Cleaner Chemical Engineering最新文献

This work investigates the combustion analysis of coal, petroleum coke and their blends. Coal and petroleum coke were characterized by proximate analysis, ultimate analysis, gross calorific value determination and ash analysis. Combustion performance of parent fuels and their blends were evaluated by thermogravimetric analysis followed by the analysis of different characteristics parameters, namely ignition temperature, peak temperature, burnout temperature and combustion efficiency. Results signify that petroleum coke has poor combustion characteristics compared to coal. After the rise in petroleum coke from 10 to 50 mass %, ignition temperature reduced from 413 to 385 °C, while insignificant variations occurred in peak temperature and burnout temperature. Such observations show natural reduction in ignition characteristics without significant modification in coal's burning profile. Combustion efficiency at 450 °C reduced from 46.18% to 34.77% as petroleum coke increased from 10 to 50 mass %, signifying decline in the combustion properties of coal. Kinetic analysis shows that petroleum coke has the maximum activation energy (182.11 kJ/mol) than coal (84.84 kJ/mol). Analysis of changes in enthalpy, Gibbs free energy and entropy inferred that individual combustion of both coal and petroleum coke is difficult, while blends have improved combustion characteristics than petroleum coke.

If our expectations are to have a future with the resources provided by the earth, the recycling of plastics has become one of the most important topics that, as humans, we must deal with. Among the technologies developed for treating this issue is the hydrothermal liquefaction (HTL) method. In this review, subcritical and supercritical hydrothermal processes are presented. Experimental methods and product yields are disclosed and discussed. Subcritical conditions have previously been used to depolymerize synthetic polymers containing heteroatoms, such as bisphenol-A-based epoxy resin (Epoxy), polyamide 6 (PA6), polyamide 6/6 (PA66), polyethylene terephthalate (PET), polycarbonate (PC), and polyurethane (PU). This type of polymer can be broken down using this low-temperature, low-pressure method because it has heteroatoms that are easy to break down. To depolymerize polyolefins like polyethylene (PE) and polypropylene (PP), derivatives and mixtures, formed by long hydrocarbon chains, supercritical water conditions (> 374 °C; > 23 MPa) seem to be required.  These requirements make the procedure quite expensive. The review showed that a new method that uses pressures between 2.5 and 30 MPa, temperatures above 400 °C, and residence times of 20 to 60 min, named low-pressure hydrothermal liquefaction (LP-HTL), can be used to handle this type of polyolefin hydrocarbon. This review describes the conditions needed to handle this problematic type of feedstock and, in a certain way, the possible utilization of such technology for treating more complex waste mixtures.

Previous investigations reported evaluation of biological, therapeutic and pharmacological activities of phenolic bioactive extract from Huntaria Umbellate Seed (HUS). However, process modelling and optimization, upscaling as well as techno-economic evaluation of Microwave-Assisted Extraction (MAE) of HUS are seldom documented in the literature. Therefore, this study presents black-box modelling, optimization and techno-economics of MAE of HUS. Box-Behken Design (BBD) of Response Surface Methodology (RSM) was applied for modelling and optimizing experimental MAE factors: microwave power (520 – 1040 W), extraction time (2- 10 min), solid-liquid ratio (0.4 – 1 g/100 ml); and the responses: Total Phenolic Content (TPC) and Process Yield (PY). Adaptive Neuro-Fuzzy Inference System (ANFIS) codes were programmed in Matlab 2019 for the phenolic extract recovery prediction. Process scale-up simulation and techno-economics were performed in ASPEN Batch Process Developer (ABPD) software. Coefficients of determination (R²) of 0.9349 (BBD-RSM), 0.9959 (ANFIS) and 0.9772 (BBD-RSM), 0.9971 (ANFIS) were obtained for TPC and yield respectively. The optimal yield (24.2625%) and TPC (7.89125 mg GAE/gdw) were obtained at extraction time (2 min) with microwave power (780 W) and solid-liquid ratio (0.4 g/ml). HUS extract HPLC result contains bentulinic acid, chlorogenic acid, caffeic acid, elliagic acid, rutin and Qucertin. Techno-economic results gave batch size, batch time, production rate, total capital investment, annual production cost and payback time of 5 kg, 137 mins, 0.0364 kg/min, USD80398, USD456000 and 2.29 years respectively. Therefore, preliminary bioactive extract production from HUS is techno-economically feasible.

