Diffusion Behavior Research Articles

DFT Analysis on Adipic Acid to Propel Creative Advancements in Supercapacitor Technology

The increasing dependence on non-renewable resources for energy storage has accelerated the development of supercapacitor technology, which is now essential to portable devices and electric cars because of its high-power density and quick charge/discharge speed. Optimized geometry, weak C-H‧‧‧O hydrogen bonding interactions inside methylene groups affect bond lengths, and the carboxylic group in adipic acid (ADPI) shortens bond lengths (C14–C15 and C4–C5). DFT simulations demonstrate a fair agreement to experimental data. According to vibrational studies, the O-H and C=O groups' vibrational frequencies are greatly influenced by the reactive hydrogen bonding displayed by the -COOH group in carboxylic acid derivatives. With theoretical values demonstrating significant PED contributions, these interactions reduce the O-H stretching frequency, which is seen as an O-H stretching band at 3405 cm⁻¹ in the FT-IR spectra. In ADPI, atoms interact with neighboring atoms' σ* orbitals (O2-C4), (O12-C14), (C4-C5), (C14-C15), (O1-C4), and (O11-C14) through lone pairs of electrons localized on O1 (LP2), O11 (LP2), O2 (LP1), and O12 (LP1); these interactions have fairly high stabilization values of 33.78, 33.78, 17.91, 17.91, 6.75, and 6.75 kcal/mol, accordingly. Redox peaks and increased specific capacitance with scan rate are revealed by cyclic voltammetry study of ADPI, suggesting efficient electron transport, improved charge storage, and encouraging prospects for electrochemical energy storage applications. ADPI's appropriateness for high-performance electrochemical applications such as supercapacitors is supported by its impedance analysis, which is displayed by a Nyquist plot with a decreased semicircle and a sharp low-frequency slope. This plot demonstrates effective electron transfer, ion diffusion, and capacitive behavior.

Influence of gearbox oil on 3D printed carbon fiber reinforced polymer

This study builds upon prior research investigating the effects of gearbox oil on filament wound carbon fiber reinforced polymer (CFRP) materials. Here, short carbon fiber composite material was examined, motivated by the intention to use such materials in vehicle gearboxes. Automotive sector faces pressures to reduce CO2 emissions, therefore car manufacturers explore possibilities to implement CFRP into their gearboxes for parts such as shafts or casings to save weight, and also improve NVH behavior. Also, e-bike manufacturers aim to use polymers with short carbon fibers for making gears in their gearboxes. The important caveat to using these materials in gearboxes is the operating environment which is oil. While numerous studies have explored the influence of water on CFRP mechanical properties, research on the effects of oil remains scarce. Our experiment, conducted on 3D printed specimens, revealed predominantly positive effects of 60°C oil on the material’s ultimate tensile strength, with increases ranging from 2 to 10% depending on printing orientation, and on Young’s modulus, which increased by 7% in the longitudinal direction but decreased by 5% in the transversal direction. Interestingly, there was no significant change in glass transition temperature, and only negligible and inconsistent diffusion behavior was observed.

Applying clustered artificial neural networks to enhance contaminant diffusion prediction in geotechnical engineering

This paper introduces a novel approach using Clustered Artificial Neural Networks (CLANN) to address the challenge of developing predictive models for multimodal dataset with extreme parameter values. The CLANN method strategically decomposes the dataset, derived from Finite Element Analysis (FEA), into clusters, each representing distinct diffusion behaviors, and applies specialized neural networks within these clusters. The CLANN model was rigorously evaluated and demonstrated superior accuracy and consistency compared to traditional methods such as the Adaptive Neuro-Fuzzy Inference System (ANFIS) and fuzzy expert systems. While these conventional models struggled to capture the full range of diffusion dynamics, particularly under extreme conditions, CLANN consistently provided predictions that closely aligned with the actual FEA data across all scenarios. The versatility of the CLANN approach extends beyond its application to soil contamination. Its ability to handle complex, multimodal datasets suggests that this methodology can be generalized to a wide range of scientific and engineering problems characterized by similar data structures. This makes CLANN not only a powerful tool for geotechnical engineers but also a promising framework for broader applications where traditional models fall short. The findings of this study pave the way for more accurate, reliable, and adaptable predictive modeling in diverse domains, enhancing our ability to manage and mitigate environmental and engineering challenges.

