Kinetic Mechanism Research Articles

Elucidating the Selective Mechanism of Drugs Targeting Cyclin-Dependent Kinases with Integrated MetaD-US Simulation.

Cyclin-dependent kinases (CDKs), including CDK12 and CDK13, play crucial roles in regulating the cell cycle and RNA polymerase II activity, making them vital targets for cancer therapies. SR4835 is a selective inhibitor of CDK12/13, showing significant potential for treating triple-negative breast cancer. To elucidate the selective mechanism of SR4835 among three CDKs (CDK13/12/9), we developed an innovative enhanced sampling method, integrated well-tempered metadynamics-umbrella sampling (IMUS). IMUS synergistically combines the comprehensive pathway exploration capability of well-tempered metadynamics (WT-MetaD) with the precise free energy calculation capability of umbrella sampling, enabling the efficient and accurate characterization of drug-target interactions. The accurate calculation of binding free energy and the detailed analysis of the kinetic mechanism of the drug-target interaction using IMUS successfully elucidate the drug selectivity mechanism targeting the three CDKs, showing that the selectivity is primarily arising from differences in the stability of H-bonds within the Hinge region of the kinases and the interaction patterns during the protein-ligand recognition process. These findings also underscore the utility of IMUS in efficiently and accurately capturing drug-target interaction processes with clear mechanisms.

Thermochemistry of Solid-State Formation, Structure, Optical, and Luminescent Properties of Complex Oxides Eu2MeO6 (Me-Mo, W), Eu2W2O9: A Combined Experimental and DFT Study.

Complex oxides Eu2MeO6 (Me-Mo, W), Eu2W2O9 were obtained by a solid-phase reaction between binary oxides. The thermodynamic and kinetic mechanisms of the reaction processes were established using a variety of physical-chemical methods. All compounds obtained in this work crystallize in the low-symmetry monoclinic system, forming complex framework structures, which determine a set of very valuable physical-chemical properties. Comparison of experimental Kubelka-Munk functions and DFT- calculated absorption spectra shows adequate agreement and reveals the origin of the fundamental absorption. In addition, the deficiency in DFT calculations in the part of mutual contribution of CTBs of Mo-O and W-O, from one side, and Eu-O contributions, from the other side, is reported. Calculations of absorption spectra are shown to be superior to band structure analysis in the determination of optical band gaps. Additionally, luminescent properties of Eu2MeO6 and Eu2W2O9 compounds were investigated. These studies provide a better understanding of the electronic and optical properties of the compounds Eu2MeO6 and Eu2W2O9, along with their potential applications in various areas.

Development of Detailed and Reduced Chemical Kinetic Models for Ammonia Gas Turbines

Abstract The power generation sector has been recently moving towards decarbonization and there is an increased interest in replacing conventional fossil fuels with fuels that produce reduced/zero carbon emissions. One such fuel is ammonia (NH3). However, ammonia is hard to ignite, has a low flame speed, and produces a significantly large amount of nitrogen oxide (NOx) emissions. Hence, using 100% ammonia as fuel in gas turbines requires significant modifications and the development of novel combustors. Blending hydrogen with ammonia, however, helps in having better control over the combustion properties. Before utilizing hydrogen-blended ammonia in an actual gas turbine combustor, thorough simulation studies are required to evaluate its performance, possible hazards, and emissions. The literature lacks well-validated chemical kinetic models for the combustion of hydrogen-blended ammonia for undiluted mixtures at gas turbine-relevant conditions (~20 bar). Hence, in this work, we develop a detailed chemical kinetic model for hydrogen blended ammonia combustion and validate it with a wide range of experimental data for both dilute and undiluted mixtures relevant to gas turbine operating conditions. The detailed chemical kinetic mechanism was reduced to a smaller version (32 species mechanism) without significant loss in accuracy using the direct relation graph with error propagation (DRGEP) and full species sensitivity analysis. The resultant mechanism can predict a wide range of experimental results with the least cumulative error and will be a valuable tool in CFD simulations that will enable the development of gas turbines for zero-carbon power generation.

