Origin of the herringbone reconstruction of Au(111) surface at the atomic scale

Evaluation of electrodeposition synthesis of gold nanodendrite on screen-printed carbon electrode for nonenzymatic ascorbic acid sensor

Gold nanodendrite (AuND) is a type of gold nanoparticles with dendritic or branching structures that offers advantages such as large surface area and high conductivity to improve electrocatalytic performance of electrochemical sensors. AuND structures can be synthesized using electrodeposition method utilizing cysteine as growth directing agent. This method can simultaneously synthesize and integrate the gold nanostructures on the surface of the electrode. We conducted a comprehensive study on the synthesis of AuND on screen-printed carbon electrode (SPCE)-based working electrode, focusing on the optimization of electrodeposition parameters, such as applied potential, precursor solution concentration, and deposition time. The measured surface oxide reduction peak current and electrochemical surface area from cyclic voltammogram were used as the optimization indicators. We confirmed the growth of dendritic gold nanostructures across the carbon electrode surface based on FESEM, EDS, and XRD characterizations. We applied the SPCE/AuND electrode as a nonenzymatic sensor on ascorbic acid (AA) and obtained detection limit of 16.8 μM, quantification limit of 51.0 μM, sensitivity of 0.0629 μA μM-1, and linear range of 180-2700 μM (R2 value = 0.9909). Selectivity test of this electrode against several interferences, such as uric acid, dopamine, glucose, and urea, also shows good response in AA detection.

Gold oxide formation on Au(111) under CO oxidation conditions at room temperature

Although gold-based catalysts are promising candidates for selective low-temperature CO oxidation, the reaction mechanism is not fully understood. On a Au(111) model catalyst, we observe the formation of gold oxide islands under exposure to atmospheric pressures of oxygen or CO oxidation reaction conditions in an in situ scanning tunneling microscope. The gold oxide formation is interpreted in line with the water-enabled dissociation of O2 on the step edges of Au(111). Contaminants on the gold surface can strongly promote the gold oxide formation even on the terraces. On the other hand, TiO2 nanoparticles on the Au(111) do not show any influence on the formation of the gold oxide and are thus not providing a significant amount of atomic oxygen to the gold at room temperature. Overall, the presence of gold oxide is likely under industrial conditions.

Exploring fracture of H-BN and graphene by neural network force fields

Extreme mechanical processes such as strong lattice distortion and bond breakage during fracture often lead to catastrophic failure of materials and structures. Understanding the nucleation and growth of cracks is challenged by their multiscale characteristics spanning from atomic-level structures at the crack tip to the structural features where the load is applied. Atomistic simulations offer 'first-principles' tools to resolve the progressive microstructural changes at crack fronts and are widely used to explore the underlying processes of mechanical energy dissipation, crack path selection, and dynamic instabilities (e.g. kinking, branching). Empirical force fields developed based on atomic-level structural descriptors based on atomic positions and the bond orders do not yield satisfying predictions of fracture, especially for the nonlinear, anisotropic stress-strain relations and the energy densities of edges. High-fidelity force fields thus should include the tensorial nature of strain and the energetics of bond-breaking and (re)formation events during fracture, which, unfortunately, have not been taken into account in either the state-of-the-art empirical or machine-learning force fields. Based on data generated by density functional theory calculations, we report a neural network-based force field for fracture (NN-F3) constructed by using the end-to-end symmetry preserving framework of deep potential-smooth edition (DeepPot-SE). The workflow combines pre-sampling of the space of strain states and active-learning techniques to explore the transition states at critical bonding distances. The capability of NN-F3is demonstrated by studying the rupture of hexagonal boron nitride (h-BN) and twisted bilayer graphene as model problems. The simulation results elucidate the roughening physics of fracture defined by the lattice asymmetry in h-BN, explaining recent experimental findings, and predict the interaction between cross-layer cracks in twisted graphene bilayers, which leads to a toughening effect.

