A breakthrough in battery technology has been made with the development of a polyvinylidene fluoride (PVDF)-Li₂CO₃ nanofiber network. This new material, developed through electrospinning, serves as a host for stable lithium metal plating and stripping, enabling a lithium metal anode for a battery. By integrating lithium carbonate into the nanofiber structure, researchers have created a more uniform lithium deposition, reducing dendrite formation and enhancing battery performance.

The immune system plays a decisive role in determining whether damaged tissues heal through scarring or true regeneration. A new review highlights how intelligently engineered nanomaterials can dynamically modulate immune responses and reshape the tissue microenvironment, opening new possibilities for accelerating regeneration across multiple organs.

Thermochromic hydrogel smart windows have achieved significant breakthroughs in the field of building energy conservation, leveraging their ability to dynamically regulate solar transmittance and providing a revolutionary solution for intelligent thermal environment management. Optimizing the thermal response performance of thermochromic hydrogels and addressing related technical bottlenecks is of great importance for promoting their widespread application and scientific innovation in the field of building energy conservation.

As electric vehicles (EVs) surge in popularity to combat climate change and reduce fossil fuel dependence, ensuring the safety and reliability of their battery systems has become a critical challenge. Battery packs in EVs consist of hundreds or thousands of cells connected in series-parallel, but inherent inconsistencies in cell voltages can lead to faults like over-voltage, under-voltage, or even thermal runaway. Traditional fault detection methods often rely on fixed thresholds for voltage consistency, which can result in false alarms or missed detections due to varying driving conditions. This study, conducted by researchers at Wuhan University of Technology, investigates the microscopic associations between real-world driving behaviors and battery cell voltage consistency (VCC), using high-frequency data from naturalistic driving experiments. By revealing these links, the research lays the groundwork for adaptive, behavior-aware fault detection algorithms that could enhance EV safety and longevity.

The explosive growth of electric vehicles, renewable energy integration, and large-scale energy storage systems has placed lithium-ion batteries at the heart of the global transition to sustainable energy. Ensuring their safe, efficient, and long-lasting performance demands sophisticated battery management systems capable of continuously tracking critical states such as state of charge, state of health, aging, and potential faults. While conventional monitoring relies on temperature sensors, voltage-current profiling, ultrasonic probes, or embedded optical fibers, these methods often provide limited multidimensional insights, incur high implementation costs, or struggle with real-time applicability in operational environments. Electrochemical impedance spectroscopy stands out as a particularly powerful technique, offering rich, frequency-dependent information about internal electrochemical processes that reflect battery dynamics under varying conditions. However, traditional EIS measurements using dedicated electrochemical workstations remain confined to laboratory settings due to their expense, bulk, and lack of online capability.

The global surge in electric vehicle adoption stands as a cornerstone of efforts to combat climate change and reduce reliance on fossil fuels, with EVs poised to play a transformative role when paired with renewable energy sources. Public charging stations, as critical nodes in this ecosystem, face mounting pressure from uncoordinated large-scale charging that risks overloading local grids, driving up peak demand, and hindering the seamless incorporation of intermittent solar and wind power. While grid upgrades offer one path forward, their prohibitive costs make smarter management of existing infrastructure far more practical. The extended dwell times typical of most charging sessions—often far exceeding the actual energy transfer needed—create valuable flexibility for optimized scheduling, enabling EVs to act as distributed energy resources through Vehicle-to-Grid interactions that stabilize grids and maximize clean energy utilization.

The rapid rise of electric vehicles combined with breakthroughs in autonomous driving technology is reshaping the future of transportation toward greater sustainability. Intelligent electric vehicles, particularly plug-in hybrid electric vehicles (PHEVs), hold immense potential to slash energy consumption and curb emissions through smarter, more coordinated control of motion and powertrain operations. Yet achieving this dual goal of uncompromising safety and superior energy efficiency remains challenging. Traditional approaches often treat driving safety, eco-friendly trajectory planning, and powertrain energy management as separate tasks, leading to trade-offs that limit overall performance in complex, real-world driving scenarios.

As urban centers grapple with escalating traffic congestion and the limitations of traditional two-dimensional road networks, the concept of the split flying car has emerged as a transformative solution for future intelligent transportation. These innovative vehicles, which consist of a flight module, a passenger capsule, and an intelligent chassis, offer the flexibility to switch between aerial and ground travel. However, the transition between these modes—specifically the autonomous docking of the chassis to the aircraft bracket—presents a formidable technical hurdle. Researchers at Wuhan University of Technology have recently addressed this challenge by developing a lightweight, vision-based detection model that ensures high-precision, real-time docking even in complex environments and on hardware with limited computing power.