• Energy Research
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• University of Tehran close

In recent years, the main objective of developing new hydrogel systems has been to convert biomass into environmentally-friendly hydrogels. Hybrid hydrogels are usually prepared by graft copolymerization of acrylic monomers onto natural polymers or biomass. In this study, sugarcane bagasse was used to prepare semi-synthetic hybrid hydrogels without delignification, which is a costly and timeconsuming process. Sugarcane bagasse as a source of polysaccharide was modified using polymer microgels based on acrylic monomers such as acrylic acid, acrylamide and 2-acrylamido-2-methyl propane sulfonic acid which were prepared through inverse emulsion polymerization. By this process, biomass as a low-value by-product was converted into a valuable semi-synthetic hydrogel. In the following, the effect of latex type¸ the aqueous-to-organic phase ratio in the polymer latex, time and temperature of modification reaction on the swelling capacity of the hybrid hydrogel were evaluated. The chemical reaction between sugarcane bagasse and acrylic latex was carried out during heating of the modified bagasse which led to obtain a semisynthetic hydrogel with 60% natural components and 40% synthetic components. Among the latexes with different structures, poly(AA-NaAA-AM-AMPS) was the most suitable polymer latex for the conversion of biomass into hydrogel. The bagasse modified with this latex had a water absorption capacity up to 112 g/g, while the water absorption capacity of primary sugarcane bagasse was only equal to 3.6 g/g. The prepared polymer hydrogels were characterized using Fourier transform infrared spectroscopy (FTIR), dynamic-mechanical thermal analysis (DMTA), thermal gravimetric analysis (TGA), scanning electron microscopy (SEM) and determination of the amount of swelling capacity.

Environmental pollution and rapid depletion are among the chief concerns about fossil fuels such as oil, gas, and coal. Renewable energy sources do not suffer from such limitations and are considered the best choice to replace fossil fuels. The present study develops a mathematical model for optimal allocation of regional renewable energy to meet a country-wide demand and its other essential aspects. The ultimate purpose is to minimize the total cost by planning, including power plant construction and maintenance costs and transmission costs. Minimum-cost flow equations are embedded in the model to determine how regions can supply energy to other regions or rely on them to fulfill annual demand. In order to verify the applicability of the model, it is applied to a real-world case study of Iran to determine the optimal renewable energy generation-transmission decisions for the next decade. Results indicate that the hydroelectric and solar power plants should generate the majority of the generated renewable electricity within the country, according to the optimal solution. Moreover, regarding the significant population growth and waste generation in the country’s large cities, biomass power plants can have the opportunity to satisfy a remarkable portion of electricity demand.

Due to the rapid changes and developments caused by technology in the digital age and the growing importance of achieving sustainability for the survival of businesses, the need to create the capabilities needed to innovate in the business model of organizations has become inevitable. This research is trying to provide a model for business model innovation with the aim of sustainability by considering the external factor of digitalization (digital transformation) and the internal factor of dynamic capabilities. The method of this research is mixed so that in the first stage the qualitative method of Meta-Synthesis is used and in the second stage the quantitative method of Interpretive Structural Modeling (ISM) is used. In this research, based on the systematic review of previous researches in scientific databases, 402 related articles were identified and then 46 final articles were selected during the screening process. Based on the thematic analysis, a total of 4 main categories and 14 factors were extracted. In the second stage of the research, an interpretive structural model (ISM) is developed to show the inter‐relationship of different factors and their levels of importance in the food industry. The 8-level hierarchy model of factors influencing the sustainable business model innovation in the digital age with a dynamic capabilities approach was proposed. Results show that a new component called network value has been added to the traditional business model components. Furthermore, the MICMAC approach has been used to categorise factors according to their driving power and dependence. finally, digital technologies and Sensing were found to be the factors with the highest independence and the highest driving power, and “Economic Sustainability” was identified as the factor with the highest dependence and the least driving power