Atomic Properties Research Articles

Machine learning algorithms for optimization of magnetocaloric effect in all-d-metal Heusler alloys

This study examines the application of machine learning algorithms, specifically the Random Forest regression model, to optimize the magnetocaloric effect in all-d-metal Heusler alloys. The model was trained using descriptors related to the mean properties of individual atoms, the properties of simple compounds in their ground state, and measures of chemical disorder. It demonstrated high accuracy in predicting structural properties, while exhibiting moderate accuracy in predicting magnetic properties. To identify optimal alloy compositions, a genetic algorithm was used to find those with the greatest differences in magnetization during martensitic transitions. Using this combined approach, the Ni–Co–Mn–Ti alloy system was thoroughly explored, resulting in the discovery of an alloy with a maximum magnetization difference. These results are consistent with previous research based on density functional theory and highlight the effectiveness of integrating machine learning with genetic algorithms for the discovery of new materials with outstanding magnetocaloric properties. The study emphasizes the need for further refinement of models capable of accurately predicting complex magnetic interactions, which is essential for fully leveraging the potential of all-d-metal Heusler alloys in practical applications.

Location-Specific Microenvironment Modulation Around Single-Atom Metal Sites in Metal-Organic Frameworks for Boosting Catalysis.

Despite coordination environment of catalytic metal sites has been recognized to be of great importance in single-atom catalysts (SACs), a significant challenge remains in the understanding how the location-specific microenvironment in the higher coordination sphere influences their catalysis. Herein, a series of Cu-based SACs, namely Cu1/UiO-66-X (X = -NO2, -H, and -NH2), are successfully constructed by anchoring single Cu atoms onto the Zr-oxo clusters of metal-organic frameworks (MOFs), i.e. UiO-66-X. The -X functional groups dangling on the MOF linkers could be regarded as location-specific remote microenvironment to regulate electronic properties of the single Cu atoms. Remarkably, they exhibit significant differences in the catalysis toward the hydroboration of alkynes. The activity follows the order of Cu1/UiO-66-NO2 ˃ Cu1/UiO-66 ˃ Cu1/UiO-66-NH2 under identical reaction conditions, where Cu1/UiO-66-NO2 showcases the phenylacetylene conversion of 92%, ~3.5 times higher efficiency than that of Cu1/UiO-66-NH2. Experimental and calculation results jointly support that the Cu electronic structure is modulated by the location-specific microenvironment, thereby regulating the product desorption and promoting the catalysis.

Precise Synthesis of Dual‐Single‐Atom Electrocatalysts through Pre‐Coordination‐Directed in Situ Confinement for CO2 Reduction

AbstractDual‐single‐atom catalysts (DSACs) are the next paradigm shift in single‐atom catalysts because of the enhanced performance brought about by the synergistic effects between adjacent bimetallic pairs. However, there are few methods for synthesizing DSACs with precise bimetallic structures. Herein, a pre‐coordination strategy is proposed to precisely synthesize a library of DSACs. This strategy ensures the selective and effective coordination of two metals via phthalocyanines with specific coordination sites, such as −F− and −OH−. Subsequently, in situ confinement inhibits the migration of metal pairs during high‐temperature pyrolysis, and obtains the DSACs with precisely constructed metal pairs. Despite changing synthetic parameters, including transition metal centers, metal pairs, and spatial geometry, the products exhibit similar atomic metal pairs dispersion properties, demonstrating the universality of the strategy. The pre‐coordination strategy synthesized DSACs shows significant CO2 reduction reaction performance in both flow‐cell and practical rechargeable Zn‐CO2 batteries. This work not only provides new insights into the precise synthesis of DSACs, but also offers guidelines for the accelerated discovery of efficient catalysts.

