Experimental Temperature Research Articles

Surface Interaction and Wear Due to Sliding Electrical Contact of Materials

This article reports a research study on sliding electrical contacts of copper–diamond materials, involving modeling and validation, contact status simulations, and parametric studies. The simulation model includes the analyses of both mechanical and electrical heat sources, evaluations of heat partition and temperature, and the capture of material thermal softening, plastic deformation, and material removal. The simulation model is validated through result comparison with experimental average temperature and measured wear. With this model, temperature variation and surface wear accumulation were numerically predicted under the influences of material property variations. Factors influencing wear of the copper surfaces were explored, and parameter sensitivity was investigated by means of the Taguchi L18 matrix. The results reveal that thermally related parameters of the contact interface strongly affect the wear of the copper pin, and thermal conductivity of its mating surface material is of critical importance. The research also suggests that the electromagnetic field change due to switching the polarity of the power supply does not affect the friction and wear results; however, the polarity change influences material electrochemistry, which results in a difference in friction and wear.

The dual action of N2 on morphology regulation and mass-transfer acceleration of CO2 hydrate film

The morphology characteristics of CH4, CO2 and CO2+N2 hydrate film forming on the suspending gas bubbles are studied using microscopic visual method at supercooling conditions from 1.0 to 3.0 K. The hydrate film vertical growth rate and thickness along the planar gas-water interface are measured to study the hydrate formation kinetics and mass transfer process. Adding N2 in the gas mixture plays the same role as lowering the supercooling conditions, both retarding the crystal nucleation and growth rates, which results in larger single crystal size and rough hydrate morphology. N2 in the gas mixture helps to delay the secondary nucleation on the hydrate film, which is beneficial to maintain the pore-throat structure and enhance the mass transfer. The vertical growth rate of hydrate film mainly depends on the supercooling conditions and gas compositions but has weak dependence with the experimental temperature and pressure. Under the same gas composition condition, the final film thickness shows a linear relationship with the supercooling conditions. The mass transfer coefficient of CH4 molecules in hydrates ranges from 4.54 to 7.54×10–8 mol·cm–2·s–1·MPa–1. The maximum mass transfer coefficient for CO2+N2 hydrate occurs at the composition of 60% CO2+40% N2, which is 3.98×10–8 mol·cm–2·s–1·MPa–1.

Application of semiempirical correlations for multidimensional heat transfer in rocket engine cooling channels

Heat transfer in cooling channels of liquid rocket engine thrust chambers is an intrinsically multidimensional problem due to the geometry of the channels, often rectangular in section, and the asymmetric distribution of heat input from the hot combustion gas. In this study, the possibility of addressing this problem with semiempirical correlations for the coolant heat transfer and multidimensional numerical simulations for the heat conduction in the wall is investigated. Using experimental data from a test campaign of a cooling channel representative of liquid rocket engine conditions, semiempirical correlations are derived. Both cases of constant and variable heat transfer coefficient along the perimeter of the channel section are considered. The resulting correlations are then used to evaluate their reliability in reproducing the experimental wall temperature data from the same test campaign. For comparison, a correlation taken from the open literature and obtained with experimental data of circular heated tubes is also considered. The results demonstrate that correlations based on a constant heat transfer coefficient fail to reproduce with sufficient accuracy the test cases characterized by higher wall temperatures, while correlations based on a variable heat transfer coefficient overestimate the wall temperature in the initial sections of the channel.

