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Novel N-methyl-4-piperidinol (MPDL)-based solvents have been considered as high potential solvents for post combustion carbon capture, especially for power generation industry. To comprehensively investigate the CO2 absorption-regeneration performance of MPDL-based solvents, transport properties (i.e., density, viscosity, and physical CO2 diffusivity) are required. These data are reported in the literature and can be estimated by conventional predictive correlations. However, the conventional correlation is applicable for an individual solvent at various blended ratios and temperatures. Thus, artificial neural network (ANN) was then applied for prediction of the transport properties of MPDL-based solvents, including aqueous solutions of MPDL, MPDL-monoethanolamine (MEA), MPDL-2-amino-2-methyl-1-propanol (AMP), and MPDL-piperazine (PZ). Three learning algorithms of (i) Levenberg–Marquardt (LM), (ii) Bayesian Regularization (BR), and (iii) Scaled Conjugate Gradient (SCG) were applied to develop the predictive ANN models with various hidden neurons. As a result, 6 hidden neurons BR-ANN model was the most convincible single prediction platform for the three transport properties. The develop model can be very beneficial for further applications associated with the novel MPDL-based solvents.

In this work, maize residue pellets were torrefied in a macro thermogravimetric analyzer with simulated dry flue gas from mixing of CO2 and N2. The effects of temperature (220–300 °C), residence time (10–40 min), and the presence of CO2 (0–18% v/v) in the reacting gas were investigated on products’ yields, distribution, and torrefied pellet properties such as higher heating value (HHV), elemental composition (C, H, O, N, S, K, and Cl), grindability, and moisture uptake ability. Temperature and residence time were found to affect the distribution of products’ yield and the properties of torrefied pellets considerably. In comparison with the untreated biomass pellets, the torrefied pellets appeared to have improved HHV and grindability but reduced moisture uptake ability. In the presence of CO2, the Boudouard reaction caused slight reductions in the C content and HHV of the torrefied pellets. Changes in torrefaction conditions did not prove to have a statistically significant effect on S, K, and Cl contents of the torrefied biomass materials.

A giant sensitive plant (Mimosa pigra L.) or Mimosa is a fast growing woody weed that poses a major environmental problem in agricultural and wet land areas. It may have potential to be used as a renewable energy source. In this work, thermal behaviour of dried Mimosa was investigated under inert atmosphere in a thermogravimetric analyzer at the heating rates of 10, 30, and 50 degrees C/min from room temperature to 1000 degrees C. Pyrolysis kinetic parameters in terms of apparent activation energy and pre-exponential factor were determined. Two stages of major mass loss occurred during the thermal decomposition process, corresponding to degradation of cellulose and hemicellulose between 200-375 degrees C and decomposition of lignin around 375-700 degrees C. The weed mainly devolatilized around 200-400 degrees C, with total volatile yield of about 60%. The char in final residue was about 20%. Mass loss and mass loss rates were strongly affected by heating rate. It was found that an increase in heating rate resulted in a shift of thermograms to higher temperatures. As the heating rates increased, average devolatilization rates were observed to increase while the activation energy decreased.

AbstractA two-stage thermophilic fermentation for hydrogen and methane production from wastewater of cassava rice and corn starch at different concentration (5,10 and 15g/L) was studied. The hydrogen production from cassava starch at concentrations of 5g/L gave the highest hydrogen yield and followed by cassava starch at a concentration 10g/L, rice starch at concentrations of 15g/L. The hydrogen and methane yields from cassava starch processing wastewater by two-stage was 81.5 L H2 kgCOD-1 and 310.5 L CH4 kgCOD-1, respectively with total energy yield of 13363kJ kgCOD-1. Mixed hydrogen and methane (biohythane) production was 9.51 L biogas l-1 with containing of 55% CH4, 11% H2 and 34% CO2.

