A physics- and spatially informed diffusion model was developed to achieve rapid Monte Carlo–consistent dose prediction for CyberKnife radiotherapy. The model integrates finite-size pencil beam dose distributions, planning CT images, and signed distance maps to incorporate physical, anatomical, and spatial prior information. PSIDMViT improved agreement with Monte Carlo reference doses across head-and-neck, lung, and liver cancer cases. The model reduced the time required for Monte Carlo–consistent dose estimation from approximately one hour to about 18 minutes, supporting more efficient high-precision radiotherapy planning and verification.

This study develops a novel “Hydrology–Environment–Ecology” framework that integrates aquatic ecological risk (AER) with landscape ecological risk (LER) across lake basin boundaries. Using Chaohu Lake—one of China's largest freshwater lakes—as a case study, the research reveals that both aquatic and terrestrial ecological risks increased significantly from 2000 to 2019, with habitat quality identified as the dominant driver of aquatic risk. The framework identifies an 8-km riparian buffer zone as the critical threshold for integrated conservation, and uncovers human activity as the dominant factor elevating landscape ecological risk through both direct and indirect pathways. The study provides a transferable paradigm for cross-scale lake ecosystem management.

A research team has uncovered the chemical basis behind the distinctive honey aroma and mellow sweetness of leafhopper-pierced tea, showing that insect piercing reshapes both volatile and non-volatile metabolites across green, yellow, white, and oolong teas. 

Developed by Renmin University of China, the comprehensive Climate-gOvernance Modeling & Policy ASsessment System (COMPASS) integrates multiple complementary modeling tools to deliver multi-scale, cross-dimensional simulations for energy transition and climate governance. Combining a top-down computable general equilibrium model (CE3-CGE), a bottom-up energy technology model (PECE), an integrated assessment model (GCAM-CHN), and data-driven econometric and machine learning approaches, COMPASS effectively bridges macroeconomic trends and micro-level technological changes, providing robust scientific support for China’s carbon neutrality strategy and global climate policy research.

As China’s power system shifts from coal-dominated generation toward higher shares of variable renewable energy, maintaining reliable electricity supply is becoming more complex. A new study published in Energy and Climate Management uses causal loop diagrams to examine interactions among renewable energy deployment, storage utilization, capacity remuneration, and coal retirement decisions. By comparing China’s coal-focused capacity payments with the United Kingdom’s capacity market experience, the paper identifies potential risks including overinvestment, coal lock-in, and limited incentives for emerging flexible resources. The study suggests that capacity market pilots, broader revenue channels for energy storage, long-duration storage support, carbon pricing improvements, and strategic reserves could help manage supply security during the transition.

Protonic ceramic fuel cells (PCFCs) offer clean and efficient energy conversion at intermediate temperatures, yet their commercialization is constrained by sluggish cathode reaction kinetics and limited operational durability. A research team from Anhui University and collaborators has developed a self-assembled triple-conducting cathode via synergistic Zn/Yb B-site co-doping combined with temperature-induced nanoparticle exsolution. The optimized cathode delivers a peak power density of 0.99 W cm^-2 at 600 ℃ and stable operation for over 100 h with a degradation rate of only 0.091% h^-1, offering a promising pathway for high-performance intermediate-temperature PCFCs.

Siqi Chen and Fei Guo at Shandong University developed the MESSAGEix-China-Building-R31 model, an integrated assessment model for China’s provincial building sectors. The model consists of five core modules: building stock turnover, energy demand, material demand, carbon emissions, and low-carbon transition. The model can simulate the coupled evolution of "stock-energy-material-carbon" interactions across China’s 31 provincial-level administrative regions from 2025 to 2100. Model validation results demonstrate that the model reliably reproduces the historical evolution patterns of building vintage distributions and end-use energy intensities. As a comprehensive quantitative analytical tool, the model systematically links key regionally heterogeneous factors including floor area demand, building lifetime distribution, demolition and retrofitting requirements, building energy technologies and occupant behavioral characteristics, and demand for major building materials. Through scenario analysis, this model enables quantitative evaluation of low-carbon transition pathways for provincial building sectors in China.