Friday, April 18, 2025

 

“Faster charging, longer lifespan”: Next-generation battery breakthrough from POSTECH and KIER




Pohang University of Science & Technology (POSTECH)
Behavior of Hard Carbon–Tin Nanocomposite Anodes in Lithium-Ion and Sodium-Ion Batteries 

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Behavior of Hard Carbon–Tin Nanocomposite Anodes in Lithium-Ion and Sodium-Ion Batteries

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Credit: POSTECH




As the demand continues to grow for batteries capable of ultra-fast charging and high energy density in various sectors—from electric vehicles to large-scale energy storage systems (ESS)—a joint research team from POSTECH (Pohang University of Science and Technology) and the Korea Institute of Energy Research (KIER) has developed a promising next-generation anode material that may address these critical needs.

 

While graphite, the most common anode material in lithium-ion batteries (LIBs), offers robust structural stability, it is limited by its low theoretical capacity and sluggish charge/discharge rates. To overcome these limitations, the researchers have proposed a novel electrode design that combines hard carbon with tin (Sn).

 

Hard carbon is a disordered carbon material with an abundance of micropores and pathways, facilitating fast diffusion of lithium and sodium ions. This structure enables both high energy storage and mechanical robustness, making it ideal for high-rate and long-life applications.

 

However, incorporating tin presented another challenge. The smaller the tin particles, the more effectively the problematic volume expansion during cycling is reduced, enhancing the overall stability. Unfortunately, tin's low melting point (∼230 °C) makes it difficult to synthesize such fine particles. The research team addressed this issue using a sol–gel process followed by thermal reduction, successfully embedding uniformly distributed sub-10 nm tin nanoparticles within the hard carbon matrix.

 

The resulting composite structure exhibits functional synergy beyond simple physical mixing. The tin nanoparticles not only act as active materials but also serve as catalysts that promote the crystallization of the surrounding hard carbon. During electrochemical cycling, the reversible formation of Sn–O bonds contributes to enhancing battery capacity via conversion reactions.

 

The engineered electrode has demonstrated excellent performance in lithium-ion cells, maintaining stable operation over 1,500 cycles under 20-minute fast-charging conditions, while achieving a 1.5-fold higher volumetric energy density compared to conventional graphite anodes. This achievement represents a successful integration of high power, high energy, and long cycle life in one electrode.

 

Remarkably, the electrode also shows outstanding performance in sodium-ion batteries (SIBs). Sodium ions generally exhibit poor reactivity with conventional anode materials like graphite or silicon. However, the hard carbon–tin nano-composite structure maintains excellent stability and fast kinetics in sodium environments, underscoring its versatility across multiple battery platforms.

 

Professor Soojin Park of POSTECH stated, “This research represents a new milestone in the development of next-generation high-performance batteries and holds promise for applications in electric vehicles, hybrid systems, and grid-scale ESS.” Dr. Gyujin Song of KIER added, “The realization of an anode with simultaneously high power, stability, and energy density, along with its compatibility with sodium-ion systems, marks a turning point in the rechargeable battery market.”

 

This work was conducted by Professor Soojin Park, Dr. Sungho Choi, and Dr. Dong-Yeob Han at POSTECH, in collaboration with Dr. Gyujin Song at KIER. The results were recently published in the internationally renowned journal ACS Nano and were supported by funding from the Ministry of Trade, Industry and Energy and the Ministry of Science and ICT of Korea.

 

Unveiling the mechanism underlying the peak observed in the extratropical cyclone activity during spring in East Asia




University of Tsukuba





Tsukuba, Japan—Extratropical cyclones traveling along the Kuroshio in East Asia, called "Kuroshio cyclones," bring heavy rain and snowfall in populated and industrial areas in East Asian countries. They considerably affect societies and economic sectors, including agriculture, transportation, logistics, and renewable-energy-based power generation sectors. Although extratropical cyclones in East Asia are known to occur frequently in spring, the reason behind this seasonality is not yet clarified.

The research group previously developed a method for objectively identifying mobile high- and low-pressure systems from global atmospheric data to elucidate the mechanism underlying the seasonality of extratropical cyclones and recent changes in high- and low-pressure systems in the North Pacific. In the current study, the researchers employed the method to four-dimensional atmospheric data spanning several decades. Results indicated that the activity of the "Kuroshio cyclones" peaks in spring because the low-level jet stream around the East China Sea is intensified by air over Eurasia in the west of Japan warmed from winter to spring, facilitating the formation of low-pressure systems.

