Feed Rate Conditions Research Articles

Brewery CO2 conversion into acetic acid at an optimized set of microbial electrosynthesis process parameters

Direct utilization of unpurified industrial CO2 is desired to minimize feedstock transportation and purification costs and develop cost-efficient carbon utilization technologies. To this end, utilization of brewery CO2, which is a readily available yet underexplored carbon source, is feasible via microbial electrosynthesis (MES) technology, though the productivity indicators remain lower. This study provides insights into enhancing the MES productivity from unpurified brewery CO2 through optimization of feed rate and cathode potential (Ecathode), besides assessing the impact of catholyte recirculation on overall production parameters. At an Ecathode of –1V, the Acetobacterium-dominated enriched mixed microbial culture produced up to 6.6g/L acetic acid at 85% coulombic efficiency and cell voltage (Ecell) of 2.98V from brewery CO2 fed continuously at 0.7L/d rate. Acetic acid production decreased at the lower or higher Ecathode and gas feed rate conditions, emphasizing the importance of maintaining an optimal balance between the gas flow rate and Ecathode to achieve efficient H2-mediated production. With the catholyte recirculation loop in reactors operated under the optimized Ecathode and feed rate conditions, acetate production enhanced further to 7.6±0.65g/L at 92% coulombic efficiency and 2.9V Ecell. The improved productivity can be attributed to better mixing and retention of CO2 and H2 in MES reactors, besides the enhanced growth and dominance of key CO2-fixing acetogens belonging to Acetobacterium and Eubacterium genera under the catholyte recirculation condition. The findings suggest that fine-tuning various process parameters is pivotal to achieving the desired MES productivity.

Spraying Power Effect on Micro-Structure and Mechanical Property of TaSi2 Coating Prepared by Supersonic Air Plasma Spraying for SiC-Coated C/C Composites

In order to further improve the oxidation resistance of SiC-coated C/C composites used in extreme environments, TaSi2 coatings were deposited on the surfaces of SiC-coated C/C composites by supersonic air plasma spraying (SAPS) with different spraying power parameters, under other fixed parameter (gas flow, power feed rate, spraying distance and nozzle diameter) conditions. The micro-structures and phase characteristics of the TaSi2 coatings prepared with the four kinds of spraying powers (40 kW, 45 kW, 50 kW and 55 kW) were analyzed. Also, the inter-facial bonding strengths and fracture modes between the four TaSi2 coatings and the SiC coating were studied. The results showed that with an increase in the spraying power, the morphologies of the TaSi2 coatings appeared from loose to dense to loose. When the spraying power was 50 kW, the deposition rate reached a maximum of 39.8%. The TaSi2 coating presented an excellent micro-structure without obvious pores and microcracks, and its inter-facial bonding strength was 15.3 ± 2.3 N. Meanwhile, the fracture surface of the sample exhibited a brittle characteristic.

Prediction of Bonding Strength of Heat-Treated Wood Based on an Improved Harris Hawk Algorithm Optimized BP Neural Network Model (IHHO-BP)

In this study, we proposed an improved Harris Hawks Optimization (IHHO) algorithm based on the Sobol sequence, Whale Optimization Algorithm (WOA), and t-distribution perturbation. The improved IHHO algorithm was then used to optimize the BP neural network, resulting in the IHHO-BP model. This model was employed to predict the bonding strength of heat-treated wood under varying conditions of temperature, time, feed rate, cutting speed, and grit size. To validate the effectiveness and accuracy of the proposed model, it was compared with the original BP neural network model, WOA-BP, and HHO-BP benchmark models. The results showed that the IHHO-BP model reduced the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE) by at least 51.16%, 40.38%, and 51.93%, respectively, while increasing the coefficient of determination (R2) by at least 10.85%. This indicates significant model optimization, enhanced generalization capability, and higher prediction accuracy, better meeting practical engineering needs. Predicting the bonding strength of heat-treated wood using this model can reduce production costs and consumption, thereby significantly improving production efficiency.

