Two-phase flow within the channels of proton exchange membrane fuel cells critically governs reactant transport and overall cell performance, yet the role of channel length in modulating these effects remains insufficiently understood. In this study, we develop a coupled multiphysics framework that integrates a volume-of-fluid model for gas–liquid interface tracking with comprehensive transport and electrochemical governing equations. This approach enables, for the first time, a systematic investigation of how channel length influences two-phase flow morphology and, in turn, the underlying mass transfer and reaction rate. The results reveal that while channels of different lengths capture the same qualitative trends of two-phase flow effects, shorter channels systematically overestimate the detrimental impacts on mass transport and performance degradation. Specifically, as channel length increases from 50 mm to 150 mm, the two-phase-to-single-phase pressure drop ratio decreases from 14.04 to 3.48, and the amplitude of current density fluctuations increases from 8 to 9% to 25–30%. Moreover, the average oxygen concentration in the cathode catalyst layer predicted by two-phase simulations exhibits a reversal relative to single-phase predictions beyond 125 mm, indicating that longer channels with detailed interface tracking yield more realistic oxygen transport characteristics. These findings highlight the critical importance of channel-length-dependent two-phase dynamics and provide rational guidance for selecting computational domain dimensions in large-scale fuel cell simulations.

In this study, a computational fluid dynamics (CFD) study focused on a compact methanol steam reaction (MSR) reformer for aviation applications is proposed. Three-dimensional (3-D) transient CFD models of 1 kW MSR reformers are developed to analyze the start-up period, optimize geometric configurations and flow modes. The effect of heating tube position, heating film position, reformer diameter and length are studied. And counter-flow is found to be the more suitable choice than co-flow.Strategies are proposed to enhance methanol conversion rates and accelerate start-up phase to improve the reliability and compactness of reformers in aviation power systems.

In this study, a 1 kW compact methanol steam dual-reformer arrangement is proposed to improve the start-up performance of SOFC systems and different configurations are categorized based on the difference in partitioned geometric design. A 3-D CFD transient reformer model is developed to numerically investigate the start-up period of different reformer configurations. The results demonstrate that the new concept significantly reduces the start-up time of the reformer due to reduced heat losses, the addition of precious metal catalysts, and the effective utilization of heat-concentrated areas. In addition, the influence of the gas flow mode on the rapid startup is analyzed, and counter-flow is found to be the more suitable choice for dual-reformers than co-flow. Finally, a hot start-up strategy considering the features of the new reformer design is proposed, and an SOFC stack model is established. By the co-simulation of the reformer and the fuel cell model, the feasibility of the strategy is proved. The interaction between dual-reformers and SOFC stacks is utilized, and the thermal start-up process of the reforming subsystem is reduced by about 400 s compared with the conventional single-reformer configuration.

Ammonia-polyoxymethylene dimethyl ether 3 (PODE3) dual fuel mode shows great potential in enhancing ammonia combustion performance, reducing carbon-related and pollutant emissions, and promoting the widespread application of ammonia-fueled engines. In this study, the ignition delay times (IDTs) of NH3/PODE3 blends were measured using a rapid compression machine (RCM) within a wide temperature (Teff) range at elevated pressures (Peff). Moreover, the laminar burning velocities (LBVs) of NH3/PODE3 blends were determined employing a constant-volume combustion vessel at wide initial pressures, temperatures, and ammonia molar ratios (AMRs). The outcomes demonstrate that the incorporation of PODE3 conspicuously shortens the IDTs and augments the LBVs of NH3. Based on these data, a detailed chemical reaction mechanism for NH3/ PODE3 blends has been developed, encompassing 319 species and 2015 reactions. This proposed mechanism was meticulously validated against IDTs, LBVs, and major species mole fraction profile data over an extensive spectrum of experimental conditions, covering not only pure NH3 and pure PODE3 but also NH3/PODE3 blends with diverse ammonia fractions. The results evince a high degree of prediction accuracy when applying this mechanism, thereby corroborating the efficacy and appropriateness of the mechanism for CFD simulations in NH3-PODE3 dual fuel engines. Pathway analysis and sensitivity analysis were also conducted. The results demonstrate that the H-abstraction reactions of PODE3 by NH2 radical, R9: PODE3 + NH2=PODE3B + NH3 and R10: PODE3 + NH2=PODE3A + NH3, are sensitive only under the condition of AMR = 92.5 % and 1.5 MPa with respect to IDTs. The chain branching reactions, R#1: O2 + H = O + OH, exhibits the highest sensitivity coefficients for LBV. The NNH radical plays a crucial role in both IDTs and LBVs of NH3/PODE3 blends, whereas the CH3 radical is more prominent at rich regime for LBVs. The results further indicate that increasing AMR can enhance the flame stability of NH3/PODE3 blends.