Grain boundary self-diffusion and point defect interactions in α-U via molecular dynamics

Though metallic U-Zr fuel has been used in nuclear reactors since the 1960s, many of its fundamental and thermodynamic properties are still unknown. The α-U phase, which has a highly anisotropic crystal structure and physical properties, is present in U-Zr fuel. The character and behavior of α-U grain boundaries will strongly impact fuel thermophysical performance under irradiation. We study the interaction of point defects with grain boundaries, diffusion along grain boundaries, and the predicted diffusional creep behavior of α-U via molecular dynamics. We calculate the segregation energy of vacancies and interstitials to grain boundaries and quantify the biased sink strength of the grain boundaries, and observe that this sink strength is not strongly dependent on the grain boundary orientation. We also find that grain boundary diffusivity is strongly dependent on the grain boundary energy and grain boundary orientation. The presence of point defects within the grain boundary can induce diffusion in grain boundaries with low formation energies and can enhance diffusion in high-energy grain boundaries. We also find that diffusional creep of α-U at prototypical metallic fuel operation conditions is extremely high and could help explain observed metallic fuel swelling behaviors.

Dynamics of water, CO2, ethane and their mixtures in ZSM-22 zeolite: the role of polarity and hydrogen bonding

Abstract Understanding the interplay between confinement effects and intermolecular interactions is essential for predicting molecular diffusion in zeolites. In this study, we investigate the diffusion behavior of ethane, CO2, and water in ZSM-22 molecular sieves, focusing on the effects of mixing these fluids. Our results reveal that while CO2 has minimal impact on ethane diffusion, water significantly slows ethane’s motion by forming molecular bridges across the pore structure, reducing ethane’s diffusion by up to 30%. Ethane, in turn, restricts water’s mobility, and reduces the water–water coordination number from 2.22 to 0.73 depending on concentration. The diffusion of CO2 in mixtures shows a 40% increase in pure state under confinement. The role of polarity and hydrogen bonding is crucial, with water molecules exhibiting 1.2 hydrogen bonds in the confined state—much lower than the 3.4 bonds in bulk water. Molecular rotation in ZSM-22 of all fluids occurs at two distinct time scales: the short-time fast rotation dominated by molecular inertia and the long-time rotation hindered by fluid-zeolite interactions. For water, hydrogen bonding further restricts full rotational freedom. These findings provide a comprehensive understanding of how ethane, water, and CO2 interact and diffuse in nanoporous materials.

Interdiffusivity matrices and atomic mobilities in fcc Ni–Fe–Mo alloys: Experiment and modeling

Accurate diffusivities in fcc Ni–Fe–Mo alloys are of significant importance in designing high-quality magnetic alloys. In this work, totally twelve fcc single-phase diffusion couples are assembled to determine the diffusivities of fcc Ni–Fe–Mo alloys at 1373, 1423 and 1437 K. The diffusivity matrices at the intersection compositions of diffusion paths are determined by the Matano-Kirkaldy method. In addition, the diffusivity matrices along the whole composition profiles of individual diffusion couple and the atomic mobilities of fcc Ni–Fe–Mo alloys are evaluated by the numerical inverse approach incorporated in CALTPP program. The reliability of the obtained atomic mobilities is verified by comparing the predicted diffusion behaviors with the experimental ones. Furthermore, applying the presently obtained atomic mobilities in combination with thermodynamic descriptions, the three-dimensional maps of interdiffusivites, activation energy and frequency-factor planes of fcc Ni–Fe–Mo alloys are constructed to display the composition- and temperature-dependent diffusion properties. The presently obtained diffusivities and atomic mobilities of the Ni–Fe–Mo fcc phase are expected to contribute to high-efficiency Ni–Fe–Mo magnetic alloy design.

Investigation of Methane Adsorption and Diffusion Behavior in Hydrogen Sulfide-Containing Coal Seams.

