Empirical and machine learning models are estimation tools relevant to obtaining scalable solutions to engineering problems. In this study, response surface methodology (RSM) was incorporated to correlate the experimental findings based on mathematical models. Artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) were the artificial intelligence tools used to create trainable algorithms. Feed data consolidated hydration temperature (50 to 90 °C), hydration time (3 to 7 hours), sulphation temperature (120 to 160 °C), diatomite to hydrated lime ratio (0 to 1) and inlet gas concentration (500 to 2500 ppm) as the independent variables mapped against sulphur capture capacity (Y₁ - 5 to 54 %) and reagent utilization (Y₂ - 4 to 42 %) as the dependent variables. The model accuracy and cost analysis were determined using the statistical error analysis tools including root mean square (RMSE), mean square error (MSE) and coefficient of determination (R²). The ANN models presented more acceptable and reliable data estimation with R² values greater than 99% compared to the RSM and ANFIS models. The ANFIS models exhibited overfitting deficiencies that affected learning and training. These findings suggest that the ANN models are a more suitable option for accurate data forecasting in similar engineering applications.

Raman spectroscopy (RS) is soft technique to study the vibronic, and electronic properties of material. Single-walled carbon nanotubes (SWCNTs) have unique chemical and physical properties. The chemical functionalization methods such as filling, intercalation, substitution of carbon atoms in walls, covalent, noncovalent modifications allow changing precisely the electronic properties. Raman spectroscopy investigates these modifications. Raman spectrum of pristine SWCNTs includes four regions: radial breathing mode (RBM) at 50-300 cm^-1, D-band at 1350 cm^-1, G-band at 1590 cm^-1, and 2D-band at 2700 cm^-1. There are five main modifications upon charge transfer: shift of peaks, change of peak shape, decreasing or increasing in the intensity of peaks, disappearance of peaks, change of band profile. In the typical p-doped spectrum of SWCNTs, i.e. the spectrum of metal halogenide-filled SWCNTs, peaks are positioned at 50-300 cm^-1 (RBM), 1350 cm^-1 (D-band), 1600 cm^-1 (G-band), and 2700 cm^-1 (2D-band), depending on the laser wavelength (458-1064 nm). These changes are observed in the spectra of filled SWCNTs, which are encapsulated with n-dopant substances, too. The mechanisms of Raman spectra modifications are different for p, and n doping, which is discussed here.

The process of distillation purification of the constituent of an industrial mixture of products of electrochemical fluorination of naphthalene – perfluorinated cycloalkanes, is considered. As an investigation object, in the present work, perfluoro(7-methylbicyclo[4.3.0]nonane) (MBCN) is considered. The last one is a close-boiling impurity in the production of perfluorodecalin, and has its own commercial value, that leads to purity requirements for the MBCN – not less than 0.998 mass fraction. According to the experimental data, the distillation purification of MBCN fractions with component content above 0.950 mass fraction is not effective and requires the use of special separation methods. The heteroazeotropic distillation was used to intensify the separation process. Acetone (Ac) and dimethylformamide (DMF) were considered as heteroazeotropic agents. All experiments were performed at atmospheric pressure on a semicommercial distillation column with an efficiency of 85 theoretical separation stages. The content of the MBCN in all initial fractions of the investigated samples of the reaction mixture ranged from 0.950 to 0.975 mass fraction, the mixture itself was taken directly from industry. According to experimental data, the separation factor of the initial mixture during distillation with no additional substances is close to 1. The adding of DMF and Ac makes it possible to significantly intensify the process, while Ac shows greater efficiency. Ac allowed to obtain a fraction of MBCN with purity higher than 0.998 mass fraction in one separation cycle, the degree of recovery was more than 0.80 by weight. The paper presents data on the distribution of components (target products, identified and unidentified impurities; the nomenclature of the latter is unknown because of the lack of relevant scientific studies and difficulties during their concentration and purifying) between the distillate and bottom product fractions; recovery ratio; separation factor; liquid-liquid phase equilibrium in the Ac-MBCN system and characteristics of the Ac-MBCN heteroazeotrope.