A better elucidation of the mechanism underlying the seasonality of extratropical cyclone activity in East Asia can improve our understanding of the changes in the climate system around the region under the global warming scenario and improve the accuracy of seasonal forecasts in East Asian countries.

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This study is supported in part by the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) through the Arctic Challenge for Sustainability II (ArCS-II; JPMXD1420318865) and the Advanced Studies of Climate Change Projection (SENTAN; JPMXD0722680395, by the Japan Science and Technology Agency through COI-NEXT JPMJPF2013, by the Japanese Ministry of Environment through Environmental Restoration and Conservation Agency Fund JPMEERF20242001, and by the Japan Society for the Promotion of Science (JSPS) through Grants-in-Aid for Scientific 681 Research 19H05702 (on Innovative Areas 6102), 20H01970, 21H01164, 22H01292, and 22K14097. RP acknowledges support from NOAA Climate Variability and Predictability Program NA22OAR4310617.

 

Original Paper

Title of original paper:

Mechanisms for an Early Spring Peak of Extratropical Cyclone Activity in East Asia

Journal:

Journal of Climate

DOI:
10.1175/JCLI-D-24-0203.1

Related Link

Institute of Life and Environmental Sciences

 

Environmental variability promotes the evolution of cooperation among humans: A simulation-based analysis




University of Tsukuba





Tsukuba, Japan—Previous scholars have widely proposed that the emergence of advanced cognitive abilities and sociality in humans originated in Africa during the MSA. However, the specific mechanisms and processes underlying this evolutionary transition lack clarification. While the VSH is considered a leading explanation for this mystery, it has traditionally focused on the evolution of individual cognitive abilities. The current study aims to expand its explanatory scope to include the evolution of sociality and examines the influence of EV on the evolution of cooperative behavior among humans using multiagent simulation models grounded in evolutionary game theory.

The researchers developed two simple models of EV, namely, a regional and a universal variability model. The analysis was focused on the influence of changes in environmental conditions on cooperation among geographically distant groups. The results reveal that regional variability poses new opportunities for cooperators in resource-poor areas, thereby promoting the evolution of cooperation. In contrast, the effect of universal variability was weak, which implies that EV contributes little to the evolution of cooperation without changes in interregional resource distribution.

These findings provide new perspectives for archeological inquiry into the origins and development of social behavior during the MSA in Africa. In addition, they offer potential insights into the mechanisms through which EVs and large-scale crises shape cooperative behavior in modern society.

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This work was supported by JSPS KAKENHI (Grant Number JP21H00694、JP21H01568).
 

Original Paper

Title of original paper:
Environmental variability promotes the evolution of cooperation among geographically dispersed groups on dynamic networks

Journal:
PLOS Complex Systems

DOI:
10.1371/journal.pcsy.0000038

Correspondence

INABA, Masaaki
Doctoral Programs in Policy and Planning Sciences, Degree Programs in Systems and Information Engineering, Graduate School of Science and Technology, University of Tsukuba

Professor AKIYAMA, Eizo
Institute of Systems and Information Engineering, University of Tsukuba

Related Link

Doctoral and Master's Programs in Policy and Planning Sciences, Degree Programs in Systems and Information Engineering, Graduate School of Science and Technology

Institute of Systems and Information Engineering

 

Genetic engineering drives innovative material design for enhanced uranium extraction from seawater





Science China Press

Genetic engineering of protein to incorporate dual uranyl-binding sites for enhanced uranium extraction from seawater. 

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Genetic engineering of protein to incorporate dual uranyl-binding sites for enhanced uranium extraction from seawater.

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Credit: ©Science China Press





Researchers at Hainan University have developed a novel protein named LSUBP, specifically designed with twin uranyl-binding sites to significantly enhance uranium extraction from seawater. Compared to previously developed adsorption-based materials, LSUBP demonstrates markedly improved adsorption capacity.

Uranium is essential for the nuclear energy industry, yet terrestrial resources are limited. In contrast, seawater holds approximately 4.5 billion tons of uranium, providing a nearly inexhaustible resource. Despite its abundance, extracting uranium from seawater remains challenging due to its extremely low concentration and competition from other dissolved metal ions.

