The global nitrogen cycle holds immense importance due to its crucial role in supporting life, supplying vital nutrients for plant growth, preserving environmental balance, and enabling the proper functioning of ecosy...
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The global nitrogen cycle holds immense importance due to its crucial role in supporting life, supplying vital nutrients for plant growth, preserving environmental balance, and enabling the proper functioning of ecosystems. However, human activities frequently disrupt this cycle, leading to the accumulation of nitrates and nitrites in water bodies. This accumulation causes environmental pollution and health risks. Traditional methods for treating nitrogen pollution, including biological, physical, and chemical approaches, have inherent limitations. In recent years, electrocatalysis has emerged as a promising and sustainable approach for nitrogen management. This technology offers superior efficiency, high selectivity, and environmental *** not only enables accurate detection of nitrogen pollutants in the environment but also facilitates their conversion into harmless nitrogen gas. Moreover, recent advancements have focused on the upcycling of nitrogen pollutants into valuable compounds,such as ammonia and urea. In this comprehensive review, we showcase the applications of electrocatalysis in sustainable nitrogen management. Specifically, we highlight its use in the sensing, removal, and upcycling of major nitrogen pollutants,including nitrate(NO3-), nitrite(NO2-), and nitric oxide(NO). We discuss the use of catalysts, such as Pd alloys, Cu-based, and Fe-based materials, in electrochemical sensing and catalysis. Additionally, we explore recent advancements in the conversion of nitrogen pollutants into valuable compounds like ammonia and urea. The review also addresses current challenges and future opportunities in the field, including innovations in sensor and catalyst design, as well as large-scale treatment strategies. We anticipate that these perspectives will provide profound insights for effective nitrogen pollution control and sustainable utilization of nitrogen resources.
Photoacoustic imaging,an acoustic imaging modality with potentially optical resolution in an optical turbid medium,has attracted great ***,the convergence of wavefront optimization and raster scanning in computational...
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Photoacoustic imaging,an acoustic imaging modality with potentially optical resolution in an optical turbid medium,has attracted great ***,the convergence of wavefront optimization and raster scanning in computational photoacoustic imaging leads to the challenge of fast mapping,especially for a spatial resolution approaching the acoustic deep-subwavelength *** a sparse sampling paradigm,compressive sensing has been applied in numerous fields to accelerate data acquisition without significant quality *** this work,we propose a dual-compressed approach for photoacoustic surface tomography that enables high-efficiency imaging with 3D spatial resolution unlimited by the acoustics in a turbid *** dual-compressed photoacoustic imaging with single-pixel detection,enabled by spatially optical modulation with synchronized temporally photoacoustic coding,allows decoding of the fine optical information from the modulated acoustic signal even when the variance of original photoacoustic signals is *** perform a proof-of-principle numerical demonstration of dual-compressed photoacoustic imaging, that resolves acoustic sub-acoustic-wavelength details with a significantly reduced number of measurements,revealing the potential for dynamic *** dual-compressed concept,which transforms unobtrusive spatial difference into spatio-temporal detectable information,can be generalized to other imaging modalities to re alize efficient,high-spatial-resolution imaging.
The memory effect in a single-crystal spin glass (Cu0.92Mn0.08) has been measured using 1 Hz ac susceptibility techniques over a temperature range of 0.4–0.7Tg, and a model of the memory effect has been developed. A ...
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The memory effect in a single-crystal spin glass (Cu0.92Mn0.08) has been measured using 1 Hz ac susceptibility techniques over a temperature range of 0.4–0.7Tg, and a model of the memory effect has been developed. A double-waiting-time protocol is carried out where the spin glass is first allowed to age at a temperature below Tg, followed by a second aging at a lower temperature, Tw2, after it has fully rejuvenated. The model is based on calculating typical coincident growth of correlated regions at the two temperatures. It accounts for the absolute magnitude of the memory effect as a function of both waiting times and temperatures. The data can be explained by the memory loss being a function of the relative change in the correlated volume at the first waiting temperature because of the growth in the correlations at the second waiting temperature.
Multifunctional fibers with high mechanical strength enable advanced applications of smart textiles,robotics, and biomedicine. Herein, we reported a one-step degumming method to fabricate strong, stiff, and humidity-r...
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Multifunctional fibers with high mechanical strength enable advanced applications of smart textiles,robotics, and biomedicine. Herein, we reported a one-step degumming method to fabricate strong, stiff, and humidity-responsive smart cellulosic fibers from abundant natural grass. The facile process involves partially removing lignin and hemicellulose functioning as glue in grass, which leads to the separation of vessels,parenchymal cells, and cellulosic fibers, where cellulosic fibers are manufactured at kilogram scale. The resulting fibers show dense and unidirectional fibril structure at both micro-and nano-scales, which demonstrate high tensile strength of ~0.9 GPa and Young's modulus of 72 GPa, being 13-and 14-times higher than original grass. Inspired by stretchable plant tendrils, we developed a humidity-responsive actuator by engineering cellulosic fibers into the spring-like structures, presenting superior response rate and lifting capability. These strong and smart cellulosic fibers can be manufactured at large scale with low cost, representing promising a fiber material derived from renewable and sustainable biomass.
