Scientists have made major progress in explaining friction, but predicting and controlling it still depends heavily on experiments. A comprehensive review examines the physics-based models behind friction, highlights why friction remains difficult to predict, and identifies key challenges that could make friction control more precise and reliable.

Researchers summarized how friction and electrical current interact to wear down moving components in electrified systems, such as railways and aerospace devices. They also evaluated predictive models for wear and highlighted the need for more realistic testing and improved AI-based forecasting.

Neural radiance fields (NeRFs) are a powerful form of artificial intelligence (AI) that utilizes 2D images to synthesize a 3D scene and “learn” what a realistic 3D representation of the base information would look like. While NeRFs initially revolutionized computer vision in the early 2020s, a new method called Gaussian Splatting quickly overtook NeRFs. In this comprehensive review, researchers explore some of the differences between these two methods and their applications in the hopes of better informing future computer vision practitioners.

Advances in foundation models (FM) have opened the gates to an advanced use of artificial intelligence for healthcare. FMs are an AI system with a great ability to perform accurately on new sets of data or tasks, instead of just memorizing the material it was trained with. Vision-language foundation models (VLFM) are particularly of interest to clinicians as a means to aid in report generation and question answering, with vision-language agents (VLAs) being representative of the next frontier for AI acting in a healthcare space.

Traditional solid oxide cell cathodes have insufficient electrocatalytic activity and poor CO₂ tolerance. High-entropy perovskite cathodes are synthesized via temperature regulation to tailor crystal structures. The optimized cathode reaches an area-specific resistance of 0.040 Ω·cm² and a power density of 1.38 W·cm^-2, running stably for over 260 h. This approach facilitates the commercial development of high-performance reversible solid oxide cells.

Increasing pavement skid resistance on a London highway by 50% reduced the total number of accidents over four years by 45%, according to the United Kingdom Transport and Road Research Laboratory. The United States National Transportation Safety Board and Federal Highway Administration stated that poor pavement skid resistance is a major cause of driving accidents. These are just two sources cited by an international team of researchers who recently reviewed more than 3,000 studies on tire-road friction and found that while tire-road friction theory and simulations have been well developed across the research scales — rubber-pavement scale, the tire-road scale and the vehicle scale — the scales themselves remain largely unconnected.

Factors that contribute to rubber friction have been widely characterized, but few studies have focused on methods by which rubber grip can be improved in the presence of lubricants. A team of scientists recently compiled a comprehensive review designed to help researchers weigh the benefits and drawbacks of various rubber grip-enhancing approaches in the presence of common lubricants to enhance the safety of everyday products.

Scientists are looking to nature for bioinspired adhesion and friction materials. Geckos, tree frogs and octopuses all provide scientists with the inspiration for these materials. Current research focuses mostly on a single environment or single performance for these materials, lacking a systematic framework across scales, media, and disciplines. A research team has proposed a framework that overcomes these barriers by creating highly adaptable, multifunctional systems for bioinspired adhesion and friction materials. Potential applications range from space environments that are tolerant of robotics for lunar exploration to self-adjusting biomedical devices for health monitoring.

A new conceptual article published in eGastroenterology proposes that metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-associated liver disease (MetALD), and alcohol-associated liver disease (ALD) should be viewed as a dynamic continuum rather than fixed diagnostic entities. The authors highlight how fluctuations in alcohol intake and metabolic dysfunction drive transitions across disease categories over time. The work also emphasizes objective alcohol biomarkers, particularly phosphatidylethanol (PEth), as emerging tools for improving risk stratification and personalized management in steatotic liver disease.

Rolling contact bearings are an important part of mechanical systems that reduce friction between moving parts. Scientists need to be able to accurately model these bearings so they can predict their performance, durability, and failure mechanisms. Even though significant advancements have been made, there is still a need for a unified framework to evaluate and compare the existing modeling approaches. A research team has studied the most significant rolling contact bearing models, identifying key trends and advancements. Their findings reveal a significant variability in the modeling approaches used and highlight the lack of standardized methodology for modeling these complex systems.