SIMULATION OF LIQUID FUEL SPRAY FORMATION AND DISTRIBUTION IN A REACTING TURBULENT FLOW

The paper presentsthe computational experiments of the liquid fuels spray and its droplets distribution in a turbulent reacting flow. Primary and secondary atomization of two types of liquid fuel droplets (isooctane and dodecane) in the presence of combustion was described by the equations of continuity, momentum, internal energy, concentration of components of reacting substances and a two-parameter model for calculating turbulent flow. The study results of the spray, dispersion and combustion of droplets of hydrocarbon liquid fuels in a model combustion chamber when changing the injector injection angle were obtained. The injection angle values varied from 2 to 10 degrees. Based on the computational experiment temperature profiles and concentration characteristics of combustion products and gas in the combustion chamber at various times were obtained. Numerical calculations of the droplets’ Sauter mean diameter distributions have the same dispersion pattern for dodecane. This suggests that the accuracy and adequacy of developed complex model of the formation and distribution of spray in a reacting flow has been confirmed by its strong correlation and good agreement of the modeling results with experimental data from other researchers. This kind of modeling methods and the obtained computational experiments results from them are widely used not only in traditional thermal power engineering, but also in the study of technological processes in the new generation engines chambers, combustion of alternative types of fuels and optimization of their combustion.

Oxidation resistance, corrosion behavior and grinding performance of laser-deposited TaMoCrTiAl refractory high-entropy coating

In this study, TaMoCrTiAl refractory high-entropy alloy coating without defects was successfully prepared on the Ti6Al4V substrate by laser metal deposited. Microstructure and properties were investigated systematically by multiple characterization methods. The results of phase and morphology experiments indicate that the coating comprised a BCC phase and a partial Laves phase. The coating, with an average thickness of 990 μm, exhibits good metallurgical bonding with the substrate. Further observation reveals that the cladding region consists of irregular bulk crystals. The heat-affected zone has a fine grain size, whereas the substrate has coarse and uneven grains. The high-temperature oxidation test shows that the formation of an Al2O3 oxide layer enhances the coating's high-temperature oxidation resistance. According to the results of microhardness tests, the average microhardness in the coating is about 570.98 HV (1.87 times that of the substrate) due to the formation of the leave phase particles and the fine-grain strengthening. The presence of Titanium, chromium and molybdenum elements in the coating facilitates the formation of a passivation film, thereby enhancing its corrosion resistance. Furthermore, the coating exhibits the smallest grinding force (43.637 N) and the lowest roughness (0.506 μm) at an experimental temperature of 100 °C, which demonstrates that appropriately elevating the experimental temperature can decrease the grinding force and enhance the flatness of the grinding surface.

Assessment of CFD Predictions Using Experiments from a Heated Gas-Cooled Pebble Bed Facility

This paper presents computational fluid dynamics (CFD) simulations of the coolant gas flow in a pebble bed reactor core to assess the suitability of CFD models to accurately predict the temperature distribution and possible occurrence of local hot spots that may affect pebble integrity. This study assessed CFD predictions against temperature distribution measurements from the SANA test facility at the Research Center Jülich in Germany. A realistic pebble bed structure of randomly packed 1584 pebbles was produced using the discrete element method to model the pebble packing in detail. A total of 96 experimental temperature pebble points were used for the assessments, covering a broad range of heating powers (10 kW ≤ Poperation ≤ 35 kW). A good agreement between the CFD predictions and the SANA measurements was obtained for two coolants, nitrogen and helium, along the height of the pebble bed. It is anticipated that a better understanding of the suitability of the existing CFD models gained through this study will aid in the identification of gaps and areas of improvement for CFD to support the design and safety evaluations for pebble bed small modular reactors.

Heat and moisture transfer through skin-clothing microclimate

The microclimate between clothing and human skin plays an important role in the heat and moisture exchange between body and ambient environment, which is essential to the thermo-physiological comfort. Despite extensive research on microclimate heat transfer, the sweating process accompanying heat transfer has often been neglected, and the investigation of transport mechanisms is limited. In this study, the heat and moisture transfer from skin to environment was experimentally and numerically simulated with focus on factors such as microclimate thickness (0 mm ∼ 40 mm), tilt angle (0° ∼ 90°), and airflow direction (parallel and normal to the fabric surface). The skin was represented by a surface with uniform temperature in experiments and numerical simulations, and the fabric was modeled as an air-permeable porous medium in the numerical simulations. The experimentally validated numerical model provided detailed distributions of temperature, vapor concentration, and airflow patterns in the microclimate for both dry and wet skins. The airflow of natural convection featured multiple circulation cells, and their circulation times were calculated and then related to the microclimate transport performance. It was found that natural convection dominates the heat and moisture transfer in thicker microclimates. It was also found that normal airflow was more effective in facilitating the heat and moisture transfer as compared to parallel airflow. The results are useful for developing high-performance clothing optimized for thermal regulation and moisture management, improving comfort and safety in different conditions.

