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Category: transportation – Page 2

New strategy for designing ultra-fast charging batteries could prevent hazardous lithium plating

A redesigned lithium-ion anode retained 86% of its initial capacity at a demanding 10C charge rate and stayed stable for more than 250 cycles, while aiming to reduce hazardous lithium plating during fast charging.

The rapid progress in electric vehicles and high-power electronics has increased the demand for ultra-fast-charging lithium-ion (Li-ion) batteries. However, during fast charging, current Li-ion rechargeable batteries suffer from severe degradation in power and potential catastrophic failure, increasing safety risks. This is mainly due to electrochemical instability at the anode–electrolyte interface, causing hazardous Li metal plating on their surface and poor thermal stability.

Recently, high-voltage anode materials have emerged as promising alternatives because they prevent excessive lithium plating and the formation of unstable solid-electrolyte interface layers. Despite these advantages, current state-of-the-art materials are limited by poor ionic conductivity and thermal stability, reducing power output and long-term reliability.

To address these issues, a research team led by associate professor Dongwook Han from Seoul National University of Science and Technology in South Korea developed a novel strategy.

Zoox gets the green light to offer paid rides

The Department of Transportation has approved a request from the driverless vehicle company Zoox to start offering rides to paying customers. A California-based company owned by Amazon, Zoox has been testing its driverless electric vehicle with free rides. Now, it has approval to commercially deploy up to 5,000 vehicles over the next two years, starting in Las Vegas. Unlike Google’s Waymo, which adds driverless technology to existing vehicles, Zoox’s vehicles look like a box on wheels and don’t have steering wheels or pedals. Find “NPR News Now” wherever you listen to podcasts. Host: Jeanine Herbst/NPR Reporter: Camila Domonoske/NPR Producer: Michael Zamora/NPR

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AI tech proactively prevents subway door entrapment accidents

A research team led by Professor Jo Woon Chong of the School of Electronic and Electrical Engineering at Sungkyunkwan University (SKKU), in collaboration with researchers from KAIST and Texas Tech University in the United States, has developed the Passenger Movement Estimation System (PMES). This AI-based system predicts passenger movements using CCTV footage to prevent subway door entrapment accidents before they occur.

Overcoming the limitations of conventional reactive methods, in which sensors trigger only after a passenger has entered the danger zone, the system proactively identifies risks before passengers reach the boarding area. The findings are published in IEEE Transactions on Intelligent Transportation Systems.

Chong, who has led research at Sungkyunkwan University on human-centered AI, multimodal signal processing and AI-embedded systems, oversaw the study. Hee Jo, the first author and a Ph.D. student, led the data analysis and AI model design.

Predicted Noncrystalline Structures Have Bonus Properties

Simulations reveal disordered structures that are also surprisingly resistant to impacts and cracks.

Metamaterials derive their unique properties from their tailored, macroscale structures, not from their chemical compositions or atomic-scale structures. Although designers often rely on regular, repeating architectures, many of nature’s toughest materials—from bone to spider silk—owe their resilience to structural disorder. Now, inspired by those biological examples, researchers have used machine learning to find new designs for disordered metamaterials [1]. These structures not only have the properties for which they were optimized, but they also resist deformation and fracture. The researchers have built a prototype car bumper based on their designs, and they propose uses in ballistic shields, helmets, and other protective equipment.

The design of functional metamaterials has conventionally focused on ordered structures, where the repeating nature of the patterns allows predictions of macroscopic behavior. Amorphous structures lack that periodicity, leaving an enormous number of possible disordered arrangements that are difficult to explore systematically. Yet disorder can also be an asset, enabling mechanical behaviors that are otherwise difficult or impossible to achieve. The main challenge has been to search the large number of potential structures efficiently enough to identify the rare ones that combine useful functionality with physical stability.

Ancient Chinese seeds spanning 5,000 years train AI to ease archaeology’s specialist bottleneck

Ancient plant seeds provide important archaeological evidence for studying the evolution of human civilization. Lingnan University and Shandong University have jointly developed the world’s first artificial intelligence (AI) archaeological system dedicated to identifying ancient Chinese plant seeds. The system emulates the identification process of archaeobotanical experts and achieves a classification accuracy of more than 90%.

The researchers said identifying plant seeds excavated from archaeological sites has traditionally relied on experts examining each seed individually, a process that is both time-consuming and difficult to scale. The large, standardized database they created helps improve research efficiency while advancing archaeobotanical research and the digitization of cultural heritage.

The findings have been published in Heritage Science.

World Labs’ SimtoReal Leap Let Robots Run An Hour Alone

🚨 World Labs just showed a big sim-to-real leap: robots that can run autonomously for a full hour without human help.

Better world models and physics transfer are making longer, more reliable autonomous runs possible.

This is a practical win for factories and warehouses — less supervision, higher uptime, and lower deployment costs.

The sim-to-real gap is getting smaller.

Full analysis: [ https://creedtec.online/world-labs-sim-to-real-leap-let-robo…our-alone/](https://creedtec.online/world-labs-sim-to-real-leap-let-robo…our-alone/)

#IndustrialRobotics #SimToReal #Automation

Continue reading “World Labs’ SimtoReal Leap Let Robots Run An Hour Alone” | >

Repeating distance patterns let optical systems tackle large optimization problems

From planning transportation networks to organizing massive datasets, many of society’s most important challenges boil down to an optimization problem: finding the best solution among an enormous number of possibilities. As these problems increase in size and scope, however, the computational resources required to solve them can increase dramatically.

Now, researchers from Japan have identified a new way to tackle a broad class of optimization problems while keeping computational demands manageable.

Nimbus Manticore Deploys NightLedger and Turns Victim Systems Into Covert Relays

The Iranian state-backed hacking group tracked as Nimbus Manticore (aka GalaxyGato, Mirage Kitten, Smoke Sandstorm, Subtle Snail, and UNC1549) has been attributed to a fresh set of attacks targeting entities across the Middle East, Africa, and South Asia.

The intrusions involve the use of a previously undocumented Windows backdoor called NightLedger and two custom WebSocket tunnelers, BridgeHead and ArcBridge, with an aim to maintain covert access.

Targets of the campaign include Egypt, SMB and government environments in Jordan and Tanzania, aviation organizations in Pakistan, telecommunication companies in Ethiopia, and financial-sector entities in Burkina Faso, per Kaspersky.

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