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Single atoms or ions on surfaces affect processes from nucleation1 to electrochemical reactions2 and heterogeneous catalysis3. Transmission electron microscopy is a leading approach for visualizing single atoms on a variety of substrates4,5. It conventionally requires high vacuum conditions, but has been developed for in situ imaging in liquid and gaseous environments6,7 with a combined spatial and temporal resolution that is unmatched by any other method-notwithstanding concerns about electron-beam effects on samples. When imaging in liquid using commercial technologies, electron scattering in the windows enclosing the sample and in the liquid generally limits the achievable resolution to a few nanometres6,8,9. Graphene liquid cells, on the other hand, have enabled atomic-resolution imaging of metal nanoparticles in liquids10. Here we show that a double graphene liquid cell, consisting of a central molybdenum disulfide monolayer separated by hexagonal boron nitride spacers from the two enclosing graphene windows, makes it possible to monitor, with atomic resolution, the dynamics of platinum adatoms on the monolayer in an aqueous salt solution. By imaging more than 70,000 single adatom adsorption sites, we compare the site preference and dynamic motion of the adatoms in both a fully hydrated and a vacuum state. We find a modified adsorption site distribution and higher diffusivities for the adatoms in the liquid phase compared with those in vacuum. This approach paves the way for in situ liquid-phase imaging of chemical processes with single-atom precision.
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Recent advancements in machine learning potentials (MLPs) have significantly impacted the fields of chemistry, physics, and biology by enabling large-scale first-principles simulations. Among different machine learning approaches, kernel-based MLPs distinguish themselves through their ability to handle small datasets, quantify uncertainties, and minimize over-fitting. Nevertheless, their extensive computational requirements present considerable challenges. To alleviate these, sparsification methods have been developed, aiming to reduce computational scaling without compromising accuracy. In the context of isothermal and isobaric ML molecular dynamics (MD) simulations, achieving precise pressure estimation is crucial for reproducing reliable system behavior under constant pressure. Despite progress, sparse kernel MLPs struggle with precise pressure prediction. Here, we introduce a virial kernel function that significantly enhances the pressure estimation accuracy of MLPs. Additionally, we propose the active sparse Bayesian committee machine (BCM) potential, an on-the-fly MLP architecture that aggregates local sparse Gaussian process regression (SGPR) MLPs. The sparse BCM potential overcomes the steep computational scaling with the kernel size, and a predefined restriction on the size of kernel allows for fast and efficient on-the-fly training. Our advancements facilitate accurate and computationally efficient machine learning-enhanced MD (MLMD) simulations across diverse systems, including ice-liquid coexisting phases, Li10Ge(PS6)2 lithium solid electrolyte, and high-pressure liquid boron nitride.
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Supersolid is a mysterious and puzzling state of matter whose possible existence has stirred a vigorous debate among physicists for over 60 years. Its elusive nature stems from the coexistence of two seemingly contradicting properties, long-range order and superfluidity. We report computational evidence of a supersolid phase of deuterium under high pressure (p>800 GPa) and low temperature (T<1.0 K). In our simulations, that are based on bosonic path integral molecular dynamics, we observe a highly concerted exchange of atoms while the system preserves its crystalline order. The exchange processes are favored by the soft core interactions between deuterium atoms that form a densely packed metallic solid. At the zero temperature limit, Bose-Einstein condensation is observed as the permutation probability of N deuterium atoms approaches 1/N with a finite superfluid fraction. Our study provides concrete evidence for the existence of a supersolid phase in high-pressure deuterium and could provide insights on the future investigation of supersolid phases in real materials.
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The structure of oxide-supported metal nanoclusters plays an essential role in their sharply enhanced catalytic activity over that of bulk metals. Simulations provide the atomic-scale resolution needed to understand these systems. However, the sensitive mix of metal-metal and metal-support interactions, which govern their structure, puts stringent requirements on the method used, requiring calculations beyond standard density functional theory (DFT). The method of choice is coupled cluster theory [specifically CCSD(T)], but its computational cost has so far prevented its application to these systems. In this work, we showcase two approaches to make CCSD(T) accuracy readily achievable in oxide-supported nanoclusters. First, we leverage the SKZCAM protocol to provide the first benchmarks of oxide-supported nanoclusters, revealing that it is specifically metal-metal interactions that are challenging to capture with DFT. Second, we propose a CCSD(T) correction (ΔCC) to the metal-metal interaction errors in DFT, reaching accuracy comparable to that of the SKZCAM protocol at significantly lower cost. This approach forges a path toward studying larger systems at reliable accuracy, which we highlight by identifying a ground-state structure in agreement with experiments for Au20 on MgO, a challenging system where DFT models have yielded conflicting predictions.
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Closed-shell light-emitting diodes (LEDs) suffer from the internal quantum efficiency (IQE) limitation imposed by optically inactive triplet excitons. Here, an unrevealed emission mechanism of lead halide perovskites (LHPs) APbX3 (A = Cs/CN2 H5 ; X = Cl/Br/I) that circumvents the efficiency limit of closed-shell LEDs is explored. Though efficient emission is prohibited by optically inactive J = 0 in inversion symmetric LHPs, the anharmonicity arising from stereochemistry of Pb and resonant orbital-bonding network along the imaginary A+ X- (T1u ) transverse optical (TO) modes, breaks inversion symmetry, introducing disorder and Rashba-Dresselhaus spin-orbit coupling (RD-SOC). This results in bright cohelical and dark antihelical excitons. Many-body theory and first-principles calculations show that the optically active cohelical exciton is the lowest excited state in organic/inorganic LHPs. Thus, RD-SOC can drive to achieve the ideal 50% IQE by utilizing anharmonicity, much over the 25% IQE limitation for closed-shell LEDs.