PERFORMANCE OPTIMIZATION OF BS970 MILD STEEL TURNING PARAMETERS UNDER SiC-MoS2 HYBRID NANOFLUID USING HYBRID DEEP BELIEF NETWORK BASED COOT OPTIMIZATION

In the modern world of competitive manufacturing, turning is a basic and important process that needs to be optimized for the fast-evolving industrial nature. It has its application in various fields involving numerous materials. This research study deals with modeling with optimization on the turning process parameters of turning E2-BS970 mild steel with cryogenically treated tungsten carbide tool under NFMQL having [Formula: see text] nanofluid. The parameters considered as the input factors are spindle speed and depth of cut along with feed rate and lubrication condition. The design of the experiment is done based on Box–Behnken design for 27 trials in the response surface method. The Deep Neural Network (DBN) and the Coot optimization algorithm are employed using MATLAB software for the prediction modeling. The prediction model developed by the DBN sigmoid function gave minimal error with prediction regression values of 0.99988 for MRR, 0.99516 for Cutting temperature, and 0.99545 for Tool life. The optimized result by CO shows a value of 188.89 rpm for spindle speed, 0.2318[Formula: see text]mm/rev for feed rate, Doc of 1.45[Formula: see text]mm, and 0.5015[Formula: see text]vol.% nanofluid MQL condition. The optimized values of MRR are 3.35[Formula: see text]mm3/min, [Formula: see text]C cutting temperature, and 1543.12[Formula: see text]s of tool life. The DBN model combined with the Coot algorithm shows minimal deviation compared to the experimental results validation and confirmatory analysis and is deemed suitable for efficient prediction.

Study on the friction drilling behaviors and tribological properties of aluminum matrix composites

This study investigates Al 6063 matrix composites reinforced with different weight percentages of B4C (5%, 10%, 15%, and 20%) produced through powder metallurgy and hot extrusion. The resulting specimens were subjected to a comprehensive investigation to elucidate the effect of B4C reinforcement on the density, tensile strength, transverse rupture strength (TRS), hardness, tribological characteristics, and friction drilling behavior. The pin-on-disk wear tests were conducted in a dry environment, while the friction drilling experiments were performed under constant spindle speed and feed rate conditions, both in dry and minimum quantity lubrication (MQL) environments. The findings revealed a uniform B4C particle dispersion and strong interface bonding in the matrix and that the hardness, tensile strength, TRS, and wear resistance of the specimens increased as the weight fraction of the reinforcement increased. The 15 wt% and 20 wt% B4C composites showed the highest wear resistance, improving by 62.78% compared to Al6063. Higher B4C content reduced specific wear rates and reduced friction coefficients. Among the specimens under investigation, the Al6063 composite reinforced with 15 wt% B4C indicated the highest tensile, transverse rupture, whereas the Al6063 composite with 10 wt% B4C exhibited the best thread-pull-out strength (TPS). The friction-drilled 10 wt% B4C composites showed the highest thread-pull-out strength reaching 373.44 N/mm² in MQL and 329.74 N/mm² in dry conditions.

Characteristic research of regeneration process of particulate filter medium in vibrated fluidized bed

Abstract The vibrational fluidized bed is innovatively adopted to regenerate the particulate filter medium for the purification of crude synthesis gas from the coal gasification process. Characteristic research of vibrated fluidized beds during dust-containing particulate filter medium regeneration has been carried out. The ideal transport model of particulate filter medium on the distributor is established and verified by using experiments. The mean residence time of the particulate filter medium can be reduced by 72% from 5.5 to 1.5 min with an increase in the working frequency from 50 to 60 Hz. The thickness of the bed layer is linearly increased with the feeding rate of the particulate filter medium under ideal working conditions. The resistance models of the fluidizing air are built up and validated, and they can be used to calculate the pressure drop of the static bed layer of the particulate filter medium on the fluidizing air distributor, which is the maximum value of the dynamic bed layer with the same thickness. The fluidizing air makes the mean residence time of the particulate filter medium decrease by 50% and reduces the difference in the particulate mean residence time under different feeding-rate conditions. The regeneration effect of dust-containing filter medium particles in a vibrated fluidized bed is evaluated. Fluidizing air with superficial velocity ranging from 0 to 0.6~0.9 m·s–1 makes the regeneration efficiency increase from 29.41% to 70.59~88.24%. This article provides a reference for the industrial application of a vibrated fluidized bed for the particulate filter medium recycling system.

