In a paper published in National Science Review, an international team of scientists present a highly visible-transparent thermochromic smart window based on a two-way shape memory polymer to enable reversible transformation with modulation on near-infrared transmissivity of 44.0% and mid-infrared emissivity of 76.5%. This device can exhibit excellent performance on thermal regulation in field tests and is expected to promote the progress of thermochromic windows for energy-efficient buildings.

The study conducted in Beijing highlights a significant association between long-term exposure to fine particulate matter (PM_2.5) and the incidence of gynecologic cancer; and identifies sulfate (SO₄²⁻) and carbon black (BC) as the key constituents contributing to the association.

Achieving net-zero CO₂ emissions is the current main focus of China’s carbon neutrality goal. However, non-CO₂ greenhouse gases (GHGs) are more powerful climate forcers, making their emission reduction an opportunity to rapidly mitigate future warming. This study evaluates non-CO₂ mitigation potentials, costs and climate benefits in the context of China’s carbon neutrality goals. The findings indicate that mitigation technologies can largely reduce fluorinated gas emissions from industrial sectors, but long-term non-CO₂ reductions of energy sector activities rely heavily on fuel switching. Furthermore, the cumulative costs of deploying non-CO₂ mitigation technologies are projected to be less than 10% of the total costs of achieving carbon neutrality from 2020 to 2060. If non-CO₂ mitigation measures are included in the overall mitigation portfolio, the benefits of avoided warming would by far outweigh the total mitigation cost increase.

In a paper published in SCIENCE CHINA Chemistry, a facile and applicable method to in-situ modify the Al anode surface with F–Al–O chemical bonds has been developed, which could preferentially induce the planar growth of Al on Al anode, thus leading to the dendrite-free morphology evolution and improved cycling stability of Al metal batteries. This work provides novel insights on low-cost and facile strategies against the Al dendrite growth in rechargeable aluminum batteries.

In a paper published in SCIENCE CHINA Chemistry, mechanism investigations and catalyst design strategies of catalytic upgrading ethanol and acetic acid into C4 energy-intensive fuels and chemicals are understood comprehensively, in order to provide guidelines for the development and application of highly efficient catalysts.

A recent study has reported a novel breeding strategy to rapidly create climate-smart crops that show higher yield under normal conditions and greatly rescue yield losses under heat stress both in staple grain and vegetable crops.

A research team reveals that β-ionone, a naturally occurring compound with known anti-inflammatory and antimicrobial properties, may offer a novel preventive strategy for ulcerative colitis (UC), a chronic and debilitating inflammatory bowel disease.

The challenges posed by climate change and greenhouse gas net-zero transition are discussed. Several key technology areas which require innovation are briefly reviewed in this article, including renewables, energy storage, distributed energy resources, CO₂ utilization, agriculture, and the synergy between Al and energy transition. The shift in mindset from “re-cycling” to “re-using” and a redefinition of “wealth” for a more sustainable future are also proposed.

Cancer is a heterogeneous and multifaceted disease with a significant global footprint. Despite substantial technological advancements for battling cancer, early diagnosis and selection of effective treatment remains a challenge. With the convenience of large-scale datasets including multiple levels of data, new bioinformatic tools are needed to transform this wealth of information into clinically useful decision-support tools. In this field, artificial intelligence (AI) technologies with their highly diverse applications are rapidly gaining ground. Machine learning methods, such as Bayesian networks, support vector machines, decision trees, random forests, gradient boosting, and K-nearest neighbors, including neural network models like deep learning, have proven valuable in predictive, prognostic, and diagnostic studies. Researchers have recently employed large language models to tackle new dimensions of problems. However, leveraging the opportunity to utilize AI in clinical settings will require surpassing significant obstacles—a major issue is the lack of use of the available reporting guidelines obstructing the reproducibility of published studies. In this review, we discuss the applications of AI methods and explore their benefits and limitations. We summarize the available guidelines for AI in healthcare and highlight the potential role and impact of AI models on future directions in cancer research.