A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information

Both academic and corporate interest in sustainable supply chains has increased in recent years. Supplier selection process is one of the key operational tasks for sustainable supply chain management. This paper examines the problem of identifying an effective model based on sustainability principles for supplier selection operations in supply chains. Due to its multi-criteria nature, the sustainable supplier evaluation process requires an appropriate multi-criteria analysis and solution approach. The approach should also consider that decision makers might face situations such as time pressure, lack of expertise in related issue, etc., during the evaluation process. The paper develops a novel approach based on fuzzy analytic network process within multi-person decision-making schema under incomplete preference relations. The method not only makes sufficient evaluations using the provided preference information, but also maintains the consistency level of the evaluations. Finally, the paper analyzes the sustainability of a number of suppliers in a real-life problem to demonstrate the validity of the proposed evaluation model.     

On modelling of surface tension of CMC-α-Fe2O3 nanoparticles by fuzzy-hybrid approach: A comparison study

Surface tension is one of the most important rheological parameters of nanoliquids. It influences the thermophysical and mass transfer properties of nanostructures. Accurate estimation of the surface tension from operating variables is critical for determining optimal production processes. However, the challenges of producing nanoparticles and measuring their properties introduce experimental errors in the data used for mathematical modelling. Crisp regression approaches provide adequate representation of the data, but they do not provide information about the experimental uncertainty. In this study, a fuzzy-hybrid approach is proposed for mathematical modelling of surface tension of carboxymethyl cellulose/chitosan-α-Fe₂O₃ nanoparticles. Then, the proposed model is compared with a crisp model from a previous study. Error analysis is conducted to validate the constructed fuzzy model. It is observed that the fuzzy-hybrid modelling approach has yielded significantly lower error values (a 60%–90% improvement in all error metrics on average), and thus, it is superior to the crisp approach. This study contributes to the subject of modelling rheological properties. It is shown that the fuzzy-hybrid approach has impressive potential to be utilized for modelling the rheological properties of nanostructures.     

Critical assessment of extracellular polymeric substances extraction methods from mixed culture biomass

Extracellular polymeric substances (EPS) have a presumed determinant role in the structure, architecture, strength, filterability, and settling behaviour of microbial solids in biological wastewater treatment processes. Consequently, numerous EPS extraction protocols have recently been published that aim to optimize the trade off between high EPS recovery and low cell lysis. Despite extensive efforts, the obtained results are often contradictory, even when analysing similar biomass samples and using similar experimental conditions, which greatly complicates the selection of an extraction protocol. This study presents a rigorous and critical assessment of existing physical and chemical EPS extraction methods applied to mixed-culture biomass samples (nitrifying, nitritation-anammox, and activated sludge biomass). A novel fluorescence-based method was developed and calibrated to quantify the lysis potential of different EPS extraction protocols. We concluded that commonly used methods to assess cell lysis (DNA concentrations or G6PDH activities in EPS extracts) do not correlate with cell viability. Furthermore, we discovered that the presence of certain chemicals in EPS extracts results in severe underestimation of protein and carbohydrate concentrations by using standard analytical methods. Keeping both maximum EPS extraction yields and minimal biomass lysis as criteria, it was identified a sonication-based extraction method as the best to determine and compare tightly-bound EPS fractions in different biomass samples. Protein was consistently the main EPS component in all analysed samples. However, EPS from nitrifying enrichments was richer in DNA, the activated sludge EPS had a higher content in humic acids and carbohydrates, and the nitritation-anammox EPS, while similar in composition to the nitrifier EPS, had a lower fraction of hydrophobic biopolymers. In general, the easily-extractable EPS fraction was more abundant in carbohydrates and humic substances, while DNA could only be found in tightly bound EPS fractions. In conclusion, the methodology presented herein supports the rational selection of analytical tools and EPS extraction protocols in further EPS characterization studies.     

Biosorption of Acid Red P-2BX by lichens as low-cost biosorbents

The aim of this study is to examine the dye biosorption properties of lichen species called Cladonia convoluta and Evernia prunastri. Since lichens are extensively found in the environment, their suitability as a cheap adsorbent has been investigated in this study. The optimal parameters for textile dye biosorption were also determined. The dried lichen biomass showed better dye biosorption capacity than ash lichen biomass. C. convoluta had better dye biosorption capacity than E. prunastri. Dye biosorption rate was found as 71.41% at optimal conditions. This study concluded that C. convoluta was a successful and cheap biosorbent for treatment of water contaminated by Acid Red P-2BX dye.     

A systematic comparative study of the efficient co-catalyst-free photocatalytic hydrogen evolution by transition metal oxide nanofibers

The efficiencies of a series of hydrogen evolving catalysts based on metal oxide nanofibers (NiO, Co₃O₄, Mn₃O₄) are investigated for the photocatalytic hydrogen evolution from water without using any co-catalyst under the visible light irradiation by using triethanolamine (TEOA) as an electron donor and Eosin-Y (EY) dye as a photosensitizer. It is found that the photocatalytic hydrogen evolution activities follow the order as: Mn₃O₄<Co₃O₄<NiO (196 μmolg^?1h^?1, 5552 μmolg^?1h^?1, 7757 μmolg^?1h^?1, respectively). Moreover, the catalytic behavior of these nanofibers on the hydrogen production has been also compared to bulk forms of NiO, Co₃O₄ and Mn₃O₄ by producing hydrogen 937 μmolg^?1h^?1, 901 μmolg^?1h^?1 and 135 μmolg^?1h^?1, respectively. The nanofiber structures demonstrated much higher photocatalytic activity than bulk forms due to the effect of the increased surface to volume ratio deduced from the fibrous character. The photocatalytic plausible pathway for the hydrogen production is also discussed.