Analysis of Friction stir processed surface quality of AA2098 aluminum alloy for aeronautical applications

FSP is a relatively new technique that changes the microstructure on the surface of the material to improve mechanical properties in the desired zone. This study aimed to investigate the surface quality of AA2098 sheets after being subjected to friction stir processing under different conditions of feed rate and rotational speed. A DoE analysis was developed with two factors, feed rate and rotational speed, and three different levels of 75, 100, 125 mm/min and 1000, 1250, 1500 rpm respectively, in order to assess the processed surface quality. The Sa parameter was used to represent the surface quality in different zones of the process, near entrance tool, middle and near exit tool, and ANOVA analysis was conducted. The results indicated that only the position and feed rate have a statistical influence on surface roughness. Additionally, the surface quality is strongly affected by the position relative to the entrance of the tool and the side (retreating or advancing sides). The roughness was found to be significantly lower on the advancing side rather than on the retreating side.

Growth of high-density single-wall carbon nanotubes with a uniform structure using a CoRu catalyst

The inefficient production of structurally uniform single-wall carbon nanotubes (SWCNTs) is an obstacle to their practical use in high-performance electronic devices. We have synthesized SWCNTs with a narrow diameter distribution (1.35 ± 0.25 nm) using a CoRu catalyst. Monodispersed nanoparticles with a narrow size distribution (2.4 ± 0.6 nm) and different compositions were prepared and used as catalysts for SWCNT growth. A furnace with an 80 cm-long uniform temperature zone (±10 °C) was designed and used to study the effect of catalyst composition on the growth of SWCNTs under the same conditions. By optimizing the composition of the bimetallic CoRu catalyst, SWCNTs with a uniform structure were efficiently synthesized. In addition, the effect of the growth conditions of temperature and carbon feed rate was investigated, and it was found that with an increase in yield, the structural uniformity of SWCNTs usually became worse. Both catalysts with elements in the suitable proportions and appropriate growth conditions are critical to achieving the high-efficiency structure-controlled growth of SWCNTs.

A comparative study on the machinability of β-type novel Ti29Nb13Ta4.6Zr (TNTZ) biomedical alloys under micro-milling operation

β-type Ti29Nb13Ta4.6Zr (TNTZ) alloy is a new-generation alloy that does not contain toxic/allergic elements. The alloys have low Young's modulus (⁓60 GPa) close to the cortical bone, providing excellent biocompatibility over familiar commercial CP Ti or Ti6Al4V ELI. Different macro/micro-machining methods can be used to obtain the final shape of Ti alloys and impact on the implant's bio ecosystem and performance. This study compared the micro-mill machining performance of the TNTZ alloys with commercial CP Ti and Ti6Al4V ELI. Machining experiments were performed under similar and different cutting speeds and constant feed rate conditions. In the study, cutting forces, surface roughness, burr size and tool wear were obtained. The results showed that the Fx cutting forces for TNTZ are about 3 and 2 times higher than for CP Ti and Ti6Al4V alloys, respectively. Depending on the increasing cutting distance, the surface roughness of CP Ti and Ti6Al4V materials followed a similar trend. However, the surface roughness values for TNTZ alloy are higher and decrease with increasing cutting distance. Burr widths for CP Ti and Ti6Al4V are similar, but the milling direction at which maximum burr occurs varies. In the TNTZ alloy, the burr width is about 3 times higher, and the burr occurred inside the slot, not at the edge of the machined slot. The predominant type of damage in milling Ti6Al4V and CP Ti materials is abrasive and adhesive. The dominant damage type in TNTZ alloy is chipping. Increasing the number of revolutions in TNTZ causes the cutting forces and burr width to increase.

Grinding parameters prediction under different cooling environments using machine learning techniques

ABSTRACT Selection of optimum process parameters is vital for performing a sound grinding operation on Inconel 751 alloy. This paper co-relates the relationship between the most influential input parameters like cutting velocity, depth of cut, feed rate, and environmental conditions to the output parameters, namely, tangential grinding forces, normal grinding forces, temperature, and surface roughness. Three types of machine-learning (ML) algorithms such as support vector machine (SVM), Gaussian process regression (GPR), and boosted tree ensemble techniques are employed to develop a ML model for predicting the output variables during grinding operation of Inconel 751. In order to develop a better ML model, K-fold technique is employed on a total of 81 datasets which are extracted from experimental studies. ML models developed from different algorithms are compared based on performance metrics like R2 score and root-mean-square error (RMSE). GPR algorithm exhibits best results with relatively better R2 score and RMSE value in predicting grinding forces and temperature at wheel work interface. From analyzing the ML models, it is found that cooling environments determined the output grinding parameters to a greater extent when compared with the input grinding parameters.

