Characterization and application of electrodeposited Pt, Pt/Pd, and Pd catalyst structures for direct formic acid micro fuel cells

In this work, we study the preparation, structural characterization, and electrocatalytic analysis of robust Pt and Pd-containing catalyst structures for silicon-based formic acid micro fuel cells. The catalyst structures studied were prepared and incorporated into the silicon fuel cells by a post CMOS-compatible process of electrodeposition, as opposed to the more common introduction of nanoparticle-based catalyst by ink painting. Robust, high surface area, catalyst structures consisting of pure Pt, pure Pd, and Pt/Pd = 1:1 were obtained. In addition, Pt/Pd catalyst structures were obtained via spontaneous deposition on the electrodeposited pure Pt structure. The catalyst structures were characterized electrochemically using cyclic voltammetry and chronoamperometry. All Pd-containing catalyst structures facilitate formic acid oxidation at the lower potentials and deliver higher oxidation currents compared to pure Pt catalyst structures. Fuel cells of these catalyst structures show that pure Pd catalyst structures on the anode exhibit the highest peak power density, i.e. as high as 28.0 mW/cm². The MEMS compatible way of catalyst electrodeposition and integration presented here has yielded catalyst structures that are highly active towards formic acid oxidation and are sufficiently robust to be compatible with post-CMOS processing.     

A Genetic Programming Approach to System Identification of Rainfall-Runoff Models

Advancements in data acquisition, storage and retrieval are progressing at an extraordinary rate, whereas the same in the field of knowledge extraction from data is yet to be accomplished. The challenges associated with hydrological datasets, including complexity, non-linearity and multicollinearity, motivate the use of machine learning to build hydrological models. Increasing global climate change and urbanization call for better understanding of altered rainfall-runoff processes. There is a requirement that models are intelligible estimates of underlying physics, coupling explanatory and predictive components, maintaining parsimony and accuracy. Genetic Programming, an evolutionary computation technique has been used for short-term prediction and forecast in the field of hydrology. Advancing data science in hydrology can be achieved by tapping the full potential of GP in defining an evolutionary flexible modelling framework that balances prior information, simulation accuracy and strategy for future uncertainty. As a preliminary step, GP is used in conjunction with a conceptual rainfall-runoff model to solve model configuration problem. Two datasets belonging to a tropical catchment of Singapore and a temperate catchment of South Island, New Zealand with contrasting characteristics are analyzed in this study. The results indicate that proposed approach successfully combines the merits of evolutionary algorithm and conceptual knowledge in the generation of optimal model structure and associated parameters to capture runoff dynamics of catchments.     

Comparison of folate losses in soybean during the preparation of tempeh and soymilk

The changes in undeconjugated and total folate content of soybean during various stages of tempeh and soymilk preparation were studied. Total folate was extracted by the tri‐enzyme technique. The ratio of total folate to undeconjugated folate was compared in all samples. Raw soybeans used for tempeh and soymilk preparation contained 4.04 and 4.50 mg total folate kg^?1 respectively. Soaking and boiling soybean caused a significant loss of folate during tempeh and soymilk preparation. Leaching was identified as the major cause of folate loss, as soaking and cooking waters were found to contain a large amount of folate. Rhizopus fermentation of boiled soybean caused an increase of 68 and 100% in undeconjugated and total folate contents respectively. Frying reduced the folate content of tempeh significantly. Milling of boiled soybean in soymilk preparation significantly reduced the undeconjugated folate content of blanched soybean but increased the total folate. UHT treatment of soymilk caused a loss of 9 and 14% of undeconjugated and total folates respectively. The total folate content of deep‐fried tempeh and soymilk was 2.35 and 2.76 mg kg^?1 respectively. Analysed values are expressed on a dry weight basis. © 2002 Society of Chemical Industry     

Influence of fiber orientation on abrasive wear of unidirectionally reinforced carbon fiber–polyetherimide composites

A composite with continuous carbon fibers (CF) (80% by vol.) and high performance thermoplastic polyetherimide (PEI) matrix was developed and evaluated for various mechanical properties as a function of fiber orientation angle (0°, 30°, 45°, 60° and 90°). It was observed that Young's modulus, Poisson's ratio, toughness and % strain decreased with the increase of fiber orientation angle with respect to loading direction. In-plane shear modulus was highest for fibers with 45°. Overall, unidirectional (UD) CF reinforcement enhanced all strength properties of PEI significantly. Composites with fibers in 0° (parallel to loading direction) proved best in almost all the properties. Tribological evaluation in abrasive wear mode under different loads and fiber orientations indicated that coefficient of friction (μ) and specific wear rate (K₀) decreased with load, in general. Comparatively low specific wear rate (K₀), (in the order of 0.7 1×10^?9 m³/Nm) was observed for 0° fiber orientation, while fibers in 90° showed almost three times higher wear rate. Overall fiber reinforcement in 0° orientations proved beneficial from both strength and tribological performance point of view. SEM proved useful to correlate wear rate with surface topography.     

