Pt/Y0.16Zr0.84O1.92/Pt thin film solid oxide fuel cells: Electrode microstructure and stability considerations

Symmetric, free standing thin film micro-solid oxide fuel cells of Pt/Y_0.16Zr_0.84O_1.92/Pt structure are studied in this report. The role of parameters such as electrolyte thickness and electrode porosity on fuel cell power output was investigated. A peak power density of 1037 mW cm⁻² was exhibited with an optimized structure consisting of nano-porous Pt electrodes and 100 nm thick Y_0.16Zr_0.84O_1.92 with an open circuit voltage of 0.968 V at 500 °C using H₂ as fuel and standing air as the oxidant. A twelve hour test of these devices indicates that overall performance shows extreme sensitivity to microstructural changes in the pure metallic electrodes. Results presented herein enable mechanistic routes to performance optimization, provide device stability data and are relevant to advancing micro-fuel cells for portable energy.     

Electronic Granularity and the Work Function of Transparent Conducting ZnO:Al Thin Films

Controlling the efficiency of electron transport across oxide interfaces is essential for numerous emerging technologies including advanced photovoltaics and light emitting devices. This work illuminates the connections between granular structure, defect chemistry, and the work function of a technologically important transparent conductor, ZnO:Al. Visual evidence is provided for a model of grain boundary oxidation in the form of nanometer‐scale heterogeneity in the contact potential between grains and grain boundaries, a phenomenon referred to as electronic granularity. By correlating scanning probe data with photoemission spectroscopy we relate electronic granularity to defect chemistry and, importantly, account for the overall trends in work function. The resulting physical picture connects heterogeneity at the nanoscale to macroscopic properties, informs the design of transparent electrodes, and may be broadly relevant to granular oxide conductors.     

Dynamic Load Flow Technique for Power System Simulators

This paper presents a dynamic load flow technique for power system simulators. The approach presented can be applied to a system when there is a net accelerating or decelerating power in the system. It possesses all the attractive features and basic structure of the normal fast decoupled method, and it does not depend on the selected reference bus. The modifications to the standard fast decoupled power flow algorithm are derived, and power system simulator implementation considerations are discussed. The algorithm has been tested on standard IEEE test cases and on a metropolitan utility 559 bus model. A numerical example of the above algorithm on the 559 test case is presented which demonstrates convergence characteristics and computation requirements of the proposed algorithm. These results are compared with those of normal fast decoupled load flow.     

Mining gene–sample–time microarray data: a coherent gene cluster discovery approach

