Showing papers by "Beijing University of Technology published in 2012"

Zirconium-Metalloporphyrin PCN-222: Mesoporous Metal–Organic Frameworks with Ultrahigh Stability as Biomimetic Catalysts†

Abstract: In nature, metalloporphyrins are well known for performing many biological functions in aqueous media, such as light harvesting, oxygen transportation, and catalysis. Heme, the iron–porphyrin derivative, is the cofactor for many enzyme/ protein families, including peroxidases, cytochromes, hemoglobins, and myoglobins. Using synthetic systems to mimic natural enzymes with high catalytic activity and substrate selectivity has been a sought-after goal in the last decade. Direct application of a heme as an oxidation catalyst in aqueous solution is usually challenging due to the formation of catalytically inactive dimers and catalyst self-destruction in the oxidizing reaction media. One promising approach is to load heme on supports, such as zeolites, clays, nanoparticles, hydrogels, or carbon materials, a practice which inevitably dilutes the density of active sites. An alternative approach is to protect the heme center by modifying the porphyrin to produce dendrimers or molecular crystals, which is a synthetically demanding method. Herein, we propose a unique strategy employing heme-like active centers as structural motifs for the assembly of highly stable porous materials, which should possess well-defined mesochannels and ultrahigh stability in aqueous solution. Metal-organic frameworks (MOFs) are a new class of crystalline porous materials with fascinating structures and intriguing properties, such as permanent porosity, high surface area, and uniform open cavities. The availability of various building blocks consisting of metals and organic linkers makes it possible to construct MOFs with unique properties for diverse applications. However, these desirable features of MOFs have rarely been applied to an enzymatic mimic, especially for catalysis in an aqueous medium, despite the fact that the assembly of ligands bearing high-density active sites into 3D frameworks may provide an ideal system to both enhance the catalytic activity and protect the cofactors. One of the main reasons is the lack of water-stable MOFs containing redox-active metal centers. Furthermore, most MOFs are microporous (pore size< 2 nm). Although they are suitable for gas storage, the small pore size slows down diffusion and limits the access of large substrate molecules to the active sites inside a MOF. Therefore, MOFs with mesopores, accessible redox sites, and ultrahigh stability, especially in aqueous media, are indispensible for any successful biomimetic attempt. Herein we have employed Fe-TCPP (TCPP= tetrakis(4carboxyphenyl)porphyrin) as a heme-like ligand and chosen highly stable Zr6 clusters as nodes for the assembly of stable Zr-MOFs. With carefully selected starting materials, we have successfully constructed a 3D heme-like MOF, designated as PCN-222(Fe) (Figure 1; PCN= porous coordination net-

Methane storage in advanced porous materials

Abstract: The need for alternative fuels is greater now than ever before. With considerable sources available and low pollution factor, methane is a natural choice as petroleum replacement in cars and other mobile applications. However, efficient storage methods are still lacking to implement the application of methane in the automotive industry. Advanced porous materials, metal–organic frameworks and porous organic polymers, have received considerable attention in sorptive storage applications owing to their exceptionally high surface areas and chemically-tunable structures. In this critical review we provide an overview of the current status of the application of these two types of advanced porous materials in the storage of methane. Examples of materials exhibiting high methane storage capacities are analyzed and methods for increasing the applicability of these advanced porous materials in methane storage technologies described.

Manganese Oxides with Rod-, Wire-, Tube-, and Flower-Like Morphologies: Highly Effective Catalysts for the Removal of Toluene

Abstract: Nanosized rod-like, wire-like, and tubular α-MnO(2) and flower-like spherical Mn(2)O(3) have been prepared via the hydrothermal method and the CCl(4) solution method, respectively. The physicochemical properties of the materials were characterized using numerous analytical techniques. The catalytic activities of the catalysts were evaluated for toluene oxidation. It is shown that α-MnO(2) nanorods, nanowires, and nanotubes with a surface area of 45-83 m(2)/g were tetragonal in crystal structure, whereas flower-like spherical Mn(2)O(3) with a surface area of 162 m(2)/g was of cubic crystal structure. There were the presence of surface Mn ions in multiple oxidation states (e.g., Mn(3+), Mn(4+), or even Mn(2+)) and the formation of surface oxygen vacancies. The oxygen adspecies concentration and low-temperature reducibility decreased in the order of rod-like α-MnO(2) > tube-like α-MnO(2) > flower-like Mn(2)O(3) > wire-like α-MnO(2), in good agreement with the sequence of the catalytic performance of these samples. The best-performing rod-like α-MnO(2) catalyst could effectively catalyze the total oxidation of toluene at lower temperatures (T(50%) = 210 °C and T(90%) = 225 °C at space velocity = 20,000 mL/(g h)). It is concluded that the excellent catalytic performance of α-MnO(2) nanorods might be associated with the high oxygen adspecies concentration and good low-temperature reducibility. We are sure that such one-dimensional well-defined morphological manganese oxides are promising materials for the catalytic elimination of air pollutants.