Stage development characteristics of oxygen-lean combustion of coal in fire zone: Leap-migration mechanism, kinetic transition mechanism, and critical oxygen concentration

Effectively preventing the re-ignition of fire zones and safely unsealing enclosed fire zones are challenging. To address these issues, a thermogravimetric analysis technique was used to explore the leap-migration mechanism of the characteristic parameters (burnout index (H), comprehensive combustion performance parameters (Cb, S, and HF), and maximum combustion mass loss rate (dWmax))/temperatures (maximum pyrolysis mass loss rate point temperature (TVmax), pyrolysis endpoint temperature (Td), thermal polycondensation endpoint temperature (Tp), maximum combustion mass loss rate point temperature (TWmax), burnout temperature (Th), and combustion half-peak width (ΔT1/2)) of low-rank coal oxygen-lean combustion under different time-scale effects (TSEs). The sensitivity of characteristic parameters/temperatures to changes in oxygen concentration under coal rank transition was analyzed. Simultaneously, the kinetic real-time transformation mechanism during the oxygen-lean combustion stage progression was investigated. The results revealed that because of the competition between oxidation and pyrolysis, the leap-migration interval of characteristic parameters/temperatures for oxygen-lean combustion of low-rank coals is in the range of 5 %–3% oxygen concentration. This feature was less affected by the coal rank but is not affected by the TSE. In the low oxygen-lean range (5 %-1%), a change of oxygen concentration was more sensitive to the coal rank, and the high sensitivity of the oxygen concentration change reduced the influence of the coal rank on coal combustion performance. In addition, the apparent activation energy (Eα) curves during the early stage of combustion were relatively concentrated with the change of oxygen concentration, but relatively dispersed during the late stage of combustion. At 3 % oxygen concentration, the Eα values of different coals began to continuously decrease with increasing conversion rate, approaching the spontaneous reaction activation energy value of 40 kJ/mol. At oxygen concentration of 1 % reflected the complete limitation of the oxidation consumption reaction. Therefore, the critical oxygen concentration of typical low-rank coal oxygen-lean combustion was determined below 3 % oxygen concentration. The results of this study can provide scientific guidance for the unsealing of fire zones, and the effective prevention and control of the formation of new fire zone disasters.

Convergent synthesis, kinetics and computational attributions of indole-N-phenyltriazole hybrids bearing N-(aryl)butanamides as alkaline phosphatase inhibitors

In the research delineate herein, an innovative sequence of new series of multi-functional target molecules (9a-i) having indole-N-phenyltriazole bi-heterocyclic hybrids unified with N-arylated butanamides was synthesized as alkaline phosphatase inhibitor. The structural validation of all the formulated compounds was accomplished through IR, EI-MS, 1H NMR, 13C NMR and CHN analysis data. The in vitro enzyme inhibitory investigation revealed the efficacy of these bi-heterocyclic derivatives, 9a–i, as potent inhibitors of alkaline phosphatase relative to the standard used. The compound 9h was found to be the most active compound (IC50 = 0.062 ± 0.017 μM), and its inhibitory activity is about 10 times higher than potassium dihydrogen phosphate (KH2PO4) (IC50 = 5.251 ± 0.468 μM). The kinetics mechanism was attributed by evaluating the Lineweaver–Burk plots, which revealed that compound 9h inhibited the alkaline phosphatase non-competitively to form an enzyme–inhibitor complex. The inhibition constant Ki determined from Dixon plots for this compound was 0.045 μM. The computational study was in full agreement with the experimental records and these ligands exhibited good interactions and binding energy values. These molecules also demonstrated mild cytotoxicity toward red blood cell membranes when analyzed through hemolysis. So, based on the presented results, these molecules, being the promising inhibitors of alkaline phosphatase, might be deliberated as suitable medicinal scaffolds to render normal calcification of bones and teeth.

An experimental study of surrogates of diesel from indirect coal liquefaction and the development of an improved kinetic mechanism