Simulations of a fluidised bed reactor for gasification of municipal solid refuse-derived fuel were performed using OpenFOAM software. Firstly, evaluation was made of a simplified gas-solid two-phase model, considering sand and air as the components, according to a transient Eulerian-Eulerian approach. A scale-up study was also performed to obtain thermal-fluid dynamic parameters. Then, a real dimensions non-reacting model was developed, based on the experimental information from a semi-industrial gasification plant with capacity for processing 7.1 t day⁻¹ of municipal refuse-derived fuel, producing 16.9 t day⁻¹ of syngas. The fluidising regime was mapped for different inlet conditions, at 1,123 K, with air velocities ranging from 0.01 to 1.25 m s⁻¹, and the continuous operation of the reactor was analysed, where in the solid particles packing remained at approximately 88% from maximum, with bed height of 2.05 m. The results were in good agreement with data available in the scientific literature, and the computational model was able to provide consistent results when compared to the experimental information for the semi-industrial reactor. The authors’ major remark was the hability of this computational model in obtaining consistent results from simulations of the semi-industrial scale reactor, with good prediction of the internal fluid dynamics characteristics.

In this research, we have developed an energy-efficient modified version of the traditional Tchar stove for household use. The gasifier and charcoal stoves of a traditional Tchar have been incorporated into a single structure by movable fuel bed and pot support for the ease of operation .Traditional Tchar stove utilizes unidirectional preheated secondary air stream, which is unable to reach the flame core efficiently, and results in poor combustion. The modified Tchar stove under this study was designed with the provision of two preheated secondary air streams from opposite direction for crossflow mixing of secondary air and gaseous fuel for improved combustion. The characteristics parameters of the modified Tchar stove were measured following the standard water boiling test (WBT) method to compare with previously reported models. The high power (cold start), and simmering phases were used in WBT for the evaluation of the thermal performance of the modified Tchar stove. The thermal efficiency of the Tchar stove was 39.64±2.29% for the cold start high power phase and 51±3.12% for the low power simmering phase, respectively. In the cold start high power phase, the specific energy consumption values ranged from 1465.99 to 1855.9 kJ/liter. The thermal efficiency of the modified Tchar stove increased with decreasing firepower (kW). The designed stove allows enhanced heat transfer both at low and high fire power with its moveable structure. Moreover, it gives better combustion due to the cross-flow air mixing, which makes it a better alternative compared to the traditional Tchar stove.

Palm kernel oil (PKO) is one of the promising starting materials for biodiesel production. Economic viability of large-scale biodiesel production from PKO happens to be the major challenge, as investors would like to know the overall cost-benefit value before making decisions. Therefore, this study develops artificial intelligence (AI) techno-economic models for predicting overall cost-benefit value which will provide fundamental investment decisions for potential investors. The two AI techniques used in this study were artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS). The input-output data for modelling was gotten from a previous work which based solely on experimental design for PKO for biodiesel production. The input variables are Methanol:oil ratio, temperature, catalyst quantity, residence time and catalyst calcination temperature, while return on investment (ROI), payback time (PBT), net present value (NPV) and production capacity (PC) are the responses. ANN and Fuzzy Logic Toolboxes in MATLAB R2013a were used for model implementation. The developed models were appraised using statistical indices such as coefficient of determination (R²) and root mean square error (RMSE). The results showed that, trimf based ANFIS models (ROI- R²: 0.9999; RMSE: 7.39 × 10⁻⁷; PBT- R²: 0.9999; RMSE: 5.32 × 10⁻⁷; NPV- R²: 0.9999; RMSE: 5.89 × 10⁻⁷; PC- R²: 0.9999; RMSE: 5.89 × 10⁻⁷) performed marginally better than ANN models (ROI- R²: 0.9496; RMSE: 0.0599; PBT- R²: 0.9945; RMSE: 0.0373; NPV- R²: 0.9957; RMSE: 0.0384; PC- R²: 0.9959; RMSE: 0.0376). Also, the relative significance of input parameters based on sensitivity analysis showed catalyst calcination temperature (C_T) as the most significant input parameter. These findings show that both the ANFIS and ANN models are effective in predicting techno-economic parameters.

