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ABSTRACTThe multi‐field coupling relationship and temperature evolution mechanism of gas‐containing coal in areas affected by geological structures were investigated, focusing specifically on the engineering aspects of a reverse fault in the No. 3 coal seam at the Xinjing Coal Mine. An analysis was conducted to examine the thermal‐fluid‐solid coupling behavior of gas‐containing coal. A thermal‐fluid‐solid coupling model for gas‐containing coal, accounting for the effects of damage, was developed to simulate the incubation process of coal and gas outbursts within the fault zone during the advancement of the working face. The study has indicated that faults not only degrade the mechanical properties of the surrounding coal‐rock mass, but also disrupt the continuity of coal seam stress. Gas tends to accumulate near fault zones, resulting in differences in the gas pressure and content on either side of the fault, thereby substantially increasing the likelihood of coal and gas outbursts. The primary factors influencing temperature variations include deformation energy, energy from gas expansion, thermal convection, thermal conduction, and the thermal effects associated with adsorption and desorption. Among these factors, the endothermic effect associated with adsorption and desorption significantly influences the temperature fluctuations in coal. The results of this study provide a theoretical foundation for exploring the mechanisms underlying coal and gas outbursts, improving the interdisciplinary coupling theory for coal and gas systems and employing temperature metrics to predict such outbursts.

Underwater wireless sensor networks (UWSNs) widely used for maritime object detection or for monitoring of oceanic parameters that plays vital role prediction of tsunami to life-cycle of marine species by deploying sensor nodes at random locations. However, the dynamic and unpredictable underwater environment poses significant challenges in communication, including interference, collisions, and energy inefficiency. In changing underwater environment to make routing possible among nodes or/and base station (BS) an adaptive receiver-initiated deep adaptive with power control and collision avoidance MAC (DAWPC-MAC) protocol is proposed to address the challenges of interference, collisions, and energy inefficiency. The proposed framework is based on Deep Q-Learning (DQN) to optimize network performance by enhancing collision avoidance in a varying sensor locations, conserving energy in changing path loss with respect to time and depth and reducing number of relaying nodes to make communication reliable and ensuring synchronization. The dynamic and unpredictable underwater environment, shaped by variations in environmental parameters such as temperature (T) with respect to latitude, longitude, and depth, is carefully considered in the design of the proposed MAC protocol. Sensor nodes are enabled to adaptively schedule wake-up times and efficiently control transmission power to communicate with other sensor nodes and/or courier node plays vital role in routing for data collection and forwarding. DAWPC-MAC ensures energy-efficient and reliable time-sensitive data transmission, improving the packet delivery rati (PDR) by 14%, throughput by over 70%, and utility by more than 60% compared to existing methods like TDTSPC-MAC, DC-MAC, and ALOHA MAC. These enhancements significantly contribute to network longevity and operational efficiency in time-critical underwater applications.

This work aims at designing and evaluating scheduling algorithms that minimize carbon cost on edge platforms. When a job is released to some edge server, difficult scheduling questions arise: should the job be executed on that server? If yes, when? If no, which other edge server should the job be transferred to? Typically, jobs are submitted online, and have a deadline to enforce. Online scheduling problems are already difficult without accounting for different energy sources, so one should not expect any optimal solution. Still, an important research goal is to revisit standard algorithms such as Earliest Completion Time (ECT) and Earliest Deadline First (EDF) in order to design and evaluate carbon-aware variants. This paper introduces several new algorithms that use sophisticated scheduling policies to efficiently decrease carbon cost; these algorithms maximize the use of green energy both on local and remote edge servers, by re-evaluating previous decisions whenever needed to accommodate newly released jobs. We provide a comprehensive simulation campaign based on actual platform/job data and carbon traces and report an average gain of 42% over standard approaches.

This study evaluates the economic and environmental sustainability of protein-rich crops (quinoa, faba beans, chickpeas, and lentils) cultivated in Europe. Using life cycle assessment (LCA) and life cycle cost (LCC) analyses, it examines the impacts of these crops grown in the Netherlands, Spain, and Italy under both organic and conventional farming methods. Unlike previous agri-food studies that mostly assess sustainability dimensions in isolation, this research integrates LCA and LCC to provide a comprehensive eco-efficiency evaluation, offering novel insights into the trade-offs between environmental impact and economic viability. In addition, this study focuses on the cultivation of four protein-rich crops that are novel to Europe. The results reveal significant variability in environmental impacts, including climate change impact and land use, as well as profitability, across different crops, countries, and farming practices. Dutch conventionally grown faba beans demonstrate the highest eco-efficiency, while organic lentils in Italy and organic quinoa in the Netherlands also perform well. The study highlights the instability of crop yields and suggests that local production of these protein-rich crops could reduce Europe's dependency on imported soy, although careful consideration of regional suitability and farming methods is necessary. The findings aim to guide farmers and policymakers in promoting sustainable protein-rich crop production in Europe.