Enzyme (α-Glucosidase, α-Amylase, PTP1B & VEGFR-2) Inhibition and Cytotoxicity of Fluorinated Benzenesulfonic Ester Derivatives of the 5-Substituted 2-Hydroxy-3-nitroacetophenones

The prevalence of small multi-target drugs containing a fluorinated aromatic moiety among approved drugs in the market is due to the unique properties of this halogen atom. With the aim to develop potent antidiabetic agents, a series of phenylsulfonic esters based on the conjugation of the 5-substituted 2-hydroxy-3-nitroacetophenones 1a–d with phenylsulfonyl chloride derivatives substituted with a fluorine atom or fluorine-containing (-CF3 or -OCF3) group were prepared. Their structures were characterized using a combination of spectroscopic techniques complemented with a single-crystal X-ray diffraction (XRD) analysis on a representative example. The compounds were, in turn, assayed for inhibitory effect against α-glucosidase, α-amylase, protein tyrosine phosphatase 1 B (PTP1B) and the vascular endothelial growth factor receptor-2 (VEGFR-2) all of which are associated with the pathogenesis and progression of type 2 diabetes mellitus (T2DM). The antigrowth effect of selected compounds was evaluated on the human breast (MCF-7) and lung (A549) cancer cell lines. The compounds were also evaluated for cytotoxicity against the African Green Monkey kidney (Vero) cell line. The results of an in vitro enzymatic study were augmented by molecular docking (in silico) analysis. Their ADME (absorption, distribution, metabolism and excretion) properties have been evaluated on the most active compounds against α-glucosidase and/or α-amylase to predict their drug likeness.

Satellite Pd Single-Atom Embraced AuPd Alloy Nanoclusters for Enhanced Hydrogen Evolution.

The fabrication of hybrid active sites that synergistically contain nanoclusters and single atoms (SAs) is vital for electrocatalysts to achieve excellent activity and durability. Herein, we develop a ligand-assisted pyrolysis strategy using nanoclusters (Au4Pd2(SC2H4Ph)8) with alloy cores and protected ligands to build AuPd cluster sites embraced by satellite Pd SAs. In the thermal drive control process, different thermodynamic properties of the alloy atoms and the confinement effects of organic ligands allow for the mild spillover of the single-component metal Pd, resulting in the formation of AuPd alloy nanoclusters tightly encompassed by isolated Pd atoms. Experiments and theoretical calculations indicated that the satellite Pd atoms can optimize the electronic structure of the AuPd nanoclusters and Au sites in the alloy to facilitate the adsorption and dissociation of H2O, thus enhancing the hydrogen evolution reaction (HER) activity. The optimal AuPdNCs/PdSAs-600 exhibits outstanding electrocatalytic activity toward HER, with overpotentials of 21 and 38 mV at 10 mA cm-2 in acidic and alkaline media, respectively. Moreover, the mass activity and turnover frequency of AuPdNCs/PdSAs-600 are one order of magnitude higher than those of commercial Pd/C and Pt/C catalysts. This facile strategy for constructing hybrid catalytic centers using ligand-protected nanoclusters provides efficient insights for the further design of nanocluster-based electrocatalysts synergized by SAs.

Effect of the electronic properties of the side charges of neutral solvent molecules on the charges of the N and H atoms of the carbazole molecule: IR experiment and DFT calculations

The IR spectral parameters of the absorption band of the valence vibration of the NH bond of the carbazole molecule in several neutral solvents (n-hexane C6H14, carbon tetrachloride CCl4, chloroform CHCl3, benzene C6H6) have been measured. It has been experimentally established that the position of the maximum of the NH vibrational band of the carbazole molecule in solvents undergoes a low-frequency shift relative to the gas phase. This shift increases in the series C6H14, CCl4, CHCl3, C6H6. The change in the magnitude of the linear shift is well described by the Kirkwood-Bauer-Magat KBM ratio in C6H14, CCl4, CHCl3. The presence of a linear shift may indicate that only universal interactions take place. The deviation of this ratio of shift magnitude for carbazole in benzene is interpreted as a manifestation of intermolecular complexation. Quantum-chemical calculations of the position of the absorption band position of the valence vibration of the NH bond of the carbazole molecule in these solvents, carried out by the electron density functional method B3LYP/6-31G using the Gaussian 09W program package, also showed a low-frequency shift relative to the gas phase.It was found that for the carbazole molecule in the condensed phase relative to the gas phase the following effects of changing the magnitude of charges on atoms N13 and H14 take place: 1 – increase in the positive sign of the charge on both atoms; 2 – the change in charge magnitude is larger on the nitrogen atom than on the hydrogen atom for both solvents (whose molecules have a dipole moment ∼0: C6H14, CCl4); 3 – the chlorine containing environment has a greater effect on the charge change in the carbazole molecule than the proton containing environment (whose molecules have a dipole moment ∼0: C6H14, CCl4).The correlation between the change of charges on atoms N13 and H14 with the value of electronegativity ξ of the side solvent atoms was established.Thus, it is shown that the charges on the 13N and 14H atoms of the carbazole molecule undergo changes in the presence of universal interactions, and the magnitude of the charge change depends on the electronic properties of the side atoms of the nearest solvent molecules. A hypothesis is proposed to explain the different frequency shift of the NH vibrational frequency of the molecule for chlorine-containing and hydrogen-containing side atoms of neutral solvent molecules, which takes into account different values of ξ for nitrogen and hydrogen atoms.