Pressure-based hybrid Kurganov-Noelle-Petrova (KNP)-PIMPLE algorithms have been widely used in all-Mach compressible flows to ensure the solution stability and maintaining physical consistency, but it suffers from high numerical diffusion at contact discontinuities and resulting in non-physical numerical oscillations at the two-phase regions, limiting the physical understanding of non-equilibrium phase change (flash boiling). In this work, a new hybrid solver named twoPhaseMixingHLLCFoam was proposed to avoid the drawbacks with three improvements: 1) Harten-Lax-van Leer-Contact (HLLC) scheme was used to replace the KNP scheme as a part of the hybrid framework to reduce the numerical diffusion; 2) The interpolation method of sound speed for Riemann solvers was modified to correctly reproduce the sound speed in two-phase buffer regions; 3) A new blending function based on local sound speed for identification of compressible and incompressible regimes was introduced. The solver has been verified and validated against the analytical and experimental results. The improvement in numerical diffusion and the capability to resolve the pressure waves and shock waves propagation in gas-gas, gas-liquid and liquid-liquid flows were verified by a series of typical 1D cases. Then, the solver's capability in resolving complex flow structures using 2D cases was demonstrated, especially in terms of the effectiveness of the transition between compressible and incompressible fluxes for all-Mach flows containing sub-, tran-and supersonic regimes simultaneously. Finally, a numerical study of acetone flash boiling jet has been conducted to demonstrate the solver's capability of resolving under-expanded compressible two-phase jets with phase change. Scaling tests have shown that parallel performance of the new and original hybrid solvers is almost the same. Due to the adoption of a generalized mixture model, the new solver can be extended to multicomponent and even multiphase scenarios.

Understanding the transcritical mixing behavior of fuel droplets under multicomponent gases is essential for low-carbon, high-pressure propulsion systems. However, the influence of CO₂, a major combustion product, on transcritical behavior remains unclear. In this study, molecular dynamics (MD) simulations combined with phase-equilibrium analysis of binary/ternary systems are employed to investigate the effects of ambient pressure and initial CO₂ concentration on the transcritical behavior of methanol droplets. Elevated pressure and CO₂ concentration accelerate methanol droplet morphology disintegration, while the quasi-steady-state evaporation rate exhibits a non-monotonic dependence on CO₂ concentration due to competing effects of different gas-phase transport properties. CO₂ shows higher solubility in methanol, whereas its equilibrium solubility decreases with increasing temperature, in contrast to N2. Increasing ambient pressure and CO₂ concentration accelerate the supercritical transition of methanol droplets, while the critical temperature criterion based on global thermodynamic equilibrium assumption may overestimate the transcritical mixing rate of droplets. Furthermore, interfacial transport analysis found that supercritical high pressure significantly reduces molecular mean free path, weakening the non-equilibrium kinetic effects with a smaller temperature jump across the boundaries of Knudsen (Kn) layer. Ambient-gas velocity distributions in Knudsen layer deviate markedly from Maxwell–Boltzmann equilibrium with apparent interfacial temperature gradients under subcritical conditions, whereas enhanced molecular collisions under supercritical conditions significantly reduce the deviations. However, the fuel vapor molecules exhibit small deviations under both conditions. These findings indicate that the local thermodynamic equilibrium assumption adopted at the Kn layer's inner boundary in non-equilibrium droplet models may be available even at high-pressure supercritical conditions.

