “sees.” The research shows that the new technique, called RisingAttacK, is effective at manipulating all of the most widely used AI computer vision systems.

At issue are so-called “adversarial attacks,” in which someone manipulates the data being fed into an AI system to control what the system sees, or does not see, in an image. For example, someone might manipulate an AI’s ability to detect traffic signals, pedestrians or other cars—which would cause problems for autonomous vehicles. Or a hacker could install code on an X-ray machine that causes an AI system to make inaccurate diagnoses.

“We wanted to find an effective way of hacking AI vision systems because these vision systems are often used in contexts that can affect human health and safety—from autonomous vehicles to health technologies to security applications,” says Tianfu Wu, co-corresponding author of a paper on the work and an associate professor of electrical and computer engineering at North Carolina State University.

Tesla’s 2024 impact report highlights the company’s progress in accelerating its mission to sustainable energy through innovative technologies, including autonomy, AI, and reduced emissions, with a focus on expanding its ecosystem and making sustainable transportation and energy solutions more accessible ## ## Questions to inspire discussion.

Sustainable Transportation.

Q: How will Tesla’s robo taxi network impact transportation?

A: Tesla’s autopilot-powered robo taxi network will be far safer than human drivers, lower emissions, and increase accessibility of sustainable transportation, improving city sustainability and accelerating Tesla’s mission.

Q: What are the benefits of Tesla vehicles compared to other options?

A: Tesla vehicles offer premium features rivaling luxury cars while maintaining a total cost of ownership comparable to mass market vehicles, providing significantly more value at a similar price point.

How reliable is artificial intelligence, really? An interdisciplinary research team at TU Wien has developed a method that allows for the exact calculation of how reliably a neural network operates within a defined input domain. In other words: It is now possible to mathematically guarantee that certain types of errors will not occur—a crucial step forward for the safe use of AI in sensitive applications.

From smartphones to self-driving cars, AI systems have become an everyday part of our lives. But in applications where safety is critical, one central question arises: Can we guarantee that an AI system won’t make serious mistakes—even when its input varies slightly?

A team from TU Wien—Dr. Andrey Kofnov, Dr. Daniel Kapla, Prof. Efstathia Bura and Prof. Ezio Bartocci—bringing together experts from mathematics, statistics and computer science, has now found a way to analyze neural networks, the brains of AI systems, in such a way that the possible range of outputs can be exactly determined for a given input range—and specific errors can be ruled out with certainty.

BYD, an electric vehicle company, is accused of cooking the books and faking profitability, potentially hiding financial issues such as a liquidity crisis and unprofitable electric vehicle business.

Questions to inspire discussion.

Financial Concerns Q: What are the warning signs of BYD’s potential financial trouble? A: BYD is offering massive discounts of 10–30% on already affordable vehicles, with some models selling for as low as $10,000, and allegedly has a 12-month payment delay to suppliers. Q: How is BYD’s automotive business reportedly staying afloat? A: BYD’s automotive business is allegedly being carried by their highly profitable battery cell supply business, which is not separately reported in their financials, making it difficult to determine the true profitability of their electric vehicle sales.

Tesla’s autonomous driving technology, particularly its vision-only approach, is being showcased and defended in response to criticism from Ford’s CEO and others, who prefer LiDAR-based solutions ## Questions to inspire discussion.

Tesla’s Autonomous Technology.

Q: How does Tesla’s autonomous vehicle technology differ from competitors? A: Tesla uses a vision-only approach without LiDAR, while competitors like Waymo rely on LiDAR and radar systems.

Q: What makes Tesla’s approach to autonomous vehicles more scalable? A: Tesla aims to make all 8 million+ vehicles on the road capable of self-driving with a software update, unlike competitors focusing on specific areas.

Market Comparison.

Q: How does Tesla’s autonomous vehicle fleet compare to Waymo’s? A: Tesla has over 8 million vehicles capable of autonomy, while Waymo has less than 2,000 vehicles on the road.