Theoretical Study on BiCoO3: Pressure‐Tuned Transformation of Structure, Magnetism, Charge, and Spin State

AbstractThe atomic structures, electronic structures, magnetic properties, and spin states of BiCoO3 multiferroic material under hydrostatic pressure are comprehensively investigated by using first‐principles calculation based on density functional theory. Firstly, we found the pressure‐tuned structural symmetry transition from tetragonal P4 mm (No. 99) to cubic Pmm (No. 221) space group. The structural transformation prompts the Co─O polyhedral coordination transfer from a CoO5 pyramidal to a CoO6 distorted octahedron. Secondly, the pressure‐induced magnetic change from C‐type antiferromagnetic state to ferromagnetic state and then to paramagnetic configuration occurred after continuous compression of the volume. Essentially, the fundamental reason for the transition of the magnetic structure lies in the change of the internal atomic structure, such as the pressure induced abrupt changes of Co─O bond length and <Co─O─Co> bond angle. Meanwhile, an obvious volume collapse was observed when the pressure was applied to 51–56 GPa. Finally, as the pressure increases, the magnetism changes from C‐type antiferromagnetic state to paramagnetic configuration, accompanying the transformation from high spin state with b2g2eg2a1g1b1g1 configuration in pyramid structure to low spin state with t2g6eg0 in octahedral field. Therefore, our results demonstrate that applied hydrostatic pressure in BiCoO3 can trigger the transformation of structure, magnetism, charge, and spin state.

Investigating the atomic structures and electronic properties of WS2 thin films with sulfur vacancies via a neural network potential-aided first-principles study

Transition metal dichalcogenides are promising materials for high-performance electronics, whereas the impact of defects on their electronic properties remains elusive. Here, we employ neural network potentials (NNPs) constructed from density functional theory (DFT) data to investigate defect-laden WS2 thin films. Molecular dynamics simulations reveal that at low defect concentrations (S/W ratio of 1.9), single sulfur vacancies are predominant. Conversely, at high defect concentrations (S/W ratio of 1.7), complex defects with short lifetimes appear. Additionally, DFT results indicate that the band gap persists at S/W = 1.9 but disappears at 1.7, aligning with observed device degradation at high defect concentrations.

Electronic and Magnetic Properties of Cobalt Clusters on Pristine and Divacancy Graphene

Using ab initio calculations we investigate the adsorption of Co atoms, dimers and small cobalt clusters of 5 and 13 atoms on pristine graphene and graphene with a double vacancy. We report the atomic, electronic, magnetic and energetic properties of these systems. Stable adsorption configurations tend to maximize the number of cobalt-carbon bonds. On graphene, the adsorption energy of the clusters is only about 0.4 to 1 eV, and the clusters are relatively mobile on graphene. Interestingly, for different adsorbed Co13 isomers on graphene it is found that they converge to the same atomic structure. On graphene with a divacancy, the Co clusters bind in the divacancy site and isomerisation also occurs for the Co5 cluster system as well as for Co13. Co atoms and clusters can be effectively immobilized on the divacancy with corresponding adsorption energy being significantly enhanced by about 5 to 7 eV. All clusters act as electron donors in the interaction with the graphene/divacancy systems, and the amount of electron charge transfer increases with cluster size. Finite magnetic moments occur for all systems, where upon adsorption, the magnetic moment of the isolated Co atom (3μB) is significantly reduced due to electron transfer and bonding, resulting in values varying from ≈0.9-2.2 μB per Co atom. For the pristine graphene substrate, the total induced magnetic moments on the carbon atoms are negligible, while on the divacancy system, they are of the order of 0.1-0.3 μB. The attractive physical properties of these hybrid systems could find applications in catalysis and materials science.