Influence of Plasma Treatment on Carbon Fabric for Enhancing Abrasive Wear Properties of Polyetherimide Composites

Interfacial adhesion between matrix and fiber plays a crucial role in controlling performance properties of composites. Carbon fibers have major constraint of chemical inertness and hence limited adhesion with the matrix. Surface treatment of fibers is the best solution of the problem. In this work, cold remote nitrogen oxygen plasma (CRNOP) was used for surface treatment. Twill weave carbon fabric (CF) (55–58 vol%) was used with and without plasma treatment with varying content of oxygen (0–1%) in nitrogen plasma to develop composites with Polyetherimide (PEI) matrix. The composites were developed by compression molding and assessed for mechanical and tribological (abrasive wear mode) properties. Improvement in tensile strength, flexural strength, and interlaminar shear strength (ILSS) was observed in composites due to treatment. Similarly, improvement in wear resistance (W _R) and reduction in friction coefficient (μ) were observed in treated fabric composites when slid against silicon carbide (SiC) abrasive paper under varying loads. A correlation between wear resistance and tensile strength was slightly better than that in Lancaster–Ratner plot indicating that ultimate tensile strength (S) and elongation to break (e) were contributing to control the W _R of the composites. It was concluded that enhanced adhesion of fibers with matrix was responsible for improvement in performance properties of composites, as evident from SEM, Fourier Transform Infrared spectroscopy-Attenuated Total Reflectance (FTIR-ATR) technique.     

Prolonged Exposure to Simulated Microgravity Changes Release of Small Extracellular Vesicle in Breast Cancer Cells

Breast cancer is the leading cause of cancer incidence worldwide and among the five leading causes of cancer mortality. Despite major improvements in early detection and new treatment approaches, the need for better outcomes and quality of life for patients is still high. Extracellular vesicles play an important role in tumor biology, as they are able to transfer information between cells of different origins and locations. Their potential value as biomarkers or for targeted tumor therapy is apparent. In this study, we analyzed the supernatants of MCF-7 breast cancer cells, which were harvested following 5 or 10 days of simulated microgravity on a Random Positioning Machine (RPM). The primary results showed a substantial increase in released vesicles following incubation under simulated microgravity at both time points. The distribution of subpopulations regarding their surface protein expression is also altered; the minimal changes between the time points hint at an early adaption. This is the first step in gaining further insight into the mechanisms of tumor progression, metastasis, the education of the tumor microenvironments, and preparation of the metastatic niche. Additionally, this may lighten up the processes of the rapid cellular adaptions in the organisms of space travelers during spaceflights.     

Separation of multicomponent aromatic/aliphatic mixtures by simulated moving bed adsorption: Modeling and experiments

Simulated moving bed (SMB) adsorption has potential for efficient separation of many valuable chemical mixtures, but considerably less attention has been devoted to multicomponent feeds relative to binary mixtures. We take a rigorous experimental and modeling approach to study multicomponent separation of aromatics and aliphatics with a mesoporous silica adsorbent, which is relevant in many petrochemical applications such as separation of reformate and distillate streams. Our approach involves refining multicomponent adsorption, mass transfer, and SMB process parameters based upon detailed experimental inputs, with progressive addition of components. We develop a robust model that quantitatively predicts the influence of key operating parameters such as stream flow rates, desorbent/feed ratio, and switch time on the separation results and concentration profiles. The model is validated as a function of feed complexity by SMB experiments and column concentration profile measurements in a 16-column mini-plant. Furthermore, conditions for clear separation of each mixture are developed.     

Analysis of a Chiral Dielectric Supported Broadband Helix Slow-Wave Structure for Millimeter-Wave TWTs

A novel technique of broadbanding a helical slow-wave structure through negative dispersion shaping is proposed. The model considers a simple continuous chiral dielectric support for the helix inside a metallic barrel, unlike conventional helix slow-wave structures with three discrete dielectric supports at 120⁰ apart. The dispersion relation of the slow-wave structure was derived following sheath-helix abstraction, suitably benchmarked for special cases, and was used for analyzing the dispersion behavior of a typical slow-wave structure. Chiral dielectric loading could easily provide negative dispersion characteristics (required for broadband operation) by merely controlling the chirality parameter alone. The scheme with its simple geometric configuration is expected to be useful for millimeter-wave devices providing better thermal management.