Magnetic Particle Imaging-Guided Thermal Simulations for Magnetic Particle Hyperthermia.

Magnetic particle hyperthermia (MPH) enables the direct heating of solid tumors with alternating magnetic fields (AMFs). One challenge with MPH is the unknown particle distribution in tissue after injection. Magnetic particle imaging (MPI) can measure the nanoparticle content and distribution in tissue after delivery. The objective of this study was to develop a clinically translatable protocol that incorporates MPI data into finite element calculations for simulating tissue temperatures during MPH. To verify the protocol, we conducted MPH experiments in tumor-bearing mouse cadavers. Five 8-10-week-old female BALB/c mice bearing subcutaneous 4T1 tumors were anesthetized and received intratumor injections of Synomag®-S90 nanoparticles. Immediately following injection, the mice were euthanized and imaged, and the tumors were heated with an AMF. We used the Mimics Innovation Suite to create a 3D mesh of the tumor from micro-computerized tomography data and spatial index MPI to generate a scaled heating function for the heat transfer calculations. The processed imaging data were incorporated into a finite element solver, COMSOL Multiphysics®. The upper and lower bounds of the simulated tumor temperatures for all five cadavers demonstrated agreement with the experimental temperature measurements, thus verifying the protocol. These results demonstrate the utility of MPI to guide predictive thermal calculations for MPH treatment planning.

Droplet freeze desalination high fidelity modeling for sustainable water purification and diverse applications

Freeze desalination (FD) is an environmentally clean water purification technique that holds a great promise for low-energy consumption and with unlimited brine's salinity levels. The brine cooling induces freezing, rendering separation and removing contaminants. A high-fidelity molding using CFD is employed to explain the purification of ice from saline droplets in a sub-cold environment under natural free-convection. Comparisons were made with analytical predictions derived from experimentally acquired data through brine cooling in bulk and droplet scales. The procedural sequence employed facilitated the model's ability to accurately represent the ion diffusion and phase-change phenomena across various temperatures (−15 °C and − 25 °C), concentrations, partition & heat-transfer coefficients, and droplet volumes (3 μL to 9 μL). The salt concentration ranged from seawater (35 g/L) to RO (70 g/L) salinity levels. The model successfully accommodates the experimental temperatures observed during the equilibrium between the solid and liquid phases. The achieved desalination efficiency ranges from 20 % to above 40 %. Lastly, machine learning is implemented to identify the principal experimental parameters influencing desalination efficiency. In the suggested system, dynamic salinity/impurity and temperature profiles enable natural free convection brine cooling research. The current framework can study the purification/concentration efficiency of diverse range of mixtures subjected to freeze crystallization.

Study on thermodynamic parameters of volatile components in polydimethylsiloxane and polystyrene

In polymer production, devolatilization is an important unit operation that separates low molecular weight components from the polymer system. The presence of volatile matter not only reduces the quality of the product, but may also cause harm to users and the environment. The Henry’s coefficient is the most fundamental parameter in the vapor–liquid equilibrium relationship. The Henry’s coefficient of n-pentane, n-hexane, and n-octane for polydimethyl siloxane (PDMS) and polystyrene (PS) were measured using the pressure difference method. The influence of different operating conditions on Henry’s coefficient has been studied. The results indicate that as the experimental temperature increases, the Henry’s coefficient of volatile matter gradually increases. The viscosity of polymers has little effect on the Henry’s coefficient. Under the same volatile matter conditions, when the viscosity increases from 50 cst to 5000 cst, the maximum growth rate of the Henry’s coefficient is only 5%. As the number of carbon atoms increases, the Henry’s coefficient decreases. This work provides theoretical guidance for polymer devolatilization processes in industry.