The dynamics of detonation is governed by intrinsic longitudinal and transverse instabilities. This work fills the research gap of detonation stability at elevated pressure as real gas effects, including the finite molecular volume and inter-molecular attraction forces, become non-negligible. The stability of one-dimensional pulsating and two-dimensional cellular detonations at elevated pressure was investigated using both linear stability analysis and high-fidelity numerical simulations. For pulsating detonations, the neutral stability boundaries derived from the linear stability analysis reveal that the impact of real gas effects on detonation stability depends on the heat content. Specifically, real gas effects stabilise pulsating detonation at high heat content, destabilise it at intermediate levels and exhibit competing influences, i.e. destabilisation from finite molecular volume and stabilisation from the inter-molecular attraction force, at low heat content. For cellular detonations, a stability map is proposed in the Mach number-reduced activation energy plane, demonstrating that real gas effects stabilise detonation and lead to more regular cellular structures or even fully planar detonations. Theoretical predictions show good agreement with numerical simulations. An oscillator model was used to elucidate the interplay between the heat release and shock dynamics. It shows that the stabilising effect of real gas is associated with reduced velocity oscillation amplitude, increased phase lag between heat release and shock speed variations and lower values of the coupling parameter. The comprehensive linear stability analysis with complete real gas models is an effective predictive tool for the detonation dynamics at elevated pressure.

While it is well established that high temperatures can significantly increase brake wear particle emissions, the detailed emission patterns have seldom been reported. To address this gap, this study investigated brake particle number (PN) emissions under high-temperature conditions, focusing on detailed PN patterns and fundamental reasons. Particles smaller than 1 μm (PN1), which are the dominant source of total PN, were analyzed under various brake temperature conditions. The main findings include: delayed and reduced PN1 spikes were observed due to the reduce of the materials with low decomposition temperature and the reduce of organic material availability. The protective layer, which is composed of pyrolyzed residues and secondary plateaus, could also reduce the PN1 concentration. Within one brake event, alternating PN1 increase and decrease were noted, which was caused by the alternating formation and breakdown of protective layer. The break of the protective layer is hard to predict, which leads to occasional PN1 spikes and significant PN1 concentration variations among tests. Both increase and decrease in PN1 concentration were observed upon brake release due to the coupled effects from temperature, surface condition, and organic material availability. Notably, PN1 emissions occur even without disc rotation, indicating that PN1 is caused by thermal processes rather than the brake drag. These findings highlight a potential approach to PN1 control: rapidly establishing and stabilizing the protective layer while utilizing thermally stable organic materials.

Under China’s dual-carbon targets, battery electric vehicles are widely regarded as a central pathway for passenger-vehicle decarbonization, while battery safety and extreme-temperature performance remain challenges. However, the long-term role of emerging internal combustion engine (ICE) technologies powered by renewable electrofuels (e-fuels) has not been systematically evaluated. This study develops the Transformation of Transportation Energy and Carbon in China (TransTEC-CN) model to assess the decarbonization contribution and cost-effectiveness of e-fuel-based ICE pathways as complements to electrification, including e-gasoline blending, e-methanol internal combustion engine vehicles (ICEVs), and e-hydrogen ICEVs under different carbon tax levels, power-sector decarbonization trajectories, and infrastructure conditions. E-gasoline blending can achieve cumulative emission reductions comparable to an extreme carbon-tax electrification benchmark, while incurring approximately one-quarter of the social welfare loss. Adding e-methanol ICEVs to the e-gasoline-dominated policy portfolio can further reduce carbon abatement welfare loss by about 62% while reversing the cumulative emissions reduction by only about 2%.

This study develops an advanced electrochemical model integrated with the Teaching-Learning Based Collective Intelligence (TLBCI) algorithm to investigate degradation mechanisms in solid oxide fuel cells (SOFCs), with a focused analysis on nickel (Ni) agglomeration/oxidation at the anode and yttria stabilized zirconia (YSZ) agglomeration at the cathode. Key model parameters are directly extracted from experimental data, enabling accurate performance prediction. The model systematically evaluates the impact of temperature fluctuations on long-term SOFC degradation. Compared to conventional methods (Kalman filters, particle filters) and data-driven approaches (Long Short-Term Memory networks (LSTM), Echo State Networks (ESN)), the proposed mechanism-based model achieves superior accuracy, lower Mean Squared Error (MSE), and enhanced predictive capability in both short- and long-term forecasts. Furthermore, the work provides an in-depth analysis of electrochemical performance decay, including the evolution of overpotential components and material properties. This comprehensive degradation framework advances the understanding of SOFC longevity and provides a theoretical foundation for optimizing cell design, improving reliability, and enhancing operational efficiency—thereby supporting their commercial and industrial deployment (e.g., in distributed generation and backup power systems). The findings offer critical insights for boosting SOFC performance under real-world operating conditions.

