Application of ionic liquids for the removal of heavy metals from wastewater and activated sludge

This paper presents the results of adsorption studies on the removal of heavy metals (Cr, Cu, Cd, Ni, Pb and Zn) from standard solutions, real wastewater samples and activated sewage sludge using a new technique of liquid-liquid extraction using quaternary ammonium and phosphonium ionic liquids (ILs). Batch sorption experiments were conducted using the ILs [PR4][TS], [PR4][MTBA], [A336][TS] and [A336][MTBA]. Removal of these heavy metals from standard solutions were not effective, however removal of heavy metals from the industrial effluents/wastewater treatment plants were satisfactory, indicating that the removal depends mainly on the composition of the wastewater and cannot be predicted with standard solutions. Removal of heavy metals from activated sludge proved to be more successful than conventional methods such as incineration, acid extraction, thermal treatment, etc. For the heavy metals Cu, Ni and Zn, ≥90% removal was achieved.     

Probleme bei Planung und Betrieb von Absetzbecken für Straßenabwässer

Sedimentation basins are incorporated into runoff infiltration systems and serve as a retention system, in which the sedimentation of particles occurs as a result of gravitational force. The effectiveness of sedimentation basins in terms of removing particles is highly dependent on design parameters such as their dimensions and drainage times. To evaluate the flow distribution within sedimentation basins, a conceptual model was developed using a tracer and compared to the actual condition at the treatment system. Here, a significant difference in the height of the connecting tube between settling basin and filter basin was found. This leads to a drying out of the basin, which significantly affects the flow rates and hence the sedimentation there. Based on a model experiment with colour tracer, the flow paths were visually represented in the basin, and both the concrete variant and the effects of internal structures were considered. It was found that the incorporation of a baffle led to an improved utilization of the basin, and to water being retained for longer times. Due to the lower flow rate and these longer times, fine and medium-sized sediments could be easily settled. In a field study, the performance of a sedimentation basin for the removal of particles was evaluated based on the influent and effluent concentrations of total suspended solids (TSS). The street runoff treatment plant was monitored for one year and results showed that there was no particle accumulation in the sedimentation basin (there was no permanent retention of the particle loads). The mean TSS concentrations were 89 mg/L at the inlet of the sedimentation basin and 94 mg/L at the end of the settling tank, respectively. The structural design and operation of the system showed higher flow and turbulent flow conditions in the sedimentation basin, in which settlement of fine and medium sized particles was very low; as a result, the soil filter basin was loaded with runoff particles. Thus the particulate matter had to be removed either on the surface of the filter basin or within the porous space of the filter. The build-up of such particles can result in a significant increase of head loss due to clogging; therefore, filters must be maintained by removing the accumulated particles on a regular basis.     

Untersuchung der Funktion von Leichtflüssigkeitsabscheidern bei Verwendung von Kraftstoffen mit unterschiedlichen FAME-Zusätzen

The use of biogenic additives in fuels is required by law for environmental reasons. This raises the question of whether the oil separator tested according to ÖNORM EN 858-1 complies with these new requirements. In this study, a commercial mineral oil separator was tested with different fuels with up to 100?% biodiesel (FAME) and its elimination performance was described in terms of the parameters KW, KW-Index DIN EN ISO 9377-2 H 53 (2000), and also the non-standardized parameters for mineral oil analysis in accordance with H 18 and H 53 without the purification stage. The results showed that all the tests with different fuel mixtures complied with the test value of 5 mg/l laid out in EN 858-1 (2005) and based on the parameter mineral oil analysis in accordance with DIN 38409-H 18 (1981). As the purification stage of this method removes the biofuel fraction, the question arises as to whether fuels with increased biogenic content can be analyzed satisfactorily using these standardized mineral oil parameters; and whether the use of pure mineral oil for ÖNORM EN 858-1 (2005) performance tests is still suitable, or whether other fuels should also be used as test media.     

Ensemble model for the degradation prediction of proton exchange membrane fuel cell stacks

Proton exchange membrane fuel cell (PEMFC) stacks are widely used in mobile and portable applications due to their clean and efficient model of operation. We propose an ensemble model based on a stacked long short-term memory model that combines three machine-learning models, including long short-term memory with attention mechanism, support vector regression, and random forest regression, to improve the degradation prediction of a PEMFC stack. The prediction intervals can be derived using the dropout technique. The proposed model is compared with some existing models using two PEMFC stacks. The results show that the proposed model outperforms the other models in terms of mean absolute percentage error and root mean square error. Regarding the remaining useful life prediction, the proposed model with the sliding window approach can provide better results.     

