Slow and fast pyrolysis of Douglas-fir lignin: Importance of liquid-intermediate formation on the distribution of products

The formation of liquid intermediates and the distribution of products were studied under slow and fast pyrolysis conditions. Results indicate that monomers are formed from lignin oligomeric products during secondary reactions, rather than directly from the native lignin. Lignin from Douglas-fir (Pseudotsuga menziesii) wood was extracted using the milled wood enzyme lignin isolation method. Slow pyrolysis using a microscope with hot-stage captured the liquid formation (>150 °C), shrinking, swelling (foaming), and evaporation behavior of lignin intermediates. The activation energy (E_a) for 5–80% conversions was 213 kJ mol⁻¹, and the pre-exponential factor (log A) was 24.34. Fast pyrolysis tests in a wire mesh reactor were conducted (300–650 °C). The formation of the liquid intermediate was visualized with a fast speed camera (250 Hz), showing the existence of three well defined steps: formation of lignin liquid intermediates, foaming and liquid intermediate swelling, and evaporation and droplet shrinking. GC/MS and UV-Fluorescence of the mesh reactor condensate revealed lignin oligomer formation but no mono-phenols were seen. An increase in pyrolytic lignin yield was observed as temperature increased. The molar mass determined by ESI-MS was not affected by pyrolysis temperature. SEM of the char showed a smooth surface with holes, evidence of a liquid intermediate with foaming; bursting from these foams could be responsible for the removal of lignin oligomers. Py-GC/MS studies showed the highest yield of guaiacol compounds at 450–550 °C.     

Low natural gas prices and the financial cost of ramp rate restrictions at hydroelectric dams

Peaking hydroelectric dams that employ variable, stop-start reservoir releases can have adverse impacts on downstream river ecosystems. Efforts to mitigate these impacts have relied predominantly on the use of ramp rate restrictions, which limit the magnitude of hour-to-hour changes in reservoir discharge. Ramp rate restrictions shift hydropower production towards less valuable off-peak hours, imposing a financial penalty on dam owners that is a function of the “spread” (difference) between peak and off-peak electricity prices. This study examines how low natural gas prices in the U.S. have reduced the cost of implementing ramp rate restrictions at dams by narrowing the peak/off-peak price spread. Significantly lower costs of ramp rate restrictions could open new opportunities for improving environmental flows at dams, including the “purchase” of more natural streamflow patterns by downstream stakeholders, a type of arrangement for which there is growing precedent. We also explore the role that uncertainty in the cost of ramp rate restrictions could play in precluding downstream stakeholders from forming these types of agreements with dam owners. Results suggest that financial “collar” contracts could mostly eliminate inter-annual variability in the net cost of restrictions and provide those purchasing more natural flows with greater certainty.     

Recent progress in integration of reforming catalyst on metal-supported SOFC for hydrocarbon and logistic fuels

The metal-supported solid oxide fuel cell (MS-SOFC) is of current research interest in the clean energy field due to its high performance, quick start-up, thermal cycle stability, and lower raw material cost compared to the conventional cermet-based SOFC. To efficiently operate a MS-SOFC using complex hydrocarbon and logistic fuels, it is required to introduce an internal reforming catalyst within the anode metal scaffold. This review article discusses some examples of the performance of MS-SOFCs under hydrocarbon and logistic fuels with and without an additional reforming catalyst. We also discuss the performance improvement of conventional cermet-based SOFCs by adding reforming catalysts via the infiltration method. This information can be directly applied to future MS-SOFC applications. Furthermore, this review article proposes possible novel methods such as direct precursor infiltration, catalyst-anode premixing, and atomic layer deposition methods to introduce the reforming catalyst into a MS-SOFC for improving its initial electrochemical performance and long-term stability under hydrocarbon and logistics fuel.     

Effects of freeze-thaw cycles of Pacific white shrimp (Litopenaeus vannamei) subjected to radio frequency tempering on melanosis and quality

This study was conducted to investigate the effects of different tempering methods and freeze-thaw cycles on melanosis and quality parameters of pacific white shrimp. Frozen pacific white shrimps tempered with radio frequency tempering (RFT) were compared to that in water tempering (WT) and refrigerator tempering (RT) in terms of temper loss, total volatile base nitrogen (TVBN), polyphenol oxidase (PPO) activity, melanosis, total sulfhydryl contents, differential scanning calorimetry (DSC), and texture properties after 0, 1, 3, 5 freeze-thaw cycles. Results showed that crushed ice was effective as an effective surrounding medium for six layers of frozen shrimp reaching −2 °C within 6 min in RFT. For quality attributes, the temper loss of samples tempered with radio frequency is lower than that of RT and WT after all freeze-thaw cycles, and RFT resulted in the lowest TVBN value (9.17 mgN/100 g) of shrimps after the 5th freeze-thaw cycle. The PPO activity and melanosis of samples increased as the number of freeze-thaw cycles increased, and RFT effectively inhibited the development of melanosis. After the 3rd freeze-thaw cycle, the enthalpy change (△H) and the sulfhydryl content (0.16 mmol/gprot) of radio frequency tempered samples was significantly higher (p < 0.05) than that of WT and RT. RFT retained the hardness and chewiness of shrimp samples in all freeze-thaw cycles. Therefore, RFT effectively inhibited melanosis and reduce protein oxidation in Pacific white shrimp during freeze-thaw cycles with its fast and uniform heating characteristics.     