Standardized driving cycles often fail to represent real-world driving conditions, limiting their effectiveness for hybrid electric vehicles energy management strategy (EMS) optimization. Current research on customizing driving cycles typically relies on limited datasets. Moreover, existing methods often construct feature spaces using statistical parameters, such as average speed, neglecting the importance of transient features inherent in speed-time profiles, to which EMS is particularly sensitive. In this study, a novel method for driving cycle development is proposed that leverages large-scale real-world driving data compression technology and multi-dimensional Dynamic Time Warping (DTW) to generate representative cycles considering the transient feature. The DTW algorithm is adept at extracting these crucial transient driving features. To address the computational challenge brought by DTW, a Long Short-Term Memory auto-encoder is designed for data compression, achieving a compression ratio of 500 while maintaining a speed–acceleration frequency distribution difference low to 0.827%. After micro-trip classification via principal component and clustering analysis, both one-dimensional and two-dimensional DTW algorithms are employed to extract representative micro-trips. A comprehensive evaluation demonstrates that the driving cycle generated by 2D DTW exhibits superior representativeness compared to a traditional statistical method and 1D DTW method. When applied to EMS optimization, the driving cycle generated using 2D DTW achieves better fuel economy, with up to nearly 3% reduction in equivalent fuel consumption per 100 km. The results demonstrate that the proposed method can effectively generate highly representative driving cycles based on large-scale data and 2D DTW, significantly enhancing the optimization performance of EMS.

Methane-fueled laser-drilled metal-supported solid oxide fuel cells (MS-SOFCs) involve coupled multicomponent diffusion, electrochemical oxidation, internal reforming, and carbon-related reactions across multiple structural scales. Here, we develop a multiscale reactive-transport framework based on a modified multicomponent lattice Boltzmann method with temporal interpolation for different lattice speeds and second-order discretization of the diffusion force. Effective transport coefficients are extracted from heterogeneous anode simulations and are then used to construct a larger-scale homogenized model containing support holes. The method is validated against transient diffusion, steady-state diffusion, and diffusion with source terms. Heterogeneous-anode simulations show highly uniform gas compositions, with a maximum mole-fraction difference of only 0.24%, supporting homogenized modeling. In contrast, the support hole introduces pronounced composition non-uniformity: under the baseline condition, CH4 and H2O mole-fraction differences reach 21.96% and 15.53% inside the hole, compared with 5.54% and 4.28% inside the anode. Hole-induced transport limitation increases the CO electrochemical contribution up to 20.94% of the H2 current and intensifies carbon-generation hot spots. Reducing the inter-hole spacing from 100 to 30 mu m increases the total current density by 17.53% but raises the instantaneous carbon-generation rate by 179.72%.

Driving cycles are essential for vehicle energy and emission standards, but standard cycles often overlook regional variations. This study proposes a novel framework for constructing representative driving cycles for heavy-duty vehicles by optimizing a Markov chain with a hybrid Multi-Population Genetic Algorithm and Wavelet Threshold Denoising (hMPGA-WTD). The methodology involves: (1) spectral clustering of 1.27 million telematics data points to identify operational scenarios; (2) generating scenario-specific cycles using a two-dimensional Markov chain; and (3) enhancing driving cycle fidelity with hMPGA-WTD to reduce feature distortions. The method achieves a mean relative error of 4.61% across key parameters, with velocity standard deviation error below 1%. It outperforms micro-trip concatenation and conventional Markov approaches. Fuel consumption is validated via real-world and chassis dynamometer tests under identical loads, showing a 4.26% deviation, better than the 7.71% under CHTC-TT. The framework offers a robust basis for efficiency assessment and standard development.

The electrochemical performance and impedance response of metal-supported SOFC (MSC) single cells under direct-ammonia operation were investigated by combining fuel-composition/current-density variation, electrochemical impedance spectroscopy, quantitative distribution of relaxation times (DRT) analysis, and CFD simulation. Two anode-related Gerischer-like contributions were resolved from the DRT spectra. The low-frequency process was interpreted as associated with coupled gas transport, hydrogen generation/consumption, and electrochemical reaction in the anode, whereas the mid-frequency process was interpreted as a more local interfacial process related to electrochemical oxidation and oxygen-vacancy transport. Experimental results together with CFD simulations supported the presence of rib/channel-induced gas-composition non-uniformity in the anode active layer, arising from internal ammonia decomposition, restricted gas exchange, and lateral diffusion. Quantitative analysis further suggested that the P1 contribution scales with the degree of hydrogen non-uniformity, while ammonia-containing feeds were associated with a 60%-90% increase in the effective chemical capacitance inferred from P2. These results provide an experimentally and numerically supported interpretation of coupled ammonia decomposition, gas transport, and electrochemical processes in direct-ammonia MSCs, and demonstrate the usefulness of EIS-DRT analysis for diagnosing coupled transport and reaction processes in internally reforming cell designs.

