Here, copper single atoms anchored on a nitrogen-doped porous carbon (Cu-N/PC) derived from zeolitic imidazolate frameworks (ZIFs) as highly efficient electrocatalysts for ORR were demonstrated. Specifically, as a nit...
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Aqueous hybrid supercapacitors are promising due to their low cost and high safety. Herein, a freestanding battery-type electrode of Bi2O3 nanoflake@C on carbon cloth is designed for aqueous sodium ion hybrid supercap...
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Aqueous hybrid supercapacitors are promising due to their low cost and high safety. Herein, a freestanding battery-type electrode of Bi2O3 nanoflake@C on carbon cloth is designed for aqueous sodium ion hybrid supercapacitors. Due to the integration of nanoarray architecture and the conductive carbon,the Bi2O3@C electrode exhibits a high specific capacity of 207 mAh/g at 2 A/g(6C), good rate capability and cycling stability(133 m Ah/g after 1000 cycles). With the activated carbon as the capacitive electrode and neutral sodium salts as the electrolyte, a 1.9 V hybrid supercapacitor is assembled,delivering a high energy density of 18.94 Wh/kg. The device can still maintain 72.3% of initial capacity after 650 cycles. The present work holds great promise for developing next-generation hybrid supercapacitors.
The thermal history during laser powder bed fusion (LPBF) processing is significantly influenced by variations in laser power and scanning speed, which can be optimised to improve the microstructure and mechanical pro...
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Metal-air batteries are considered an efficient energy storage technology due to their high energy density, environmental friendliness, and potential for long-term cycle lifetime. However, current research on metal-ai...
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Although optical aperture synthesis has been generally regarded as the only access to very large imager for over a century, the problem of phasing all the giant sub-apertures on the scale of wavelength is still prohib...
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Porous metallic biomaterials developed from pentamode metamaterials (PMs) were rationally designed to mimic the topological, mechanical, and mass transport properties of human bones. Here, A series of diamond-based PM...
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Pressure swing adsorption(PSA) modeling remains a challenging task since it exhibits strong dynamic and cyclic behavior. This study presents a systematic physics-informed machine learning method that integrates transf...
Pressure swing adsorption(PSA) modeling remains a challenging task since it exhibits strong dynamic and cyclic behavior. This study presents a systematic physics-informed machine learning method that integrates transfer learning and labeled data to construct a spatiotemporal model of the PSA process. To approximate the latent solutions of partial differential equations(PDEs) in the specific steps of pressurization, adsorption, heavy reflux,counter-current depressurization, and light reflux, the system's network representation is decomposed into five lightweight sub-networks. On this basis, we propose a parameter-based transfer learning(TL) combined with domain decomposition to address the long-term integration of periodic PDEs and expedite the network training process. Moreover, to tackle challenges related to sharp adsorption fronts, our method allows for the inclusion of a specified amount of labeled data at the boundaries and/or within the system in the loss function. The results show that the proposed method closely matches the outcomes achieved through the conventional numerical method,effectively simulating all steps and cyclic behavior within the PSA processes.
The technical problems and relating reasons of semi-endless rolling were introduced in this paper. Regarding the problems, we carried out a series of improvement towards these problems. The application of semi-endless...
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