A universal potential for all-purpose atomic simulations has been pursued for decades, but remains challenging due to limitations in model expressiveness and dataset construction. Now, writing in the journal Science China Chemistry, the research team led by Professor Zhi-Pan Liu at Fudan University has developed a generalized global neural network potential (GG-NN) based on a newly proposed low-cost, high-accuracy High-order Pair-reduced Neural Network (HPNN) model and a comprehensive global potential energy surface dataset of 5.84 million configurations covering 83 elements. GG-NN achieves high-precision predictions for both energies and forces, offering the potential to significantly accelerate the prediction and design of molecular and materials systems.

Biochar has been widely promoted as a sustainable solution for improving soil health, cleaning polluted water, and capturing carbon. However, a comprehensive review warns that its environmental safety may be more complex than previously thought.

Researchers from Koç University have developed a new artificial intelligence model that predicts where people direct their attention in 360-degree videos by integrating both audio and visual cues, addressing a key challenge in immersive media where viewers are free to explore their surroundings rather than being guided by a fixed camera frame; unlike conventional approaches that rely mainly on visual information, the model jointly analyzes sound and image data to better reflect how humans perceive complex, dynamic environments, resulting in more accurate attention prediction in virtual reality and 360-degree video settings, with potential applications ranging from immersive media design and video production to human–computer interaction and content optimization.

Osaka Metropolitan University researchers proposed a geometry-aware framework for automatically removing human noise from TLS point clouds by projecting 2D instance segmentation masks into 3D space and validating candidates through multi-stage geometric filtering.

Phosphorus is essential for plant growth, yet much of the phosphorus in soils worldwide remains locked in forms that crops cannot use. A new review study highlights how biochar, a carbon-rich material derived from biomass, could play a key role in improving phosphorus availability and boosting agricultural sustainability.

Researchers from Koç University and international collaborators have developed a new algorithm that enables faster and more equitable distribution of disaster relief supplies. By integrating fairness directly into logistics planning, the model reduces inequality in unmet demand by up to 34% without compromising delivery speed. The approach offers a practical tool for improving decision-making in real-world emergency response operations.

An Osaka Metropolitan University research team proposed a non-contact approach for characterizing post-regurgitation deep inhalation in calves using infrared thermography and deep learning-based nostril segmentation.