The increasing energy shortage and environmental pollution make the use of clean and efficient alternative fuels an effective way to solve the emission problem. Diesel from indirect coal liquefied (DICL) is a clean and efficient alternative fuel for diesel engines. The composition and chemical kinetics mechanism of DICL research contributes to a better understanding of combustion and pollutant formation process. The components of DICL were analysed by gas chromatography-mass spectrometry (GC-MS). The proportion of normal alkanes contained in DICL is particularly high, 93.82%, which proves that its reactivity is particularly good. The mixture of n-dodecane and iso-octane was selected as the surrogates of DICL. The oxidation process of DICL surrogates was examined by a jet-stirred reactor (JSR) over the temperature range of 500–890 K. A detailed kinetic mechanism of surrogates encompassing 1356 species and 6008 reactions was constructed. The critical reactions associated with the reactivity of surrogates were adjusted by the sensitivity analysis method to increase the accuracy of mechanism prediction. The predicted value of the improved mechanism is in good agreement with the experimental value. The improved mechanism can reasonably predict the oxidation process and the ignition characteristics of DICL and the improved mechanism can provide a good reference value for the subsequent analysis of combustion and emission problems of DICL. Abbreviations: C/H, C/H ratio; CN, cetane number; DDCL, direct coal liquefy diesel; DICL, Diesel from indirect coal liquefied; GC-MS, gas chromatography-mass spectrometry; HMN, 2,2,4,4,6,8,8-heptamethylnonane; HXN, n-hexadecane; IDT, ignition delay time; JSR, jet-stirred reactor; LHV, low heating value; LLNL, Lawrence Livermore National Laboratory; NSRL, National Synchrotron Radiation Laboratory; NTC, negative temperature coefficient; PICS, photoionization cross section; PRF, gasoline substitute; PSR, perfectly stirred reactor; SVUV-PIMS, Synchrotron VUV photoionization mass spectrometry; TOF-MS, time-of-flight mass spectrometer

Isoconversional Analysis of the Catalytic Pyrolysis of ABS, HIPS, PC and Their Blends with PP and PVC.

Thermochemical recycling of plastics in the presence of catalysts is often employed to facilitate the degradation of polymers. The choice of the catalyst is polymer-oriented, while its selection becomes more difficult in the case of polymeric blends. The present investigation studies the catalytic pyrolysis of polymers abundant in waste electric and electronic equipment (WEEE), including poly(acrylonitrile-butadiene-styrene) (ABS), high-impact polystyrene (HIPS) and poly(bisphenol-A carbonate) (PC), along with their blends with polypropylene (PP) and poly(vinyl chloride) (PVC). The aim is to study the kinetic mechanism and estimate the catalysts' effect on the activation energy of the degradation. The chosen catalysts were Fe2O3 for ABS, Al-MCM-41 for HIPS, Al2O3 for PC, CaO for Blend A (comprising ABS, HIPS, PC and PP) and silicalite for Blend B (comprising ABS, HIPS, PC, PP and PVC). Thermogravimetric experiments were performed in a N2 atmosphere at several heating rates. Information on the degradation mechanism (degradation steps, initial and final degradation temperature, etc.) was attained. It was found that for pure (co)polymers, the catalytic degradation occurred in one-step, whereas in the case of the blends, two steps were required. For the estimation of the activation energy of those degradations, isoconversional kinetic models (integral and differential) were employed. In all cases, the catalysts used were efficient in reducing the estimated Eα, compared to the values of Eα obtained from conventional pyrolysis.

MAX phases: Unexpected reactivity under impact

This study reveals that MAX phase materials can exhibit extraordinary reactivity when subjected to impact loading. This previously unknown behavior was discovered and examined in a case study of Ti3SiC2 subjected to Split Hopkinson pressure bar (SHPB) testing. The employed methodology integrated SHPB coupled with thermal measurements and ex-situ spectroscopic analysis, yielding crucial quantitative insights into MAX phase reactivity and mechanical impact response. We observed a substantial release of high energy in the form of elevated temperatures upon impact and disintegration of the MAX phase. Surprisingly, it was found that oxidation, usually the prominent contributor to reactivity, only plays a secondary role. Instead, microstructural transformation emerges as the primary source of energy release. It is postulated that the transformative kinetic mechanism involves rapid kinking, delamination, and bond breakage within the bulk material. These findings shed light on the fundamental energetics of MAX phases and highlight their potential as versatile reactive structural materials.

