Biological treatment and nanofiltration of denim textile wastewater for reuse

This study aims at coupling of activated sludge treatment with nanofiltration to improve denim textile wastewater quality to reuse criteria. In the activated sludge reactor, the COD removal efficiency was quite high as it was 91+/-2% and 84+/-4% on the basis of total and soluble feed COD, respectively. The color removal efficiency was 75+/-10%, and around 50-70% of removed color was adsorbed on biomass or precipitated within the reactor. The high conductivity of the wastewater, as high as 8 mS/cm, did not adversely affect system performance. Although biological treatment is quite efficient, the wastewater does not meet the reuse criteria. Hence, further treatment to improve treated water quality was investigated using nanofiltration. Dead-end microfiltration (MF) with 5 microm pore size was applied to remove coarse particles before nanofiltration. The color rejection of nanofiltration was almost complete and permeate color was always lower than 10 Pt-Co. Similarly, quite high rejections were observed for COD (80-100%). Permeate conductivity was between 1.98 and 2.67 mS/cm (65% conductivity rejection). Wastewater fluxes were between 31 and 37 L/m2/h at 5.07 bars corresponding to around 45% flux declines compared to clean water fluxes. In conclusion, for denim textile wastewaters nanofiltration after biological treatment can be applied to meet reuse criteria.     

Determinants of college students' use of online collaborative help‐seeking tools

Research has noted the effectiveness of online tools (e.g., discussion boards) for supporting help seeking among class members. However, help seeking is not necessarily warranted via online learning tools because some factors (e.g., low Internet self‐efficacy) may influence students' intention to use them. This study aims to identify the determinants of students' use of a web‐based help‐seeking tool called EchoLu. For this purpose, a structural model was developed based on technology acceptance model and tested using a structural equation modelling approach. According to the data analysis results, general Internet self‐efficacy, information‐search self‐efficacy, web‐based learning self‐efficacy, and EchoLu‐specific self‐efficacy play a significant role in students' intentions to use online help‐seeking tools. Contrary to the previous research, no statistically significant relationship was found between general Internet self‐efficacy and EchoLu‐specific self‐efficacy, and between web‐based learning self‐efficacy and perceived usefulness. Implications of the findings for guiding practitioners in supporting effective help‐seeking are presented. Limitations of the study and future research prospects are discussed as well.     

Feedback Linearization Control for Systems with Mismatched Uncertainties via Disturbance Observers

This paper focuses on a novel feedback linearization control (FLC) law based on a self‐learning disturbance observer (SLDO) to counteract mismatched uncertainties. The FLC based on BNDO (FLC‐BNDO) demonstrates robust control performance only against mismatched time‐invariant uncertainties while the FLC based on SLDO (FLC‐SLDO) demonstrates robust control performance against mismatched time‐invariant and ‐varying uncertainties, and both of them maintain the nominal control performance in the absence of mismatched uncertainties. In the estimation scheme for the SLDO, the BNDO is used to provide a conventional estimation law, which is used as the learning error for the type‐2 neuro‐fuzzy system (T2NFS), and T2NFS learns mismatched uncertainties. Thus, the T2NFS takes the overall control of the estimation signal entirely in a very short time and gives unbiased estimation results for the disturbance. A novel learning algorithm established on sliding mode control theory is derived for an interval type‐2 fuzzy logic system. The stability of the overall system is proven for a second‐order nonlinear system with mismatched uncertainties. The simulation results show that the FLC‐SLDO demonstrates better control performance than the traditional FLC, FLC with an integral action (FLC‐I), and FLC‐BNDO.     

An artificial immune system approach to CNC tool path generation

Reduced machining time and increased accuracy for a sculptured surface are both very important when producing complicated parts, so, the step-size and tool-path interval are essential components in high-speed and high-resolution machining. If they are too small, the machining time will increase, whereas if they are too large, rough surfaces will result. In particular, the machining time, which is a key factor in high-speed machining, is affected by the tool-path interval more than the step size. The present paper introduces a ‘system software’ developed to reduce machining time and increased accuracy for a sculptured surface with Non-Uniform Rational B-Spline (NURBS) patches. The system is mainly based on a new and a powerful artificial intelligence (AI) tool, called artificial immune systems (AIS). It is implemented using C programming language on a PC. It can be used as stand alone system or as the integrated module of a CNC machine tool. With the use of AIS, the impact and power of AI techniques have been reflected on the performance of the tool path optimization system. The methodology of the developed tool path optimization system is illustrated with practical examples in this paper.     