As global population rises,accompanied by escalating environmental pollution and climate change,numerous countries find themselves grappling with an acute scarcity of natural freshwater resources^([1]).Seawater desali...
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As global population rises,accompanied by escalating environmental pollution and climate change,numerous countries find themselves grappling with an acute scarcity of natural freshwater resources^([1]).Seawater desalination presents a compelling solution to this looming crisis,especially considering the oceans are Earth’s largest water reservoir^([2]).
We synthesized CaRuO3 (001) thin films on a set of substrates and investigated their electronic and magnetic properties via combining magnetotransport measurements with first-principles density-functional theory calcu...
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We synthesized CaRuO3 (001) thin films on a set of substrates and investigated their electronic and magnetic properties via combining magnetotransport measurements with first-principles density-functional theory calculations. The experimental results indicate that a moderate strain can introduce the Kondo effect in the system, leading to a significant modulation of the non-Fermi liquid behavior. Moreover, when the strain reaches a certain threshold, the system undergoes a metal-semiconductor transition, accompanied by a transition from a nonmagnetic state to a plausible G-type antiferromagnetic state. We attribute the observed phenomena in CaRuO3 to strain-induced disruption of the delicate balance between the itinerant and the local Ru 4d electrons. These findings shed light on the intriguing magnetic and non-Fermi liquid behavior of CaRuO3, systematically tailored by heteroepitaxial strain.
Xenotime rare-earth(RE)phosphates are emerging as promising materials for environmental barrier coatings(EBCs)for SiC-based ceramic-matrix composites(CMCs)because of their close coefficients of thermal expansion(CTEs)...
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Xenotime rare-earth(RE)phosphates are emerging as promising materials for environmental barrier coatings(EBCs)for SiC-based ceramic-matrix composites(CMCs)because of their close coefficients of thermal expansion(CTEs)and resistance to calcium-magnesium-alumina-silicate(CMAS)*** this work,high-entropy(HE)(Sc_(0.2)Lu_(0.2)Yb_(0.2)Er_(0.2)Y_(0.2))PO_(4) and five single-component REPO4(RE=Sc,Lu,Yb,Er,and Y)compounds were synthesized,and their stability,thermal properties,and CMAS corrosion resistance were *** CTE values of four REPO_(4) compounds(RE=Lu,Yb,Er,and Y;~(5.6-6)×10^(−6)℃^(−1))are close to those of SiC-CMC((4.5-5.5)×10^(−6)℃^(−1)),whereas ScPO_(4)(6.98×10^(−6)℃^(−1))and HE(5RE_(0.2))PO_(4)(6.39×10^(−6)℃^(−1))have slightly higher values in the temperature range of 200-1300℃.HE phosphate has the lowest thermal conductivity due to its size and mass *** CMAS corrosion tests at 1300℃ for 5,45,and 96 h revealed that all RE phosphates formed a continuous and dense reaction layer predominantly composed of Ca_(8)MgRE(PO_(4))_(7),effectively impeding CMAS ***,REPO_(4) with smaller RE³−cations displays a slower reaction rate and reduced corrosion kinetics,as evidenced by the smaller thickness of the reaction layer.A larger negative difference in the optical basicity(OB)value between REPO_(4) and CMAS signifies greater corrosion resistance.A mechanistic understanding of CMAS corrosion and elucidation of the effects of critical parameters such as the ionic mass and ionic radius of RE elements on their thermal properties and CMAS corrosion kinetics are useful for the development of novel xenotime-type phosphates as EBCs for SiC-CMCs.
Emerging machine learning(ML)approaches have been adopted in various material systems to predict novel properties with the assistance of the corresponding large *** new materials,however,collecting sufficient data poi...
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Emerging machine learning(ML)approaches have been adopted in various material systems to predict novel properties with the assistance of the corresponding large *** new materials,however,collecting sufficient data points for model training is not feasible,which is the case for gold nanoparticle/polymer hybrid *** this study,an ML approach coupled with finite element modeling was proposed for predicting the optical and photothermal properties of gold nanoparticle/polymer hybrid *** datasets of the optical and photothermal properties were built using results from the ***,finite element analyses were conducted to generate synthetic data to satisfy the quality and quantity of the data required for training *** analysis and model training were performed using the datasets with and without synthetic data to evaluate their effects on predicting the performance of the ML *** relative importance of features to targets(properties)was evaluated by correlation *** models with high accuracy were obtained by training various models from conventional to newly developed ***,weaknesses,and improvement of the synthetic data addition were *** proposed workflow and framework offer reliable prediction of optical and photothermal properties over different combinations of gold nanoparticles and polymer matrices,which can be extended to include more features related to processing parameters and microstructures.
The mechanical and corrosion characteristics of aluminum alloys can be influenced not only by the addition of grain refiners but also by heat treatment that modifies the microstructure and introduces variations in the...
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