Effective waste management through Co-pyrolysis of EFB and tire waste: Mechanistic and synergism analysis

Driven by the need for solutions to address the global issue of waste accumulation from human activities and industries, this study investigates the thermal behaviors of empty fruit bunch (EFB), tyre waste (TW), and their blends during co-pyrolysis, exploring a potential method to convert waste into useable products. The kinetics mechanism and thermodynamics properties of EFB and TW co-pyrolysis were analysed through thermogravimetric analysis (TGA). The rate of mass loss for the blend of EFB:TW at a 1:3 mass ratio shows an increase of around 20% due to synergism. However, the blend's average activation energy is higher (298.64 kJ/mol) when compared with single feedstock pyrolysis (EFB = 257.29 kJ/mol and TW = 252.92 kJ/mol). The combination of EFB:TW at a 3:1 ratio does not result in synergistic effects on mass loss. However, a lower activation energy is reported, indicating the decomposition process can be initiated at a lower energy requirement. The reaction model that best describes the pyrolysis of EFB, TW and their blends can be categorised into the diffusion and power model categories. An equal mixture of EFB and TW was the preferred combination for co-management because of the synergistic effect, which significantly impacts the co-pyrolysis process. The mass loss rate experiences an inhibitive effect at an earlier stage (320 °C), followed by a promotional impact at the later stage (380 °C). The activation energy needed for a balanced mixture is the least compared to all tested feedstocks, even lower than the pyrolysis of a single feedstock. The study revealed the potential for increasing decomposition rates using lower energy input through the co-pyrolysis of both feedstocks. These findings evidenced that co-pyrolysis is a promising waste management and valorisation pathway to deal with overwhelming waste accumulation. Future works can be conducted at a larger scale to affirm the feasibility of EFB and TW co-management.

Influence of Temperature on the Nucleation and Adsorption Kinetic Mechanisms for Copper Corrosion

Copper is a valuable catalyst that is widely used in electrochemical devices, particularly in the generation of clean, renewable energy and the CO2 reduction reaction (CO2RR). Gaining insight into the fundamentals of corrosion/deposition of Cu in an electrochemical cell can aid in the design of more durable and efficient devices. To take advantage of the capabilities of Cu and comprehend the broader impacts, it is crucial to understand the kinetics of nucleation and adsorption mechanisms and conduct a thorough investigation of the underlying principles. Here, we utilize a model system with Cu underpotential deposition (UPD) on an Au(111) electrode surface in sulfuric acid electrolyte and investigate the impact of temperature change on the kinetics of Cu corrosion/deposition. The Transient technique, chronoamperometry, is employed to differentiate and illustrate the effects of the nucleation process and adsorption of ions. At temperatures below 20°C, peaks indicate the nucleation and adsorption processes can be identified individually. At temperatures 20°C and above, more adsorption characteristics are seen which may be due to the interactions between less-ordered monolayers at the interface, further demonstrated by the loss of nucleation characteristics. Electrochemical devices operate across a wider temperature range in practical uses. The aim of this study is to examine and quantify the influence of temperature on the nucleation and adsorption mechanisms for the kinetics of Cu in order to optimize the durability of Cu-containing electrochemical devices.

(Industrial Electrochemistry and Electrochemical Engineering Division H. H. Dow Memorial Student Achievement Award) Tailoring Electrode-Electrolyte Interfaces through Non-Covalent Interactions for Electrochemical Energy Storage and Conversion

Li-ion batteries and fuel cells play essential roles in electrifying transportation. Central to the electrochemical systems is the electrode-electrolyte interface, where (electro)chemical surface reactions or intercalation occur, and its thermodynamic and kinetic properties determine the energy density, power density, and lifetime of the electrochemical devices. However, the molecular structures at the electrical double layer and reaction mechanisms remain poorly understood, hindering the rational material design for more efficient electrochemical devices. This talk focuses on the mechanisms of (electro)chemical reactions and charges transfer kinetics at the electrode-electrolyte interface, providing design principles based on non-covalent interactions in electrolytes.First, an in situ Fourier-transform infrared spectroscopy (FTIR) method was developed for Li-ion batteries, which revealed unique evidence for dehydrogenation of carbonate electrolytes on Ni-rich lithium nickel, manganese and cobalt oxides (NMC), accounting for interface impedance build-up and battery capacity fading. Based on the proposed mechanism, strategies on suppressing electrode and electrolyte reactivity were demonstrated to improve battery cycling. Next, the kinetic mechanism for ion intercalation at the electrode-electrolyte interface will be discussed. Li-ion concentration-dependent intercalation kinetics was demonstrated from charge-adjusted electrochemical experiments and fit into a coupled ion-electron transfer mechanism, which governed the current-dependent maximum capacity and power density of intercalation batteries. Finally, for electrocatalytic reactions central to fuel cell technologies, we demonstrated tuning interfacial hydrogen bonding through protic ionic liquids with different acid dissociation constants and organic solvents with different donor numbers to tailor oxygen-reduction reaction (ORR) and hydrogen evolution reaction (HER). Strengthening hydrogen bonding between ORR products and ionic liquids, or between interfacial water molecules facilitated proton-coupled electron transfer kinetics, revealed by in situ surface-enhanced infrared absorption spectroscopy and density functional theory (DFT) calculations. The study can pave the way for the electrolyte and electrode design of electrochemical storage devices with improved energy and power density and cycle life.

