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\"For reasons both financial and environmental, there is a perpetual need to optimize the design and operating conditions of industrial process systems in order to improve their performance, energy efficiency, profitability, safety and reliability. However, with most chemical engineering application problems having many variables with complex inter-relationships, meeting these optimization objectives can be challenging. This is where Multi-Objective Optimization (MOO) is useful to find the optimal trade-offs among two or more conflicting objectives.This book provides an overview of the recent developments and applications of MOO for modeling, design and operation of chemical, petrochemical, pharmaceutical, energy and related processes. It then covers important theoretical and computational developments as well as specific applications such as metabolic reaction networks, chromatographic systems, CO2 emissions targeting for petroleum refining units, ecodesign of chemical processes, ethanol purification and cumene process design.Multi-Objective Optimization in Chemical Engineering: Developments and Applications is an invaluable resource for researchers and graduate students in chemical engineering as well as industrial practitioners and engineers involved in process design, modeling and optimization\"--

The EURODELTA III exercise has facilitated a comprehensive intercomparison and evaluation of chemistry transport model performances. Participating models performed calculations for four 1-month periods in different seasons in the years 2006 to 2009, allowing the influence of different meteorological conditions on model performances to be evaluated. The exercise was performed with strict requirements for the input data, with few exceptions. As a consequence, most of differences in the outputs will be attributed to the differences in model formulations of chemical and physical processes. The models were evaluated mainly for background rural stations in Europe. The performance was assessed in terms of bias, root mean square error and correlation with respect to the concentrations of air pollutants (NO2, O3, SO2, PM10 and PM2.5), as well as key meteorological variables. Though most of meteorological parameters were prescribed, some variables like the planetary boundary layer (PBL) height and the vertical diffusion coefficient were derived in the model preprocessors and can partly explain the spread in model results. In general, the daytime PBL height is underestimated by all models. The largest variability of predicted PBL is observed over the ocean and seas. For ozone, this study shows the importance of proper boundary conditions for accurate model calculations and then on the regime of the gas and particle chemistry. The models show similar and quite good performance for nitrogen dioxide, whereas they struggle to accurately reproduce measured sulfur dioxide concentrations (for which the agreement with observations is the poorest). In general, the models provide a close-to-observations map of particulate matter (PM2.5 and PM10) concentrations over Europe rather with correlations in the range 0.4–0.7 and a systematic underestimation reaching −10 µg m−3 for PM10. The highest concentrations are much more underestimated, particularly in wintertime. Further evaluation of the mean diurnal cycles of PM reveals a general model tendency to overestimate the effect of the PBL height rise on PM levels in the morning, while the intensity of afternoon chemistry leads formation of secondary species to be underestimated. This results in larger modelled PM diurnal variations than the observations for all seasons. The models tend to be too sensitive to the daily variation of the PBL. All in all, in most cases model performances are more influenced by the model setup than the season. The good representation of temporal evolution of wind speed is the most responsible for models' skillfulness in reproducing the daily variability of pollutant concentrations (e.g. the development of peak episodes), while the reconstruction of the PBL diurnal cycle seems to play a larger role in driving the corresponding pollutant diurnal cycle and hence determines the presence of systematic positive and negative biases detectable on daily basis.

Increasingly, consumers want products containing little or no synthetic compounds. Avocado seeds, which are a residue of the food industry, could be used to obtain extracts with high antioxidant power. In the present study, the most popular radical scavenging methods are presented, establishing a comparison between them, besides working with two different extractions: pure methanol and ethanol–water (50:50 v/v). The radical scavenging assay methods ORAC and ABTS were performed, as well as a novel method: the reaction to methoxy radical, as determined by electron paramagnetic resonance (EPR). Peroxide value and thiobarbituric acid reactive compounds (TBARs) were used to monitor the oxidation of avocado seed oil, as well as the power of the avocado seed extract (ASE) to delay oil oxidation by oxidation induction time (OIT) and measured by differential scanning calorimetry (DSC). Radical scavenging methods have values between 1310–263 µmol TE/g of mass dissolved for ORAC and ABTS, respectively. The individual contribution of each of the compounds present in the extract was analyzed. The sum of all of them contributed up to 84% of the total radical scavenging activity. The concentration of 0.75% ASE causes a delay in the oxidation that is close to 80%, as measured by OIT. This implies that avocado seed residue may have a use as a natural antioxidant source, providing added value to organic waste.

Dynamics of epithelial tissues determine key processes in development, tissue healing and cancer invasion. These processes are critically influenced by cell–cell adhesion forces. However, the identity of the proteins that resist and transmit forces at cell–cell junctions remains unclear, and how these proteins control tissue dynamics is largely unknown. Here we provide a systematic study of the interplay between cell–cell adhesion proteins, intercellular forces and epithelial tissue dynamics. We show that collective cellular responses to selective perturbations of the intercellular adhesome conform to three mechanical phenotypes. These phenotypes are controlled by different molecular modules and characterized by distinct relationships between cellular kinematics and intercellular forces. We show that these forces and their rates can be predicted by the concentrations of cadherins and catenins. Unexpectedly, we identified different mechanical roles for P-cadherin and E-cadherin; whereas P-cadherin predicts levels of intercellular force, E-cadherin predicts the rate at which intercellular force builds up. Trepat and colleagues conduct a systematic analysis of how key cell–cell adhesion molecules affect intercellular forces and epithelial monolayer dynamics.

The innate ability of poly(N-isopropylacrylamide) (PNIPAAm) thermo-responsive hydrogel to copolymerize and to graft synthetic polymers and biomolecules, in conjunction with the highly controlled methods of radical polymerization which are now available, have expedited the widespread number of papers published in the last decade—especially in the biomedical field. Therefore, PNIPAAm-based hydrogels are extensively investigated for applications on the controlled delivery of active molecules, in self-healing materials, tissue engineering, regenerative medicine, or in the smart encapsulation of cells. The most promising polymers for biodegradability enhancement of PNIPAAm hydrogels are probably poly(ethylene glycol) (PEG) and/or poly(ε-caprolactone) (PCL), whereas the biocompatibility is mostly achieved with biopolymers. Ultimately, advances in three-dimensional bioprinting technology would contribute to the design of new devices and medical tools with thermal stimuli response needs, fabricated with PNIPAAm hydrogels.

Acrylate chemistry has found widespread use in dual-curing systems over the years. Acrylates are cheap, easily handled and versatile monomers that can undergo facile chain-wise or step-wise polymerization reactions that are mostly of the “click” nature. Their dual-curing processes yield two distinct and temporally stable sets of material properties at each curing stage, thereby allowing process flexibility. The review begins with an introduction to acrylate-based click chemistries behind dual-curing systems and relevant reaction mechanisms. It then provides an overview of reaction combinations that can be encountered in these systems. It finishes with a survey of recent and breakthrough research in acrylate dual-curing materials for shape memory polymers, optical materials, photolithography, protective coatings, structured surface topologies, and holographic materials.