Rongrong Li

Dec 4, 2024 | onlinelibrary.wiley.com | Cong Liu |Yanguo Yin |Rongrong Li |Haoping Wang

Conflicts of Interest The authors declare no conflicts of interest. References 1, , and , “Load Capacity of Lubricated Bismuth Bronze Bimetal Bearing Under Elliptical Sliding Motion,” Wear 388–389 (2017): 72–80. 2 and , “ Frictional Heating Calculations,” in Friction, Lubrication and Wear Technology, eds. P. J. Blau and D. S. Henry (Ohio: ASM International, 1992), 39–44. 3, , , and , “Solid Lubrication at High-Temperatures-A Review,” Materials 15 (2022): 1695.

Oct 16, 2024 | pubs.rsc.org | Rongrong Li |Yue Liu |Xinxin Lin |Gaohui Shi

Protective activity of health-promoting compounds in leaves of Crataegus pinnatifida Bge. The leaves of Crataegus pinnatifida Bge., a kind of brewed tea and a traditional medicine, but always obtained as a by-product of its fruit consumption, have been demonstrated to possess cardiovascular protection and lipid-lowering effects. To further explore their potential applications, nine new compounds (1–9), along with 12 known flavonoids, were isolated from the leaves of C.

Sep 27, 2024 | nature.com | Qiang Wang |Xinhua Wang |Rongrong Li

This study examines the impact of geopolitical risk on energy transition, focusing on the moderating roles of environmental regulations and green innovation within OECD countries. By employing a multivariate linear and nonlinear regression model, we identify a substantial positive effect of geopolitical risk on energy transition. Our analysis indicates that stronger environmental regulations and advancements in green innovation significantly amplify this effect. Through threshold effect bootstrap sampling tests, we detect a nonlinear relationship between geopolitical risk and energy transition at varying levels of environmental regulation and green innovation. We also explore lag effects, revealing that the influence of geopolitical risk on energy transition grows stronger over time. The inclusion of interaction terms in our analysis further clarifies the moderating influences of environmental regulation and green innovation. Utilizing a range of geopolitical risk indicators and regression methods, our findings are robust, consistently highlighting the proactive role of geopolitical risk in fostering energy transition. These insights highlight the importance of integrated strategies that harness environmental regulations and technological innovation to facilitate a resilient and efficient energy transition in the face of challenges posed by geopolitical uncertainties.

Sep 9, 2024 | pubs.rsc.org | Jun Yang |Mingzi Sun |Rongrong Li |Lijiang Yin

Fluorine-rich deep eutectic electrolytes enabling robust interphases and nonflammability of high-voltage lithium metal batteries High-voltage Li metal batteries (LMBs) are characterized by the superior energy density over state-of-the-art Li-ion batteries, but it is an essential challenge to develop electrolytes which can be stably and safely cycled with both reactive Li metal anodes and high-voltage cathodes.

Aug 14, 2024 | nature.com | Qiang Wang |Rongrong Li |Yuanfan Li

This study examines the multifaceted impact of artificial intelligence (AI) on environmental sustainability, specifically targeting ecological footprints, carbon emissions, and energy transitions. Utilizing panel data from 67 countries, we employ System Generalized Method of Moments (SYS-GMM) and Dynamic Panel Threshold Models (DPTM) to analyze the complex interactions between AI development and key environmental metrics. The estimated coefficients of the benchmark model show that AI significantly reduces ecological footprints and carbon emissions while promoting energy transitions, with the most substantial impact observed in energy transitions, followed by ecological footprint reduction and carbon emissions reduction. Nonlinear analysis indicates several key insights: (i) a higher proportion of the industrial sector diminishes the inhibitory effect of AI on ecological footprints and carbon emissions but enhances its positive impact on energy transitions; (ii) increased trade openness significantly amplifies AI’s ability to reduce carbon emissions and promote energy transitions; (iii) the environmental benefits of AI are more pronounced at higher levels of AI development, enhancing its ability to reduce ecological footprints and carbon emissions and promote energy transitions; (iv) as the energy transition process deepens, AI’s effectiveness in reducing ecological footprints and carbon emissions increases, while its role in promoting further energy transitions decreases. This study enriches the existing literature by providing a nuanced understanding of AI’s environmental impact and offers a robust scientific foundation for global policymakers to develop sustainable AI management frameworks.