Feasibility of preparing additive manufactured porous stainless steel felts with mathematical micro pore structure as novel catalyst support for hydrogen production via methanol steam reforming

In this paper, an additive manufacturing prepared porous stainless steel felt (AM-PSSF) is proposed as a novel catalyst support for hydrogen production via methanol steam reforming (MSR). In the method, 316 L stainless steel powder with diameter of 15–63 μm is processed by the additive manufacturing technology of selective laser melting (SLM). To accomplish the preparation, the reforming chamber where the AM-PSSF is embedded is firstly divided into an all-hexahedron mesh. Then, the triply periodic minimal surface (TPMS) unit with mathematical form, high interconnectivity and large specific surface area is mapped into the hexahedrons based on shape function, forming the fully connected three-dimensional (3D) micro pore structure of the AM-PSSF. By correlating the mathematical parameter and the porosity of the TPMS unit, and taking into account the SLM process, the porosity of the AM-PSSF is well controlled. Based on the designed 3D pore structure model, the AM-PSSF is produced using standard SLM process. The application of the AM-PSSF as catalyst support for hydrogen production through MSR indicates that: 1) both the naked and catalyst-coated AM-PSSF have the characteristics of high porosity, large specific surface area and high connectivity; 2) the MSR hydrogen production performance of the AM-PSSF is better than that of the commercial stainless steel fiber sintered felt. The feasibility of AM-PSSF as catalyst support for MSR hydrogen production may pave a better way to balance different requirements for catalyst support, thanks to the excellent controllability provided by AM on both the external shape and the internal pore structure, and to the produced rough surface morphology that benefits the catalyst adhesion strength. In addition, catalyst support with pore structures that are more accommodated with the flow field and the reaction rate of MSR reaction may be prepared in future, since the entire catalyst support structure, from macro scale to micro scale, is under control.     

Modeling patterns of activities using activity curves

Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve, which represents an abstraction of an individual’s normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics.     

First ply failure study of thin composite conoidal shells subjected to uniformly distributed load

The civil engineers often need to cover large column free open spaces with thin shell structures. The doubly curved shells are characteristically stiff and the ruled surfaces are easy to fabricate. The aesthetically pleasing conoidal shells satisfy both these criteria and are preferred by structural engineers. The engineers now look out for strong but lightweight materials and as a result the laminated composites have evolved. The first ply failure is very important issue for laminated composites. Such studies for plates are reported but similar work on thin shells is very scanty. This paper is aimed to fulfill this lacuna.     

Application of soft-thresholding on the decomposed Lamb wave signals for damage detection of plate-like structures

Effective application of the Lamb waves for structural health monitoring and damage identification intensively relies on the accurate damage-related feature extraction in the received signals. Most of existing signal processing methods extract the damage-related features from the time–frequency joint spectrum which requires a quite amount of effort. In this paper, the soft-thresholding process, based on different signal decomposition methods, is introduced to damage identification so that the damage-related signal features can be manifested more distinctively. By applying two popular signal decomposition methods (i.e., the discrete wavelet transform (DWT) and the empirical mode decomposition (EMD)), the signal of interest can be represented by a series of components with different frequencies. Since most noises exist in the high frequency range, it is feasible to alleviate noise by restricting the energy of high-frequency components. Finally, a denoised signal is synthesized using the corresponding reconstruction method. As an application, the soft-thresholding process is performed to detect a small crack on an isotropic aluminum plate under the white Gaussian noise contamination. The results, from both the numerical finite element simulation and experimental test, indicate that the soft-thresholding process is capable of effectively reducing the effect of noise, convincingly improving the sensitivity of damage identification, and discriminating relatively small damage.     

The value of mixed conduction for oxygen electroreduction on graphene–chitosan composites

Graphene-based electrocatalysts have been widely investigated for their excellent performance in electrocatalytic oxygen reduction. The surface chemistry of graphene-based electrocatalysts is important for developing more efficient fuel cells and metal-air batteries. In addition, the nanostructured gas-diffusion electrode (GDE) on which the electrocatalysts are loaded needs to be carefully tailored to facilitate mass transport (reactants and products). A polymer binder is often used to fabricate the GDE which means there is a need to optimize the ratio of binder to electrocatalyst. Herein we demonstrate the impacts of graphene-based GDE nanostructures on the efficiency of oxygen electroreduction by comparing a series of graphene/chitosan composites with varying compositions. In these nanostructured GDEs graphene acts as the electrocatalyst and chitosan as the binder. Our results illustrate a critical ratio of graphene to chitosan for enhanced electrocatalytic surface area and facilitated mass transport, while a continuous network for electron conduction is effectively established. We believe this work is an important piece of the puzzle to better understanding the electrode behavior of electrocatalysts consisting of graphene-like two-dimensional materials in oxygen reduction reaction.     

Dissipating energy flow method for locating the source of sustained oscillations

The modification of an energy-based approach called the dissipating energy flow (DEF) method is proposed, which uses data from phasor measurement units (PMUs) to trace the source of poorly damped natural and forced oscillations in power systems. The original energy-based approach (Chen et al., 2013) assumes the ability to determine steady-state values of variables measured by PMU during the transient process and that prevents the reliable use of the original method with actual PMU data. PMU data processing, proposed in the DEF method, is a key step in converting the energy-based method into a robust and automated tool for use with actual PMU data. The effectiveness of the proposed DEF method is demonstrated by testing multiple simulated cases of sustained oscillations, including both poorly damped natural and forced oscillations and more than 30 actual events in ISO New England (ISO-NE) and two events in Western Electricity Coordination Council (WECC) systems. The study also demonstrates the potential for using the DEF method to estimate the contribution of any generator to the damping of a specific oscillation mode.