Abstract Gasification has been increasingly seen as a method to convert solid fuel into combustible syngas. However, these applications require syngas with strict requirements and raw syngas often does not meet these requirements. Therefore, a form of syngas upgrading needs to be applied. One of the most common form of syngas upgrading is removal of CO2, which is often present in large concentrations in raw syngas. The currently existing CO2 removal technologies were either designed not with syngas in mind or for large scale industries, which makes them somewhat inefficient for application with gasification syngas. This calls for more research into efficient removal of CO2, from syngas. In this review, the application of deep eutectic solvent (DES) as one of the potential new absorbent for CO2 removal from gas streams and more specifically from syngas are discussed. DES has garnered attention due to its high CO2 absorption performance, process friendliness, and environmental friendliness. At present, most studies on DES are still limited to basic absorption behavior of the absorbent. This review aims to provide not just a clear picture of the current research situation for DES as CO2 removal absorbent, but also detail the possible research directions that might be taken for the development of DES as CO2 absorbent from syngas. To that end, this paper shall discuss the specific situation of gasification development, syngas utilization, and the current DES research situation including: its advantages compared to conventional absorbents, its current research situation, challenges, and possible future research directions.

To mitigate climate change, individual greenhouse gas emissions need to decline substantially. This paper empirically explores the relationship between individual carbon footprints and carbon literacy as well as socio-economic and attitudinal factors. To operationalize carbon literacy, we distinguish between carbon knowledge and carbon engagement. Our econometric analysis uses widely representative survey data for 1000 individuals in Germany and distinguishes between components of an aggregate carbon footprint and of carbon footprints related with electricity consumption, heating, motorized individual transport, aviation, and dietary choices. We find a negative and sizeable correlation between carbon engagement and the aggregate footprint, as well as the footprints related to electricity consumption and diet. For example, a one-unit increase in our index reflecting carbon engagement corresponds to a decrease in the aggregate carbon footprint of about 4%. Furthermore, for carbon knowledge we find a negative correlation with the carbon footprint from diet. We also find significant correlations between the carbon footprints and gender, age, income, education, environmental preferences, and policy orientation, which generally exhibit the intuitively expected signs, but differ somewhat across activities. Overall, our findings support the notion that fostering carbon engagement represents a more effective strategy for reducing individuals' carbon footprints than enhancing carbon knowledge.

C57BL/6J (C57) and DBA/2J (DBA) mice respond differently to drugs that affect dopamine systems, including alcohol. The current study compared effects of D1 and D2 receptor agonists and antagonists, and the interaction between D1/D2 antagonists and alcohol, on intracranial self-stimulation in male C57 and DBA mice to determine the role of dopamine receptors in the effects of alcohol on brain stimulation reward (BSR). In the initial strain comparison, dose effects on BSR thresholds and maximum operant response rates were determined for the D1 receptor agonist SKF-82958 (±-6-chloro-7,8-dihydroxy-3-allyl-1-phenyl-2,3,4,5-tetrahydro-1H-3-benzazepine; 0.1–0.56 mg/kg) and antagonist SCH 23390 (+-7-chloro-8-hydroxy-3-methyl-1-phenyl-2,3,4,5-tetrahydro-1H-3-benzazepinehydrochloride; 0.003–0.056 mg/kg), and the D2 receptor agonist quinpirole (0.1–3.0 mg/kg) and antagonist raclopride (0.01–0.56 mg/kg). For the alcohol interaction, SCH 23390 (0.003 mg/kg) or raclopride (0.03 mg/kg) was given before alcohol (0.6–2.4 g/kg p.o.). D1 antagonism dose-dependently elevated and SKF-82958 dose-dependently lowered BSR threshold in both strains; DBA mice were more sensitive to SKF-82958 effects. D2 antagonism dose-dependently elevated BSR threshold only in C57 mice. Low doses of quinpirole elevated BSR threshold equally in both strains, whereas higher doses of quinpirole lowered BSR threshold only in C57 mice. SCH 23390, but not raclopride, prevented lowering of BSR threshold by alcohol in DBA mice. Conversely, raclopride, but not SCH 23390, prevented alcohol potentiation of BSR in C57 mice. These results extend C57 and DBA strain differences to D1/D2 sensitivity of BSR, and suggest differential involvement of D1 and D2 receptors in the acute rewarding effects of alcohol in these two mouse strains.