Proton exchange membrane fuel cells (PEMFCs) offer a promising pathway to decarbonize regional aviation. However, the internal heat and mass transport mechanisms high-power PEMFC stacks under flight conditions remain insufficiently studied. To address this, this paper develops a novel multi-methodological framework that integrates a flow network model (FNM) of a shared-manifold configuration parameterized by CFD analysis of a novel large-scale modular flow field, a 1D PEMFC multi-physics model resolving core electrochemical phenomena, and key balance-of-plant (BoP) subsystems. This integrated approach establishes a scalable, minute-scale, physics-based modeling framework for 400-kW class stack performance prediction, calibrated against multi-scale experimental data and capable of capturing water-thermal-gas distributions from stack to individual cells. A multi-objective optimization using the NSGA-II algorithm is then applied to a specific flight mission to enhance operational uniformity and reduce hydrogen consumption. The results reveal that altitude-induced performance degradation above 4000 m is primarily driven by severe reactant maldistribution, leading to a 50 mV voltage loss increase and a tripling of the voltage deviation rate (CV) at 8000 m. As transitioning from a challenging water-thermal condition and maldistributed gas distribution state at take-off to a stable state at cruise, the high-load state result in an ohmic loss that is nearly double that of the cruise phase. Optimization significantly improves stack performance, achieving 13.2 % reduction in CV and 26.9 % and 17.2 % increases in oxygen and hydrogen concentrations at the catalytic layers during take-off phase. System-level analysis confirms hydrogen savings of 0.727 g/s per stack during cruise, resulting in a total 1569.7 L reduction in storage volume per 2-h flight for a 72-seat regional aircraft. This study establishes a high-fidelity, multi-scale modeling and optimization platform that bridges cell-to-stack level water-thermal transport mechanisms with system level design, providing critical insights and tools for developing next-generation aviation fuel cell systems.

To extend the range of unmanned aerial vehicles (UAVs), internal combustion engines using aviation kerosene are utilized because of its high efficiency and power density. The air assisted nozzle are used in the engines of UAVs due to the requirement of light weight. But the extreme low temperature at high altitude pose a great challenge to the air assisted nozzle because of the high viscosity and low volatility of fuel under low temperature. In this paper, a cryogenic fuel injection system coupled with an air assisted nozzle are utilized to realize the injection under low fuel temperature down to – 55 °C. The high-speed imaging and Phase Doppler Particle Analyzer (PDPA) technologies are employed to analyze the spray and droplets characteristics. Results showed that large visible droplets come out of the nozzle under low temperature, indicating the incomplete breakup inside the nozzle. The Sauter mean diameter (SMD) significantly increase from 14 μm to 25.4 μm with the fuel temperature decrease from 25°C to – 55°C, leads to deterioration in atomization and evaporation. Furthermore, increasing assisted air injection pressure and duration can reduce the large droplets and improve the atomization. Results indicate that eliminating the large visible droplets is a key issue to improve the atomization performance. The design of fuel storage grooves or threads on the inside surface of the nozzle may reduce the fuel accumulation in the exit of the nozzle and reduce the incomplete breakup.

The structure of the anode functional layer (AFL) strongly governs the performance of solid oxide fuel cells (SOFCs). However, the AFL exhibits a complex pore-scale three-phase structure, and systematic decoupling analyses of the influence of microstructural parameters on performance are still lacking. In this work, a tunable stochastic reconstruction model for AFL microstructures is established to decouple the key microstructural parameters. The lattice Boltzmann method is used to predict the electrochemical performance of the AFL. The proposed framework is comprehensively validated against literature data in terms of domain size, phase volume fractions, effective diameters, tortuosity, three-phase boundary (TPB), and current-polarization characteristics. It is found that the volume fraction of the ceramic phase and the TPB length density are the dominant descriptors. To maintain sufficiently low ohmic resistance, the ceramic phase fraction within 6 mu m of the electrolyte should reach about 33 %. Reducing TPB length density from 13 mu m/mu m3 to 3 mu m/mu m3 lowers the current density by 63 %-69 %. In addition, smaller or fewer pores increase the mass transfer resistance and result in higher humidity near the electrolyte, which enhances the local reaction current. These results provide quantitative guidelines for tailoring AFL microstructures in compact SOFCs for transportation and distributed power applications.

