Abstract: Excessive CO2 emissions in the atmosphere from anthropogenic activity can be divided into point sources and diffuse sources. The capture of CO2 from flue gases of large industrial installations and its conversion into fuels and chemicals with fast catalytic processes seems technically possible. Some emerging technologies are already being demonstrated on an industrial scale. Others are still being tested on a laboratory or pilot scale. These emerging chemical technologies can be implemented in a time window ranging from 5 to 20 years. The massive amounts of energy needed for capturing processes and the conversion of CO2 should come from low-carbon energy sources, such as tidal, geothermal, and nuclear energy, but also, mainly, from the sun. Synthetic methane gas that can be formed from CO2 and hydrogen gas is an attractive renewable energy carrier with an existing distribution system. Methanol offers advantages as a liquid fuel and is also a building block for the chemical industry. CO2 emissions from diffuse sources is a difficult problem to solve, particularly for CO2 emissions from road, water, and air transport, but steady progress in the development of technology for capturing CO2 from air is being made. It is impossible to ban carbon from the entire energy
supply of mankind with the current technological knowledge, but a transition to a mixed carbon–hydrogen economy can reduce net CO2 emissions and ultimately lead to a CO2-neutral world.

Abstract: Low-temperature plasmas are gaining a lot of interest for environmental and energy applications. A large research field in these applications is the conversion of CO2 into chemicals and fuels. Since CO2 is a very stable molecule, a key performance indicator for the research on plasma-based CO2 conversion is the energy efficiency. Until now, the energy efficiency in atmospheric plasma reactors is quite low, and therefore we employ here a novel type of plasma reactor, the gliding arc plasmatron (GAP). This paper provides a detailed experimental and computational study of the CO2 conversion, as well as the energy cost and efficiency in a GAP. A comparison with thermal conversion, other plasma types and other novel CO2 conversion technologies is made to find out whether this novel plasma reactor can provide a significant contribution to the much-needed efficient conversion of CO2. From these comparisons it becomes evident that our results are less than a factor of two away from being cost competitive and already outperform several other new technologies. Furthermore, we indicate how the performance of the GAP can still be improved by further exploiting its non-equilibrium character. Hence, it is clear that the GAP is very promising for CO2 conversion.

Abstract: Dry reforming of methane (DRM) in a gliding arc plasmatron is studied for different CH4 fractions in the mixture. The CO2 and CH4 conversions reach their highest values of approximately 18 and 10%, respectively, at 25% CH4 in the gas mixture, corresponding to an overall energy cost of 10 kJ L@1 (or 2.5 eV per molecule) and an energy efficiency of 66%. CO and H2 are the major products, with the formation of smaller fractions of C2Hx (x=2, 4, or 6) compounds and H2O. A chemical kinetics model is used to investigate the underlying chemical processes. The calculated CO2 and CH4 conversion and the energy efficiency are in good agreement with the experimental data. The model calculations reveal that the reaction of CO2 (mainly at vibrationally excited levels) with H radicals is mainly responsible for
the CO2 conversion, especially at higher CH4 fractions in the mixture, which explains why the CO2 conversion increases with increasing CH4 fraction. The main process responsible for CH4 conversion is the reaction with OH radicals. The excellent energy efficiency can be explained by the non-equilibrium character of the plasma, in which the electrons mainly activate the gas molecules, and by the important role of the vibrational kinetics of CO2. The results demonstrate that a gliding arc plasmatron is very promising for DRM.

Abstract: Titania/silica composites with different Ti/Si ratios are synthesized via a nonconventional synthesis route. The synthesis involves non-aqueous reaction of metal alkoxides and formic acid at 75 °C in supercritical carbon dioxide. The as-prepared composite materials contain nanometer-sized anatase crystallites and amorphous silica. Large specific surface areas are obtained. The composites are evaluated in the photocatalytic degradation of phenol in aqueous medium, and in the elimination of acetaldehyde from air. The highest photocatalytic activity in both processes is achieved with a composite containing 40 wt % TiO2.

Abstract: Natural deep eutectic solvents (NADES) are mixtures of naturally derived compounds with a significantly decreased melting point due to the specific interactions among the constituents. NADES have benign properties (low volatility, flammability, toxicity, cost) and tailorable physicochemical properties (by altering the type and molar ratio of constituents), hence they are often considered as a green alternative to common organic solvents. Modeling the relation between their composition and properties is crucial though, both for understanding and predicting their behavior. Several efforts were done to this end, yet this review aims at structuring the present knowledge as an outline for future research. First, we reviewed the key properties of NADES and relate them to their structure based on the available experimental data. Second, we reviewed available modeling methods applicable to NADES. At the molecular level, density functional theory and molecular dynamics allow interpreting density differences and vibrational spectra, and computation of interaction energies. Additionally, properties at the level of the bulk media can be explained and predicted by semi-empirical methods based on ab initio methods (COSMO-RS) and equation of state models (PC-SAFT). Finally, methods based on large datasets are discussed; models based on group contribution methods and machine learning. A combination of bulk media and dataset modeling allows qualitative prediction and interpretation of phase equilibria properties on the one hand, and quantitative prediction of melting point, density, viscosity, surface tension and refractive indices on the other hand. In our view, multiscale modeling, combining the molecular and macroscale methods, will strongly enhance the predictability of NADES properties and their interaction with solutes, yielding truly tailorable solvents to accommodate (bio)chemical reactions.