Electronic Structure of Rh and Ir Single Atom Catalysts Supported on Defective and Doped ZnO: Assessment of Their Activity Towards CO Oxidation.

This study investigated the electronic structure of single-atom Rhodium (Rh) and Iridium (Ir) adsorbed on defective and impurity-doped ZnO(0001) surfaces, and assessed their activity towards the CO oxidation reaction. Our findings reveal that surface impurities significantly influence the binding energies and electronic properties of the metal atoms, with Al and Cr serving as particularly effective promoters. While Rh and Ir acquire a positive charge upon incorporation on the unpromoted Zn(0001) surface, adsorption directly on the promoter results in a net negative charge, thus facilitating the activation of both CO and O2 species. These results highlight the potential of impurity-promoted ZnO surfaces in modulating and tailoring the electronic properties of SACs, which can be used for a rational design of active single-atom catalysts.

A computational study and analysis of Variational Quantum Eigensolver over multiple parameters for molecules and ions

AbstractMaterial discovery is a phenomenon practiced since the evolution of the world. The discovery of materials has led to significant development in varied fields such as Science, Engineering and Technology. Computationally simulating molecules has been an area of interest in the industry as well as academia. However, simulating large molecules can be computationally expensive in terms of computing power and complexity. Quantum computing is a recent development that can improve the efficiency in predicting properties of atoms and molecules which will be useful for material design. The Variational Quantum Eigensolver (VQE) is one such quantum algorithm used to calculate the ground state energy of molecules or ions. In this study, we have done a comparative analysis of the parameters that constitute the VQE algorithm. This includes components such as basis, qubit mapping, ansatz, and optimizers used. We have also developed a database consisting of 79 single atoms and their variations of oxidation states and 33 molecules with the data of their Hamiltonian and ground state energy and dipole moment.

QM9star, two Million DFT-computed Equilibrium Structures for Ions and Radicals with Atomic Information

Ions and radicals serve as key intermediates in molecular transformation, with their chemical properties being essential for understanding and predicting reaction reactivity and selectivity. In this data descriptor, we report a quantum chemical dataset named QM9star, comprising cations, anions, and radicals. This dataset is derived from the molecular structures of the QM9 dataset, created by removing terminal hydrogens followed by optimization using B3LYP-D3(BJ)/6-311 + G(d,p) level of density functional theory. The QM9star dataset includes approximately 1.9 million cations, anions, and radicals, along with 120 kilo neutral molecules prior to hydrogen removal. Each entry encompasses both molecular and atomic information: representative global properties include orbital energies, vibrational frequencies, etc., while local properties cover aspects such as charges and spin densities at each atomic site. The QM9star dataset not only serves as a comprehensive source of quantum chemical information for intermediates but also offers insights into the principle of atomic property distribution. We anticipate that these data will aid in machine learning studies related to chemical intermediates and contribute to the molecular representation learning.

Exploring the properties of antituberculosis drugs through QSPR graph models and domination-based topological descriptors

Tuberculosis (TB) is a global health concern caused by the bacterium Mycobacterium tuberculosis. This infectious disease primarily affects the lungs but can also impact other organs. Effective TB control involves early diagnosis, appropriate treatment with a combination of antibiotics, and public health measures to prevent transmission. However, ongoing challenges include drug-resistant strains and socioeconomic factors influencing its prevalence. Drugs such as isoniazid, pyrazinamide, ethambutol, ethionamide, linezolid, and levofloxacin are approved for the treatment of drug-susceptible tuberculosis. The properties and other activities of the drug, can be analyzed by modelling its chemical structure in terms of a molecular graph \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$G=\\left(V,E\\right)$$\\end{document}, by considering the atoms as the vertex set \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$V\\left(G\\right)$$\\end{document} and the bonds between the two atoms as the edge set \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$E\\left(G\\right)$$\\end{document}. A molecular descriptor or topological index of \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$G$$\\end{document} represents the corresponding chemical molecule as a numerical value. Domination is one of the key concepts in the molecular structure used to analyze the properties of atoms. In this article, the domination distance-based topological indices of the drugs isoniazid, pyrazinamide, ethambutol, ethionamide, linezolid, and levofloxacin are computed to conduct QSPR (Quantitative Structure–Property Relationship) analysis, exploring their physicochemical and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties. Quadratic regression is then used in the QSPR analysis to examine the physicochemical and ADMET properties of these drugs. The results of this analysis indicate that the domination Schultz index and domination SM index are the indices most strongly correlated with the majority of the physicochemical and ADMET properties. The QSPR analysis can also be extended to analogs of these drugs and to other treatment drugs, such as rifampin and rifapentine, to further explore their properties.