Photoemission spectroscopy (PES) is the method of investigation of material that studies the bonding environment and electronic properties of material. The single-walled carbon nanotubes (SWCNTs) have unique properties, and are interesting for different applications. The PES techniques, such as X-ray photoelectron spectroscopy (XPS), ultraviolet photoelectron spectroscopy (UPS) are very useful for studying of filled SWCNTs. Among other functionalization methods, filling of SWCNTs allows modifications of properties of carbon nanotubes in a precise manner. The C 1s XPS spectrum of pristine SWCNTs include a single peak positioned at 284.6 eV. In the UPS spectrum of valence band of the pristine SWCNTs, there are two peaks at 3 eV, and 8 eV. The control of properties during the synthesis procedure and precise investigation methods allow tailoring the properties for applications in nanoelectronics, thermoelectric power generation, light emission. The typical C 1s XPS spectrum of SWCNTs filled with p-dopant, i.e. the spectrum of metal halogenide-filled SWCNTs, includes C 1s XPS peak shifed by 0.3-0.4 eV toward lower binding energies. The C 1s XPS spectrum of SWCNTs filled with n-dopants, i.e. spectra of metal, or molecule-filled SWCNTs, include C 1s XPS peak shifted by 0.05-0.3 eV toward higher binding energies. The changes in XPS, UPS spectra such as shift of peaks, increasing width of spectra, asymmetry testifies about changed electronic properties.

Spray dry scrubbing is a popular method for removing sulphur dioxide (SO₂) gas from industrial flue gases, with hydrated lime (Ca[OH]₂) being a preferred sorbent due to its high reactivity. This study investigated the feasibility of using Industrial Brine Sludge Waste (IBSW) from the chlor-alkali industry as a source of Ca[OH]₂. XRF analysis revealed that IBSW had a high content of CaO (89.05%), making it a suitable starting material for the production of a calcium-based sorbent. A laboratory-scale spray dry scrubber was used to test the performance of the prepared Ca[OH]₂ sorbent. The desulphurization efficiency was analyzed by investigating how the SO₂ capture in the spray dryer was influenced by the inlet flue gas temperature (120 °C - 180 °C), slurry pH (6 - 12), Ca:S ratio (1.0 - 2.5), and sorbent particle size (-45µm to -90µm). The highest SO₂ capture rate of 88.54% was achieved under the following conditions: inlet flue gas temperature of 120°C, Ca:S ratio of 2.5, particle size of -45µm, and a slurry pH of 12. The results suggest that IBSW can be a viable starting material for producing Ca[OH]₂ sorbent, which could then be utilized in the spray dry scrubbing process to remove SO₂ from industrial flue gases

Single-walled carbon nanotubes (SWCNTs) are filled with metals. This is very useful filler for investigation of the electronic properties, future applications in optoelectronics. This is very important field of utilization of work time, and the filled carbon nanotubes are very clean, and not toxic for human, and environment. The filling of SWCNTs with such metals as silver, copper, europium, and intercalation with potassium, sodium was achieved. The iron filling was also shown. The investigation of magnetic, electronic, electrical, thermal, optoelectronic properties of filled SWCNTs was performed. Silver and copper filling was performed in the solution, using salts with subsequent thermal treatment. The intercalation with metals is performed with the gas phase method. Different methods can be used for the filling of carbon nanotubes with metals, which are discussed here. Applications of metal filled carbon nanotubes include the fields of nanoelectronics as field effect transistor components, components of solar cells, light emitters, thermoelectric power generators with partial filling with metal, catalysts for chemical reactions, sensors for gases and bioobjects, biomedical theranostic agents for bioimaging and delivery, spintronics devices, magnetic storage, magnetic recording with high coercive force, electrochemical energy storage devices, capacitors and supercapacitors. These applications can be realized with controlled filling processes, filling morphology, filling ratio. Therefore, the control of chemical processes of encapsulation is important for all applications.