Low thermal conductivity oxides

Abstract: Oxides hold great promise as new and improved materials for thermal-barrier coating applications. The rich variety of structures and compositions of the materials in this class, and the ease with which they can be doped, allow the exploration of various mechanisms for lowering thermal conductivity. In this article, we review recent progress in identifying specific oxides with low thermal conductivity from both theoretical and experimental perspectives. We explore the mechanisms of lowering thermal conductivity, such as introducing structural/chemical disorder, increasing material density, increasing the number of atoms in the primitive cell, and exploiting the structural anisotropy. We conclude that further systematic exploration of oxide crystal structures and chemistries are likely to result in even further improved thermal-barrier coatings.

Robust rank correlation based screening

Abstract: Independence screening is a variable selection method that uses a ranking criterion to select significant variables, particularly for statistical models with nonpolynomial dimensionality or “large $p$, small $n$” paradigms when $p$ can be as large as an exponential of the sample size $n$. In this paper we propose a robust rank correlation screening (RRCS) method to deal with ultra-high dimensional data. The new procedure is based on the Kendall $\tau$ correlation coefficient between response and predictor variables rather than the Pearson correlation of existing methods. The new method has four desirable features compared with existing independence screening methods. First, the sure independence screening property can hold only under the existence of a second order moment of predictor variables, rather than exponential tails or alikeness, even when the number of predictor variables grows as fast as exponentially of the sample size. Second, it can be used to deal with semiparametric models such as transformation regression models and single-index models under monotonic constraint to the link function without involving nonparametric estimation even when there are nonparametric functions in the models. Third, the procedure can be largely used against outliers and influence points in the observations. Last, the use of indicator functions in rank correlation screening greatly simplifies the theoretical derivation due to the boundedness of the resulting statistics, compared with previous studies on variable screening. Simulations are carried out for comparisons with existing methods and a real data example is analyzed.

Activity, propene poisoning resistance and hydrothermal stability of copper exchanged chabazite-like zeolite catalysts for SCR of NO with ammonia in comparison to Cu/ZSM-5

Abstract: Copper, iron, and mixed copper/iron exchanged zeolites containing ZSM-5 and chabazite-like zeolites (SSZ-13, SAPO-18 and SAPO-34) were studied for selective catalytic reduction (SCR) of NO with NH3 with or without propene. Cu/ZSM-5, Cu/SSZ-13, Cu/SAPO-18 and Cu/SAPO-34 exhibited high NO conversions without propene. However, as compared to Cu/ZSM-5, NO conversions over Cu/SSZ-13, Cu/SAPO-18 and Cu/SAPO-34 were more stable with propene, due to coke formation over Cu/ZSM-5. The results of N2-adsorption/desorption and XPS showed that the surface area, Cu+/Cu2+ ratio and the surface amount of Cu content of Cu/ZSM-5 catalysts changed from 324 m2/g, 0.03 and 11.5 wt% for the fresh Cu/ZSM-5 catalyst to 68 m2/g, 0.34 and 5.3 wt% for the used sample. However, there were little changes between fresh and used Cu/SSZ-13, Cu/SAPO-18 and Cu/SAPO-34 catalysts. Moreover, Cu/ZSM-5 catalyst showed a larger decline in NO conversion with time on stream and a higher adsorption amount of propene compared to Cu/SSZ-13, Cu/SAPO-18 and Cu/SAPO-34 catalysts. The resistance to hydrocarbon poisoning depended on the pore geometry of the zeolites. During NH3-SCR, the presence of medium-pore sizes in Cu/ZSM-5 led to hydrocarbon deposition, which blocked the active sites and also decreased the active intermediates needed for NO conversion. Cu/SSZ-13, Cu/SAPO-18 and Cu/SAPO-34 catalysts, on the other hand, with small pores and cage diameters and with one-dimensional channel structures, showed higher hydrocarbon poison resistance. Moreover, these copper exchanged small-pore zeolites showed much higher hydrothermal stability than the medium-pore Cu/ZSM-5.

Graphene oxide mode-locked femtosecond erbium-doped fiber lasers

Abstract: We demonstrated the femtosecond erbium-doped all-fiber lasers mode-locked with graphene oxide, which can be conveniently obtained from natural graphite by simple oxidation and ultra-sonication process. With proper dispersion management in an all-fiber ring cavity, the laser directly generated 200 fs pulses at a repetition rate of 22.9 MHz and the average output power was 5.8 mW. With the variation of net cavity dispersion, output pulses with pulse width of 0.2~3 ps were obtained at a repetition rate of 22.9~0.93 MHz. These results are comparable with those of graphene saturable absorbers and the superiority of easy fabrication and hydrophilic property of graphene oxide will facilitate its potential applications for ultrafast photonics.