Abstract: Plasma‐based CO₂conversion has attracted increasing interest. However, to understand the impact of plasma operation on post‐plasma processes, we studied the effect of adding N₂, N₂/CH₄and N₂/CH₄/H₂O to a CO₂gliding arc plasmatron (GAP) to obtain valuable insights into their impact on exhaust stream composition and temperature, which will serve as feed gas and heat for post‐plasma catalysis (PPC). Adding N₂improves the CO₂conversion from 4 % to 13 %, and CH₄addition further promotes it to 44 %, and even to 61 % at lower gas flow rate (6 L/min), allowing a higher yield of CO and hydrogen for PPC. The addition of H₂O, however, reduces the CO₂conversion from 55 % to 22 %, but it also lowers the energy cost, from 5.8 to 3 kJ/L. Regarding the temperature at 4.9 cm post‐plasma, N₂addition increases the temperature, while the CO₂/CH₄ratio has no significant effect on temperature. We also calculated the temperature distribution with computational fluid dynamics simulations. The obtained temperature profiles (both experimental and calculated) show a decreasing trend with distance to the exhaust and provide insights in where to position a PPC bed.

Abstract: A Langmuir probe and an ICCD are employed to study the discharge mode transition in Ar inductively coupled plasma. Electron density and plasma emission intensity are measured during the E (capacitive discharge) to H (inductive discharge) mode transitions at different pressures. It is found that plasma exists with a low electron density and a weak emission intensity in the E mode, while it has a high electron density and a strong emission intensity in the H mode. Meanwhile, the plasma emission intensity spatial (2D image) profile is symmetrical in the H mode, but the 2D image is an asymmetric profile in the E mode. Moreover, the electron density and emission intensity jump up discontinuously at high pressure, but increase almost continuously at the E to H mode transition under low pressure.

Abstract: In the light of global warming, this paper develops a framework to compare energy and transportation technologies in terms of cost-efficient GHG emission reduction. We conduct a simultaneous assessment of economic and environmental performances through life cycle costing and life cycle assessment. To calculate the GHG mitigation cost, we create reference systems within the base scenario. Further, we extend the concept of the mitigation cost, allowing (i) comparision of technologies given a limited investment resource, and (ii) evaluation of the direct impact of policy measures by means of the subsidized mitigation cost. The framework is illustrated with a case of solar photovoltaics (PV), grid powered battery electric vehicles (BEVs), and solar powered BEVs for a Belgian small and medium sized enterprise. The study's conclusions are that the mitigation cost of solar PV is high, even though this is a mature technology. The emerging mass produced BEVs on the other hand are found to have a large potential for cost-efficient GHG mitigation as indicated by their low cost of mitigation. Finally, based on the subsidized mitigation cost, we conclude that the current financial stimuli for all three investigated technologies are excessive when compared to the CO2 market value under the EU Emission Trading Scheme.

Abstract: The global climate is changing, and farmers must increase their adaptive capacity to avoid negative impacts. This study aimed to examine the adaptive capacity of farmers’ household to tolerate climate changes and identify factors affecting the climate in Hamadan province, Iran. The adaptive capacity was evaluated quantitatively by using 23 indicators and was categorized into high, moderate, low, and very low adaptive capacity. The study was based on a cross sectional survey and was conducted with a random sample of 280 household farmers distributed in five counties of Hamadan province in the west of the country whose climatic data revealed signs of climate change. The result showed that farmers’ negative perception toward climate change generally increases during dry seasons and decreases when the precipitation and water resources are more available. Regarding the available information, only 15% of farmers had a high level of adaptive capacity, while 10% of them were highly adapted, and 27.5% showed a very low level of adaptive capacity. Adaptive capacity in the current study was influenced by some socio-economic variables including total farm size, irrigated farm size, number of agricultural land plots, and perception and knowledge of climate change.

Abstract: The Ricardian model is a widely used approach based on cross-sectional regression analysis to estimate climate change impacts on agricultural productivity. Up until now, researchers have focused on the impacts of gradual changes in temperature and precipitation, even though climate change is known to encompass also changes in the severity and frequency of extreme weather events. This research investigates the impact of heatwaves on European agriculture, additional to the impact of average climate change. Using a dataset of more than 60,000 European farms, the study examines whether adding a measure for heatwaves to the Ricardian model influences its results. We find that heatwaves have a minor impact on agricultural productivity and that this impact is moderated by average temperature. In colder regions, farm productivity increases with the number of heatwave days. For warmer regions, land values decrease with heatwave frequency. Despite the moderating effect, the marginal effect of heatwave frequency, i.e. the percentage change in agricultural land values caused by one more heatwave day per year, is small in comparison to the effect of average temperature increases. Non-marginal effects are found to be relevant, but only in the case of increased heatwave frequency. According to our results, farms are not expected to suffer more from extreme weather than from mean climate change, as was claimed by several previous studies.