Study on Machining Parameters and Mechanical Properties of Hybrid Agave Sisalana and Glass Fiber-reinforced Polyester Composites (A/GFRP)

ABSTRACT Agave fiber/polymer matrix composites have recently been used in automotive, aerospace, and construction field, where they will be secure for shape-made applications. Hand lay-up is used to make Agave and Glass fiber-reinforced polyester composites (A/GFRP), Agave fiber-reinforced polyester composites (AFRP), and Glass fiber-reinforced polyester composites (GFRP). The impact energy absorbed and tensile strength for A/GFRP material are higher than those for AFRP material. Drilling of GFRP, AFRP, and A/GFRP composites is carried out by using carbide twist drill D 5407060 of 6 mm diameter. Process parameters include two distinct speeds (800 rpm and 1200 rpm) and two distinct feeds (0.02 mm/rev and 0.04 mm/rev). The influences of processing parameters on thrust force and delamination while drilling GFRP, AFRP, and A/GFRP materials are investigated. For the optimum process parameter (feed = 0.02 mm/rev and 800 rpm) for GFRP, AFRP, and A/GFRP, the thrust force and delamination factor are limited at these feed rate conditions. In comparison to AFRP, delamination is minimum for A/GFRP drilled with carbide tools at lower feed rates as per microstructural examination. The Taguchi technique is used to determine the best feed and speed parameters for machining responses, and it demonstrates that acceptable values are achievable with A/GFRP.

Influence of single diamond wire sawing of photovoltaic monocrystalline silicon on the feed force, surface roughness and micro-crack depth

To gain an in-depth understanding of the influence of diamond wire sawing of monocrystalline silicon on the feed force and wafer quality, experiments with a single diamond wire in the form of a loop were performed. The cutting parameters of wire cutting speed, feed rate and wire tension were varied. The feed force was monitored and surface roughness of the specimen was measured. The micro-crack depth was determined using an image processing. The results show that cutting conditions of higher feed rate and higher wire tension increased the feed force by 78% and 20%, respectively, since for chip removal these conditions is required a higher force per grain. On increasing the wire cutting speed, the feed force reduced by 66% due to a decrease in penetration depth of the grains. Based on an analytical model, it was evidenced that volume of material removed per wire length has a significant effect on feed force. The variation of the feed rate and wire cutting speed had a greater effect on surface roughness Ra and Rq, with a minor effect on Rz. With a higher feed rate the micro-crack depth increased, whereas it was reduced on increasing the wire cutting speed. A strong correlation between sawn surface and subsurface damage was found, indicating that the micro-crack depth is around 1.37 times higher than Rz value. The combination of a lower feed rate and lower wire tension with higher wire cutting speed resulted in lower feed force, smoother surface and shallower micro-crack depth.

SOLVENT OPTIMIZATION OF ELECTROSPUN POLY(ACRYLIC ACID) NANOFIBERS

In this study, it was investigated experimentally the influence of various solvents (distilled water and ethanol) on the solution properties, spinning performance, and fibre morphology of the electro spun Poly (acrylic acid) nanofibers. Firstly, polymer solutions were prepared at 5 wt % PAA with various solvent ratios of ethanol and distilled water. Then, solution properties such as viscosity, density, pH, conductivity, and surface tension were determined. The production of nanofiber samples was carried out by electrospinning under the optimum process parameters (voltage, distance between electrodes, feed rate, and atmospheric conditions). Finally, the morphological characterization of the nanofiber surface was carried out with SEM. According to the results, it was observed that conductivity, surface tension and the density of the solution increase as the ethanol ratio decreases. On the other hand, pH value increases as the ethanol ratio increases and, so, the acidic value of the solutions decreases. The viscosity increased until the ethanol/distilled water ratio was 50/50 and then decreased as the ethanol percentage decreased to under 50%. In addition, average fibre diameter decreases with ethanol ratio decreases. It is possible to say that solvent type affects solution properties, fibre morphology and spinning performance significantly. Generally, fine, uniform and bead free nanofibers could be electro spun and the PAA solution containing 70 wt % distilled water and 30 wt % ethanol was selected as the optimum in terms of fibre morphology, web quality and spinning performance.

