First-principles modeling for optimal design,operation, and integration of energy conversion and storage systems

Energy and electricity consumption is expected to increase in the foreseeable future. Concurrently, sustainability concerns of fossil-based energy resources have motivated the use of renewable and reusable energy resources, and the use of more efficient energy-converting and energy-consuming systems. Consequently, for the past decade, there have been major theoretical and experimental advances in (1) energy generation from renewable and reusable resources and (2) energy-consuming and energy-converting devices. This review article focuses on the recent theoretical advances in renewable energy conversion devices such as photovoltaic and fuel cells, and in energy storage devices such as rechargeable batteries, flow batteries, and supercapacitors. Due to similar chemistry, electrochemistry, and physics of these systems, modeling similarities between different energy systems are highlighted. This review puts into perspective how first-principles mathematical modeling has contributed to systematic advances in the optimal design, operation, and integration of these systems. © 2018 American Institute of Chemical Engineers AIChE J, 65: e16482 2019     

CO2 reforming of methane over Ni-Cu/Al2O3-ZrO2 nanocatalyst : The influence of plasma treatment and process conditions on catalytic properties and performance

Argon glow discharge plasma was applied for treatment of impregnated Ni-Cu/Al₂O₃-ZrO₂ nanocatalyst. The catalytic performance toward CO₂ reforming of methane and the physicochemical properties were investigated by means of GC, BET, XRD, FESEM, TEM, EDX, TG-DTG, XPS and FTIR techniques. The plasma-treated nanocatalyst contains smaller crystal size and high dispersion of NiO. Plasma treatment decreased particle size and plasma high energy species flattened particles on support, increasing the interaction between support and active metals which leads to high catalytic activity. Low temperature activity and H₂/CO ratio closer to 1 was observed for plasma-treated nanocatalyst compared to non-treated sample. Moreover, higher product yield and H₂/CO ratio was found in CH₄/CO₂=1 rather than CH₄/CO₂=1.5. Time on stream test during 1,440 min at 850 °C showed plasma-treated Ni-Cu/Al₂O₃-ZrO₂ nanocatalyst did not experience any deactivation in terms of CH₄ and CO₂ conversion and H₂/CO ratio.     

Improved gas transport properties of polyurethane–urea membranes through incorporating a cadmium-based metal organic framework

The increasing need for more efficient separation processes has motivated the development of polymer membranes that can provide fast and selective transport. In this work, cadmium-based metal–organic framework (MOF) nanoparticles and a polyurethane–urea (PUU) elastomer were synthesized. New mixed-matrix membranes (MMMs) were then fabricated from the nanoparticles and the PUU. SEM images verified that embedding the nanoparticles changes the morphology of the PUU and the nanoparticles disperse well in the PUU due to satisfactory compatibility of the polymer and nanoparticles. Fourier transform infrared spectroscopy and X-ray diffraction analysis confirmed the dispersion of the nanoparticles in the soft segment of the PUU. With increased temperature, gas permeabilities of the MMMs improved but their sieving ability deteriorated. An MMM incorporating 2.5 wt % of the MOF showed a CO₂ permeability of ~140 barrer and a CO₂/N₂ selectivity of ~30, which are 89 and 38% higher than those of the pristine membrane. Gas permeation tests showed that the higher CO₂/N₂ selectivity of the MMMs was due to improved solubility selectivity and the higher CO₂ permeability was a result of improved CO₂ diffusivity and solubility coefficients. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 137, 48704.     

Optimization of Ozonation Process for Disinfection of Dental Unit Waterlines Using Response Surface Methodology

ABSTRACT

The reduction of microbial contamination in dental unit waterlines (DUWLs) appears to be necessary because of a potential risk of infections in immunocompromised patients and medical staff, which are regularly exposed to water and aerosols generated from DUWLs. In the present study, the qualitative and quantitative microbial contamination of water in DUWLs were determined and the conventional biomedical diagnostic tests were applied to identify microorganisms. A 3-level, 2-factor central composite design was utilized to investigate the effects of chief operating parameters and optimize ozone disinfection conditions. Also, the activity of three disinfectant (ozone, NaOCl, and peracetic acid) in microbial decontamination of DUWLs were compared. The results indicated that Microbacterium laevaniformans were the most prevalent genera (21%) among both Gram-negative and positive species in all samples. Regression analysis illustrated the good fit of the experimental data to the predicted model with R² and R²_adj correlation coefficients of 0.988 and 0.980, respectively. Moreover, under the optimal circumstances (Ozone concentration = 1.2 ppm and reaction time = 13.5 min) the disinfection efficiency was 97.52%. The results also revealed that ozone was effective disinfectant to reduce prevalent genera (with the removal of 93.75%, 92.57% and 96.15% of Pseudomonas aeruginosa, Microbacterium ?laevaniformans, and Alcaligenes faecalis, respectively) and already formed biofilms under optimum conditions. Based on achieved results, ozone was highly effective on microbial decontamination compared to peracetic acid and NaOCl disinfectant and can be used for disinfection of DUWLs.     

