Synthesis and Characterization of Novel Functional Materials based on Cellulose and Graphene Oxide

This thesis focused on the synthesis and characterization of novel functional materials based on cellulose and graphene derivatives. Cellulose/GO hydrogels were produced as the starting material by dissolving cellulose and dispersing GO in NaOH/urea solution. This method is considered as an efficient, simple, environmentally friendly, and low-cost method. Novel functionalities, such as sensing, catalytic and EMI shielding properties have been “built-in” to cellulose/GO hydrogels. Cellulose/rGO composite films and aerogels were successfully fabricated by dissolving cellulose and dispersing GO in NaOH/urea solution, followed by the chemical reduction with vitamin C as the reducing agent. The cellulose/rGO films and aerogels with various rGO contents were prepared by air-drying and freeze-drying of the prepared cellulose/rGO composite hydrogels. The resultant cellulose/rGO composites prepared by this efficient and simple method show high resistance sensitivity to environmental stimuli like temperature, humidity, liquids, vapours, and strain stress. Thus, the cellulose/rGO films can be applied in detecting human motions and human breath cycles. Liquid temperature, liquid type, and ion concentration also be determined by our cellulose/rGO films. Moreover, the composite aerogels are fast responding and extremely sensitive sensors for vapour detection and testing with good repeatability. It was also revealed that discriminating and quantitative responses can be obtained when analyzing various vapours and different vapour concentrations. For methanol vapour, the aerogel shows linear response to the vapour concentration. Thus cellulose/rGO composite aerogel can be used to quantify methanol vapour concentrations. The efficient, scalable, and environmentally friendly preparation of novel and high-performance of vapour sensing materials with well reproducibility is promising to achieve practical vapour sensing applications. We have successfully presented an effective, facial, simple, and scalable method to form Fe3O4 nanoparticles onto cellulose/GO hydrogels. XRD, FTIR, XPS and TEM indicated that Fe3O4 nanoparticles with good dispersion and uniform size are successfully coated on cellulose matrix and GO sheets. This material was tested as catalyst for the cleaning of dye-contaminated water by oxidation with H2O2.The optimized experiment conditions for AO7 degradation are: [AO7] = 0.1 mM, T = 298 K, [H2O2] = 22 mM, and pH = 3. Under these conditions, the resulting hydrogels display 97 % AO7 removal within 120 min and retained strong degradation performance after twenty consecutive cycles of reuse. Especially, the detailed XPS analysis of cellulose/GO/Fe3O4 and cellulose/Fe3O4 composites indicated that the cellulose/GO/Fe3O4 hydrogel retain its high degradation activity by keeping the ratio of Fe3+/Fe2+ at 2 during the 20 heterogeneous Fenton-like reaction cycles. Therefore, the cellulose/GO/Fe3O4 hydrogel is recommended to test the treatment of other dye-contaminated wastewaters. Cellulose/rGO/Fe3O4 films and aerogels were successfully fabricated by the in-situ grown of Fe3O4 nanoparticles within a cellulose matrix containing rGO sheets. Cellulose/rGO (8 wt.%)/Fe3O4 aerogels with the thickness of 0.5 mm exhibited high EMI shielding performance with the EMI SE value at 32.4-40.1 dB in the 8.2-12.4 GHz frequency range. High loading of rGO and large thickness of the composites are beneficial for the excellent EMI shielding performance of our aerogels. The lightweight aerogel is suitable for the practical application as EMI shielding materials such as spacecraft, aircraft, energy conversion application, and energy storage

Misallocation of human capital and productivity: evidence from China

The purpose of the paper is to outline the empirical framework of the model of the impact misallocation of human capital on productivity (TFP).Using provincial panel data from 2001 to 2015, this paper studies the effect of the misallocation of human capital on productivity in China. We find that misallocation of human capital reduces China’s productivity significantly. Most importantly, we argue that the important channels through which misallocation of human capital affects productivity are industrial structure upgrading, technological innovation and labour productivity. Furthermore, counterfactual experiments show that eliminating the labour mismatch between industries completely could be associated with an increase in productivity of around 41% for the whole sample in China. The results suggest correcting the current imperfections of incentives in non-productive sectors, where encouraging more human capital to work in high-tech enterprises may be a vital measure to stimulate the development of emerging economies

Combining Particle and Tensor-network Methods for Partial Differential Equations via Sketching

In this paper, we propose a general framework for solving high-dimensional partial differential equations with tensor networks. Our approach offers a comprehensive solution methodology, wherein we employ a combination of particle simulations to update the solution and re-estimations of the new solution as a tensor-network using a recently proposed tensor train sketching technique. Our method can also be interpreted as an alternative approach for performing particle number control by assuming the particles originate from an underlying tensor network. We demonstrate the versatility and flexibility of our approach by applying it to two specific scenarios: simulating the Fokker-Planck equation through Langevin dynamics and quantum imaginary time evolution via auxiliary-field quantum Monte Carlo

Is pension insurance a barrier to entrepreneurship? New evidence from China

This article provides evidence of the impact of pension insurance on entrepreneurship. It uses recent, nationally representative sample data from the Chinese General Social Survey (2013). We use a probit regression model to investigate whether the pension insurance converge rate affects the probability of a person becoming an entrepreneur. We find that the presence of both basic pension and business pension insurance reduce individual entrepreneurial probability. We also find that the two types of pension insurance do not appear to increase entrepreneurship among any particular subgroup, based on geo graphical regions, gender, education, social connection or marital status. Moreover, we argue that the basic pension and business pension insurance actually have a negative effect on the probability of small business entrepreneurship. Even, we have found there seems to be one important exception to this general pattern. For, most importantly, basic pension and business pension insurance have a positive effect on the probability of one particular kind of entrepreneurship: Innovation-driven entrepreneurship. Exploring possible mechanisms, we find that the important transmission channels through which pension insurance affects business creation is the lack of security and total family income

Generative Modeling via Hierarchical Tensor Sketching

We propose a hierarchical tensor-network approach for approximating high-dimensional probability density via empirical distribution. This leverages randomized singular value decomposition (SVD) techniques and involves solving linear equations for tensor cores in this tensor network. The complexity of the resulting algorithm scales linearly in the dimension of the high-dimensional density. An analysis of estimation error demonstrates the effectiveness of this method through several numerical experiments

Fe3O4 Nanoparticles Grown on Cellulose/GO Hydrogels as Advanced Catalytic Materials for the Heterogeneous Fenton-like Reaction

Cellulose/graphene oxide (GO)/iron oxide (Fe3O4) composites were prepared by coprecipitating iron salts onto cellulose/GO hydrogels in a basic solution. X-ray photoelectron spectroscopy (XPS), Fourier-transform infrared, and X-ray diffraction characterization showed that Fe3O4 was successfully coated on GO sheets and cellulose. Cellulose/GO/Fe3O4 composites showed excellent catalytic activity by maintaining almost 98% of the removal of acid orange 7 (AO7) and showed stability over 20 consecutive cycles. This performance is attributable to the synergistic effect of Fe3O4 and GO during the heterogeneous Fenton-like reaction. Especially, the cellulose/GO/Fe3O4 composites preserve their activity by keeping the ratio of Fe3+/Fe2+ at 2 even after 20 catalysis cycles, which is supported by XPS analysis