PARTICLE SWARM OPTIMIZATION AND CFD ANALYSIS OF A HEAT SINK FOR FORCED CONVECTIVE COOLING OF A DC/AC INVERTER

Power inverters play a crucial role in converting DC voltage and current to AC voltage and current. Its efficient operation relies on effective thermal management of the semiconductor devices, such as the IRF 3205 MOSFET chip which facilitate the switching operations to prevent thermo-mechanical stress that could to failure. This research developed and optimize a heat sink for an IRF 3205 MOSFET chip in a 3.5 KVA power inverter, using the Particle Swarm Optimization technique and experimented with a 3.5 KVA 24 V power inverter operating a 1.5HP air-conditioning unit. The heat sink geometry has 26 fins, 4 mm fin thickness, 40 mm fin height, 3 mm fin spacing, 2 mm fin base thickness, 179 mm length, 80 mm width and a thermal resistance of 60.75 °C/W. The thermal performance was evaluated using ANSYS Computational Fluid Dynamics (CFD) and results showed maximum base temperature of 65.85°C and experimental temperature of 64°C after two hours of steady operation dissipating heat of 45W. The results from both numerical and experimental data demonstrate the effectiveness of the optimized heat sink in maintaining the chip's temperature below its maximum working threshold of 170°C.

Response of hyporheic biofilms to temperature changes and dissolved organic carbon enrichment: a mesocosm study

PurposeHyporheic biofilms are the central site for biogeochemical cycling in streams and rivers. In view of global warming and increasing human pressures, this study aimed to compare the response of hyporheic biofilm biomass and activities from an unpolluted reference stream reach surrounded by forest with those from a stream reach exposed to agricultural and urban land use using a mesocosm experiment in which the water temperature and dissolved organic carbon (DOC) contents were manipulated.MethodsHyporheic sediments collected in the field from the two study reaches (i.e. reference and impacted) were incubated in the laboratory at two different temperatures (10 °C, 14 °C) and wetted with three types of synthetic water (control [C] – 0 mg L−1; low DOC – 5 mg L−1; high DOC – 30 mg L−1) for four weeks. The responses of the hyporheic biofilms were measured weekly using structural (total protein content [TPC] as a proxy for biofilm biomass) and functional measures (electron transport system activity [ETSA] and community-level physiological profiling [CLPP]).ResultsThe response of hyporheic biofilms to temperature changes and DOC enrichment was site-specific for all studied measures (TPC, ETSA and CLPP, including measured average well colour development [AWCD]). The addition of DOC to biofilms from the pristine stream reach significantly heightened the responses at 10 °C, a temperature within the normal environmental temperature ranges of the reference location, but not at 14 °C, which was here, a temperature outside normal environmental range. On the other hand, biofilms from the impacted stream reach exhibited increased responses following DOC enrichment under both temperature regimes, with a particularly pronounced response at 14 ºC, in this case, both experimental temperatures were within the normal environmental temperature ranges of the study locations.ConclusionHyporheic biofilms were shown to be, like benthic biofilms, sensitive to temperature changes and organic enrichment, but their response to temperature changes and enrichment caused by climate change and/or other anthropogenic pressures (i.e. point and non-point pollution, removal of the riparian zone, hydromorphological modifications, etc.) was not simply linear but site-specific. The intensity of the response, characterized by increased activity and biomass production, appears to be constrained within the temperature ranges prevalent in the environment from which the biofilms originate. These findings emphasize the importance of site-specific considerations in predicting the impacts of climate change and anthropogenic pressures on these critical components of river and stream ecosystems.

Validation of a Hybrid Domain Overlapping Coupling Between SAM and CFD Against the TALL-3D Transients