Today, the common problem in all countries of the world is the presence of different environmental pollutants in water, air, and soil environments. In particular, endocrine disruptors represent a broad group of pollutants. Copper, which is both in this group and among the heavy metals, reaches aquatic environments directly and indirectly from anthropogenic activities. The adsorption process is the most environmentally friendly, economical, and practical method to prevent pollution caused by these Cu²⁺ ions, and intensive studies have been carried out on this method in recent years. The main target of these studies is to prefer adsorbents that do not cause pollution after removal. In this study, iron shavings (FeS) were considered to be used as an adsorbent. Laboratory scale batch analyzes were performed in synthetic solution under constant stirring speed (150 rpm) and temperature (20±2 ^oC) with different pH (2.0 - 6.0), FeS dose (0.1-5 g), and contact times (1-60 minutes). . The maximum removal efficiency of Cu²⁺ was determined as 78% under optimum operating conditions. The aim of this research article is to understand the application possibility of FeS adsorbent for the efficient removal of Cu²⁺. Interestingly, laboratory studies have shown that the use of FeS adsorbent can efficiently remove the endocrine-disrupting Cu²⁺.

Water scarcity is currently one of the world's major issues. Water treatment technologies are a solution to the water crisis problems. In this study, the outcomes of pre-pilot scale testing of solar-powered Ion-exchange resin technology is presented. The tests were carried out using industrial wastewater at the "Kungrad Soda Plant" in Kungrad, Uzbekistan. From the plant, about 1500 m³/day of wastewater containing total dissolved solids (TDS) is discharged into the environment. In order to reduce the negative impact on the environment and to reuse wastewater, the factory proposed to conduct water purification tests from unwanted ions (Са²⁺, Mg²⁺, Cl^-, SO₄^2-, dissolved СО₂). During the test of the technology, water with a TDS of about 2000 ppm was passed through the ion-exchange resin and clean water of around 30 ppm was obtained (recovery 98-99 %). However, according to the requirement of the plant, a certain amount of daily water is purified and added to the total water, and no more than 1600 ppm of water is produced and sent for reuse. Experiments have been successfully carried out on a pre-pilot scale using this technology

The city of Johannesburg in South Africa generates a lot of restaurant food waste. This waste is currently diverted to landfills. The three (3) major landfills being used are fast running out of space as waste generation is increasing every day. The Municipality of Johannesburg city suffers limited land space to develop new landfills and such an exercise would also require huge sums of capital outlay. Globally, managing organic waste through landfilling has lost popularity as new and more sustainable strategies have now advanced to commercial scale. Some of these strategies include biomethanation, compositing and reuse of waste in resource recovery. Practitioners in waste management, rank strategies on “The Hierarchy of Waste Management” to reflect the sustainability attributes of each strategy or technology. Selecting the appropriate waste management technology for each situation depends on several sustainability factors such as available human skills, cost, environmental impacts as well as value of end products produced. This study seeks to choose a suitable technology from the hierarchy of waste management that can potentially replace landfilling for Johannesburg’s restaurant food wastes management. Literature published in South Africa’s Department of Higher and Tertiary Education (DHET) accredited journals and that sourced from existing and officially registered South African companies that participate in the waste management space shall be used in this study to arrive on conclusions.

Steam Generator (SG) is an important energy exchange equipment for nuclear power plants, and the level control of steam generators plays a key role in the stable operation of the plants. In order to improve the level control performance of steam generators, it is necessary to adjust the parameters of the level control system during the commissioning process of nuclear power plants. However, the parameter tuning process is heavily dependent on engineers' experience, requires a large amount of operational history data, and is difficult to ensure optimal performance. To address these issues, this paper proposes a hybrid iterative model reconstruction-based steam generator level control performance optimization method based on the idea of data-driven optimization. The method proposes a fusion idea and implementation mechanism in which process data and hybrid model are jointly driven under the data-driven framework to maximize the advantages of different modeling mechanisms in order to achieve the performance optimization of SG level control system. The method first constructs the initial data set with a small-sample Latin-square experiment design, and builds two different fitting models, SVM and Kriging, based on the initial data set respectively under the hybrid model fusion idea. After that, the particle swarm optimization algorithm is used to calculate the optimal point of the current valid model, and the optimization process is controlled by establishing the iteration termination judgment based on the historical iteration data. Then, the current iteration point is used to dynamically reconstruct the two types of models. Finally, the two types of models are dynamically reconstructed using the current iteration points. The above process is iterated until the optimal iterative process of the system is satisfied. The results of this paper show that this method has better optimization performance and can significantly improve the efficiency of steam generator level control performance optimization than the traditional optimization estimation method under the framework of single model optimization.