On the optical properties of the imidazolium ionic liquids

Room-temperature ionic liquids, particularly those based on substituted imidazolium cations, are currently being extensively studied for a variety of applications. Herein, we explore the suitability of several imidazolium salts in optical applications by carefully examining the electronic absorption and fluorescence behavior of these substances, generally believed to be transparent in most of the UV region and fully transparent in the visible region. It is shown that all imidazolium ionic liquids are characterized by significant absorption in the entire UV region and a long absorption tail that extends into the visible region. These absorption characteristics are attributed to the imidazolium moiety and its various associated structures. When excited in the UV or early part of the visible region, these liquids exhibit fluorescence, which covers a large part of the visible region and shows dramatic excitation wavelength dependence. The excitation wavelength dependent shift of the fluorescence maximum has been rationalized taking into consideration the existence of the various associated structures of the ionic liquids and the inefficiency of the excitation energy-transfer process between them. The results imply that these liquids may have serious drawbacks in some of the optical studies.     

Incorporating fault debugging activities into software reliability models: a simulation approach

A large number of software reliability growth models have been proposed to analyse the reliability of a software application based on the failure data collected during the testing phase of the application. To ensure analytical tractability, most of these models are based on simplifying assumptions of instantaneous & perfect debugging. As a result, the estimates of the residual number of faults, failure rate, reliability, and optimal software release time obtained from these models tend to be optimistic. To obtain realistic estimates, it is desirable that the assumptions of instantaneous & perfect debugging be amended. In this paper we discuss the various policies according to which debugging may be conducted. We then describe a rate-based simulation framework to incorporate explicit debugging activities, which may be conducted according to the different debugging policies, into software reliability growth models. The simulation framework can also consider the possibility of imperfect debugging in conjunction with any of the debugging policies. Further, we also present a technique to compute the failure rate, and the reliability of the software, taking into consideration explicit debugging. An economic cost model to determine the optimal software release time in the presence of debugging activities is also described. We illustrate the potential of the simulation framework using two case studies.     

Population Balance Modeling with Coupled Agglomeration and Disintegration Processes for TiO2 Nanoparticles Formation and Experimental Validation

Particle size distribution of nanoparticles plays an important role in modelling many scientific and engineering problems. In this article, we proposed a Finite Volume Method (FVM) to model TiO₂ nanoparticles formation using population balance equations (PBEs) by incorporating the simultaneous agglomeration and disintegration processes. The superposition of the PBEs for agglomeration and disintegration with different kernels leads to a system of partial-integro differential equations, which are numerically solved by using FVM. The precipitation of TiO₂ nanoparticles in the batch reactor is studied experimentally as well as by numerical simulations based on Austin and Diemer disintegration kernels and Shear agglomeration kernel. Finally, the capability of the precipitation model is evaluated and the experimental results on particle sizes are compared with the numerical results.

     

A simulation as a service cloud middleware

Many seemingly simple questions that individual users face in their daily lives may actually require substantial number of computing resources to identify the right answers. For example, a user may want to determine the right thermostat settings for different rooms of a house based on a tolerance range such that the energy consumption and costs can be maximally reduced while still offering comfortable temperatures in the house. Such answers can be determined through simulations. However, some simulation models as in this example are stochastic, which require the execution of a large number of simulation tasks and aggregation of results to ascertain if the outcomes lie within specified confidence intervals. Some other simulation models, such as the study of traffic conditions using simulations may need multiple instances to be executed for a number of different parameters. Cloud computing has opened up new avenues for individuals and organizations with limited resources to obtain answers to problems that hitherto required expensive and computationally-intensive resources. This paper presents SIMaaS, which is a cloud-based Simulation-as-a-Service to address these challenges. We demonstrate how lightweight solutions using Linux containers (e.g., Docker) are better suited to support such services instead of heavyweight hypervisor-based solutions, which are shown to incur substantial overhead in provisioning virtual machines on-demand. Empirical results validating our claims are presented in the context of two case studies.     