The system thermal-hydraulic (STH) code SAM has been coupled to the computational fluid dynamics (CFD) code Simcenter STARCCM+ utilizing a hybrid domain overlapping coupling method in space and an explicit coupling in time. The coupling aims to extend the STH code’s applicability to scenarios where local momentum and energy transfers are important yet difficult for STH standalone models to capture, such as three-dimensional (3D) mixing and thermal stratification. The coupling method’s numerical stability was previously verified against multiple test cases including two closed-loop configurations, and it was validated against a double T-junction experiment with 3D scalar mixing. In the present work, the method is validated against the TALL-3D STH/CFD coupling benchmark facility. TALL-3D is a liquid-metal facility with a large, pool-type enclosure (test section) that exhibits 3D flow effects to be modeled by a CFD code. The rest of the system exhibits approximately one-dimensional behavior that is well predicted by a STH code. First, a STAR-CCM+ CFD model of the 3D test section is validated against experimental temperature data. Then a SAM-STARCCM+ coupled model is validated against six different TALL-3D steady states and includes SAM standalone results for comparison. Last, the coupled model is validated against two TALL-3D transients: one exhibiting flow reversal in the test section and one exhibiting nonlinear, limit cycle oscillations (LCOs). For the first transient, the SAM-STARCCM+ coupled model properly predicts an increase in the test section’s inlet temperature during flow reversal, and this increase is not predicted by the SAM standalone model. The coupled model also better predicts initial flow recovery and subsequent oscillations as the system approaches a final natural circulation state. For the second transient, no true final steady state is observed due to LCOs. Neither the SAM-STARCCM+ coupled model nor the SAM standalone model can perfectly capture the experiment’s changing oscillation frequency during the transient. Nevertheless, the coupled model does reproduce the general oscillatory feedback observed. This is a significant achievement because the present coupling only uses an explicit coupling in time, as opposed to a tighter, semi-implicit coupling. In comparison, STH/CFD coupling efforts previously performed by other authors required a semi-implicit coupling to obtain similar results to this work. The strengths of the novel coupling scheme validated in the present paper lie in the superior convergence characteristics and the much simpler, nonintrusive implementation.

Key determinants of soil labile nitrogen changes under climate change in the Arctic: A meta-analysis of the responses of soil labile nitrogen pools to experimental warming and snow addition

The Arctic terrestrial ecosystems are undergoing rapid climate change, causing shifts in the dynamics of soil nitrogen (N), a pivotal but relatively underexplored component. To understand the impacts of climate change on soil labile N pools, we performed meta- and decision-tree analyses of 391 observations from 38 peer-reviewed publications across the Arctic, focusing on experimental warming and snow addition. Soil dissolved organic nitrogen (DON), ammonium (NH4+), and nitrate (NO3-) pools under experimental warming exhibited overall standard mean differences (SMDs) ranging from −0.08 to 0.02, with no significance (P > 0.05); however, specific conditions led to significant changes. The key determinants of soil labile N responses to warming were experimental duration and mean annual summer temperature for DON; annual precipitation, soil moisture, and sampling timing for NH4+; and soil layer for NO3-. Snow addition significantly increased all labile N pools (overall SMD = 0.23–0.36; P < 0.05), influenced by factors such as sampling timing and vegetation type for DON; experimental duration and soil moisture for NH4+; and soil pH for NO3-. By consolidating and reprocessing datasets, we not only showed the overall responses of soil labile N pools to climate manipulation experiments in Arctic tundra ecosystems but also identified key determinants for changes in soil N pools among environmental and experimental variables. Our findings demonstrate that warming and snow-cover changes significantly affect soil labile N pools, highlighting how the unique environmental characteristics of different sites influence terrestrial N cycling and underscoring the complexity of Arctic N dynamics under climate change.

Insights into pyrolysis product characteristics and carbon structure evolution of bituminous coal under high-temperature thermal shock

The current investigation aims to reveal the pyrolysis characteristics and particle microstructure evolution of bituminous coal under the high-temperature thermal shock. In the experimental temperatures, the purification of carbon matrix in the coal char is a successive process linear on temperature. In contrast, the graphitization process of carbon structure existed a transition temperature (1600 ℃). Specifically, the range of 1000–1500 ℃ is critical for the transformation of amorphous carbon to disordered graphite, but the growth of graphite microcrystals was minimally affected. While the range of 1600–1900 ℃ is critical for the formation of the graphite-like carbon structure. It is characterized by the release of defective structures such as oxygen-containing functional groups, and a significant increase in crystal size. Although beneficial for the subsequent study of carbon materials, the ordered graphite transformation led to the deactivation of char. The pyrolysis behavior study under thermal shock insight into the thermal behavior of coal char in high-temperature furnaces, as well as a new idea for the clean utilization of coal resources.

