Technological and Economic Optimization of Wheat Straw Black Liquor Decolorization by Activated Carbon

Wheat straws are a globally abundant agro-waste that may play a critical role in the global transition from single-use plastics to green materials as an inexpensive and renewable raw material. Vast amounts of wastewater are produced during the technological process of wheat straw-cellulose/hemicellulose conversion. In this context, this work focuses on wastewater decolorization via activated carbon adsorption. A set of carefully planned experiments enabled the identification of a model that described the relationship between the system’s outputs and parameters. While process optimization is frequently connected with identifying process parameters that improve efficiency, this work employed a multi-objective optimization approach from both a technological and economic aspect. Nondominated sorting genetic algorithm versions II and III—NSGA-II and NSGA-III algorithms—were applied. As objectives, maximum efficiency and minimum cost per experiment were followed in different scenarios using pseudoweights and trade-off metrics. When optimizing only the efficiency, the results indicated a 95.54% decolorization yield, costing 0.1228 Euro/experiment, and when considering both the efficiency and cost, different solutions were obtained. The lowest cost was 0.0619, with a 74.42% decolorization. These findings indicate that incorporating an economic perspective into the optimization procedure can improve cost estimation and facilitate managerial decision-making

An Experimental Study on the Hot Alkali Extraction of Xylan-Based Hemicelluloses from Wheat Straw and Corn Stalks and Optimization Methods

In this paper, we describe an experimental study on the hot alkali extraction of hemicelluloses from wheat straw and corn stalks, two of the most common lignocellulosic biomass constituents in Romania. The chemical compositions of the raw materials were determined analytically, and the relevant chemical components were cellulose, hemicelluloses, lignin, and ash. Using the response surface methodology, the optimum values of the hot alkaline extraction parameters, i.e., time, temperature, and NaOH concentration, were identified and experimentally validated. The physicochemical characterization of the isolated hemicelluloses was performed using HPLC, FTIR, TG, DTG, and 1H-NMR spectroscopy. The main hemicellulose components identified experimentally were xylan, arabinan, and glucan. The study emphasizes that both corn stalks and wheat straw are suitable as raw materials for hemicellulose extraction, highlighting the advantages of alkaline pretreatments and showing that optimization methods can further improve the process efficiency

Artificial Intelligence-Based Tools for Process Optimization: Case Study—Bromocresol Green Decolorization with Active Carbon

This study highlights the benefits of optimizing the decolorization of bromocresol green (a colorant/pH indicator widely used in the industry, whose degradation produces toxic byproducts) by adsorption on active carbon. A set of experiments were planned and performed based on the design of experiments methodology for the following parameters: the colorant concentration (0.009-0.045 g/L), the amount of adsorbent (0.5-3 g/L), and the contact time (60-240 min). Modeling and optimization strategies were employed to determine the working conditions leading to efficiency maximization. Using the response surface methodology, the optimum values of the primary process parameters were established. In addition, a modified bacterial foraging optimization algorithm was applied as an alternative optimizer in combination with artificial neural networks in order to determine multiple combinations of parameters that can lead to maximum process efficiency. Different solutions were obtained with the considered strategies, and the maximum efficiency obtained was >99%. The study emphasizes that adsorption on active carbon is an effective method for bromocresol green decolorization in wastewater that can be further improved using advanced optimization methods

Optimization of Alkaline Extraction of Xylan-Based Hemicelluloses from Wheat Straws: Effects of Microwave, Ultrasound, and Freeze–Thaw Cycles

The alkaline extraction of hemicelluloses from a mixture of three varieties of wheat straw (containing 40.1% cellulose, 20.23% xylan, and 26.2% hemicellulose) was analyzed considering the following complementary pre-treatments: freeze–thaw cycles, microwaves, and ultrasounds. The two cycles freeze–thaw approach was selected based on simplicity and energy savings for further analysis and optimization. Experiments planned with Design Expert were performed. The regression model determined through the response surface methodology based on the severity factor (defined as a function of time and temperature) and alkali concentration as variables was then used to optimize the process in a multi-objective case considering the possibility of further use for pulping. To show the properties and chemical structure of the separated hemicelluloses, several analytical methods were used: high-performance chromatography (HPLC), Fourier-transformed infrared spectroscopy (FTIR), proton nuclear magnetic resonance spectroscopy (1H-NMR), thermogravimetry and derivative thermogravimetry analysis (TG, DTG), and scanning electron microscopy (SEM). The verified experimental optimization result indicated the possibility of obtaining hemicelluloses material containing 3.40% glucan, 85.51% xylan, and 7.89% arabinan. The association of hot alkaline extraction with two freeze–thaw cycles allows the partial preservation of the hemicellulose polymeric structure