This study aimed to investigate the methane adsorption-diffusion problem in coal seams containing hydrogen sulfide. Molecular simulations and Materials Studio software were used to study the difference in behavior between hydrogen sulfide and methane adsorption, as well as the effect of hydrogen sulfide on methane adsorption-diffusion behavior in coal seams. Comprehensive data were obtained on the influence of hydrogen sulfide on methane's adsorption amount, probability density distribution, interaction energy, and diffusion coefficient during the adsorption. The results showed that as the hydrogen sulfide content increased from 0 to 1.9%, porosity decreased from 14.41% to 11.25%, representing a 21.93% reduction. When methane and hydrogen sulfide were adsorbed in the coal seam, the adsorption amount of hydrogen sulfide was notably higher, with an adsorption heat of 38.25 kJ/mol, which is 24.65 kJ/mol greater than that for methane. An increase in the hydrogen sulfide content caused several adverse effects, including a decrease in methane's adsorption amount, Langmuir adsorption constant, and number of available adsorption sites within bituminous coal. Furthermore, the interaction energy and diffusion coefficient of methane molecules diminished during adsorption.

Effect of Rare Earth Y and Metal X (Co, Mn, Ni, Cu) Elements on Cr Diffusion Behavior of SOFC Metallic Interconnect

ABSTRACTAt present, the metallic interconnects of the solid oxide fuel cell (SOFC) can result in Cr poisoning problem of cathode after long‐term high‐temperature oxidation. Such problem seriously affects the efficiency of battery power generation. In order to optimize the performance of the metallic interconnect, this paper firstly studies the doping effect of rare earth element Y and metal element X (Co, Mn, Ni, Cu) on the diffusion behavior of Cr at the FeCr/Cr2O3 interface by the first principles method. The Cr diffusion pathway and energy barriers under different elemental doping models are calculated by CI‐NEB method. Based upon the theoretical results, the Mn1.8CoY0.2O4 spinel coating is further deposited on the surface of Crofer 22 APU substrate by sol–gel and electrophoretic deposition method to verify the theoretical results. The performance of the coating samples after high‐temperature oxidation are tested and analyzed. The experimental results show that the Mn1.8CoY0.2O4 spinel coating significantly improves the high‐temperature antioxidation, Cr resistance performance, and electrical conductivity of the interconnect, providing a feasible solution for solving the Cr poisoning problem in cathode and accelerating the application of Crofer 22 APU alloy materials in SOFC metallic interconnects.

Optimal Configuration of Physical Process Parameterization Scheme Combination for Simulating Meteorological Variables in Weather Research and Forecasting Model: Based on Orthogonal Experimental Design and Comprehensive Evaluation Method

The weather research and forecasting (WRF) model is frequently used to investigate the meteorological field around nuclear installations. The configuration of physical process parameterization schemes in the WRF model has a significant impact on the accuracy of the simulation results. Consequently, carrying out a pre-experiment to quickly obtain the optimal combination of parameterization schemes is essential before conducting meteorological parameter research. To obtain the optimal combination of physical process parameterization schemes from the planetary boundary layer (PBL), land surface (LSF), microphysical (MP), long-wave (LW), and short-wave (SW) radiation processes of the WRF model for simulating the near-surface meteorological variables near a nuclear power plant in Sanshan Town, Fuqing City, Fujian Province, China on 4 June 2019 were observed. Orthogonal experimental design (OED), a comprehensive evaluation method based on the CRiteria Import Through Intercriteria Correlation (CRITIC) weight analysis, and comprehensive balance method were employed for the first time to conduct the research. The sensitivity of meteorological variables to physical processes was first discussed. The findings revealed that the PBL scheme configuration had a profound impact on simulating wind fields. Furthermore, the LSF scheme configuration had a significant influence on simulating near-surface temperature and relative humidity, which was much greater than that of other physical processes. In addition, the choice of the radiation scheme had a significant impact on how the temperature was distributed close to the ground and how the wind field was simulated. Furthermore, the configuration of the MP scheme was found to exert a certain influence on the simulation of relative humidity; however, it demonstrated a weak influence on other meteorological variables. Secondly, The MYNN3 scheme for PBL process, the NoahMP scheme for LSF process, the WSM5 scheme for MP process, the RRTMG scheme for LW process, and the Dudhia scheme for SW process are found to be the comprehensive optimal physical process parameterization scheme combination for simulating meteorological variables in the research area selected in this study. As evident from the findings, the use of the OED method to obtain the combinations of the optimal physical process parameterization scheme could successfully reproduce the wind field, temperature, and relative humidity in the current study. Thus, this method appears to be highly reliable and effective for use in the WRF models to explore the optimal combinations of the physical process parameterization scheme, which could provide theoretical support to quickly analyzing accurate meteorological field data for longer periods and contribute to deeply investigating the migration and diffusion behavior of airborne pollutants in the atmosphere.