Bayes‐conditional Control Charts for Weibull Quantiles under Type II Censoring

In this paper, we develop a Bayesian approach for monitoring Weibull quantiles under Type II censoring when prior information is negligible relative to the data. The posterior median of quantiles is considered as the monitored statistic. A method based on the relationship between Bayesian and conditional limits under an appropriate prior distribution is proposed to obtain the posterior median of quantiles in closed form. A pivotal quantity based on the monitored statistic is proposed, and its distribution is conditionally derived. Then, the Bayes‐conditional control limits are proposed. For the proposed charts, the probability of out‐of‐control can be derived without use of simulation. The performance of the Bayes‐conditional charts is compared with the bootstrap charts through the simulation methods. The results show that to monitor the first quantiles, the lower‐sided Bayes‐conditional charts perform better than bootstrap charts in detecting a downward shift caused by decreasing in the shape parameter. Finally, an illustrative example is provided. Copyright © 2016 John Wiley & Sons, Ltd.     

Experimental investigations of the environmental effects on stability and integrity of composite sandwich T‐joints

The superior mechanical properties of sandwich composites made them to favored materials, in particular in the aviation industry. However, environmental influences along the manufacturing process and during usage can reduce the strength and the life expectation of the composite parts. This contribution presents an experimental investigation on the effect of accelerated ageing on the mechanical properties of perpendicular honeycomb sandwich connections. Static tensile tests have been carried out on sets of new and 25 days artificially aged specimens and the load carrying capacity of the T‐joints has been measured. In parallel to the experimental part, a three dimensional finite element analysis has been performed. This combined approach allows quantifying the reduction of the fracture toughness of the connections. The obtained results will help to fulfill design requirements and to predict the long‐term structural behavior of sandwich composite constructions.     

Optofluidic SERS: synergizing photonics and microfluidics for chemical and biological analysis

Surface enhanced Raman spectroscopy (SERS) leverages the specificity of Raman scattering and the sensitivity provided by localized plasmonic effects for applications in chemical and biomolecular detection. However, nearly four decades after the first report of SERS, practical uses of the technique remain limited. Optofluidic SERS??the synergistic use of microfluidics to improve the performance of SERS??may finally lead to practical devices for chemical and biomolecular detection. In this review, we describe recent advances in optofluidic SERS microsystems that have been developed to improve the performance and applicability of SERS. These techniques include designs that improve the light?Canalyte interaction, that perform active or passive concentration of metal nanoparticles and/or analyte molecules, and that utilize microfluidic techniques to improve functionality. In addition, we present optofluidic SERS techniques that enable new applications that have not been possible before the advent of optofluidics. Finally, we project future advances in optofluidic SERS and present a vision for the disruptive technologies that will enable the translation of SERS from the research lab to practical uses.     

Experimental measurement and correlation of solubility of β-carotene in pure and ethanol-modified subcritical water

For the first time, the solubility of β-carotene in pure and ethanol-modified subcritical water (SW) using the static method was determined. The experimental runs were performed at a temperature ranging from 298.15 to 403.15 K and 0-10% (w/w) of ethanol as a modifier at a constant pressure of 5 MPa. Samples were analyzed by UV-vis spectrophotometer. The solubility of β-carotene was found to range from 1.084×10^-8 to 227.1×10^-8 mol fractions in the subcritical water in above mentioned conditions. The obtained β-carotene solubility data were correlated using the linear model and modified Apelblat model. The obtained results showed the modified Apelblat model was better for estimating the solubility of β-carotene in SW. The values of the rootmean-square deviation (RMSD) between experimental and correlated data were calculated and used as the index of validity and accuracy for the model. Also, thermodynamic properties of the solution such as the Gibbs free energy of solution, enthalpy, and entropy of solution were estimated.     

Conditional Control Charts for Weibull Quantiles Under Type II Censoring

In this article, we propose control charts for the quantiles of the Weibull distribution, for type II censored data, based on the distribution of a pivotal quantity conditioned on ancillary statistics. These control charts must be considered as alternatives to bootstrap type control charts. We derive an analytical form of the conditional distribution function of the monitored statistic and we use this function to propose ARL‐unbiased control limits. We further demonstrate that the proposed conditional chart have a general analytical form for the ARL that can be evaluated numerically without use of simulations and we also show that these charts perform at least as well as the bootstrap type ones. We finally apply the conditional charts to a dataset on the strength of carbon fibers to detect shifts in a specified Weibull quantile. Copyright © 2014 John Wiley & Sons, Ltd.