MIT’s SceneSmith creates realistic 3D worlds where robots safely train, reducing costs and speeding AI-powered robot development.
Category: transportation – Page 2
Secure glass containers for storing chemical waste through laser welding
As the adoption of electric vehicles continues to grow, so does the need for the safe and permanent storage of battery materials and industrial chemical waste. Certain waste streams require disposal in what are known as Category IV landfills, which impose particularly stringent requirements on storage containers. These must simultaneously ensure environmental protection, safe handling and long-term structural integrity.
Glass is a highly promising material for this application: It is exceptionally chemically inert—meaning it reacts with virtually no other substances—making thick-walled glass containers especially well-suited for the permanent containment of hazardous materials. Glass containers are also of particular interest in the context of potential new recycling methods in the future. The stored residual materials do not react with the containers and can be readily recovered from them.
Until now, these glass containers have been manufactured primarily using thermal gas processes. However, these are limited by uncontrolled heat input, high residual stresses and restricted automation potential. Laser welding, on the other hand, enables high processing speeds and shows excellent potential for automation.
Metals’ atomic arrangement can create ‘corrosion highways’ in nuclear reactors
Nuclear reactors are traditionally powered with dense fuel rods that can produce about 1 gigawatt of carbon-free electricity, enough to power about 100,000,000 lightbulbs. Newer power plant designs using molten salt for cooling instead of the water found in traditional reactors could offer better efficiency and stability, but they face a problem—the extreme chemical environment created by the molten salt can corrode the metal comprising the reactor.
A team led by engineers at Penn State found that adjusting the subtle atomic arrangement of structural metals can significantly affect the rate and extent of this corrosion, even with identical baseline chemical compositions. They did this by creating a series of reactive simulations to isolate and study this corrosion mechanism. Their findings are available online ahead of publication in the August issue of Corrosion Science.
New research enables a robot to chart a better course
In the aftermath of a devastating earthquake, unpiloted aerial vehicles (UAVs) could fly through a collapsed building to map the scene, giving rescuers information they need to quickly reach survivors.
But this remains an extremely challenging problem for an autonomous robot, which would need to swiftly adjust its trajectory to avoid sudden obstacles while staying on course.
Researchers from MIT and the University of Pennsylvania developed a new trajectory-planning system that tackles both challenges at once. Their technique enables a UAV to react to obstacles in milliseconds while staying on a smooth flight path that minimizes travel time.
Some People Can ‘Absorb’ a Richer Version of Reality, Scientists Say. Are You One of Them?
“A lot of [the research subjects] are engineers, scientists—like very rational people,” Lifshitz says. “And it just shows me that the imagination is so powerful, that there’s so much we don’t even know yet about, if you invest energy into your imagination, it can actually come to life.”
He believes that through experiences like nature exposure, psychedelic therapy, or practices like creating a Tulpa, people can train themselves to be more absorptive. And that, from his perspective, would create a better world.
“I’m personally really interested in the idea that you can actually train yourself to have life feel more magical,” Lifshitz says. “You can make life enchanted through the power of your mind.”
Meituan Trains the First Frontier-Scale LLM Entirely on Chinese Domestic Chips: LongCat-2.0
* Performance: The model is optimized for “agentic coding” tasks. In benchmarks, it scored 59.5 on SWE-bench Pro, surpassing Google’s Gemini 3.1 Pro and slightly exceeding OpenAI’s GPT-5.5. It also performed strongly on other agent and reasoning tests.
* Inference and Release: Before its official launch, it operated anonymously on OpenRouter as “Owl Alpha,” becoming one of the platform’s top three most-used models. The model weights and technical infrastructure are expected to be released soon on platforms like Hugging Face. API pricing is set at $0.75 per million input tokens and $3 per million output tokens, with promotional rates available.
Meituan trained LongCat-2.0 on over 50,000 unnamed Chinese AI ASICs arranged in superpods with high-bandwidth interconnects. The chips share architectural similarities with Huawei’s Ascend 910C series, though Meituan has not publicly named the exact vendor.
The training run consumed more than 35 trillion tokens, including hundreds of billions of tokens with approximately 1-million-token context lengths. This level of scale — previously achieved only on NVIDIA GPUs or Google TPUs — required extensive custom engineering in parallelism, fault tolerance, and numerical stability.
The team implemented 6D parallelism (tensor, context, expert, data, pipeline, and embedding parallelism) to efficiently distribute both the MoE layers and the novel embedding components across the cluster.
Microstructure-based model predicts sheet metal behavior in seconds for car and battery design
A research team led by Kyung Mun Min and Seonghwan Choi of Materials Processing Research Division (Korea Institute of Materials Science) has developed a new analysis model capable of predicting the anisotropic mechanical behavior of sheet metals within seconds using only microstructural information of metallic materials.
The technology is expected to reduce the time and cost required to design forming processes for metallic materials used in automobiles and batteries by enabling fast, accurate prediction of how sheet metals stretch and deform without complex, repetitive experiments.
The study is published in the International Journal of Plasticity.
LiDAR approach could change factory inspections for tiny hard-to-reach parts
Researchers have developed a new LiDAR approach that makes it possible to image small objects with much greater precision and accuracy than conventional LiDAR. The method could be useful for acquiring noncontact measurements of critical parts or features during manufacturing.
“LiDAR systems like the ones used in autonomous cars typically measure large objects like roads, cars and trees at large distances with an accuracy of a few centimeters,” said research team leader Derryck T. Reid from Heriot-Watt University in the U.K. “Our LiDAR imaging technique makes it possible to acquire measurements with much greater accuracy while maintaining fully electronic detection, which avoids the complexity and scalability challenges of some high-precision systems.”
In the journal Optics Letters, the researchers describe their new imaging technique, which is based on two-photon dual-comb ranging. They show that the approach can be used to create detailed 3D representations of small aluminum objects with micron-scale precision from 40 centimeters (16 inches) away.