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Cooperation Fund of the Institute of Clean Energy Innovation, Chinese Academy of Sciences[2022YFA1504100]
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Foundation of Innovation Academy for Green Manufacture Institute, Chinese Academy of Sciences[IAGM2022D06]
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High-performance asymmetric supercapacitor based on nickel-MOF anchored MXene//NPC/rGO
No full textMXene has been considered a viable 2D electrode material for supercapacitors due to its good conductivity and remarkable cycling stability. However, its low specific capacitance has limited its applications. To address this, we deposited nickel-metal-organic-framework (Ni-ZIF-67) on MXene. Firstly, Ni-ZIF-67 composites were syn-thesized at various temperatures (150-450 celcius), with different masses of Ni. Among the Ni-ZIF-67 (NZ) compos-ites, the NZ-R-2-200 electrode exhibited the largest specific surface area of 549.78 m2/g, and the highest specific capacity of 365.5 C/g at 0.5 A/g. Then, the NZ-R-2-200/K-Ar-MXene composite was prepared by dec-orating intercalated 2D MXene (K-Ar-MXene) with NZ-R-2-200. NZ-R-2-200 were anchored on the surface of K-Ar-MXene. Significantly, an electrode based on NZ-R-2-200/K-Ar-MXene composite demonstrates a remarkable specific capacity of 557 C/g at 0.5 A/g and long-time stability of 66 % capacitance retention after 5000 cycles at 2 A/g. An assembled asymmetric supercapacitor (ASC) based on NZ-R-2-200/K-Ar-MXene as the positive and porous carbon composite of (NPC/rGO) as the negative electrodes showed a high energy density of 27.48 Wh/Kg and a power density of 400 W/Kg combined with cyclic stability up to 2000 cycles
Generalised Latent Assimilation in Heterogeneous Reduced Spaces with Machine Learning Surrogate Models
No full textReduced-order modelling and low-dimensional surrogate models generated using machine learning algorithms have been widely applied in high-dimensional dynamical systems to improve the algorithmic efficiency. In this paper, we develop a system which combines reduced-order surrogate models with a novel data assimilation (DA) technique used to incorporate real-time observations from different physical spaces. We make use of local smooth surrogate functions which link the space of encoded system variables and the one of current observations to perform variational DA with a low computational cost. The new system, named generalised latent assimilation can benefit both the efficiency provided by the reduced-order modelling and the accuracy of data assimilation. A theoretical analysis of the difference between surrogate and original assimilation cost function is also provided in this paper where an upper bound, depending on the size of the local training set, is given. The new approach is tested on a high-dimensional (CFD) application of a two-phase liquid flow with non-linear observation operators that current Latent Assimilation methods can not handle. Numerical results demonstrate that the proposed assimilation approach can significantly improve the reconstruction and prediction accuracy of the deep learning surrogate model which is nearly 1000 times faster than the CFD simulation
Modelling toluene sorption in ionic liquid/metal organic framework composite materials
No full textToluene is a prevalent pollutant in indoor environments and its removal is essential to maintain a healthy environment. Adsorption is one of the best alternatives for organic vapours removal, specially at low indoor concentrations. Metal Organic Frameworks (MOFs) and Ionic Liquids (ILs) are potential materials for this mean. In this work, the synthesis and application of IL/MOF composite materials for toluene removal is reported. Loading [BMIM][CH3COO] ionic liquid into MIL101 porous structure improves parent materials affinity towards toluene capture by two orders of magnitude (as Henry's constants, attesting to their synergy). MIL101(Cr) and absorption in [BMIM][CH3COO] IL is best described by Henry's Law, while the Langmuir adsorption model predicts toluene adsorption on [BMIM][CH3COO]/MIL101(Cr) better than Freundlich and Toth equations. Diffusional and kinetics models revealed that toluene diffusion is the rate limiting step for pristine MIL101. Kinetic and diffusion rates were systematically improved upon the incorporation of the ionic liquid due to shorter toluene hops with the adsorbed IL and the increased hydrophobicity in the composites making the sorption more favourable. This study provides a systematic analysis and modelling of the toluene capture process in IL/MOF composites aiding a better understanding of the sorption process in these novel materials