The effect of uniaxial stress on hydrogen diffusion in α-Fe: A molecular dynamics study

Hydrogen diffusion in metals is of great significance for hydrogen embrittlement and requires comprehension on the atomic scale. In this study, molecular dynamics simulations are conducted to investigate hydrogen diffusion of atoms in α-Fe under different stresses. The increase in uniaxial tensile and compressive stress tends to reduce the diffusion coefficient, suppress the diffusion of hydrogen atoms in α-Fe, and lead to differences in diffusion behavior in different directions. The change in the migration barrier explains the differences in hydrogen atom diffusion behavior under different unidirectional stresses.

Application of terahertz technology in detecting dynamic moisture diffusion behavior within the oil-impregnated insulating pressboard

Application of terahertz technology in detecting dynamic moisture diffusion behavior within the oil-impregnated insulating pressboard

Synergistic effects of mediated by different 1,2-epoxybutane addition numbers butoxylated alkyl block alcohol ethers and SDS in mixed systems

In this study, nonionic surfactant butoxylated alkyl block ether (AE9Bn) and anionic surfactant sodium dodecyl sulphate (SDS) with different BO additions were mixed at different molar ratios to make a hybrid system. The interaction parameters and aggregation behaviors of the blended systems were investigated by observing the average direct particle drop distribution and microscopic aggregates in combination with the results of static surface tension tests of the blended systems. The diffusion process of the mixed systems was investigated using dynamic surface tension tests. The dynamic contact angle and foam properties of the solutions of the mixed systems were also studied. Finally, based on the experimental results, it was concluded that the mixed system of AE9Bn (n=2,5) and SDS formed a synergistic effect that significantly led to a decrease in CMC, with an increase in the number of BO additions leading to a more significant decrease in CMC. The mixed system is a non-ideal mixed system, which is consistent with the kinetic mechanism of mixing and diffusion. The hybrid system has good aggregation pattern and wetting diffusion behavior and has low foam stability due to slow maturation of Ostwald.

Hydrogen and Carbon Dioxide Kinetic Adsorption and Diffusion Behavior into Organic-Rich Shale: Implications of Mineralogy and Organic Content

Hydrogen and Carbon Dioxide Kinetic Adsorption and Diffusion Behavior into Organic-Rich Shale: Implications of Mineralogy and Organic Content

Abstract B033: Towards magnetic resonance microscopy for liquid biopsy in cancer therapy monitoring

Abstract The advancement of liquid biopsy techniques promises to revolutionize cancer diagnostics and therapy monitoring, by offering a minimally invasive approach to track tumor progression and treatment efficacy. One central issue preventing advancements are innovations in sensor technology, necessary to enable the detection of molecular and cellular biomarkers with sufficient precision. Over the past decade, atomic-scale quantum sensors have emerged as powerful detectors, offering the ability to perform precise measurements of temperature, pressure, and magnetic fields on the single cell scale. These sensors, based on the interaction of spin qubits with their environment, have the unique capability to amplify and exploit environmental interactions for highly accurate detection, making them ideal for complex biological applications. In this context, we present an advanced quantum sensing platform specifically tailored for liquid biopsy applications in cancer therapy monitoring. This platform integrates the capabilities of optical microscopy with magnetic resonance imaging (MRI) techniques, utilizing nitrogen-vacancy (NV) centers in diamond as quantum sensors by converting magnetic resonance signals into optical signals, which are subsequently captured by a high-speed camera. Our platform offers a novel approach, promising quantitative analysis of single cancer cells from liquid samples with unprecedented accuracy. Unlike traditional MRI, our method captures signals over a wide field of view directly in real space. Each camera pixel records a magnetic resonance spectrum, providing detailed multicomponent information about the sample, such as molecular concentration, diffusion, and relaxation behavior, which are critical for understanding the tumor’s microenvironment. Our quantum sensing technology holds significant potential for enhancing the sensitivity of liquid biopsies. By capturing detailed molecular information from blood or other body fluids, it will enable in-depth analysis of Circulating Tumor Cells (CTCs), circulating tumor DNA (ctDNA), exosomes, and other biomarkers. Citation Format: Karl D. Briegel, Robin D. Allert, Dominik B. Bucher, Julia D. Draeger, Nick R v. Grafenstein, Linyan Nie. Towards magnetic resonance microscopy for liquid biopsy in cancer therapy monitoring [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B033.