A machine-learning-designed cerium-iron MOF layer enhances Zn anode stability, achieving over 4300 hours at 1 mA cm−2 and 99.8% coulombic efficiency over 1400 cycles at 2 mA cm−2, providing a cost-effective protective strategy.

Abstract Nickel is a critical element in the shift to sustainable energy systems, with the demand for nickel projected to exceed 6 million tons annually by 20401–4, largely driven by the electrification of the transport sector. Primary nickel production uses acids and carbon-based reductants, emitting about 20 tons of carbon dioxide per ton of nickel produced5–7. Here we present a method using fossil-free hydrogen-plasma-based reduction to extract nickel from low-grade ore variants known as laterites. We bypass the traditional multistep process and combine calcination, smelting, reduction and refining into a single metallurgical step conducted in one furnace. This approach produces high-grade ferronickel alloys at fast reduction kinetics. Thermodynamic control of the atmosphere of the furnace enables selective nickel reduction, yielding an alloy with minimal impurities (<0.04 wt% silicon, approximately 0.01 wt% phosphorus and <0.09 wt% calcium), eliminating the need for further refining. The proposed method has the potential to be up to about 18% more energy efficient while cutting direct carbon dioxide emissions by up to 84% compared with current practice. Our work thus shows a sustainable approach to help resolve the contradiction between the beneficial use of nickel in sustainable energy technologies and the environmental harm caused by its production.

ABSTRACTPotassium (K) is the second most abundant nutrient element in plants after nitrogen (N), and has been shown to limit aboveground production in some contexts. However, the role of N and phosphorus (P) availability in mediating K limitation in terrestrial production remains poorly understood; and it is unknown whether K also limits belowground carbon (C) stocks, which contain at least three times more C than those aboveground stocks. By synthesizing 779 global paired observations (528, 125, and 126 for aboveground productivity, root biomass, and soil organic C [SOC], respectively), we found that K addition significantly increased aboveground production and SOC by 8% and 5%, respectively, but did not significantly affect root biomass (+9%). Moreover, enhanced N and/or P availability (through N and P addition) did not further amplify the positive effect of K on aboveground productivity. In other words, K had a positive effect on aboveground productivity only when N and/or P were limiting, indicating that K could somehow substitute for N or P when they were limiting. Climate variables mostly explained the variations in K effects; specifically, stronger positive responses of aboveground productivity and SOC to K were found in regions with high mean annual temperature and wetness. Our results suggest that K addition enhances C sequestration by increasing both aboveground productivity and SOC, contributing to climate mitigation, but the positive effects of K on terrestrial C stocks are not further amplified when N and P limitations are alleviated.

Heat pump (HP) technology has been widely adopted in electric vehicles (EVs) for cabin and battery heating in cold weather due to its high efficiency. However, when an HP works under low ambient temperatures and high humidity, frost grows on the surface of the outdoor evaporator, deteriorating system efficiency. This study experimentally investigated the performance of an automotive reversible CO2 HP system under cyclic frosting–defrosting conditions, with different defrost-initiation criteria and orientations of the outdoor heat exchanger. The relationship between the performance degradation of the heat pump system and the feature of frost accumulation on the outdoor heat exchanger is analyzed. The experimental data revealed that the heating capacity of the HP system only mildly degrades (~30%), even with an air-side pressure drop of the outdoor heat exchanger growing 10 times, which enables the system to work in HP mode for a longer time before the defrosting without significantly impacting passengers’ comfort. The horizontally installed outdoor heat exchanger is proven to have better refrigerant distribution, but with approximately a 0.16 bar (11.9%) higher pressure drop, reducing the evaporating temperature by about 0.4 K. Consequently, frost accumulates faster, and the working time in HP mode is shortened by 12 min (18.2%). Moreover, the vertical outdoor heat exchanger drains much more water during the defrosting. As a result, the defrosting time for the vertical outdoor heat exchanger is reduced by 17%.