ELECTROSPINNING OF ANTIBACTERIAL POLYURETHANE/ZnO NANOFIBERS

In this study, it is aimed to produce and characterize antibacterial polyurethane (PU)/Zinc oxide (ZnO) nanofibers by electrospinning method. Firstly, polymer solutions were prepared at various ZnO concentrations such as 0, 0.2, 0.4, 0.6, 0.8, 1. Then solution properties (conductivity, viscosity, surface tension) were determined and analysed the effects of ZnO concentration on the solution properties. PU/ZnO nanofibers produced via electrospinning under the optimum process parameters (voltage, distance between electrodes, feed rate and atmospheric conditions). Finally, the nanofibers were characterized in terms of fibre morphology, thermal stability, permeability and antibacterial activity using SEM-EDS, DSC-TGA, water vapour permeability and disk diffusion methods. According to the solution results; it was observed that conductivity and surface tension decrease significantly with ZnO addition. On the other hand, solution viscosity increases as the ZnO concentration increases. From the SEM images, it has been seen clearly that average fibre diameter increases with ZnO concentration and incorporation of ZnO particles to the fibre structure was verified by SEM-EDS. According to the thermal analyse result, nanofibers begin to degrade between 271.94 ºC and 298.73 ºC. In addition, water vapour permeability increases as the ZnO concentration increase. Lastly antibacterial activity against gram negative (E.coli) and gram positive (S. aureus) was determined with specific zone diameter.

EXPERIMENTAL INVESTIGATION AND OPTIMIZATION OF HIGH SPEED MACHINING OF TITANIUM ALLOY FOR BIOMEDICAL APPLICATION

The Ti-6Al-4V alloy is known as materials with high hardness and good mechanical properties. However, the machining process of this material faces many difficulties due to unfavorable machining conditions. When the machining parameters are not selected in accordance with the Ti-6Al-4V alloy, the surface quality of workpieces does not meet technical requirements. Therefore, the appropriate machining parameters are needed to upgrade the surface roughness of workpieces in high-speed machining (HSM) conditions. The main cutting forces Py and Pz, and surface roughness Rz during turning of Ti-6Al-4V alloy in HSM were investigated and evaluated in this study. The response surface method (RSM) was used to conduct experiments and establish the models of Rz, Py, and Pz under various cutting conditions of feed rate ([Formula: see text]), tool nose radius ([Formula: see text]), and approach angle ([Formula: see text]). As a result, the [Formula: see text] value has the largest impact on the Pz. Moreover, the machining parameters such as [Formula: see text], [Formula: see text], and [Formula: see text] have a great influence on the Py. The magnitude of Rz is mainly affected by [Formula: see text] value. Based on the optimal parameters, the average value of the force Pz has decreased from 238[Formula: see text]N to 169[Formula: see text]N, corresponding reduction of about 29%. The value of the force Py has reduced from 184[Formula: see text]N to 118[Formula: see text]N, corresponding reduction of about 36%. In addition, the surface roughness of the workpiece has been improved significantly from Rz of 5.6[Formula: see text][Formula: see text]m to 2.7[Formula: see text][Formula: see text]m under optimal parameters condition. The surface roughness of the workpiece after processing in high speed machining was reduced of 52% compared with cutting under non-optimal parameters condition. The best surface quality and minimum cutting force could be achieved under optimal processing parameters in high speed cutting method.

Stabilization of high-current buried-arc welding using large diameter ϕ1.6 mm wire by low-frequency modulated voltage control

ABSTRACT The authors focused on a buried-arc phenomenon for a high-efficiency thick-plate welding and developed a ‘low-frequency modulated voltage control’ in order to stabilize a buried arc in a high-current range, which repeats high and low voltage terms using a welding power source with constant-voltage characteristics. When the control was applied to high-current buried-arc welding using solid wires of φ1.2 mm and φ1.4 mm, a rotating transfer mode was observed at a high voltage term. It was clarified that a high-current buried-arc phenomenon was stabilized by supporting the buried space with a rotating arc. On the other hand, when the low-frequency modulated voltage control was applied to a solid wire of φ1.6 mm, it was revealed that a rotating transfer mode was not observed although the control was effective in stabilizing a high-current buried-arc phenomenon. Our study shows its stabilization mechanism based on the experimental observation of the difference in arc phenomena during a buried-arc welding with and without low-frequency modulated voltage control, in this paper. Applying this result, we additionally report a high-efficiency thick-plate welding with a low wire feed rate condition.