Optimization of kinetic mechanism for hydrogen combustion based on machine learning

Optimization of kinetic mechanism for hydrogen combustion based on machine learning

4D printing of Pickering emulsion: Temperature-driven color changes

Pickering emulsion inks were employed to demonstrate the temperature-driven 4D printing method. The Pickering emulsion consisted of water phase containing NaHCO3 and oil phase containing curcumin. Upon heating, the movement of pigment molecules was induced, resulting in color changes. The formation mechanism, rheological properties, printing properties and color changes of Pickering emulsion as well as the release kinetic mechanism of curcumin were investigated. The results indicated that relationships were also established between quantified color values (L*, a*, b*) and heating time. Moreover, the release of the curcumin in the Pickering emulsion, which was designated as a swelling process, followed the non-Fickian mechanism due to the occurrence of diffusion and erosion. The Hixson-Crowell model exhibited the highest linearity (R2: 0.9430 to 0.9825) of Pickering emulsions. In conclusion, the research offers a new perspective for the development of personalized Pickering emulsion food with bright colors.

Study on Chemical Kinetic Mechanism and Autoignition Characteristics of Isopentanol/Gasoline Surrogate Fuel

Abstract In this article, the detailed mechanism of isopentanol was simplified by direct relationship graph error propagation (DRGEP), generation rate analysis, reaction path optimization, and sensitivity analysis, and a comprehensive simplified mechanism of isopentanol/gasoline alternative fuels was obtained. Isopentanol/gasoline-characterized fuels with different blending ratios were investigated, and the results showed that blending of isopentanol promoted the autoignition of gasoline. It was found that blending isopentanol does not significantly affect the low-temperature reaction path of alkanes, but increases the reaction path flux from toluene to benzene. During combustion of isopentanol/gasoline alternative fuels, the isopentanol component exhibits a unique two-stage combustion phenomenon.

Atmospheric photo-oxidation of acetic anhydride: Kinetic study and reaction mechanism. Products distribution and fate of CH3C(O)OC(O)CH2O· radical

The rate coefficient for the gas-phase reaction of acetic anhydride (Ac2O) with chlorine atoms at 298 K and atmospheric pressure was experimentally determined (kAc2O+Cl= (1.3 ± 0.4) × 10-12 cm3molec−1s−1), while the rate coefficient for the reaction with the hydroxyl radical was estimated (kAc2O+OH=1.9 x 10-13 cm3molec−1s−1). For the Structure-Activity Relationship method, a value of 0.02 was determined for the −C(O)OC(O) group. The mechanism of photo-oxidation of acetic anhydride initiated by chlorine atoms was determined and CO, CO2, CH3C(O)OH (32 %), CH3C(O)OC(O)C(O)H, and 3-hydroxy-1,4-dioxane-2,6-dione (20 %) were identified as products by infrared spectroscopy. Here we determined for the first time the relative energies of the primary reaction pathways for the CH3C(O)OC(O)CH2O· radical using computational methods, which confirmed our experimental data. Finally, the environmental implications of acetic anhydride emissions were calculated, showing an atmospheric lifetime between 31 and 220 days for the reaction with atmospheric radicals, while its wet deposition lifetime is 1.5 years.