The Reconstruction of Pt(001) Surface and the Shell-Like Reconstruction of the Vicinal Pt(001) Surfaces Revealed by Neural Network Potential

In this work, a highly accurate neural network potential (NNP) is presented, named PtNNP, and the exploration of the reconstruction of the Pt(001) surface and its vicinal surfaces with it. Contrary to the most accepted understanding of the Pt(001) surface reconstruction, the study reveals that the main driving force behind Pt(001) quasi-hexagonal reconstruction is not the surface stress relaxation but the increased coordination number of the surface atoms resulting in stronger intralayer binding in the reconstructed surface layer. In agreement with experimental observations, the optimized supercell size of the reconstructed Pt(001) surface contains (5 × 20) unit cells. Surprisingly, the reconstruction of the vicinal Pt(001) surfaces leads to a smooth shell-like surface layer covering the whole surface and diminishing sharp step edges.

Impacts of hot electron diffusion, electron-phonon coupling, and surface atoms on metal surface dynamics revealed by reflection ultrafast electron diffraction

Metals exhibit nonequilibrium electron and lattice subsystems at transient times following femtosecond laser excitation. In the past four decades, various optical spectroscopy and time-resolved diffraction methods have been used to study electron-phonon coupling and the effects of underlying dynamical processes. Here, we take advantage of the surface specificity of reflection ultrafast electron diffraction (UED) to examine the structural dynamics of photoexcited metal surfaces, which are apparently slower in recovery than predicted by thermal diffusion from the profile of absorbed energy. Fast diffusion of hot electrons is found to critically reduce surface excitation and affect the temporal dependence of the increased atomic motions on not only the ultrashort but also sub-nanosecond times. Whereas the two-temperature model with the accepted physical constants of platinum can reproduce the observed surface lattice dynamics, gold is found to exhibit appreciably larger-than-expected dynamic vibrational amplitudes of surface atoms while keeping the commonly used electron-phonon coupling constant. Such surface behavioral difference at transient times can be understood in the context of the different strengths of binding to surface atoms for the two metals. In addition, with the quantitative agreements between diffraction and theoretical results, we provide convincing evidence that surface structural dynamics can be reliably obtained by reflection UED even in the presence of laser-induced transient electric fields.

Out-of-Plane Single-Copper-Site Catalysts for Room-Temperature Benzene Oxidation

Crafting single-atom catalysts (SACs) that possess "just right" modulated electronic and geometric structures, granting accessible active sites for direct room-temperature benzene oxidation is a coveted objective. However, achieving this goal remains a formidable challenge. Here, we introduce an innovative in situ phosphorus-immitting strategy using a new phosphorus source (phosphorus nitride, P3N5) to construct the phosphorus-rich copper (Cu) SACs, designated as Cu/NPC. These catalysts feature locally protruding metal sites on a nitrogen (N)-phosphorus (P)-carbon (C) support (NPC). Rigorous analyses, including X-ray absorption spectroscopy (XAS) and X-ray photoelectron spectroscopy (XPS), validate the coordinated bonding of nitrogen and phosphorus with atomically dispersed Cu sites on NPC. Crucially, systematic first-principles calculations, coupled with the climbing image nudged-elastic-band (CI-NEB) method, provide a comprehensive understanding of the structure-property-activity relationship of the distorted Cu-N2P2 centers in Cu/NPC for selective oxidation of benzene to phenol production. Interestingly, Cu/NPC has shown more energetically favorable C-H bond activation compared to the benchmark Cu/NC SACs in the direct oxidation of benzene, resulting in outstanding benzene conversion (50.3 %) and phenol selectivity (99.3 %) at room temperature. Furthermore, Cu/NPC achieves a remarkable turnover frequency of 263 h-1 and mass-specific activity of 35.2 mmol g-1 h-1, surpassing the state-of-the-art benzene-to-phenol conversion catalysts to date.