Understanding shape selectivity effects of hydroisomerization using a reaction equilibrium model.

We study important aspects of shape selectivity effects of zeolites for hydroisomerization of linear alkanes, which produces a myriad of isomers, particularly for long chain hydrocarbons. To investigate the conditions for achieving an optimal yield of branched hydrocarbons, it is important to understand the role of chemical equilibrium in these reversible reactions. We conduct an extensive analysis of shape selectivity effects of different zeolites for the hydroisomerization of C7 and C8 isomers at chemical reaction equilibrium conditions. The reaction ensemble Monte Carlo method, coupled with grand-canonical Monte Carlo simulations, is commonly used for computing reaction equilibrium of heterogeneous reactions. The computational demands become prohibitive for a large number of reactions. We used a faster alternative in which reaction equilibrium is obtained by imposing chemical equilibrium in the gas phase and phase equilibrium between the gas phase components and the adsorbed phase counterparts. This effectively mimics the chemical equilibrium distribution in the adsorbed phase. Using Henry's law at infinite dilution and mixture adsorption isotherm models at elevated pressures, we calculate the adsorbed loadings in the zeolites. This study shows that zeolites with cage or channel-like structures exhibit significant differences in selectivity for alkane isomers. We also observe a minimal impact of pressure on the gas-phase equilibrium of these reactions at typical experimental reaction temperatures 400-700K. This study marks initial strides in understanding the reaction product distribution for long-chain alkanes.

Enhancing Machine-Learning Prediction of Enzyme Catalytic Temperature Optima through Amino Acid Conservation Analysis.

Enzymes play a crucial role in various industrial production and pharmaceutical developments, serving as catalysts for numerous biochemical reactions. Determining the optimal catalytic temperature (Topt) of enzymes is crucial for optimizing reaction conditions, enhancing catalytic efficiency, and accelerating the industrial processes. However, due to the limited availability of experimentally determined Topt data and the insufficient accuracy of existing computational methods in predicting Topt, there is an urgent need for a computational approach to predict the Topt values of enzymes accurately. In this study, using phosphatase (EC 3.1.3.X) as an example, we constructed a machine learning model utilizing amino acid frequency and protein molecular weight information as features and employing the K-nearest neighbors regression algorithm to predict the Topt of enzymes. Usually, when conducting engineering for enzyme thermostability, researchers tend not to modify conserved amino acids. Therefore, we utilized this machine learning model to predict the Topt of phosphatase sequences after removing conserved amino acids. We found that the predictive model's mean coefficient of determination (R2) value increased from 0.599 to 0.755 compared to the model based on the complete sequences. Subsequently, experimental validation on 10 phosphatase enzymes with undetermined optimal catalytic temperatures shows that the predicted values of most phosphatase enzymes based on the sequence without conservative amino acids are closer to the experimental optimal catalytic temperature values. This study lays the foundation for the rapid selection of enzymes suitable for industrial conditions.

Density pedestal prediction model for tokamak plasmas

A model for the pedestal density prediction based on neutral penetration combined with pedestal transport is presented. The model is tested against a pedestal database of JET-ILW Type I ELMy H-modes showing good agreement over a wide range of parameters both in standalone modelling (using the experimental temperature profile) and in full Europed modelling that predicts both density and temperature pedestals simultaneously. The model is further tested for ASDEX Upgrade and MAST-U Type I ELMy H-modes and both are found to agree with the same model parameters as for JET-ILW. The JET-ILW experiment where the isotope of the main ion is varied in a D/T scan at constant gas rate and constant βN is successfully modelled as long as the separatrix density ( ne,sep) and pedestal transport coefficient ratio ( D/χ) are varied in accordance with the experimentally observed variation of ne,sep and the isotope dependence of D/χ found in gyrokinetic simulations. The predictions are found to be sensitive to ne,sep which is why the model is combined with an ne,sep model to predict the pedestal for the STEP fusion reactor.