Effects of Diffusing Squalene on the Plastic Deformation of Ultrahigh-Molecular-Weight Polyethylene─Insights from Molecular Dynamics Simulations.

Ultrahigh-molecular-weight polyethylene (UHMWPE) stands out as a popular artificial joint material. However, wear limits its service life, which is mainly caused by accumulation of plastic deformation. The plastic deformation on the frictional interface reflects the early wear of UHMWPE. To investigate the effect of squalene, a typical component in the body fluid, on the tribological properties of UHMWPE at microscopic scale, the diffusion behavior of squalene into polyethylene and its influence on the plastic deformation of polyethylene are discussed using the molecular dynamics (MD) simulation. The lubrication model shows that polyethylene reconstructed from the interface to lower substrate, with refactor gaps between polyethylene chains. This promotes squalene molecules to gradually diffuse into polyethylene from these gaps and causes the polyethylene structure to become loose. On the other hand, in the diffused model, squalene in polyethylene substrates increases the plastic deformation of polyethylene. The separation of squalene reduces the interaction strength between adjacent polyethylene chains and accelerates the disentanglement of polyethylene. The flexibility of "C═C" bonds in squalene allows the continuous adjustment of its spatial structures to adapt the space between polyethylene chains. The squalene fragments will not hinder the plastic flow of polyethylene.

Diffusion Behavior and Kinetics for the Vapor Phase Infiltration of Trimethylaluminum in Poly(ethylene oxide): An In Situ Quartz Crystal Microgravimetry Study.

Vapor phase infiltration (VPI) facilitates the incorporation of inorganic components into organic polymers, emerging as an effective technique for fabricating organic-inorganic hybrid materials. However, the complexity of diffusion behavior during the VPI process presents challenges in studying diffusion kinetics, particularly for highly reactive precursor-polymer systems such as trimethylaluminum (TMA) and poly(ethylene oxide) (PEO). In this study, we investigate the VPI process of TMA in PEO using in situ quartz crystal microgravimetry (QCM), which enables measurement of diffusion behavior and kinetics with high precision due to its high temporal resolution. Our results indicate that the VPI process consists of two main regions: a rapid diffusion process, corresponding to the initial penetration of the precursor into the film, followed by a slower relaxation process, attributed to the ongoing chemical reaction. The equivalent diffusion coefficient (De) was estimated to be on the order of 10-9 cm2/s and decreased with increasing aluminum content. Using energy application as a proof-of-concept, when optimized, VPI-modified PEO films were successfully utilized as solid polymer electrolytes (SPEs) for lithium metal batteries (LMBs), showcasing superior performance in mitigating lithium dendrite growth. This study offers valuable insights into the VPI process for PEO-TMA systems and provides guidance for optimizing VPI conditions to enhance the performance of advanced materials.

Polarity Gradient Solvent Confinement Membrane Cartridge to Broaden Metabolite Coverage of Plasma Untargeted Analysis.

Various polarity chemicals exist in complex samples, such as plasma; nontargeted comprehensive analysis naturally requires multiple polar-extracted solvents; consequently, the polarity of the solvent plays a crucial role in the extraction efficiency of analytes from complex samples. In the present study, based on the diffusion behavior and nanoconfinement effect of solvents in the nanoconfined space, the polarity gradient solvent confinement liquid-phase nanoextraction (PGSC-NLPNE) protocol aimed to perform a one-step nontargeted analysis of a wide range of metabolites in plasma was established. The continuously wide range of extracted solvent polarities on carbon nanofibers/carbon fiber (CNFs/CF) membranes was achieved using a mixture of hexane, dichloromethane, methanol, and water as nanoconfined solvents. The polarities (Log P) of gradient solvents ranged from -1.38 to 3.94. Correlational analyses indicated that metabolites with Log P values ranging from -1.90 to 3.84 were closely related according to similarity-intermiscibility theory. Coupled with a homemade modified guard column device, CNFs/CF membrane cartridge (CCMC), a PGSC-NLPNE-UHPLC-MS online protocol was established and applied in plasma untargeted analysis. By comparing metabolome coverage, reproducibility, and extraction recovery with protein precipitation and two-step liquid-liquid extraction commonly used in untargeted analysis, the PGSC-NLPNE-CCMC protocol demonstrated higher reproducibility and recovery. This protocol has shown great potential for ultrafast analysis of plasma untargeted metabolomics with broader metabolome coverage. It could be a potential tool to rapidly screen out valuable biomarkers related to diseases in the clinic.