Effect of the spray drying conditions on the physicochemical and structural characteristics and the stability of chia oil microparticles

AbstractChia oil has a high content of linolenic and linoleic acids, which are essential for the human body. However, their high degree of unsaturation (double bonds) makes the oil very susceptible to oxidation. In this context, the use of spray drying can be useful strategy to minimize the oxidation of this oil. Thus, the aim was to assess the effects of inlet temperature and feed rate conditions involved in the spray drying process on the physicochemical and morphological characteristics, and stability of the chia oil microparticles with maltodextrin and GA. The microparticles were obtained with a yield of 50%, encapsulation efficiency greater than 87%, low‐moisture content, and mean particle sizes ranging from 3.01 to 4.11 μm. The thermal evaluation and storage evidenced an increase in stability. The 1H HR‐MAS NMR technique showed that the microparticles maintained the characteristic fatty acid profile of chia oil and seeds. Results indicate that the microencapsulation methodology was suitable for preparing microparticles containing chia oil.

A simple image analysis technique for measuring bed surface texture in flume experiments

We present a simple image analysis technique for measuring the sediment composition of the bed surface during flow with bedload transport in flume experiments. The bed was composed by a bimodal mixture of natural sediments and the flow conditions were such that both fractions were mobile. A camera placed 2.5 meters above the flume framed the central part and took pictures every minute, allowing for a high-resolution data acquisition. The two sediment fractions had different colors, thus we developed an image analysis technique based on color detection. This technique provided the areal fraction content of each fraction and the detection of patterns of sorted sediments, namely patches of each grain size, and it was applied in three laboratory experiments conducted to study the influence of lateral width constraint on channel morphology, sediment sorting, and bedload transport. The three experiments were carried out under constant feeding rate conditions, in particular a sediment supply equal to the transport capacity was provided, thereby matching dynamic equilibrium conditions. The image processing was implemented through a code written in Matlab and made available for other users.

Parameter Optimization and Effect Analysis of Low-Pressure Abrasive Water Jet (LPAWJ) for Paint Removal of Remanufacturing Cleaning

As an environmentally friendly method, water jet (WJ) technology plays a significant role in the field of remanufacturing cleaning. The cleaning capacity of a WJ is severely restricted by the water pressure, while the impact force will be too large and may damage the cleaned substrate as well as cause energy waste if the pressure is too high. However, by adding abrasives, the cleaning capacity of a low-pressure water jet (LPWJ) will be considerably improved. Although abrasive water jet (AWJ) technology has been used in mechanical machining for decades, very limited research work can be found in the literature for remanufacturing cleaning. In this paper, the role of abrasives in low-pressure abrasive water jet (LPAWJ) cleaning was described. Cleaning performance with different parameters (abrasive feed rate condition, water pressure and standoff distance) in paint removal was experimentally investigated by using the Taguchi design of experiment. The experimental results indicated that the water pressure was the most dominant factor and the optimal parameter combination was the second feed rate condition, 9 MPa water pressure and 300 mm standoff distance. The influence law between the cleaning performance and various factors was explored, which can provide remanufacturers with directions in selection of the optimal parameters in the LPAWJ cleaning process. By designing contrast experiments, the results showed that the cleaning capacity of an LPAWJ is better than that of a pure LPWJ and the residual effect in terms of changes in surface roughness, residual stress and morphology is a little larger.

Antisolvent Crystallization Method and Mixed Solvent Solubility Model Study of 2-Chloro-4,6-Dinitroresorcinol

Antisolvent crystallization method of 2-chloro-4,6-dinitroresorcinol was proposed and discussed for the first time. The yield of the product crystals was over 92.5%. Crystallization was carried out under the ambient temperature; ethanol was used as a solvent and water was used as an antisolvent. The technological conditions of antisolvent feed rate were studied, and 0.75 mL/min was the best operation. The solubility of 2-chloro-4,6-dinitroresorcinol in ethanol/water mixtures at 293.15–343.15 K was determined, and the Jouyban–Acree solubility equation was established. The mean deviation between experimental values and calculated ones was 1.81%.