Development of laminar burning velocity prediction model and correlation of iso-octane air mixtures using artificial neural network

Surrogate fuels provide an economical alternative for forecasting the combustion properties of transportation fuels like diesel, gasoline, and kerosene. Iso-octane (2,2,4-trimethylpentane), a primary reference fuel for gasoline, is extensively used as a surrogate component. This study utilizes a Feed-Forward Artificial Neural Network (FFANN) with back-propagation (BP) to predict the laminar burning velocity (LBV) of iso-octane/air mixtures. The ANN model was developed using a dataset of 6339 data points, including 3788 experimental data points from literature since 2004 and 2551 simulation data points from reduced kinetic reaction mechanism (RKM) CHEMKIN simulations. The grid search cross-validation (CV) method was employed to optimize the ANN hyperparameters. Implemented in Python using Keras, the ANN model addresses research gaps by forecasting LBV for hydrocarbons beyond n-heptane and modelling LBV under conditions reflective of actual engine operations. Unlike prior studies, we optimized various ML models, their complexity, size, and hyperparameters to achieve high prediction accuracy. We also integrated a hybrid model combining Particle Swarm Optimization (PSO) with Genetic Algorithms (GA) for hyperparameter optimization, ensuring efficient configuration of the ANN. The constructed ANN model was compared to other ML models, including generalized linear regression (GLR), support vector machine (SVM), random forest (RF), and XGBoost regression. For the testing set (20 % of the total dataset), the ANN model outperformed all other ML models and empirical correlations, achieving a coefficient of determination (R2) of 0.9903, root mean square error (RMSE) of 1.911, and mean absolute error (MAE) of 1.206. Optimizing the ANN model with PSO further enhanced prediction accuracy, achieving a correlation coefficient of 0.9973 and a reduced mean absolute error of 0.753. To evaluate the ANN model's predictive ability, a reduced mechanism from the Lawrence Livermore National Laboratory (LLNL) was used. Compared to the LLNL RKM, the ANN predicted values showed lower percentage deviation from experimental data. Additionally, computation cost comparisons revealed that while RKM simulations in CHEMKIN took 244.2 s per case, the PSO-optimized ANN model required only 900 s for 150 cases. A 16-term correlation for laminar burning velocity (LBV) was derived from ANN predictions, serving as a practical tool to predict LBV based on pressure, temperature, and equivalence ratio. Unlike existing literature correlations, this newly developed correlation is valid across a wide range of operating conditions, offering a fundamental database for real-time combustion applications.

Thermodynamic cycle performance modeling and numerical simulation of higher Mach scramjet with inlet pre-injection

This paper focuses on the thermodynamic cycle performance modeling and numerical investigation of a high Mach number scramjet with inlet pre-injection of hydrogen. The scramjet model used in this study was the Hyshot-Ⅱ engine model. Flight experiments using this model at high Mach number have been conducted previously, which provides a unique testbed for validating the computational prediction of supersonic combustion. A thermodynamic cycle performance model with inlet pre-injection was developed for operating characteristics studies of the scramjet engine. A set of three-dimensional Reynolds average Navier-Stockes (RANS) simulations of the reactive flow was performed with a 9-specie and 19-step kinetic mechanism for hydrogen combustion. The turbulence is modeled by k-ω shear stress transport (SST) turbulence model. The thermodynamic cycle performance analysis results indicate that inlet pre-injection can enhance the hydrogen mixing efficiency, and a small amount of advanced heat release can improve the overall thermal cycle efficiency. Detailed flow analysis from the three-dimensional simulation results indicates flow can be ignited in the first shock wave induced boundary layer separation (SIBLS) region. Inlet pre-injection enables the propagation of the flame toward the core flow compared to the throat injection. The inlet fuel pre-injection proved to be a promising injection method due to the higher combustion efficiency, elevated from 0.75 to 0.85, and higher specific impulse potential, increased from 1570 s to 1810 s. As the ER of inlet pre-injection increases within the examined range, the performance curve exhibits an optimal point. As the geometric compression ratio increases, the entire combustion process advances, leading to a significant increase in the performance potential of the engine. The comparative analysis of the thermodynamic cycle performance modeling and computational fluid dynamics (CFD) modeling indicates the model shows a good prediction on the performance of the scramjet engine with the inlet pre-injection, with the same trend of performance curves and an error of less than 10 % compared to the numerical simulation.

