Cyclic steam stimulation is an effective thermal recovery method for heavy oil recovery. The key potential mechanism is the growth of the steam chamber after steam injection. Taking the LD5X heavy oil reservoir as an example, besides the interlayer developed in this area, the top water and bottom water distribute above and below the interlayer. These factors may have adverse effects on the development of the steam chamber, thus affecting the final heavy oil exploitation. In this work, our goal is to study the effects of interlayer permeability and well−interlayer distance on CSS performance (in the presence of top and bottom water). We developed a high-temperature-resistant interlayer. Based on the simulated interlayer, the field scale model was converted into a laboratory element model through the similarity criterion. In order to quantitatively evaluate the performance of steam stimulation, a thermal detector was used to measure the dynamic growth of the steam chamber and record the... [more]

Production practice has shown that not all low-production coalbed methane (CBM) wells can be reconstructed into high-production wells through secondary stimulation, so it is necessary and timely to establish an evaluation index system, form an evaluation method, and evaluate the reconstruction potential of low-production wells. Based on the development practice of CBM in the southern Qinshui Basin, this paper analyzes the influencing factors of low production in vertical wells from the aspects of coal and rock reservoir conditions, drilling and completion engineering, and drainage engineering. It is proposed that the evaluation of the reconstruction potential of low-production wells should focus on the quality of CBM resources, the difficulty of CBM desorption and diffusion, and the degree of damage to coal reservoirs caused by the initial reservoir stimulation. Twelve parameters, including gas content, gas saturation, reservoir pressure gradient, critical desorption−reservoir pressure... [more]

Ferric chloride (FeCl3) modified reed straw-based biochar was synthesized to remove nitrate from aqueous solutions and achieve waste recycling. The adsorption of nitrate onto Fe-RBC-600 adsorbents could be described by the pseudo-second-order kinetic model and fitted to Langmuir adsorption, and the maximum adsorption capacity predicted using the Langmuir model was 272.024 mg g−1. The adsorbent characterization indicated that a high temperature of 600 °C and an oxygen-poor environment could develop a hydrophobic surface and O-containing functional groups on the biochar, which provided more binding sites for Fe3+/Fe2+ attachment and increased the surface functionality of Fe-RBC-600 with iron oxide formation. The increasing surface functionality successfully enhanced the nitrate adsorption property. The mechanism of nitrate adsorption was mainly attributed to the physical adsorption onto the positive surface and sequential chemical reduction by Fe2+, and the electrostatic adsorption by pr... [more]

High-sensitivity biomedical sensors could make it possible to detect and classify chemical and biological species in a variety of applications, from disease diagnosis to medication discovery, thus, boosting the likelihood of life-saving intervention. Synthesized nanowires have already produced advancements in a variety of sectors, including biological sensors over the last decade. When compared to macro-sized materials, the nanowires’ large surface area-to-volume ratio increased sensitivity. Their applications for biomarker, viral, and DNA detection, as well as drug discovery, are also discussed. Self-powering, reusability, sensitivity in high ionic strength solvents, and long-term stability are all examples of recent developments. Shortly, the nanowire is likely to lead to major improvements in biomedical sensors. This review provides a full overview of the nanowire sensor’s working principle and production procedure. We have discussed how to produce nanowires that can be utilized as... [more]

The stability of active pharmaceutical ingredients (APIs) and the corresponding pharmaceutical formulations are nowadays of great importance in pharmaceutical research and technology. The quality of an API or of finished pharmaceutical products (FPPs) is time dependent under the influence of several parameters, such as light and air exposure, temperature, and humidity. Additionally, the stability profile of an API is influenced by the formulation composition, due to the presence of excipients or by the characteristic of the packaging materials. In this sense, the main objective of this study was to analyze the degradation kinetics of the antihypertensive drug moxonidine as a pure ingredient (MOX) and in two different solid mixtures, one corresponding to a pharmaceutical formulation (MOXTAB) and the other to an enriched pharmaceutical formulation in MOX (MOXMIX). As investigation techniques, FTIR (Fourier transform infrared) spectroscopy and TG/DTG/HF analysis were employed, while the t... [more]