In this study, the researchers employed targeted mutations in the protein structure, introducing a twin uranyl-binding site while maintaining structural stability. Structural analysis confirmed that these strategic modifications did not significantly alter the protein’s original conformation.

To test the practical application of this engineered protein, the researchers fabricated cross-linked hydrogel fibers containing the LSUBP protein. These fibers showed remarkable durability and reusability, critical factors for practical seawater extraction technologies. Experimental tests demonstrated that the cross-linked LSUBP fibers achieved uranium adsorption capacity of 25.60 mg g−1 in natural seawater, which represents a significant breakthrough in uranium extraction from seawater.

Molecular docking studies further confirmed that the two engineered uranyl-binding sites actively contribute to the high adsorption capacity observed, clearly demonstrating the effectiveness of the newly designed structure.

This innovative approach not only presents a promising new material for effective uranium extraction from seawater but also offers valuable insights for developing advanced adsorption materials targeting other important metal ions.

“Numerous proteins naturally rich in α-helical structures could serve as ideal platforms for engineering multiple uranyl-binding sites. By applying the genetic engineering strategy, we can rationally design additional specific binding sites, significantly enhancing the uranium extraction capabilities of protein-based adsorbents from seawater." Ning Wang said.

 

Melting snow and ice enhance cloud short-wave cooling effect, partially slowing further melting






Science China Press

Spatial and temporal distribution of the sea ice melting rate change (∆R). 

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(a) geographical distribution of the annual average of ∆R ; (b) the monthly variations of ∆CRE at the TOA and the SFC, with the error bars representing the standard deviation; (c) the monthly average trends of SIC and SA (histogram) and the variation of ∆R  (gray line), with the shadow representing the standard deviation of ∆R .

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Credit: ©Science China Press




The rate of Arctic surface warming has reached 2 to 4 times the global average—a phenomenon known as "Arctic amplification." Traditional theories suggest that snow and ice melt reduce surface albedo, leading to greater absorption of solar radiation and forming a positive "ice-albedo feedback" loop. However, a research team led by Professor Chuanfeng Zhao from Peking University has uncovered a key regulatory role played by clouds in this process, based on CERES satellite data from 2000 to 2020 and simulations from the CMIP6 climate models. The study found that even when cloud properties remain unchanged, the melting of snow and ice can trigger an enhancement in the cloud short-wave cooling effect. “This, in turn, partially slows down further melting of snow and ice, offering a new perspective on the self-regulating mechanisms of the climate system”, says Mr. Annan Chen, a PhD candidate at Peking University.

Based on satellite observations from 2000 to 2020 and CMIP6 climate model data, the analysis shows that Arctic snow and ice coverage decreased by 0.016 per decade. This triggered an increase in the cloud short-wave radiative cooling effect, leading to radiative cooling at the top of the atmosphere and surface reaching -1.25 ± 0.49 and -0.21 ± 0.20 W/m² per decade, respectively. As a result, the average annual sea ice melting rate got slowed by 3.45 cm, with localized reductions up to 10 cm per year (Figure 1). This effect peaks during the polar day in June and July. Model projections show that under the SSP585 scenario, Arctic sea ice coverage will decrease by 83% by the year 2100, with the cloud cooling effect continuing to intensify (Figure 2). The study reveals the co-evolution mechanism between clouds, snow/ice coverage, and surface albedo. At the same time, it highlights that under the influence of Arctic amplification, the trend of snow and ice loss remains irreversible.

Professor Chuanfeng Zhao from Peking University is the corresponding author of the study. The first author is PhD candidate Annan Chen. Co-authors include Professors Jing Li and Qinghong Zhang, Assistant Professor Yan Yu, postdoctoral researchers Haotian Zhang and Yikun Yang, and PhD candidate Jiefeng Li.

 

See the article:

Weakened snow and ice melting by enhanced cloud short-wave cooling effect in the Arctic

https://doi.org/10.1093/nsr/nwaf116

 

A new approach to evaluating soil contamination: How oxidative potential improves plant risk evaluation






Nanjing Institute of Environmental Sciences, MEE

Machine Learning Workflow for Identifying Key Metabolites Linked to Oxidative Potential in Contaminated Soils. 

