University of Jinan

About: University of Jinan is a education organization based out in Jinan, China. It is known for research contribution in the topics: Catalysis & Adsorption. The organization has 14203 authors who have published 14154 publications receiving 188093 citations. The organization is also known as: Jǐnán Dàxué.

Applications of 2D MXenes in energy conversion and storage systems

Abstract: Transition metal carbides and nitrides (MXenes), a family of two-dimensional (2D) inorganic compounds, are materials composed of a few atomic layers of transition metal carbides, nitrides, or carbonitrides. Ti3C2, the first 2D layered MXene, was isolated in 2011. This material, which is a layered bulk material analogous to graphite, was derived from its 3D phase, Ti3AlC2 MAX. Since then, material scientists have either determined or predicted the stable phases of >200 different MXenes based on combinations of various transition metals such as Ti, Mo, V, Cr, and their alloys with C and N. Extensive experimental and theoretical studies have shown their exciting potential for energy conversion and electrochemical storage. To this end, we comprehensively summarize the current advances in MXene research. We begin by reviewing the structure types and morphologies and their fabrication routes. The review then discusses the mechanical, electrical, optical, and electrochemical properties of MXenes. The focus then turns to their exciting potential in energy storage and conversion. Energy storage applications include electrodes in rechargeable lithium- and sodium-ion batteries, lithium-sulfur batteries, and supercapacitors. In terms of energy conversion, photocatalytic fuel production, such as hydrogen evolution from water splitting, and carbon dioxide reduction are presented. The potential of MXenes for the photocatalytic degradation of organic pollutants in water, such as dye waste, is also addressed, along with their promise as catalysts for ammonium synthesis from nitrogen. Finally, their application potential is summarized.

Nanostructured Materials for Room-Temperature Gas Sensors

Abstract: Sensor technology has an important effect on many aspects in our society, and has gained much progress, propelled by the development of nanoscience and nanotechnology. Current research efforts are directed toward developing high-performance gas sensors with low operating temperature at low fabrication costs. A gas sensor working at room temperature is very appealing as it provides very low power consumption and does not require a heater for high-temperature operation, and hence simplifies the fabrication of sensor devices and reduces the operating cost. Nanostructured materials are at the core of the development of any room-temperature sensing platform. The most important advances with regard to fundamental research, sensing mechanisms, and application of nanostructured materials for room-temperature conductometric sensor devices are reviewed here. Particular emphasis is given to the relation between the nanostructure and sensor properties in an attempt to address structure-property correlations. Finally, some future research perspectives and new challenges that the field of room-temperature sensors will have to address are also discussed.

Synthesis of functionalized 3D hierarchical porous carbon for high-performance supercapacitors

Abstract: Functionalized three-dimensional hierarchical porous carbon (THPC) is prepared via a facile modified chemical activation route with polypyrrole microsheets as precursor and KOH as activating agent. The as-obtained THPC presents a large specific surface area (2870 m2 g−1), high-level heteroatom doping (N: 7.7 wt%, O: 12.4 wt%), excellent electrical conductivity (5.6 S cm−1), and hierarchical porous nano-architecture containing macroporous frameworks, mesoporous walls and microporous textures. Such unique features make the THPC an ideal electrode material for electrochemical energy storage. As the electrode material for a supercapacitor, the THPC exhibits a high capacitance, excellent rate performance and long-term stability in both aqueous and organic electrolytes.

An adaptive estimation of dimension reduction space

Abstract: Summary. Searching for an effective dimension reduction space is an important problem in regression, especially for high dimensional data. We propose an adaptive approach based on semiparametric models, which we call the (conditional) minimum average variance estimation (MAVE) method, within quite a general setting. The MAVE method has the following advantages. Most existing methods must undersmooth the nonparametric link function estimator to achieve a faster rate of consistency for the estimator of the parameters (than for that of the nonparametric function). In contrast, a faster consistency rate can be achieved by the MAVE method even without undersmoothing the nonparametric link function estimator. The MAVE method is applicable to a wide range of models, with fewer restrictions on the distribution of the covariates, to the extent that even time series can be included. Because of the faster rate of consistency for the parameter estimators, it is possible for us to estimate the dimension of the space consistently. The relationship of the MAVE method with other methods is also investigated. In particular, a simple outer product gradient estimator is proposed as an initial estimator. In addition to theoretical results, we demonstrate the efficacy of the MAVE method for high dimensional data sets through simulation. Two real data sets are analysed by using the MAVE approach.

Self-Assembled Copper-Amino Acid Nanoparticles for in Situ Glutathione "AND" H2O2 Sequentially Triggered Chemodynamic Therapy.

Abstract: Nanoformulations that can respond to the specific tumor microenvironment (TME), such as a weakly acidic pH, low oxygen, and high glutathione (GSH), show promise for killing cancer cells with minima...