The intricate morphology of porous media can considerably affect the progression of penetration and the diffusion of grouting slurry. In this study, a Newtonian fluid’s refined seepage motion equation was proposed to incorporate the impact of tortuosity on the grouting process into gravel soil, and the column-hemispherical penetration grouting mechanism was analyzed using the method of theoretical analysis. Utilizing secondary-development programming techniques, a numerical simulation program was developed with COMSOL Multiphysics to model the penetration grouting mechanism of a Newtonian fluid in a column-hemispherical pattern, considering a medium’s tortuosity. The penetration grouting process of Newtonian cement into gravel soils was then simulated. Finally, the theoretical analysis, experimental values, and numerically simulated values were compared.The findings suggested that incorporating the tortuosity of porous media is more efficacious in depicting the penetration and diffusio... [more]

Hybrid electric vehicles (HEVs) have certain advantages over internal combustion engines in terms of energy consumption and emission performance. However, the transmission system parameters are uncertain. The low matching between the engine and the power transmission system makes it a big problem to improve the efficiency of hybrid vehicles. Therefore, the multi-objective optimization design of hybrid vehicles is studied. The transmission system parameters of hybrid vehicles are analyzed from the objective function, decision variables, and constraints. The NSGA-II algorithm with elite strategy is introduced to realize the optimal selection of parameters and formulation of energy consumption optimization strategy. The results showed that the multi-objective optimization algorithm could adjust the position of the working point of the engine and improve the efficiency by more than 10%. There was an average difference of 2.15% after the improvement in the fuel consumption of four-gear vehi... [more]

As is widely known, the issue of freshwater scarcity affects practically all people, and all are looking for innovative and workable ways to attempt to solve this issue. In this work, a novel method of desalination is proposed. The proposed system consists of a solar collector (PTSC), evacuated pipe (EP), condenser (CU), and separation unit (SU). The working principle of the system is heating the feed saline water using the PTSC and EP and controlling the water flow rate to control the output conditions of the EP. The produced vapor is therefore separated from salty water using the SU. In addition, the generated steam is condensed into the CU to produce a freshwater distillate. Consequently, the effect of solar radiation on the affecting temperatures was tested. In addition, the effect of using different water flow rates (6, 7.5, 10, 20, 40, and 60 L/h) inside the EP on the system productivity was investigated. The primary findings of this work may be highlighted in relation to the exp... [more]

The production of heavy fuel oil from hydrocracked vacuum residue requires dilution of the residue with cutter stocks to reduce viscosity. The hydrocracked residue obtained from different vacuum residue blends originating from diverse crude oils may have divergent properties and interact with the variant cutter stocks in a dissimilar way leading to changeable values of density, sediment content, and viscosity of the obtained fuel oil. H-Oil hydrocracked vacuum residues (VTBs) obtained from different crude blends (Urals, Siberian Light (LSCO), and Basrah Heavy) were diluted with the high aromatic fluid catalytic cracking (FCC) light cycle, heavy cycle, and slurry oil, and the low aromatic fluid catalytic cracking feed hydrotreater diesel cutter stocks and their densities, sediment content, and viscosity of the mixtures were investigated. Intercriteria analysis evaluation of the data generated in this study was performed. It was found that the densities of the blends H-Oil VTB/cutter sto... [more]

Mine accidents are mostly caused by human unsafe behavior. To reduce the unsafe behavior of mine operation and reduce the accident of mine operation, the main body of unsafe behavior ‘people’ is analyzed, and 24 attribute factors are selected from five aspects of people’s emotions, motivation, ability, personality, and pressure to construct the comprehensive model of human behavior SMAPP (sentiment−motivation−ability−personality−pressure). The program tool for recording, saving, and executing the mutual and interactive influence relationship of 24 attribute factors under different state values and the simulation process framework of SMAPP was constructed by using 1071 rule statements written in Python language. The fuzzy rules are used to simulate different scenarios. The simulation results are consistent with the actual research results, which shows the reliability and scientificity of the model. In addition, additional events are added to the simulation process to make the model more... [more]