Running and Tumbling Localized Structures: A Non-Brownian Motion.

Macroscopic systems present particle-type solutions. Spontaneous symmetry-breaking can cause these solutions to travel in different directions, and the inclusion of random fluctuations can induce them to run and tumble. We investigate the running and tumbling of localized structures observed on a prototype model of one-dimensional pattern formation with noise. Statistically, the dynamics of localized structures are examined, particularly the mean square displacement as a function of time. It initially shows a diffusive behavior, replaced by a ballistic one, and finally manifests itself as diffusive again. We derive a minimal model for the position and velocity of localized structures, which reveals the origin of the observed dynamics.

Prediction of Hydrogen Diffusion Behavior under the Influence of Defect Structures in Stainless Steel Passivation Film Based on Molecular Dynamics.

The excellent corrosion resistance of stainless steel primarily relies on the formation of a dense passivation film on its surface. Stress corrosion and hydrogen embrittlement are the primary forms of damage to the stainless steel passivation film, leading to film rupture and subsequent corrosion of the stainless steel substrate. The passivation film exhibits semiconducting properties and typically consists of a bilayer structure with a chromium-rich inner layer and an iron-rich outer layer. This study employs molecular dynamics simulations to investigate the interaction energy between hydrogen atoms and pristine stainless steel passivation films (Fe2O3/Cr2O3) as well as those containing three different types of defects and predicts the diffusion processes of hydrogen atoms in passivation films. The results indicate that the strongest interaction energy of -1.4402 eV is observed between hydrogen atoms and the pristine passivation film. However, as defects emerge within the passivation film, the interaction energy decreases, with a minimum energy of -0.1931 eV observed for the film containing chromium vacancies (VCr), representing a nearly one-order-of-magnitude reduction compared to the defect-free case. Furthermore, the diffusion coefficients of hydrogen atoms in the three defective passivation films are calculated as 6.437 × 10-10, 8.249 × 10-10, and 50.892 × 10-10 m2/s, respectively. Notably, the presence of a VCr defect enhances the hydrogen diffusion coefficient by an order of magnitude compared to the pristine film. Anisotropic diffusion paths and properties are elucidated through an analysis of the self-diffusion behavior of hydrogen in different detective passivation films, providing a theoretical basis for the prediction of hydrogen-induced cracking and the development of early warning technologies for passivation film surface failure.

Al-clad Cu bond wires for power electronics packaging: Microstructure evolution, mechanical performance, and molecular dynamics simulation of diffusion behaviors

With the advancement of power electronics, aluminum-clad copper thick bonding wires have garnered attentions due to superior electrical and thermal properties, making them well-suited for high-temperature and high-current applications. However, the impact remains unveiled of whether the growth of intermetallic compounds (IMCs) at the bonding interface presents critical challenges to the reliability of wedge wire bonds. Therefore, it is necessary to investigate the evolution behavior of Cu/Al IMCs in Al-clad copper wires. In this study, Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) were firstly employed to characterize the phase composition and growth behavior of Cu/Al intermetallic compounds (IMCs) at two distinct interfaces—the bonding interface and the core-shell interface—under various annealing conditions during high-temperature storage (HTS) tests, revealing a parabolic relationship between aging time and IMCs thickness. Subsequently, shear and pull tests of Al-clad copper bond wires were conducted to evaluate the bonding strength under different aging conditions, clarifying the correlation between various failure modes of the bonds and the evolution of IMCs at the bi-interfaces of this novel composite across different aging stages. Additionally, molecular dynamics (MD) simulations were employed to explore the diffusion behavior of Cu and Al atoms. It revealed that polycrystalline structures enhanced the mutual diffusion at the interface, with copper serving as the predominant element in the interdiffusion process. In conclusion, this study integrates experimental and numerical approaches to elucidate the growth mechanisms of Cu/Al intermetallic compounds and their effects on reliability, providing valuable guidance for optimizing the performance of composite bonding wires in high-temperature power device applications.