Synthesis and characterization of high strength polyimide/silicon nitride nanocomposites with enhanced thermal and hydrophobic properties

Polyimide (PI) composite films were synthesized incorporating amino modified silicon nitride (Si3N4) nanoparticles into PI matrix via in situ polymerization technique. The mechanical and thermal perfor-mances as well as the hydrophobic properties of the as prepared composite films were investigated with respect to the dosage of the filler in the PI matrix. According to Thermogravimetric (TGA) analysis, mean-ingful improvements were achieved in T5 (5％weight loss temperature) and T10 (10％weight loss temper-ature) up to 54.1 ℃ and 52.4 ℃, respectively when amino functionalized nano-Si3N4 particles were introduced into the PI matrix. The differential scanning calorimetry (DSC) results revealed that the glass transition temperature (Tg) of the composites was considerably enhanced up to 49.7 ℃ when amino func-tionalized Si3N4 nanoparticles were incorporated in the PI matrix. Compared to the neat PI, the PI/Si3N4 nanocomposites exhibited very high improvement in the tensile strength as well as Young's modulus up to 105.4％ and 138.3％, respectively. Compared to the neat PI, the composites demonstrated highly decreased water absorption behavior which showed about 68.1％ enhancement as the content of the nanoparticles was increased to 10 wt％. The SEM (Scanning electron microscope) images confirmed that the enhanced thermal, mechanical and water proof properties are essentially attributed to the improved compatibility of the filler with the matrix and hence, enhanced distribution inside the matrix because of the amino groups on the surface of Si3N4 nanoparticles obtained from surface functionalization.     

Environmental and economic prospects of biomaterials in the automotive industry

Clean Technologies and Environmental Policy - This study provides an overview of the application of biomaterials in automotive industries and their economic and environmental implications. It also...     

Highly efficient and durable phosphine reduced iron-doped tungsten oxide/reduced graphene oxide nanocomposites for the hydrogen evolution reaction

The design and development of inexpensive and highly efficient electrocatalysts for hydrogen production from water splitting are highly crucial for green energy and the hydrogen economy. Herein, we report phosphine reduced an iron-doped tungsten oxide nanoplate/reduced graphene oxide nanocomposite (Fe-WOxP/rGO) as an excellent electrocatalyst for the hydrogen evolution reaction. This electrocatalyst was synthesized using a hydrothermal method, followed by reduction with phosphine (PH₃), which was generated from sodium hypophosphite. The catalyst onset potential, Tafel slope, and stability were investigated. Accordingly, Fe-WOxP/rGO exhibited impressively high electrocatalytic activity with a low overpotential of 54.60 mV, which is required to achieve a current density of 10 mAcm^?2. The Tafel slope of 41.99 mV dec^?1and the linear sweep voltammetry curve is almost the same as 2000 cycles and electrolysis under static overpotential (54.60 mV) is remain for more than 24 h in 0.5 M H₂SO₄. The catalytic activity and conductivity of Fe-WOxP/rGO were higher than WO_XP, Fe-WOxP and WOxP/rGO. Such an outstanding performance of the Fe-WOxP/rGO nanocomposite is attributed to the coupled synergic effect between high oxygen vacancies formation on tungsten oxide in the nanoplate-like structure of Fe-WOxP and rGO nanosheet, making it as an excellent electrocatalyst for hydrogen evolution reaction.     

Hybrid approach for remaining useful life prediction of ball bearings

Remaining useful life (RUL) prediction plays an important role in predictive maintenance systems to support decision‐makers for arranging maintenance tasks and related resources. We propose a hybrid approach that is combined an exponential weighted moving average (EWMA) control chart for anomaly detection and machine learning models such as support vector regression (SVR) and random forest regression (RFR) with differential evolution (DE) algorithm to predict the RULs of ball bearings. Here, DE algorithm is used to find the optimal hyperparameters of SVR model. The datasets of ball bearings from the Prognostics Data Repository of NASA are used to compare the prediction performance of different methods. The degradation behavior of training data from the anomaly time to the end of life is used to transfer learning for the testing data in the SVR and RFR models. The results indicate that the proposed methods outperform the other four existing methods in terms of score. Therefore, the proposed hybrid approach is a reliable tool for the RUL prediction of ball bearings.     

Ethiopian sign language recognition using deep convolutional neural network

Multimedia Tools and Applications - In recent years, several technologies have been utilized to bridge the communication gap between persons who have hearing or speaking impairments and those who...     

Human motion quality and accuracy measuring method for human–robot physical interactions

Intelligent Service Robotics - In human–robot collaboration (HRC), human motion capture can be considered an enabler for switching autonomy between humans and robots to create efficient and...