To address the trade-off between accuracy and cross-city generalization in traffic flow estimation, a research team from The Hong Kong Polytechnic University and New York University proposes a novel framework based on global open multi-source (GOMS) data, including urban structures and population density. By developing an advanced graph neural network model that effectively fuses these static urban features with dynamic traffic data, the study achieves stable and accurate network-wide traffic estimation, as validated across 15 diverse cities in Europe and North America.

Researchers at National University of Singapore used multiple interpretable machine learning methods to predict traffic congestion in in Alameda County in the San Francisco Bay Area, USA, during the pre-lockdown, lockdown, and post-lockdown periods.

The development of bioinspired electronic skin plays a pivotal role in enhancing robotic environmental perception and interaction capabilities, with stretchable multimodal tactile sensors serving as the fundamental component. However, existing tactile sensors are often constrained by limited integration density and spatial resolution, hindering their applicability in complex scenarios. To address these challenges, this study proposes a multimodal tactile sensing strategy based on the synergistic integration of pressure and strain sensors. By innovatively embedding strain sensors into the gaps between pressure sensor units, both types of sensors are co-fabricated in a coplanar configuration, enabling simultaneous and high-precision detection of pressure and strain. Leveraging the dual-mode sensing data, the system further enables accurate evaluation of object hardness.

Lithium metal batteries hold great promise for high performance energy storage due to their high theoretical energy density. However, practical implementation is hindered by interfacial side reactions and dendrite growth at the Li metal anode, particularly in carbonate-based electrolytes. Hereby, the authors introduce a novel multifunctional group additive strategy using 2-fluorobenzenesulfonamide (2-FBSA) to address these challenges. The 2-FBSA additive plays a crucial role in modulating the solvation structure of the electrolyte, facilitating Li⁺ transport kinetics by lowering the desolvation energy barrier. Additionally, the preferential decomposition of 2-FBSA at the anode interface leads to the formation of a robust solid electrolyte interphase (SEI) enriched with inorganic Li salts, including LiF, Li₃N, and ROSO₂Li. This SEI layer effectively suppresses Li dendrite growth and mitigates parasitic side reactions, resulting in significantly improved cycling stability and rate performance of Li||Li symmetric cells and Li||LiFePO₄ full cells. The Li||Li symmetric cell achieves a remarkable lifespan exceeding 2400 h at 0.5 mA cm⁻²/1 mAh cm⁻² , while the Li||LiFePO₄ full cell demonstrates a capacity retention of 72% after 400 cycles at 1 C. This study highlights the potential of multifunctional group molecular additive 2-FBSA in interfacial optimization and provides new insights into additive design principles for high performance battery systems.