Low-index mesoscopic surface reconstructions of Au surfaces using Bayesian force fields

Metal surfaces have long been known to reconstruct, significantly influencing their structural and catalytic properties. Many key mechanistic aspects of these subtle transformations remain poorly understood due to limitations of previous simulation approaches. Using active learning of Bayesian machine-learned force fields trained from ab initio calculations, we enable large-scale molecular dynamics simulations to describe the thermodynamics and time evolution of the low-index mesoscopic surface reconstructions of Au (e.g., the Au(111)-'Herringbone,' Au(110)-(1 × 2)-'Missing-Row,' and Au(100)-'Quasi-Hexagonal' reconstructions). This capability yields direct atomistic understanding of the dynamic emergence of these surface states from their initial facets, providing previously inaccessible information such as nucleation kinetics and a complete mechanistic interpretation of reconstruction under the effects of strain and local deviations from the original stoichiometry. We successfully reproduce previous experimental observations of reconstructions on pristine surfaces and provide quantitative predictions of the emergence of spinodal decomposition and localized reconstruction in response to strain at non-ideal stoichiometries. A unified mechanistic explanation is presented of the kinetic and thermodynamic factors driving surface reconstruction. Furthermore, we study surface reconstructions on Au nanoparticles, where characteristic (111) and (100) reconstructions spontaneously appear on a variety of high-symmetry particle morphologies.

Molecular-Scale Visualization of Steric Effects of Ligand Binding to Reconstructed Au(111) Surfaces

Direct imaging of single molecules at nanostructured interfaces is a grand challenge with potential to enable new, precise material architectures and technologies. Of particular interest are the structural morphology and spectroscopic signatures of the adsorbed molecule, where modern probes are only now being developed with the necessary spatial and energetic resolution to provide detailed information at the molecule-surface interface. Here, we directly characterize the adsorption of individual m-terphenyl isocyanide ligands on a reconstructed Au(111) surface through scanning tunneling microscopy and inelastic electron tunneling spectroscopy. The site-dependent steric pressure of the various surface features alters the vibrational fingerprints of the m-terphenyl isocyanides, which are characterized with single-molecule precision through joint experimental and theoretical approaches. This study provides molecular-level insights into the steric-pressure-enabled surface binding selectivity as well as its effect on the chemical properties of individual surface-binding ligands.

Automated Generation and Analysis of Molecular Images Using Generative Artificial Intelligence Models

The development of scanning probe microscopy (SPM) has enabled unprecedented scientific discoveries through high-resolution imaging. Simulations and theoretical analysis of SPM images are equally important as obtaining experimental images since their comparisons provide fruitful understandings of the structures and physical properties of the investigated systems. So far, SPM image simulations are conventionally based on quantum mechanical theories, which can take several days in tasks of large-scale systems. Here, we have developed a scanning tunneling microscopy (STM) molecular image simulation and analysis framework based on a generative adversarial model, CycleGAN. It allows efficient translations between STM data and molecular models. Our CycleGAN-based framework introduces an approach for high-fidelity STM image simulation, outperforming traditional quantum mechanical methods in efficiency and accuracy. We envision that the integration of generative networks and high-resolution molecular imaging opens avenues in materials discovery relying on SPM technologies.

Realization of large-area ultraflat chiral blue phosphorene

Blue phosphorene (BlueP), a theoretically proposed phosphorous allotrope with buckled honeycomb lattice, has attracted considerable interest due to its intriguing properties. Introducing chirality into BlueP can further enrich its physical and chemical properties, expanding its potential for applications. However, the synthesis of chiral BlueP remains elusive. Here, we demonstrate the growth of large-area BlueP films on Cu(111), with lateral size limited by the wafer dimensions. Importantly, we discovered that the BlueP is characterized by an ultraflat honeycomb lattice, rather than the prevailing buckled structure, and develops highly ordered spatial chirality plausibly resulting from the rotational stacking with the substrate and interface strain release, as further confirmed by the geometric phase analysis. Moreover, spectroscopic measurements reveal its intrinsic metallic nature and different characteristic quantum oscillations in the image-potential states, which can be exploited for a range of potential applications including polarization optics, spintronics, and chiral catalysis.