The wide availability of crude glycerol and its low market price make this by-product of the biodiesel industry a promising raw material for obtaining high-value-added products through catalytic conversion processes. This work studied the effect of the composition of different industrial crude glycerol samples on the catalytic hydrogenolysis to 1,2-propylene glycol. A nickel catalyst supported on a silica−carbon composite was employed with this purpose. This catalyst proved to be active, selective to 1,2-propylene glycol and stable in the glycerol hydrogenolysis reaction in the liquid phase when analytical glycerol (99% purity) was employed. In order to determine the effect of crude glycerol composition on the activity, selectivity and stability of this catalyst, industrial crude glycerol samples were characterized by identifying and quantifying the impurities present in them (methanol, NaOH, NaCl and NaCOOH). Reaction tests were carried out with aqueous solutions of analytical glycero... [more]

In the Industry 4.0 environment, an ideal smart factory should be intelligent, green, and humanized, and the logistics transportation from raw materials to final products in the factory should be completed by smart logistics. In order to address the problems of low efficiency, poor workstation service satisfaction, high distribution costs, and non-greening during the logistics distribution processes in discrete smart manufacturing workshops are required. A mathematical model of optimized multi-objective green logistics distribution paths in a smart manufacturing workshop has been constructed in this study, with low costs, high efficiency, and workstation service satisfaction taken into consideration. Then, this mathematical model was solved with an improved ant colony optimization algorithm. A “time window span” was introduced in the basic ant colony optimization algorithm to prioritize the services to workstations with a relatively high urgency in material demand, with the aim of impr... [more]

Jacq., from the Yucatan peninsula, is recognized worldwide for its pungency, flavor, and secondary metabolites content. This has resulted in an increase in its production, which has led to an increase in the number of byproducts considered waste, mainly its leaves. Capsicum chinense leaves have been demonstrated to contain polyphenols with bioactive properties (antioxidant, anti-inflammatory, antiobesogenic capacity, etc.); hence, the extraction of polyphenols through the use of natural deep eutectic solvents (NADES) with a green technology, such as an ultrasonic probe, could help to revalue these leaves by maximizing the extraction efficiency and preserving their bioactive properties. The objective of this study was to optimize the composition of a eutectic solvent for obtaining an extract rich in polyphenols from the Capsicum chinense leaf using a sonic probe. The optimum conditions of the composition of NADES for obtaining the highest Antioxidant capacity (Ax, 79.71% inhibition) wer... [more]

A thermoelectric generator (TEG) is studied by considering different leg structures of hollow/filled legs, using new cooling nanofluids, and analyzing the segmentation effect. TEG performance is characterized by power output, conversion efficiency, and exergy efficiency. This study shows the impact of different cooling nanofluids (TiO2, graphene, and Al2O3) on the performance of the thermoelectric generator. Furthermore, in the comparative analysis of nanofluid cooling enhancement for TEG, different hollow/filled thermoelectric legs recently proposed in the literature are considered. Likewise, three segmentation types are used, 2n-2p, 1n-2p, and 2n-1p, thus will be compared with the results of the unsegmented legs. This study calculates the performance of thermoelectric leg structures through a validated numerical simulation on the ANSYS Workbench (modeling, design, and simulation). In addition, the optimal working conditions are evaluated. This study found that quenching of nanofluids... [more]

Traditional wastewater treatment methods, such as reverse osmosis, adsorption, desalination, and others, are outweighed by the photocatalytic degradation of organic pollutants. Ferrites are prominent photocatalysts due to their tunable band gaps, surface areas, and magnetic properties, which render photodegradation economical. Ferrites and their nanocomposites have been reported as promising visible light active photocatalysts. The photocatalytic system is heavily reliant on a number of factors that influence the photodegradation of organic effluents. This review demonstrates various parameters such as substrate concentration, pH of solution, photocatalyst quantity, photocatalyst surface area, metal and non-metal ion doping, light intensity, irradiation time, quenchers, etc. affecting the photocatalytic degradation of organic effluents by ferrite nanoparticles and their nanocomposites in detail. The photodegradation efficiency of the ferrite nanoparticles alters with the change in the... [more]