Electronic and Optical Properties of 2D Heterostructure Bilayers of Graphene, Borophene and 2D Boron Carbides from First Principles.

In the present work the atomic, electronic and optical properties of two-dimensional graphene, borophene, and boron carbide heterojunction bilayer systems (Graphene-BC3, Graphene-Borophene and Graphene-B4C3) as well as their constituent monolayers are investigated on the basis of first-principles calculations using the HSE06 hybrid functional. Our calculations show that while borophene is metallic, both monolayer BC3 and B4C3 are indirect semiconductors, with band-gaps of 1.822 eV and 2.381 eV as obtained using HSE06. The Graphene-BC3 and Graphene-B4C3 bilayer heterojunction systems maintain the Dirac point-like character of graphene at the K-point with the opening of a very small gap (20-50 meV) and are essentially semi-metals, while Graphene-Borophene is metallic. All bilayer heterostructure systems possess absorbance in the visible region where the resonance frequency and resonance absorption peak intensity vary between structures. Remarkably, all heterojunctions support plasmons within the range 16.5-18.5 eV, while Graphene-B4C3 and Graphene-Borophene exhibit a π-type plasmon within the region 4-6 eV, with the latter possessing an additional plasmon at the lower energy of 1.5-3 eV. The dielectric tensor for Graphene-B4C3 exhibits complex off-diagonal elements due to the lower P3 space group symmetry indicating it has anisotropic dielectric properties and could exhibit optically active (chiral) effects. Our study shows that the two-dimensional heterostructures have desirable optical properties broadening the potential applications of the constituent monolayers.

Neural-network approach to running high-precision atomic computations

Modern applications of atomic physics, including the determination of frequency standards and the analysis of astrophysical spectra, require prediction of atomic properties with exquisite accuracy. For complex atomic systems, high-precision calculations are a major challenge due to the exponential scaling of the involved electronic configuration sets. This exacerbates the problem of required computational resources for these computations and makes indispensable the development of approaches to select the most important configurations out of otherwise intractably huge sets. We have developed a neural-network (NN) tool for running high-precision atomic configuration interaction (CI) computations with iterative selection of the most important configurations. Integrated with the established atomic codes, our approach results in computations with significantly reduced computational requirements in comparison with those without NN support. We showcase a number of NN-supported computations for the energy levels of Fe16+ and Ni12+ and demonstrate that our approach can be reliably used and automated for solving specific computational problems for a wide variety of systems. Published by the American Physical Society 2024

Emerging two-dimensional ferromagnetic semiconductors.

Two-dimensional (2D) semiconductors have attracted considerable attention for their potential in extending Moore's law and advancing next-generation electronic devices. Notably, the discovery and development of 2D ferromagnetic semiconductors (FMSs) open exciting opportunities in manipulating both charge and spin, enabling the exploration of exotic properties and the design of innovative spintronic devices. In this review, we aim to offer a comprehensive summary of emerging 2D FMSs, covering their atomic structures, physical properties, preparation methods, growth mechanisms, magnetism modulation techniques, and potential applications. We begin with a brief introduction of the atomic structures and magnetic properties of novel 2D FMSs. Next, we delve into the latest advancements in the exotic physical properties of 2D FMSs. Following that, we summarize the growth methods, associated growth mechanisms, magnetism modulation techniques and spintronic applications of 2D FMSs. Finally, we offer insights into the challenges and potential applications of 2D FMSs, which may inspire further research in developing high-density, non-volatile storage devices based on 2D FMSs.