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This diagram outlines the process used to identify the top 20 metabolites associated with oxidative potential (OP) in heavy metal-contaminated soils. The analysis involves data collection from ryegrass exposed to Cu and Pb, followed by model development using various machine learning techniques, including random forest and XGBoost. Five-fold cross-validation is used for performance evaluation, and SHAP analysis is applied to interpret the importance of metabolites, leading to the identification of key metabolites related to OP.

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Credit: Eco-Environment & Health




The increasing contamination of soils by heavy metals, such as copper and lead, poses significant ecological risks. Traditional methods to assess the impact of these pollutants on plants require lengthy cultivation periods and yield uncertain results. A novel approach based on oxidative potential (OP), an index that measures reactive oxygen species (ROS) formation in contaminated soils, could provide a faster and more reliable method to assess plant risk. By examining how oxidative potential correlates with plant stress biomarkers and metabolic disturbances, the applicability of soil OP in assessing the ecological risks of heavy metal contaminated soil was demonstrated, offering a promising tool for environmental monitoring.

Heavy metals in contaminated soils induce oxidative stress in plants, leading to growth issues and metabolic disruptions. However, evaluating this stress through traditional biomarkers is slow and susceptible to environmental variability. Oxidative potential (OP), a novel index that reflects ROS induced by heavy metals in soils, offers a potentially quicker and more consistent method. By using ryegrass as a model plant, this study explores the relationship between soil OP and plant oxidative stress markers. Based on these challenges, further research is needed to establish OP as a standard indicator in ecological risk assessments of contaminated soils.

Published (DOI: 10.1016/j.eehl.2025.100140) in Eco-Environment & Health on March 3, 2025, this research from Nankai University, the University of Toronto, and Hebei University of Technology, introduces a novel method to assess the impact of heavy metals on plant health. By measuring the oxidative potential (OP) of soil and analyzing the physiological responses of ryegrass, the team employed machine learning to identify key metabolic disruptions linked to OP. This study provides new insights into the use of OP for fast and reliable ecological risk assessments.

The study applied machine learning to assess the metabolic impact of heavy metal-contaminated soils on ryegrass, focusing on oxidative potential (OP). By correlating OP with traditional biomarkers like superoxide dismutase and total antioxidant capacity, the researchers established a robust link between soil OP and plant stress. Furthermore, the use of metabolomics identified key metabolic pathways, including amino acid metabolism and alkaloid biosynthesis, that are affected by oxidative stress. The integration of machine learning models, specifically random forest, enabled the identification of the most significant metabolites associated with OP. The results show that OP not only serves as an accurate indicator of oxidative stress but also highlights specific biochemical changes in plants under heavy metal exposure, such as alterations in amino acids and sugars. This combination of biomarkers and machine learning analysis paves the way for more efficient environmental monitoring and quicker responses to soil pollution.

Dr. Chu Peng, a lead author of the study, emphasized, "This innovative use of oxidative potential to assess soil contamination provides a faster, more reliable method to evaluate the ecological risks posed by heavy metals. By linking soil OP to plant metabolic responses, we can better understand the impact of pollutants on plant health and ecosystem stability."

This study offers significant implications for environmental monitoring and soil remediation strategies. By adopting oxidative potential (OP) as a standard measurement, we can more efficiently assess the impact of pollutants on plant health, enabling faster and more targeted interventions. The integration of machine learning and metabolomics in this context opens new avenues for enhancing ecological risk assessments, improving soil management, and reducing the environmental impact of heavy metal contamination. The application of this approach in other types of pollutants can be further explored, thereby offering a versatile tool for a range of environmental challenges.

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References

DOI

10.1016/j.eehl.2025.100140

Original Source URL

https://doi.org/10.1016/j.eehl.2025.100140

Funding information

This work was supported by the National Key Research and Development Project of China (2022YFC3703200) and the Ministry of Education, China (B17025).

About Eco-Environment & Health

Eco-Environment & Health (EEH) is an international and multidisciplinary peer-reviewed journal designed for publications on the frontiers of the ecology, environment and health as well as their related disciplines. EEH focuses on the concept of "One Health" to promote green and sustainable development, dealing with the interactions among ecology, environment and health, and the underlying mechanisms and interventions. Our mission is to be one of the most important flagship journals in the field of environmental health.