This work aimed to optimize the extraction conditions of bioactive compounds obtained from three squash by-products (e.g., peel, endocarp, and seeds) using the response surface methodology (RSM). The selected independent variables were ethanol concentration, extraction time, and extraction temperature. Squash by-products’ bioactive molecules were extracted according to the matrix proposed by the experimental plan. Significant variability in total phenolic compound content (TPC) and antioxidant activity, depending on the extraction time, the solvent concentration, and the extraction temperature, was recorded for the tested by-products. The experimental results adequately fitted with second-order polynomial models and showed significant linear, quadratic, and interaction effects of the independent variables. Data analysis suggested that the optimal extraction conditions were 12.2% ethanol for 11.2 min at 55 °C for peels; 28.5% ethanol for 10.5 min at 37 °C for endocarp; and 20% ethanol f... [more]

Configuring energy storage devices can effectively improve the on-site consumption rate of new energy such as wind power and photovoltaic, and alleviate the planning and construction pressure of external power grids on grid-connected operation of new energy. Therefore, a dual layer optimization configuration method for energy storage capacity with source load collaborative participation is proposed. The external model introduces a demand-side response strategy, determines the peak, flat, and valley periods of the time-of-use electricity price-based on the distribution characteristics of load and new energy output, and further aims to maximize the revenue of the wind and solar storage system. With the peak, flat, and valley electricity price as the decision variable, an outer optimization model is established. Based on the optimized electricity price, the user’s electricity consumption in each period is adjusted, and the results are transmitted to the inner optimization model. The inter... [more]

In agro-industrial processes, microorganisms that are not pathogenic and that generate molecules are generally recognized as safe (GRAS). The Aspergillus niger fungus has different industrial applications, being used to produce citric acid and 166 other secondary metabolites. The objective of this research was to optimize a culture medium to induce the production of kojic acid (KA) by the Aspergillus niger M4 strain in a liquid fermentation process. Four fermentative kinetics were developed in flasks, using different levels of yeast extract in (1) 0.05 g/L, (2) 0.10 g/L, (3) 2.5 g/L, and (4) 2.5 g/L + Zinc sulfate. The culture medium conditions influenced the formation and speed of biomass and the synthesis and yield of KA. The optimum production points were from 72 h and 96 h with 0.552 g/L and 0.510 g/L of KA using 2.5 g/L of yeast extract and with a pH of 5.5. The Aspergillus niger M4 strain had the ability to produce kojic acid, which was induced by the concentration of the nitroge... [more]

The mechanism of high-intensity conditioning (HIC) has not been thoroughly revealed, and therefore this work investigates the effect of HIC on the surface hydrophobicity of coal with different particle sizes and the possible formation of particle−bubble clusters. The results show that different HIC conditions are required for coarse and fine particles. Coarse particles (+75 μm) require a higher turbulence intensity to increase collector dispersion, thereby increasing the adsorption of the collector. Fine particles (−75 μm) require a lower turbulence intensity to reduce the desorption of the collector. In this study, the optimum HIC conditions for coarse and fine particles are “2200 rpm + 1 min” and “1300 rpm + 1 min”, respectively. Interestingly, it seems that the adsorption capacity between fine particles and the collector is weaker than that for coarse particles. A non-enclosed HIC system produces up to 1.78 × 104/g bubbles in coarse particle−bubble clusters, and the mean bubble diam... [more]

The Mikania genus has been known to possess numerous pharmacological activities. In the present study, we aimed to evaluate the interaction of 26 selected constituents of Mikania species with (i) cyclooxygenase 2 (COX 2), (ii) human neutrophil elastase (HNE), (iii) lipoxygenase (LOX), matrix metalloproteinase ((iv) MMP 2 and (v) MMP 9), and (vi) microsomal prostaglandin E synthase 2 (mPGES 2) inhibitors using an in silico approach. The 26 selected constituents of Mikania species, namely mikamicranolide, kaurenoic acid, stigmasterol, grandifloric acid, kaurenol, spathulenol, caryophyllene oxide, syringaldehyde, dihydrocoumarin, o-coumaric acid, taraxerol, melilotoside, patuletin, methyl-3,5-di-O-caffeoyl quinate, 3,3′,5-trihydroxy-4′,6,7-trimethoxyflavone, psoralen, curcumene, herniarin, 2,6-dimethoxy quinone, bicyclogermacrene, α-bisabolol, γ-elemene, provincialin, dehydrocostus lactone, mikanin-3-O-sulfate, and nepetin, were assessed based on the docking action with COX 2, HNE, LOX, M... [more]