Globally, iron and steel production is responsible for approximately 6.3% of global man-made carbon dioxide emissions, because coal is used as both the combustion fuel and chemical reductant. Hydrogen reduction of iron ore offers a potential alternative ‘near-zero-CO₂’ route, if renewable electrical power is used for both hydrogen electrolysis and reactor heating. This paper discusses key technoeconomic considerations for establishing a hydrogen direct reduced iron (H₂-DRI) plant in New Zealand. The location and availability of firm renewable electricity generation is described, the experimental feasibility of reducing locally-sourced titanomagnetite ironsand in hydrogen is shown, and a high-level process flow diagram for a counter-flow electrically heated H₂-DRI process is developed. The minimum hydrogen composition of the reactor off-gas is 46%, necessitating the inclusion of a hydrogen recycle loop to maximise chemical utilisation of hydrogen and minimize costs. A total electrical energy requirement of 3.24 MWh per tonne of H₂-DRI is obtained for the base-case process considered here. Overall, a maximum input electricity cost of no more than US$80 per MWh at the plant is required to be cost-competitive with existing carbothermic DRI processes. Production cost savings could be achieved through realistic future improvements in electrolyser efficiency (∼ US$5 per tonne of H₂-DRI) and heat exchanger (∼US$3 per tonne). We conclude that commercial H₂-DRI production in New Zealand is entirely feasible, but will ultimately depend upon the price paid for firm electrical power at the plant.

Traditional materials have a lower commercial impact than thermoelectric (TE) nanostructure materials. These materials have advanced to the point that a thermoelectric generator (TEG) may be built using them. Bi₂Te_3-xSe_x (0.10 ≤ X ≤ 1.80) nanostructure materials would overcome the constraint of Bi₂Te₃ for TEG manufacturing in advanced TE technology. Bi₂Te_3-xSe_x (0.10 ≤ X ≤ 1.80) nanostructure materials have recently been recognized as promising TE materials from the research arena for successful use in TEG manufacture. It is already at the commercialization stage and has certain advantages over Bi₂Te₃. This material's study and development will almost certainly be difficult. The review lays forth a literature strategy for overcoming the constraints of the Bi₂Te₃ nanostructure material and finding the best composition for TE applications. Furthermore, the performance of existing Bi₂Te_3-xSe_x (0.10 ≤ X ≤ 1.80) nanostructured materials is discussed.

Pyrenes are polycyclic aromatic hydrocarbons responsible for an array of health hazards and environmental abuses. The remediation of such compounds is remaining as an area of interest for scientist community. The present study aimed for isolation and screening of pyrene degrading bacterial strains optimized at various environmental and nutritional requirement to assess their potential for pyrene degradability. The result have revealed that isolated strain GWP-2 and LOP-9 showed degradation of pyrene 86% and 82.1%, respectively at temperature 37 °C and pH 9 in presence of glucose(1%) and peptone(0.5%) within 15 days of incubated at 140 rpm in temperature controlled shaker. The variation of temperature and pH from optimized condition decrease the performance of isolated strains. The metabolite characterization through GCMS showed strain GWP-2 9,12-octadecadienoic acid, Oxido-4,17-cholestadian-3a,16a-diol, Heptadecane,2,6,10,15-tetramethyl, Heptacosane, 1,2-benzenedicarboxylic acid and Octadecane 3-ethyl-5-(2-ethylbutyl) as major product while LOP-9 showed their major product as Disiloxane,hexamethyl-(CAS), Benzene -1,2,4-triol(trimethylsilyl) ester, Octahydroquinoline-6-carboxylic acid(phenylethyl amide) and 4-methyl1,4‑hydroxy-6-(2,5,6,6′-tetramethylcyclohex-1-en-1-yl)hex-2-ynyl acetate after 15 days degradation. Many compounds detected in control were completely removed. The isolated strains were identified as Mycobacterium vaanbaalenii GWP-2 (ON715011) and Staphylococcus aureus LOP-9(ON715121) based their 16s-rRNA sequencing. These potential strains may be useful for detoxification of pyrene containing pollution in soil and water ecosystem.