Unveiling the kinetics of interphase and random quaternary Nb[sbnd]Ti precipitations, and strengthening mechanism of HSLA steel

Traditional methods for analyzing multi-element precipitation are often time-consuming, labor-intensive, and expensive. Particularly, the initial nucleation stages of such precipitations remain poorly understood. A revised precipitation theory was employed to elucidate the nucleation and growth kinetic mechanisms of quaternary (Ti, Nb)(C, N) precipitation with two modes: interphase precipitation (IP) along the migrating α/γ interface and random precipitation (RP) along dislocations. The findings indicated that TiN preferentially nucleates at the ferrite side compared to that at the austenite side. The nucleation occurring at α/γ interface leads to a precipitation particle angle of approximately 5.3° within a single IP sheet. The interface provided more favorable nucleation sites than dislocations, significantly reducing the relative nucleation time. Additionally, the initial yielding behavior and strengthening mechanism were analyzed based on the two factors of the hot-rolling microstructure and precipitation. A favorable slip system was along the RD-ND plane as the texture index of α-{110} approximately 3.74, compared to 2.20 along the TD-ND plane, resulting in the lower upper yield strength. Once the number density of mobile dislocations increased during plastic deformation, the tensile stress decreased, leading to the local plastic instability. Finally, (Ti, Nb)(C, N) contributed to a strengthening increment of about 154 MPa. This study provides critical insights into the precipitation behavior in HSLA steels, offering significant implications for the design and development of advanced materials with enhanced mechanical properties.

Development of an ammonia/diesel combustion mechanism for high ammonia energy ratio: Validation of the mechanisms in kinetic simulation and RCCI optical engine simulation

Ammonia blending in diesel is an efficient combustion strategy that overcomes the combustion resistance of ammonia while maintaining high engine adaptability. A smaller and accurate chemical kinetic mechanism is crucial for exploring the application of ammonia/diesel in engine. This study, based on the stepwise validation and optimization mechanisms, developed a novel ammonia/diesel mechanism comprising 130 species and 772 reactions. The mechanism was validated through kinetic verification for ammonia, n-dodecane, diesel and ammonia/diesel fuel. For profound understanding of the low-temperature autoignition chemistry of ammonia/diesel, applying this mechanism construct precise CFD models in RCCI optical engine. The results indicate that this mechanism can accurately capture ignition under high AER, wide working conditions, and low-temperature conditions. In the kinetic analysis, the C–N interaction reaction, particularly C2H4+NH2=C2H3+NH3, plays a crucial role in predicting the IDT of ammonia/diesel. In addition, NH2 undergoes deoxygenation reaction with HO2, converting inactive radicals HO2 into OH active radicals, enhances the reactivity of ammonia/diesel under low-temperature conditions. Applying the mechanism to CFD models, the model accurately predicts the pressure and heat release rate in RCCI optical engine, capturing the phenomenon of the high-temperature flame rapidly spreading towards the low-temperature regions in the cylinder. The research on this mechanism can construct accurate CFD model for optimizing efficient and clean combustion simulations of ammonia/diesel.

Numerical study on laminar burning velocity and ignition delay time of ammonia/methanol mixtures

As a carbon-free hydrogen-carrying fuel, ammonia can effectively alleviate the problem of CO2 emissions and has great application potential in marine engines. The low laminar burning velocity and calorific value, and the narrow flammability limit range make the combustion of pure ammonia difficult. Ammonia/methanol mixed combustion is a feasible method to improve ammonia combustion and mitigate CO2 emissions. It is difficult to accurately predict the laminar burning velocity (LBV) and ignition delay time (IDT) of ammonia/methanol combustion simultaneously by the existing chemical kinetic mechanisms. This study aims to develop a detailed chemical kinetic mechanism that can simultaneously predict the LBV and IDT. The new-developed mechanism was fully validated based on experimental data. Furthermore, it was employed to investigate the effects of methanol blending ratios and equivalence ratios on the LBV and IDT in NH3/CH3OH mixed flames. Besides, chemical kinetic analyses were conducted to elucidate the influence of methanol mixing ratios and equivalence ratios on LBV and IDT. Reaction pathway analysis revealed that the NH3 and CH3OH chemistry interacted by the sharing of H, OH and O radicals in fuels’ decomposition, and chemical interactions of N-containing radicals with the C1 species. The reactions involving C-containing species can notably improve the LBV of NH3/CH3OH mixed combustion. At low equivalence ratio, LBV increases in proportion to the fuel proportion. Conversely, at high equivalence ratio, the effect of oxygen concentration on LBV becomes the dominant factor.