Simulation and analysis of an ammonia-SOFC integrated aero engine show that specific impulse can achieve 42% of conventional airliner turbofan engines at cruise conditions, whereas the specific thrust is significantly higher at 213%. The modelled engine has a reduced bypass ratio and increased fan pressure ratio to fit the operation conditions of the SOFC and heat exchange systems consisting of an intercooler and a turbine recuperator. The compressor bleed air is cooled to enhance turbine cooling. Sensitivity analysis of the baseline case suggests modification toward a higher fan pressure ratio, smaller compressor pressure ratio and bypass ratio can further optimize the performance. The adjustment of the SOFC fuel utilization ratio can help engine thrust control. The compatibility of ammonia-based hybrid engines with medium-range, medium-size platforms is shown.

This study evaluates the performance of a conceptual turbofan engine integrated with direct-ammonia solid oxide fuel cell (DA-SOFC) and powered by ammonia, employing lumped system models. In this design, the fan is powered by the SOFC and electrical machine, instead of a low-pressure turbine. A lumped DA-SOFC model has been developed to simulate the power output of the stack under pressurized conditions. Additionally, the liquid ammonia also enhanced active cooling of the core spool turbine. The study examines the impact of various factors on engine performance, including the fuel utilization ratio of the SOFC stack, engine pressure ratios, and bypass ratio. The simulated results are compared with ammonia-fueled conventional turbo engine model results and commercial jet engine reference. At cruise conditions, the hybrid engine achieves a maximum of 44.7 % specific impulse relative to referenced CF56-7Bx engine data with comparable specific thrust output, which is notably higher than that of the ammonia-powered conventional turbo engine. By varying the fuel utilization ratio of the SOFC, without altering the airflow rate, the relative specific thrust fluctuates between 108.6 % to 151.8 %, and the relative specific impulse ranges from 44.7 % to 38.9 %. Increases in fan pressure ratios and the bypass ratio can augment overall engine performance, while net pressure ratio has minor effects. Extensive cooling of the compressor bleed air by liquid ammonia can reduce up to 95 % of bleed air requirement, facilitating simpler cooling designs.

Although the methanol oxidation process in supercritical water has been studied in some previous experiments, the methanol oxidation rate is sensitive to the supercritical water concentration, and its influence on the methanol oxidation mechanism remains unclear. Moreover, while the presence of formic acid intermediate (HCOOH) has been reported, its detailed conversion pathways are still poorly understood, and experimental detection of such transient intermediates is difficult. To address the above shortcomings, this study employed reactive molecular dynamics simulations to explore the effects of supercritical water and oxygen concentrations on the methanol oxidation mechanism at the microscale, focusing on the conversion pathways of formic acid. The reaction rate constants and activation energies for the initial methanol oxidation were calculated using first-order kinetics theory to validate the accuracy of the CHO-S22 force field used. Adding supercritical water could decrease the activation energy of initial methanol oxidation and increase the reactivity. The evolution of various species under different ambient conditions was discussed. The results suggested that increasing water concentration could promote OH/H2 production, enhance formaldehyde intermediate consumption, and inhibit CO production. The main methanol oxidation pathways were analyzed in detail. The simulations captured another important methanol supercritical water oxidation route involving formic acid: CH3OH-* CH2OH/CH3O-* CH2O-* HCOOH-* HCOO-* CO2. Formic acid can be further oxidized to HCOO/COOH, but HCOO is predominant. HCOO was converted to CO2 mainly by pyrolysis and reacting with OH, while COOH can be interconverted with CO. The reactions of formic acid, HCOO/COOH, HCO, and CO intermediates with OH were enhanced with increasing water concentration under stoichiometric conditions. Increasing oxygen concentration could promote the conversion of methanol to formaldehyde via O2 and HO2 but may inhibit the conversion of formic acid through OH radicals to HCOO/COOH. This study provides new insights into the reaction network of methanol oxidation in supercritical water from a microcosmic perspective.