Silicene growth mechanisms on Au(111) and Au(110) substrates

Despite the remarkable theoretical applications of silicene, its synthesis remains a complex task, with epitaxial growth being one of the main routes involving depositing evaporated Si atoms onto a suitable substrate. Additionally, the requirement for a substrate to maintain the silicene stability poses several difficulties in accurately determining the growth mechanisms and the resulting structures, leading to conflicting results in the literature. In this study, large-scale molecular dynamics simulations are performed to uncover the growth mechanisms and characteristics of epitaxially grown silicene sheets on Au(111) and Au(110) substrates, considering different temperatures and Si deposition rates. The growth process has been found to initiate with the nucleation of several independent islands homogeneously distributed on the substrate surface, which gradually merge to form a complete silicene sheet. The results consistently demonstrate the presence of a buckled silicene structure, although this characteristic is notably reduced when using an Au(111) substrate. Furthermore, the analysis also focuses on the quality and growth mode of the silicene sheets, considering the influence of temperature and deposition rate. The findings reveal a prevalence of the Frank-van der Merwe growth mode, along with diverse forms of defects throughout the sheets.

Aurophilic Molecules on Surfaces. Part II. (NapNC)AuCl on Au(111)

Although aurophilicity is a well-known phenomenon in structural gold chemistry and is found in many crystals of Au(I) complexes, its potential for self-assembly in thin films is not yet explored. This paper is Part II of a study, in which we investigated the ultrathin film formation of chlorido(2-naphthyl isonitrile) gold(I) on gold surfaces. Here, we present the data for the growth of (NapNC)AuCl on isotropic Au(111) surfaces. Already during physical vapor deposition, the condensation of ultrathin films is monitored by photoelectron emission microscopy (PEEM) and incremental and spectrally resolved changes in the optical reflectance (DDRS). Additional structural data obtained by scanning tunneling microscopy (STM) and low-energy electron diffraction (LEED) reveal that the "crossed swords" packing motif known from the bulk is also present in thin films.

Adsorption of sulfur on Au(111) surface: An extremely stable configuration

The sulfur adsorption on gold surface is a hot topic in catalysis, electrochemistry and chemical sensors. However, the multiple structures of adsorbed sulfur and sulfur-induced reconstruction in gold substrate topography are still open problems until now. Here we performed an extensively study on sulfur adsorption on Au(111) surface based on First-Principles calculation. Our results show that the sulfur adsorption with additional Au atoms is not favorable. Thus, the well-known lifting of the herringbone reconstruction of Au(111) after sulfur adsorption can't be attributed to the lifting gold atoms. More importantly, we proposed an extremely stable configuration of S-Au(111) surface characterized by (√3 × √3)R30° at 0.33 coverage, in which each S atom is chemisorbed in 3-fold coordinated sites and all the surface-Au atoms are terminated. Finally, the good agreement between our simulated STM and LEED images and experimental observations illuminates the truth that our proposed configuration is also favorable in experiment. This super stable S-adsorbed surface can be used as a starting point for the growth of two dimensional transition metal sulfides.

Synthesis of Self-Assembled Single Atomic Layer Gold Crystals-Goldene

We report, for the first time, a technique to synthesize free-standing, one-atom thick 2D gold crystals (namely, goldene) and self-assembled 2D periodic arrays of goldene. High-resolution transmission electron microscopy (HRTEM) imaging of goldene revealed herringbone and honeycomb lattices, which are primarily gold surface features due to its reconstruction. Imaging of these surface-only features by a nonsurface characterization technique such as HRTEM is an unequivocal proof of the absence of three-dimensionality in goldene. Atomic force microscopy confirmed 1-2 Å thickness of goldene. High-resolution X-ray photoelectron spectroscopy (HR-XPS), selective area electron diffraction, and energy-dispersive X-ray spectroscopy confirmed the chemical identity of goldene. We discovered the phenomenon of electric field-induced self-assembly of goldene supracrystals with a herringbone structure and developed an electric field printing (e-print) technique for goldene arrays. Goldene showed a semiconductor response with a knee voltage of ∼3.2 V, and I/V spectroscopy revealed periodic room temperature Coulomb blockade oscillations. These observations are consistent with the theoretical calculations reported in the literature predicting enhanced Coulombic interactions between gold valence electrons and the nucleus in stable 2D gold. Goldene exhibited multiple, intense, and well-resolved optical absorption peaks and several fine bands across the UV-vis region, and we calculated its optical band gap to be 3.59 eV. Magnetic force microscopy measurements of goldene periodic arrays showed a ∼5 mV peak amplitude confirming its ferromagnetism. Optical and magnetic properties of goldene are consistent with those reported in the literature for 2D planar gold clusters with less than 12 atoms.