Data gathering in wireless sensor networks through intelligent compressive sensing

Abstract: The recently emerged compressive sensing (CS) theory provides a whole new avenue for data gathering in wireless sensor networks with benefits of universal sampling and decentralized encoding. However, existing compressive sensing based data gathering approaches assume the sensed data has a known constant sparsity, ignoring that the sparsity of natural signals vary in temporal and spatial domain. In this paper, we present an adaptive data gathering scheme by compressive sensing for wireless sensor networks. By introducing autoregressive (AR) model into the reconstruction of the sensed data, the local correlation in sensed data is exploited and thus local adaptive sparsity is achieved. The recovered data at the sink is evaluated by utilizing successive reconstructions, the relation between error and measurements. Then the number of measurements is adjusted according to the variation of the sensed data. Furthermore, a novel abnormal readings detection and identification mechanism based on combinational sparsity reconstruction is proposed. Internal error and external event are distinguished by their specific features. We perform extensive testing of our scheme on the real data sets and experimental results validate the efficiency and efficacy of the proposed scheme. Up to about 8dB SNR gain can be achieved over conventional CS based method with moderate increase of complexity.

Size-dependent bandgap modulation of ZnO nanowires by tensile strain.

Abstract: We quantified the size-dependent energy bandgap modulation of ZnO nanowires under tensile strain by an in situ measurement system combining a uniaxial tensile setup with a cathodoluminescence spectroscope. The maximal strain and corresponding bandgap variation increased by decreasing the size of the nanowires. The adjustable bandgap for the 100 nm nanowire caused by a strain of 7.3% reached approximately 110 meV, which is nearly double the value of 59 meV for the 760 nm nanowire with a strain of 1.7%. A two-step linear feature involving bandgap reduction caused by straining and a corresponding critical strain was identified in ZnO nanowires with diameters less than 300 nm. The critical strain moved toward the high strain level with shrunken nanowires. The distinct size effect of strained nanowires on the bandgap variation reveals a competition between core-dominated and surface-dominated bandgap modulations. These results could facilitate potential applications involving nanowire-based optoelectronic devi...

In Cloud, Can Scientific Communities Benefit from the Economies of Scale?

Abstract: The basic idea behind cloud computing is that resource providers offer elastic resources to end users. In this paper, we intend to answer one key question to the success of cloud computing: in cloud, can small-to-medium scale scientific communities benefit from the economies of scale? Our research contributions are threefold: first, we propose an innovative public cloud usage model for small-to-medium scale scientific communities to utilize elastic resources on a public cloud site while maintaining their flexible system controls, i.e., create, activate, suspend, resume, deactivate, and destroy their high-level management entities-service management layers without knowing the details of management. Second, we design and implement an innovative system-DawningCloud, at the core of which are lightweight service management layers running on top of a common management service framework. The common management service framework of DawningCloud not only facilitates building lightweight service management layers for heterogeneous workloads, but also makes their management tasks simple. Third, we evaluate the systems comprehensively using both emulation and real experiments. We found that for four traces of two typical scientific workloads: High-Throughput Computing (HTC) and Many-Task Computing (MTC), DawningCloud saves the resource consumption maximally by 59.5 and 72.6 percent for HTC and MTC service providers, respectively, and saves the total resource consumption maximally by 54 percent for the resource provider with respect to the previous two public cloud solutions. To this end, we conclude that small-to-medium scale scientific communities indeed can benefit from the economies of scale of public clouds with the support of the enabling system.

Battle of the Water Calibration Networks

Abstract: Calibration is a process of comparing model results with field data and making the appropriate adjustments so that both results agree. Calibration methods can involve formal optimization methods or manual methods in which the modeler informally examines alternative model parameters. The development of a calibration framework typically involves the following: (1) definition of the model variables, coefficients, and equations; (2) selection of an objective function to measure the quality of the calibration; (3) selection of the set of data to be used for the calibration process; and (4) selection of an optimization/manual scheme for altering the coefficient values in the direction of reducing the objective function. Hydraulic calibration usually involves the modification of system demands, fine-tuning the roughness values of pipes, altering pump operation characteristics, and adjusting other model attributes that affect simulation results, in particular those that have significant uncertainty assoc...