Abstract: The development of coatings with tunable performances is critical to meet a wide range of technological applications each one with different requirements. Using the plasma-enhanced chemical vapor deposition (PECVD) process, scientists can create hydrogenated amorphous carbon coatings doped with metal (a-C:H:Me) with a broad range of mechanical properties, varying from those resembling polymers to ones resembling diamond. These diverse properties, without clear relations between the different families, make the material selection and optimization difficult but also very rich. An innovative approach is proposed here based on projected performance indices related to fracture energy, strength, and stiffness in order to classify and optimize a-C:H:Me coatings. Four different a-C:H:Cr coatings deposited by PECVD with Ar/C2H2 discharge under different bias voltage and pressures are investigated. A path is found to produce coatings with a selective critical energy release rate between 5–125 J/m2 without compromising yield strength (1.6–2.7 GPa) and elastic limit (≈0.05). Finally, fine-tuned coatings are categorized to meet desired applications under different testing conditions.

Abstract: It is a generally accepted idea that the particle size distribution strongly affects the optical spectra of colloidal plasmonic nanoparticles. It is often quoted as one of the main reasons while explaining the mismatch between the theoretical and experimental optical spectra of such nanoparticles. In this work, these aspects are critically analyzed by means of a bottom up statistical approach that considers variables such as mean, standard deviation and skewness of the nanoparticle size distribution independently from one another. By assuming normal and log-normal distributions of the particle size, the effect of the statistical parameters on the Mie analytical optical spectra of colloidal nanoparticles was studied. The effect of morphology was also studied numerically in order to understand to what extent it can play a role. It is our finding that the particle polydispersity, skewness and surface morphology in fact only weakly impact the optical spectra. While, the selection of suitable optical constants with regard to the crystallinity of the nanoparticles is a far more influential factor for correctly predicting both the plasmon band position and the plasmon bandwidth in theoretical simulations of the optical spectra. It is shown that the mean particle size can be correctly estimated directly from the plasmon band position, as it is the mean that determines the resonance wavelength. The standard deviation can on the other hand be estimated from the intensity distribution data obtained from dynamic light scattering experiments. The results reported herein clear the ambiguity around particle size distribution and optical response of colloidal plasmonic nanoparticles.

Abstract: Superparamagnetic iron oxide magnetic nanoparticles (MNPs) are successfully used as contrast agents in magnetic-resonance imaging. They can be easily functionalized for drug delivery functions, demonstrating great potential for both imaging and therapeutic applications. Here we developed new pH-responsive theranostic core-shell-corona nanoparticles consisting of superparamagentic Fe3O4 core that displays high T2 relaxivity, bovine serum albumin (BSA) shell that binds anticancer drug, doxorubicin (Dox) and poly(ethylene glycol) (PEG) corona that increases stability and biocompatibility. The nanoparticles were produced by adsorption of the BSA shell onto the Fe3O4 core followed by crosslinking of the protein layer and subsequent grafting of the PEG corona using monoamino-terminated PEG via carbodiimide chemistry. The hydrodynamic diameter, zeta-potential, composition and T2 relaxivity of the resulting nanoparticles were characterized using transmission electron microscopy, dynamic light scattering, thermogravimetric analysis and T2-relaxometry. Nanoparticles were shown to absorb Dox molecules, possibly through a combination of electrostatic and hydrophobic interactions. The loading capacity (LC) of the nanoparticles was 8 wt.%. The Dox loaded nanoparticles release the drug at a higher rate at pH 5.5 compared to pH 7.4 and display similar cytotoxicity against C6 and HEK293 cells as the free Dox. (C) 2015 Elsevier B.V. All rights reserved.

Abstract: The split-operator technique for wave packet propagation in quantum systems is expanded here to the case of propagatingwave functions describing Schrodinger particles, namely, charge carriers in semiconductor nanostructures within the effective mass approximation, in the presence of Zeeman effect, as well as of Rashba and Dresselhaus spin-orbit interactions. We also demonstrate that simple modifications to the expanded technique allow us to calculate the time evolution of wave packets describing Dirac particles, which are relevant for the study of transport properties in graphene.

Abstract: We use the Galerkin approach and the finite-element method to numerically solve the effective-mass Schrodinger equation. The accuracy of the solution is explored as it varies with the range of the numerical domain. The model potentials are those of interdiffused semiconductor quantum wells and axially symmetric quantum wires. Also, the model of a linear harmonic oscillator is considered for comparison reasons. It is demonstrated that the absolute error of the electron ground state energy level exhibits a minimum at a certain domain range, which is thus considered to be optimal. This range is found to depend on the number of mesh nodes N approximately as alpha(0) log(e)(alpha 1) (alpha N-2), where the values of the constants alpha(0), alpha(1), and alpha(2) are determined by fitting the numerical data. And the optimal range is found to be a weak function of the diffusion length. Moreover, it was demonstrated that a domain range adaptation to the optimal value leads to substantial improvement of accuracy of the solution of the Schrodinger equation.