B-Spline Curve Approximation by Utilizing Big Bang-Big Crunch Method

The location of knot points and estimation of the number of knots are undoubtedly known as one of the most difficult problems in B-Spline curve approximation. In the literature, different researchers have been seen to use more than one optimization algorithm in order to solve this problem. In this paper, Big Bang-Big Crunch method (BB-BC) which is one of the evolutionary based optimization algorithms was introduced and then the approximation of B-Spline curve knots was conducted by this method. The technique of reverse engineering was implemented for the curve knot approximation. The detection of knot locations and the number of knots were randomly selected in the curve approximation which was performed by using BB-BC method. The experimental results were carried out by utilizing seven different test functions for the curve approximation. The performance of BB-BC algorithm was examined on these functions and their results were compared with the earlier studies performed by the researchers. In comparison with the other studies, it was observed that though the number of the knot in BB-BC algorithm was high, this algorithm approximated the B-Spline curves at the rate of minor error.     

Defect and Contact Passivation for Perovskite Solar Cells

Metal‐halide perovskites are rapidly emerging as an important class of photovoltaic absorbers that may enable high‐performance solar cells at affordable cost. Thanks to the appealing optoelectronic properties of these materials, tremendous progress has been reported in the last few years in terms of power conversion efficiencies (PCE) of perovskite solar cells (PSCs), now with record values in excess of 24%. Nevertheless, the crystalline lattice of perovskites often includes defects, such as interstitials, vacancies, and impurities; at the grain boundaries and surfaces, dangling bonds can also be present, which all contribute to nonradiative recombination of photo‐carriers. On device level, such recombination undesirably inflates the open‐circuit voltage deficit, acting thus as a significant roadblock toward the theoretical efficiency limit of 30%. Herein, the focus is on the origin of the various voltage‐limiting mechanisms in PSCs, and possible mitigation strategies are discussed. Contact passivation schemes and the effect of such methods on the reduction of hysteresis are described. Furthermore, several strategies that demonstrate how passivating contacts can increase the stability of PSCs are elucidated. Finally, the remaining key challenges in contact design are prioritized and an outlook on how passivating contacts will contribute to further the progress toward market readiness of high‐efficiency PSCs is presented.     

Optimization of atrazine removal from synthetic groundwater by electrooxidation process using titanium dioxide and graphite electrodes

ABSTRACT

Atrazine is used in agriculture and is known for its high toxicity. It therefore poses a risk to surface and ground waters, and human life. In this study, an electrochemical method was optimized for atrazine removal from SGW using TiO₂ and graphite electrodes. A comparison between one factor at a time period optimization and Box-Behnken design (BBD) optimization using RSM was carried out to select the optimum conditions. The results show excellent atrazine removal efficiency (99.70%) and close optimum conditions for both applied methods (pH 7 and 7.4; current 2.5 and 2 A and time 14 and 12.12 min, respectively).     

Preparation of precursor particles by cryogenic mechanical milling for the deposition of CuInS2 thin films

Cryogenic milling process is more effective in generating nano- and micro-size particles than conventional high-energy mechanical milling in terms of their size and processing time needed as the cryogenic temperature lowers the activation energy for elastic fracture and minimizes agglomeration among particles. Following the previous success in fabricating uniform chalcopyrite CuInSe₂ nanoparticles using the cryogenic milling process, this study has deposited CuInS₂ thin films through a particle-based, non-vacuum sequential process that includes the preparation of precursor particles using a cryogenic milling process. The paste formulated with the particles was coated on Mo-deposited glass substrate and subsequently sulfurized under S/H₂/Ar atmosphere. The chalcopyrite CuInS₂ thin films were successfully made after sulfurization at the substrate temperature of 550 °C in 30 min. Optimization of pre-baking step prior to sulfurization was critical in achieving dense morphology of the films and the residual oxygen in the nanoparticles was efficiently removed by its reduction reaction with H₂ during the sulfurization process. While the cryogenic milling process can effectively produce particles in a short period of time, preventing agglomeration, further study is necessary to understand the effect of structural and morphological properties of the starting materials on the final outcome from the cryogenic milling process.