Rod-, flower-, and dumbbell-like MnO2: Highly active catalysts for the combustion of toluene

Abstract: The rod-like tetragonal α-MnO 2 , flower-like hexagonal ɛ-MnO 2 , and dumbbell-like tetragonal β-MnO 2 were prepared using the hydrothermal or water-bathing method under different conditions. It is shown that the α-MnO 2 , ɛ-MnO 2 , and β-MnO 2 catalysts possessed a surface area of ca. 53, 30, and 114 m 2 /g, respectively. The oxygen adspecies concentration and low-temperature reducibility decreased in the order of α-MnO 2 > ɛ-MnO 2 > β-MnO 2 , coinciding with the sequence of their catalytic activities for toluene combustion. The well-defined morphological MnO 2 catalysts performed much better than the bulk counterpart. At a space velocity of 20,000 mL/(g h), the temperature for 90% toluene conversion was 238, 229, and 241 °C over α-MnO 2 , ɛ-MnO 2 , and β-MnO 2 , respectively. The apparent activation energies of α-MnO 2 , ɛ-MnO 2 , and β-MnO 2 were in the range of 20–26 kJ/mol. It is concluded that higher oxygen adspecies concentrations and better low-temperature reducibility were responsible for the good catalytic performance of the α-MnO 2 , ɛ-MnO 2 , and β-MnO 2 materials.

Feature selection using rough entropy-based uncertainty measures in incomplete decision systems

Abstract: Feature selection in large, incomplete decision systems is a challenging problem. To avoid exponential computation in exhaustive feature selection methods, many heuristic feature selection algorithms have been presented in rough set theory. However, these algorithms are still time-consuming to compute. It is therefore necessary to investigate effective and efficient heuristic algorithms. In this paper, rough entropy-based uncertainty measures are introduced to evaluate the roughness and accuracy of knowledge. Moreover, some of their properties are derived and the relationships among these measures are established. Furthermore, compared with several representative reducts, the proposed reduction method in incomplete decision systems can provide a mathematical quantitative measure of knowledge uncertainty. Then, a heuristic algorithm with low computational complexity is constructed to improve computational efficiency of feature selection in incomplete decision systems. Experimental results show that the proposed method is indeed efficient, and outperforms other available approaches for feature selection from incomplete and complete data sets.

Life Cycle Energy Consumption and Carbon Dioxide Emission of Residential Building Designs in Beijing

Abstract: Summary This study is based on the three types of residential buildings with framework structures in Beijing: concrete framework construction (CFC), light-gauge steel framework construction (SFC), and wood framework construction (WFC). The analysis of the environmental load across the life cycle of the three types of buildings is conducted using life cycle assessment (LCA) according to the protocols of the International Organization for Standardization (ISO) 14040/44. The functional unit is the three material building designs, which possess the same function and design plan, and are built in concrete, light-gauge steel, and light frame wood, inclusive of their respective envelope materials. Throughout the investigation, the calculations of the environmental load data of materials, energy consumption, and carbon dioxide (CO2) emissions are comprehensively assessed and compared. The study shows that over the life cycle, the energy consumption of CFC is almost the same as that of SFC, and each of them is approximately 30% higher than that of WFC. Building use, steel material production, cement production, gypsum board production, and material transport are the main construction activities related to the energy consumption; the net CO2 emission of CFC is 44% higher than that of SFC and 49% higher than that of WFC. The main source of CO2 emission is the use of electricity; its contributions to the net CO2 emissions of WFC, SFC, and CFC are 67%, 64%, and 44%, respectively. The net CO2 emissions in the transport category cannot be ignored, with proportions amounting to 8%, 12%, and 11% for WFC, SFC, and CFC, respectively.

Thermal and insulating properties of epoxy/aluminum nitride composites used for thermal interface material

Abstract: We synthesized an epoxy matrix composite adhesive containing aluminum nitride (AlN) powder, which was used for thermal interface materials (TIM) in high power devices. The experimental results revealed that adding AlN fillers into epoxy resin was an effective way to boost thermal conductivity and maintain electrical insulation. We also discovered a proper coupling agent that reduced the viscosity of the epoxy-AlN composite by AlN surface treatment and increased the solid loading to 60 vol %. For the TIM sample made with the composite adhesive, we obtained a thermal conductivity of 2.70 W/(m K), which was approximately 13 times larger than that of pure epoxy. The dielectric strength of the TIM was 10 to 11 kV/mm, which was large enough for applications in high power devices. Additionally, the thermal and insulating properties of the TIM did not degrade after thermal shock testing, indicating its reliability for use in power devices. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012

Fe3O4/Fe/Carbon Composite and Its Application as Anode Material for Lithium-Ion Batteries

Abstract: A plum pudding-like Fe3O4/Fe/carbon composite was synthesized by a sol–gel polymerization followed by a heat-treatment process and characterized by X-ray diffraction, Raman spectroscopic analysis, ...