Predicting refractive index of inorganic compounds using machine learning

Refractive index (RI) is one of the most important optical properties of materials. Due to the high importance of this physical parameter, there has always been a demand to find a method that provides the most optimal estimation. In this research, we utilize experimentally measured RI values of 272 inorganic compounds to build a machine learning model capable of predicting the RI of materials with low computational cost. Considering the significant relationship between the band gap and RI, we select this parameter as a predictor. In addition to the band gap, the atomic properties related to the building elements of the compounds form our data set in this work. To find the most optimal model and set of suitable predictors, we examine our data in four categories with 1, 5, 10, and 21 features. In addition, we compare the predicted RIs of 6 different independent regression methods, namely, ordinary least squares (OLSR), Gaussian process (GPR), support vector (SVR), random forest (RFR), gradient boosted trees (GBTR), and extremely randomized trees regression(ERTR). We notice that ERTR predicts RI with the highest accuracy compared to other regression methods. The prediction strength of our model excels in empirical relations and provides accurate results for a wide range of RIs. Thus, we demonstrate the high potential of machine learning methods for evaluating the RI, especially when it comes to providing an estimation of a desired physical quantity.

First-principles thermodynamical modeling of molecular reactions on α-U(001) and α-UH3(001) surfaces and their influence on hydrogen activation

Density functional theory calculations coupled with thermodynamic analysis have been performed to investigate the reactions of hydrogen and impurity gases including O2, CO2, CO, N2 on α-U(001) and α-UH3(001) surfaces. Binding strength of adsorbates on α-UH3 is calculated to be weaker than α-U, suggesting enhanced poisoning-resistant properties of U-hydride compared to its metallic state. Surface phase diagrams of U under binary H2-O2, H2-N2 and H2-CO gaseous environments show that while N and C elements prefer to stay in their hydrogenated states on the hydride surface, isolated O atoms favorably interact with both α-U(001) and α-UH3(001), indicating the heavily poisoning effect of impurities containing oxygen. Global optimization of partially oxidized α-U(001) slabs induces surface geometry reconstruction and the activity of oxidized surfaces toward hydrogen adsorption can be linearly correlated with local electronic and atomic properties of the adsorption site.

Atomic and electronic properties of 2D Chevrel phases: A case study of the superatomic two-dimensional semiconductor Re6Se8Cl2

The design of two-dimensional superatomic materials, which form their atomic structures through covalently bonded clusters with variable chemical compositions, will enable the development of new materials with promised electronic properties that are beneficial for modern nanoelectronics. This paper presents ab initio calculations of the atomic and electronic structures of both bulk and 2D Re6Se8Cl2. The calculations were carried out using density functional theory, incorporating noncollinear spin density and the pseudopotential method. The results include data on the atomic structure, band gap value, formation energy of the Re6Se8Cl2 2D layer, and the redistribution of atomic charges within the structures. The differences in effective masses for electrons and holes in the two-dimensional and bulk Re6Se8Cl2 materials are demonstrated, along with an explanation of how these differences impact their transport properties. The findings are expected to be of great significance for the design, synthesis, and implementation of new two-dimensional superatomic materials with controlled properties in modern nanoelectronics.

The effects of hydrogen on the bonding properties of SiC/Cu interface via first-principles calculations

Ceramic/metal interfaces own great importance of technology, but the weak interface bond limits their applications. In this work, the effects of doping H element on the stability and bonding properties of SiC/Cu interface are studied by first principles calculations. In order to study the stability of interface, the potential surfaces were firstly studied for the C and Si terminated SiC/Cu interfaces. The C terminated interface is more stable than the Si terminated interface, which contributes the largest work of adhesion of 3.998 J/m2. The effects of hydrogen on the interface bonding properties were further studied. The occupation properties of hydrogen atoms were then studied, the hydrogen tends to occupy the octahedral position with negative formation energy. To reveal the bonding strength of SiC/Cu interface, the tensile simulations were carried out. The hydrogen owns obvious effects on the tensile strength depends on its occupation site. The movement and diffusion properties of hydrogen atoms in the interface zone were studied combining molecular dynamics and climbing image nudged elastic band method. Finally, the bonding mechanisms were analyzed by combining charge density, state density, differential charge and bader charge. Based on the above calculation results, it is found that for SiC(001)/Cu(111) interface, the H element generally has a negative impact on the bonding properties of SiC/Cu interface.