Hydrothermal processing of waste pine wood into industrially useful products

An ongoing major outbreak of mountain pine beetle in Western Canada has provided a clear opportunity to utilize waste pinewood as a source of renewable energy. Therefore hydrothermal processing of waste pinewood as a feedstock for bio-oil and biochar production using subcritical and supercritical water technology was carried out in semi-batch mode to investigate the effect of pressure (200–400 bar) and temperature (300–400 °C) on the yield and composition of bio-oil. The pinewood samples have very high cellulose and hemicellulose content but low ash content and are thus a formidable feedstock for bioenergy production. The optimum conditions for the hydrothermal processing of the pinewood in a tubular reactor were found to be 400 °C and 250 bars with respect to biochar and bio-oil yield based on the highest calorific value analysis. Detailed characterization of bio-oil and biochar was performed using GCMS, NMR, SEM, calorific value, and elemental analysis, respectively. The critical components of bio-oil were found to be phenols, methoxyphenols, hydroxymethyl furfural (HMF), and vanillin, whereas as compared to the raw pine wood, the biochar was considerably lower H:C and O:C ratios than those of the unprocessed pinewood. The analyses of bio-oil by means of GCMS and ¹H NMR showed that it was mainly composed of heterocyclic compounds, phenols, aldehydes and acids.     

Evaluation of novel ZnO–Ag cathode for CO2 electroreduction in solid oxide electrolyser

CO₂ and steam/CO₂ electroreduction to CO and methane in solid oxide electrolytic cells (SOEC) has gained major attention in the past few years. This work evaluates, for the very first time, the performance of two different ZnO–Ag cathodes: one where ZnO nanopowder was mixed with Ag powder for preparing the cathode ink (ZnO_mix–Ag cathode) and the other one where Ag cathode was infiltrated with a zinc nitrate solution (ZnO_inf –Ag cathode). ZnO_mix–Ag cathode had a better distribution of ZnO particles throughout the cathode, resulting in almost double CO generation while electrolysing both dry CO₂ and H₂/CO₂ (4:1 v/v). A maximum overall CO₂ conversion of 48% (in H₂/CO₂) at 1.7 V and 700 °C clearly indicated that as low as 5 wt% zinc loading is capable of CO₂ electroreduction. It was further revealed that for ZnO_inf –Ag cathode, most of CO generation took place through RWGS reaction, but for ZnO_mix–Ag cathode, it was the synergistic effect of both RWGS reaction and CO₂ electrolysis. Although ZnO_inf –Ag cathode produced trace amount of methane at higher voltages, with ZnO_mix–Ag cathode, there was absolutely no methane. This seems to be due to strong electronic interaction between Zn and Ag that might have suppressed the catalytic activity of the cathode towards methanation.

     

Exploration of a Cheaper Carbon Source for Extracellular β-glucosidase Synthesis from <Emphasis Type="Italic">Debaryomyces pseudopolymorphus</Emphasis> NRRL YB-4229

In the present work, interactions between common media components and fermentation conditions were explored to come up with a simple media recipe for extracellular β-glucosidase (Dβ-gl) synthesis from Debaryomyces pseudopolymorphus to substitute cellobiose, which is currently used as a sole carbon source. Taguchi L₂₅ orthogonal array design was used to screen factors influencing Dβ-gl synthesis (carbon, organic nitrogen, inorganic nitrogen, trace elements, inoculum volume, and fermentation time). A significant influence of xylose, peptone, and potassium nitrate as carbon, organic nitrogen, and inorganic nitrogen sources, respectively, on Dβ-gl synthesis was identified by Taguchi. These factors were further optimized using central composite rotatable design (CCRD) of response surface methodology (RSM). The results showed that in the range studied, potassium nitrate had insignificant effect while xylose, peptone, and xylose-peptone interaction had a significant effect on Dβ-gl synthesis. Peptone/xylose ratio of 1.33 was found to be an important parameter for inducing Dβ-gl synthesis. The regression coefficient (R ²) of 0.915 and P value of <0.0003 for the model indicated that it was highly significant. The maximum activity obtained after RSM (32.2 U/ml) was comparable with that obtained (68.8 U/ml) when cellobiose (20 g/l) was used as a sole carbon source. Considering the cost difference between xylose and cellobiose, a 16-fold cost reduction could be obtained for equivalent Dβ-gl yield. Fed-batch fermentations were carried out wherein peptone/xylose ratio of 1.33 was maintained and continuous Dβ-gl synthesis was observed.