Extensive studies have shown that mining microarray data sets is important in bioinformatics research and biomedical applications. In this paper, we explore a novel type of gene–sample–time microarray data sets that records the expression levels of various genes under a set of samples during a series of time points. In particular, we propose the mining of coherent gene clusters from such data sets. Each cluster contains a subset of genes and a subset of samples such that the genes are coherent on the samples along the time series. The coherent gene clusters may identify the samples corresponding to some phenotypes (e.g., diseases), and suggest the candidate genes correlated to the phenotypes. We present two efficient algorithms, namely the Sample-Gene Search and the Gene–Sample Search, to mine the complete set of coherent gene clusters. We empirically evaluate the performance of our approaches on both a real microarray data set and synthetic data sets. The test results have shown that our approaches are both efficient and effective to find meaningful coherent gene clusters. Daxin Jiang received the Ph.D. degree in computer science and engineering from the State University of New York at Buffalo in 2005. He received the B.S. degree in computer science from the University of Science and Technology of China. From 1998 to 2000, he was a M.S. student in Software Institute, Chinese Academy of Sciences. He is currently an assistant professor at the School of Computer Engineering, Nanyang Technology University, Singapore. His research interests include data mining, bioinformatics, machine learning, and information retrieval. Jian Pei received the Ph.D. degree in computing science from Simon Fraser University, Canada, in 2002, under Dr. Jiawei Han's supervision. He also received the B.Eng. and the M.Eng. degrees from Shanghai Jiao Tong University, China, in 1991 and 1993, respectively, both in Computer Science. He is currently an assistant professor of computing science at Simon Fraser University. His research interests include developing effective and efficient data analysis techniques for novel data intensive applications. He is currently interested in various techniques of data mining, data warehousing, online analytical processing, and database systems, as well as their applications in bioinformatics. His current research is supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the National Science Foundation (NSF) of the United States. Since 2000, he has published over 70 research papers in refereed journals, conferences, and workshops, has served in the organization committees and the program committees of over 60 international conferences and workshops, and has been a reviewer for some leading academic journals. He is a member of the ACM, the ACM SIGMOD, and the ACM SIGKDD. Murali Ramanathan is an associate professor of pharmaceutical sciences and neurology. He received the B.Tech. (Honors) in chemical engineering from the Indian Institute of Technology, India, in 1983. After a 4-year stint in the chemical industry, he obtained the M.S. degree in chemical engineering from Iowa State University, Ames, IA, in 1987, and the Ph.D. degree in bioengineering from the University of California-San Francisco and University of California-Berkeley Joint Program in Bioengineering in 1994. Dr. Ramanathan research interests are primarily focused on the treatment of multiple sclerosis (MS), an inflammatory-demyelinating disease of the central nervous system that affects over 1 million patients worldwide. MS is a complex, variable disease that causes physical and cognitive disability and nearly 50% of patients diagnosed with MS are unable to walk after 15 years. The etiology and pathogenesis of MS remains poorly understood. Dr. Ramanathan's research interests include stochastic modeling of pharmaceutical systems and novel approaches to analyzing and using genetic and genomic data for improving patient care and optimizing therapy. Chuan Lin is currently a Ph.D. student in the Department of Computer Science and Engineering, State University of New York at Buffalo. She received the B.E. and the M.S. degrees in computer science and technology from Tsinghua University in China. Her research interests include bioinformatics, data mining, and machine learning. Chun Tang received the B.S. and M.S. degrees from Peking University, China, in 1996 and 1999, respectively, and the Ph.D. degree from State University of New York at Buffalo, USA, in 2005, all in computer science. Currently, she is a postdoctoral associate of Center for Medical Informatics, Yale University. Her research interests include bioinformatics, data mining, machine learning, database, and information retrieval. Aidong Zhang received the Ph.D. degree in computer science from Purdue University, West Lafayette, Indiana, in 1994. She was an assistant professor from 1994 to 1999, an associate professor from 1999 to 2002, and has been a professor since 2002 in the Department of Computer Science and Engineering at State University of New York at Buffalo. Her research interests include multimedia systems, content-based image retrieval, bioinformatics, and data mining. She is an author of over 140 research publications in these areas. Dr. Zhang's research has been funded by NSF, NIH, NIMA, and Xerox. Zhang serves on the editorial boards of International Journal of Bioinformatics Research and Applications (IJBRA), ACM Multimedia Systems, International Journal of Multimedia Tools and Applications, and International Journal of Distributed and Parallel Databases. She was the editor for ACM SIGMOD DiSC (Digital Symposium Collection) from 2001 to 2003. She was co-chair of the technical program committee for ACM Multimedia in 2001. She has also served on various conference program committees. Dr. Zhang is a recipient of the National Science Foundation CAREER award and SUNY Chancellor's Research Recognition award.     

An InGaP/GaAs Merged HBT-FET (BiFET) Technology and Applications to the Design of Handset Power Amplifiers

The last decade has seen GaAs HBTs emerge as the dominant technology in wireless handset power amplifiers. Modern application requirements and size limitations have driven industry leaders towards the co-integration of depletion mode n-FET and GaAs HBT. The merger of Bipolar and FET, or BiFET, gives an additional degree of freedom in the design of advanced power amplifiers independent of a silicon controller. This paper provides an overview of the various techniques that can be used to join the two device technologies and then shows how a merged epitaxial structure, where an FET is formed in the emitter layers of an HBT, combines functional versatility with the high volume manufacturability needed to supply millions of power amplifiers at low cost. A large-signal model of the FET structure is developed which takes into account the unique physics and geometries of the device, including voltage-dependant parameters and charges on all four electrical terminals. Specific handset applications that can benefit or be enabled by BiFET are presented, such as on-off switching, low voltage bias controllers , Auto-Bias power amplifiers, and bias circuits with low or no voltage reference. When npn-only bias circuitry is limited to low voltage reference levels, HBT power amplifiers with BiFET bias stages are shown to have superior RF performance to their npn-only counterparts.     