The remote sensing ecological index (RSEI) has been widely used in the rapid monitoring and evaluation of the regional ecological environment; however, the research on the main factors that cause changes in RSEI and the impact of human activities in the mining area on RSEI is not often explored. To this end, this paper selected the Landsat (TM/OLI) series of remote sensing images from 1986 to 2022; extracted the four important indicators of the normalized difference vegetation index (NDVI), the wetness component of the tasseled cap transformation (WET), normalized difference built-up and soil index (NDBSI), and land surface temperature (LST); calculated the remote sensing ecological index (RSEI) based on the principal component analysis method; monitored and evaluated the ecological environment changes in the Shendong Mining Area for a period of 36 years; and analyzed the driving forces that cause these ecological environment changes. The results show the following: (1) The ecological... [more]

When designing a new type of power plants operating on pulsed detonations of gaseous or liquid fuels, the concept of fast deflagration-to-detonation transition (FDDT) is used. According to the concept, a flame arising from a weak ignition source must accelerate so fast as to form an intense shock wave at a minimum distance from the ignition source so that the intensity of the shock wave is sufficient for fast shock-to-detonation transition by some additional arrangements. Hence, the FDDT concept implies the use of special means for flame acceleration and shock wave amplification. In this work, we study the FDDT using a pulsed detonation tube comprising a Shchelkin spiral and a helical tube section with ten coils as the means for flame acceleration and shock amplification (focusing), respectively. To attain the FDDT at the shortest distances for fuels of significantly different detonability, the diameter of the pulsed detonation tube is taken close to the limiting diameter of detonation... [more]

Machine learning assists with food process optimization techniques by developing a model to predict the optimal solution for given input data. Machine learning includes unsupervised and supervised learning, data pre-processing, feature engineering, model selection, assessment, and optimization methods. Various problems with food processing optimization could be resolved using these techniques. Machine learning is increasingly being used in the food industry to improve production efficiency, reduce waste, and create personalized customer experiences. Machine learning may be used to improve ingredient utilization and save costs, automate operations such as packing and labeling, and even forecast consumer preferences to develop personalized products. Machine learning is also being used to identify food safety hazards before they reach the consumer, such as contaminants or spoiled food. The usage of machine learning in the food sector is predicted to rise in the near future as more busines... [more]

The development and optimization of lipid nanoparticle (LNP) formulations through hydrodynamic mixing is critical for ensuring the efficient and cost-effective supply of vaccines. Continuous LNP formation through microfluidic mixing can overcome manufacturing bottlenecks and enable the production of nucleic acid vaccines and therapeutics. Predictive process models developed within a QbD Biopharma 4.0 approach can ensure the quality and consistency of the manufacturing process. This study highlights the importance of continuous LNP formation through microfluidic mixing in ensuring high-quality, in-specification production. Both empty and nucleic acid-loaded LNPs are characterized, followed by a TFF/buffer exchange to obtain process parameters for the envisioned continuous SPTFF. It is shown that LNP generation by pipetting leads to a less preferable product when compared to continuous mixing due to the heterogeneity and large particle size of the resulting LNPs (86−104 nm). Particle siz... [more]

Pharmaceutical manufacturing processes are moving towards automation and real-time process monitoring with the help of process analytical technologies (PATs) and predictive process models representing the real system. In this paper, we present a digital twin developed for an adjuvant manufacturing process involving a microfluidic formation of lipid particles. The twin uses a hybrid model for estimating the current state of the process and predicting system behavior in real time. The twin is used to control the adjuvant particle size, a critical quality attribute, by varying process parameters such as the temperature and inlet flow rates. We describe steps in the design and implementation of the twin, starting from the conception of the mechanistic model, up to the generation of its surrogate model used as state estimator, PATs and the setup of the information technology—Operational technology architecture. We demonstrate the performance of the twin by introducing different disturbances... [more]