Effects of synthesis conditions on particle size and pore size of spherical mesoporous silica

The particle size and pore size of spherical mesoporous silica materials play significant roles in their application. However, relatively limited systematic research has been conducted on how preparation conditions influence these properties. In particular, the effects of some important factors have not been adequately studied, including reaction time, reaction temperature, and organic solvent type. In this work, octane and water were used as solvents, and tetraethyl orthosilicate was used as the silicon source to systematically study the effects of reaction time, reaction temperature, different organic solvents, octane/water mass ratio, styrene template concentration, and surfactant (cetyltrimethylammonium bromide, CTAB)/H2O mass ratio on the particle morphology, particle size, and pore size of silica. The results suggest that the above-mentioned neglected factors exert a substantial influence on both particle size and pore size. In the experimental temperature range, the pore diameter decreases and the particle size increases with increasing temperature. The maximum particle size and pore size are achieved after a reaction time of 3 h, and a further increase in reaction time leads to a smaller particle size and pore size. As the number of carbon atoms in the organic solvent decreases, the pore size also gradually increases. Styrene and organic solvents that dissolve in CTAB micelles are crucial factors in pore formation, while the aggregation of the swollen CTAB micelles influences the particle size. The changes in the pore structure stability and hydroxyl density of the synthesized samples in water were also studied. After undergoing water treatment at temperatures ranging from 20 to 60 °C for 72 h, both the pore structure and morphology remain relatively unchanged. When the temperature increases, the surface hydroxyl density exhibits a more pronounced increase in the presence of water. After water treatment for 5 h, the surface hydroxyl density reaches saturation.

CORROSION INHIBITION BEHAVIOUR OF CUSTARD APPLE LEAVES AND ACACIA CONCINNA EXTRACT ON MILD STEEL IN ACIDIC MEDIA: ADSORPTION AND THERMODYNAMIC STUDY

Custard apple leaves extract (CALE) was tested to evaluate corrosion inhibition efficiency for mild steel under acidic medium. The test metal substrate was collected over a period of 24 hr of contacting with acid to determine the corrosion inhibition efficiency (CIE) and corrosion rate (CR) using the Gravimetric analysis. The findings of the study were applied to examine the adsorption behavior and thermodynamic characteristics for CALE as a potential corrosion inhibitor in acidic environment. Mild steel exhibited the highest corrosion rate in the absence of a corrosion inhibitor in a 0.5 M sulphuric acid solution. However, the rate of corrosion was observed to decrease gradually with increase in CALE concentration (0.4–2.0 g/l). The similar trend was noted at the experimental temperature range of 298-328 K. Adsorption behavior was investigated using the Langmuir, Temkin, Freundlich, and Flory Huggins adsorption isotherm models. The Temkin adsorption isotherm model provides the best fit to the experimental data. Besides, the negative values of Gibb’s free energy of adsorption (ΔGad) reveal strong evidence for the spontaneous nature of CALE adsorption on mild steel surface. The increase in activation energy (Ea) from 35.05 kJ/mol in the blank test solution to 68.03 kJ/mol at 2.0 g/l concentration of CALE indicates the formation of a protective film of inhibitor molecules on the metal surface. Adsorption enthalpy values (∆H=31.28-73.79 kJ/mol) over the concentration range (0-2.0g/l of CALE) implies physical adsorption, whereas negative entropy values (ΔS) suggests free movement of inhibitor molecules in the bulk solution. Additionally, a synergistic effect was demonstrated in lowering the corrosion rate by combining Acacia concinna extract (ACE, 0.1-0.3 g/l) with CALE, thereby enhancing the overall corrosion inhibition efficiency. For citation: Jitendra Kisan Shinde, Ravindra Gulab Puri, Pawan Devidas Meshram, Rajkumar Shankarrao Sirsam Corrosion inhibition behaviour of Custard apple leaves and Acacia concinna extract on mild steel in acidic media: adsorption and thermodynamic study. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2024. V. 67. N 7. P. 119-126. DOI: 10.6060/ivkkt.20246707.7038.