Studies on slip casting behavior of lanthanum strontium manganite

Dispersion conditions for slip (slurry) formulation of a powder mixture of lanthanum strontium manganite (La_0.84Sr_0.16MnO₃ - LSM) and carbon (pore former) in water was studied through detailed zeta-potential and rheological measurements. The zeta potential variation with pH for the aqueous suspensions of only LSM or carbon exhibited a maximum value in alkaline medium (−40 mV to −50 mV at a pH of 10-11), establishing the pH window for their co-dispersion for slurry formulation. A study of the viscosity variation with shear rate for the slurries with varying solid content (in the range of 45-65 wt.%) exhibited pseudo-plastic flow behavior, indicating presence of flocculates in them. The yield stress values obtained from the Casson equation reduced with decreasing solid content, indicating reduction in the flocculate strength. The slip with solid content of 50 wt.% exhibited optimum flow characteristics to form long tubes with uniform wall thickness (wall thickness 2-4 mm and length of 150-200 mm). The tubular specimens formed after controlled carbon burn out and sintering at 1400 °C for 1 h possessed about 35% open porosity. The porosity remained the same upon further sintering at 1400 °C for 8 h.     

Study on the Effect of Loading Rate on Flexural Strength of Glass/Polyester Composites as a Function of Span-to-Depth Ratio and Fiber Volume Fraction

The influence of loading rate, span-to-thickness ratio and fiber volume fraction on composites was studied by three-point bend test on glass fiber reinforced in polyester composite laminate fabricated by compression moulding method. For lower L/h ratio, shear fracture was observed. Tensile fracture was observed for the specimen having higher L/h ratio irrespective of loading rate. Shear fracture dominates at high loading rates. This behavior was interpreted as being due to the fact that the increase in loading rate increases the brittleness of materials, subsequently increasing the defect sensitivity and leading to shear fracture.     

A molecular mechanism for electrical tuning of cochlear hair cells

Cochlear frequency selectivity in lower vertebrates arises in part from electrical tuning intrinsic to the sensory hair cells. The resonant frequency is determined largely by the gating kinetics of calcium-activated potassium (BK) channels encoded by the slo gene. Alternative splicing of slo from chick cochlea generated kinetically distinct BK channels. Combination with accessory beta subunits slowed the gating kinetics of alpha splice variants but preserved relative differences between them. In situ hybridization showed that the beta subunit is preferentially expressed by low-frequency (apical) hair cells in the avian cochlea. Interaction of beta with alpha splice variants could provide the kinetic range needed for electrical tuning of cochlear hair cells.     

Issues on the chalcopyrite/defect-chalcopyrite junction model for high-efficiency Cu(In,Ga)Se2 solar cells

Considering the chalcopyrite/defect-chalcopyrite junction model for Cu(In_1−xGa_x)Se₂-based devices and our previously reported findings for the Cu(In_1−xGa_x)₃Se₅ defect chalcopyrites, we have postulated that uniform high-Ga-content photovoltaic structures (with x > 0.35) do not yield acceptable device performance due to the electrical and structural differences between both types of materials (chalcopyrite and defect-chalcopyrite).In this contribution, the structural properties of the surface region of Ga containing absorber materials have been studied by grazing incidence X-ray diffraction. We find that there are significant differences between surface and bulk. A structural model is proposed for the growth of the chalcopyrite/defect-chalcopyrite junction relative to its Ga content. And we demonstrate that closely lattice matched high-Ga-content structures (x > 0.35) can produce solar cells withv acceptable performances. The high-voltage and low-current electrical outputs from high Ga structures are very desirable in module fabrication because overall resistive losses can be substantially reduced.     

Synthesis and characterization of one-dimensional flat ZnO nanotower arrays as high-efficiency adsorbents for the photocatalytic remediation of water pollutants

We report on facile fabrication of 1-D flat ZnO nanotower arrays on various substrates, including a metal, a semiconductor and an insulator. The nanotowers have a unique flat basal section near the substrate and taper in stages to wire-like at the tip. Electron microscopy and X-ray photoelectron spectroscopy are used to characterize these new nanostructures, revealing that their morphologies are significantly influenced by reaction temperature. A qualitative formation mechanism is proposed based on the experimental observations. A proof-of-concept demonstration shows that the ZnO nanotower arrays are highly effective at adsorbing and subsequently photo-remediating a model pollutant (Eosin B) from water. These observations could promote new applications of photocatalytic adsorbents for wastewater treatment utilizing oxide semiconductor nanostructures.