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The stories behind supercooled bulk and confined water can be different. Bulk water has a metastable liquid-liquid phase transition at deeply supercooled conditions, but the existence of such a phenomenon in confined water is in question. Herein we show simulation results of first-order phase transitions between high- and low-density liquid (HDL and LDL) in confined water in both positive and negative pressures. A mid-density state between these two local states appears, which lets the transition show the hysteresis loop with transiently stable intermediate states. On the basis of Landau theory that we have adapted for mixing of moieties with high- and low-density states, we explain the phase transitions with the order parameter-dependent free energy change which is governed by second- to higher-order interactions among those moieties.
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For efficient water splitting, it is essential to develop inexpensive and super-efficient electrocatalysts for the oxygen evolution reaction (OER). Herein, we report a phosphate-based electrocatalyst [Fe3Co(PO4)4@reduced-graphene-oxide(rGO)] showing outstanding OER performance (much higher than state-of-the-art Ir/C catalysts), the design of which was aided by first-principles calculations. This electrocatalyst displays low overpotential (237 mV at high current density 100 mA cm-2 in 1 M KOH), high turnover frequency (TOF: 0.54 s-1), high Faradaic efficiency (98%), and long-term durability. Its remarkable performance is ascribed to the optimal free energy for OER at Fe sites and efficient mass/charge transfer. When a Fe3Co(PO4)4@rGO anodic electrode is integrated with a Pt/C cathodic electrode, the electrolyzer requires only 1.45 V to achieve 10 mA cm-2 for whole water splitting in 1 M KOH (1.39 V in 6 M KOH), which is much smaller than commercial Ir-C//Pt-C electrocatalysts. This cost-effective powerful oxygen production material with carbon-supporting substrates offers great promise for water splitting.
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This spotlight discusses intriguing properties and diverse applications of graphene (Gr) and Gr analogs. Gr has brought us two-dimensional (2D) chemistry with its exotic 2D features of density of states. Yet, some of the 2D or 2D-like features can be seen on surfaces and at interfaces of bulk materials. The substrate on Gr and functionalization of Gr (including metal decoration, intercalation, doping, and hybridization) modify the unique 2D features of Gr. Despite abundant literature on physical properties and well-known applications of Gr, spotlight works based on the conceptual understanding of the 2D physical and chemical nature of Gr toward vast-ranging applications are hardly found. Here we focus on applications of Gr, based on conceptual understanding of 2D phenomena toward 2D chemistry. Thus, 2D features, defects, edges, and substrate effects of Gr are discussed first. Then, to pattern Gr electronic circuits, insight into differentiating conducting and nonconducting regions is introduced. By utilizing the unique ballistic electron transport properties and edge spin states of Gr, Gr nanoribbons (GNRs) are exploited for the design of ultrasensitive molecular sensing electronic devices (including molecular fingerprinting) and spintronic devices. The highly stable nature of Gr can be utilized for protection of corrosive metals, moisture-sensitive perovskite solar cells, and highly environment-susceptible topological insulators (TIs). Gr analogs have become new types of 2D materials having novel features such as half-metals, TIs, and nonlinear optical properties. The key insights into the functionalized Gr hybrid materials lead to the applications for not only energy storage and electrochemical catalysis, green chemistry, and electronic/spintronic devices but also biosensing and medical applications. All these topics are discussed here with the focus on conceptual understanding. Further possible applications of Gr, GNRs, and Gr analogs are also addressed in a section on outlook and future challenges.
Assuntos
Grafite/química , Catálise , Nanotubos de CarbonoRESUMO
Organic crystals deposited on 2-dimensional (2D) van der Waals substrates have been widely investigated due to their unprecedented crystal structures and electrical properties. van der Waals interaction between organic molecules and the substrate induces epitaxial growth of high quality organic crystals and their anomalous crystal morphologies. Here, we report on unique ambipolar charge transport of a "lying-down" pentacene crystal grown on a 2D hexagonal boron nitride van der Waals substrate. From in-depth analysis on crystal growth behavior and ultraviolet photoemission spectroscopy measurement, it is revealed that the pentacene crystal at the initial growth stage have a lattice-strained packing structure and unique energy band structure with a deep highest occupied molecular orbital level compared to conventional "standing-up" crystals. The lattice-strained pentacene few layers enable ambipolar charge transport in field-effect transistors with balanced hole and electron field-effect mobilities. Complementary logic circuits composed of the two identical transistors show clear inverting functionality with a high gain up to 15. The interesting crystal morphology of organic crystals on van der Waals substrates is expected to attract broad attentions on organic/2D interfaces for their electronic applications.
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Despite having outstanding electrical properties, graphene is unsuitable for optical devices because of its zero band gap. Here, we report two-dimensional excitonic photoluminescence (PL) from graphene grown on a Cu(111) surface, which shows an unexpected and remarkably sharp strong emission near 3.16 eV (full width at half-maximum ≤3 meV) and multiple emissions around 3.18 eV. As temperature increases, these emissions blue shift, displaying the characteristic negative thermal coefficient of graphene. The observed PL originates from the significantly suppressed dispersion of excited electrons in graphene caused by hybridization of graphene π and Cu d orbitals of the first and second Cu layers at a shifted saddle point 0.525(M+K) of the Brillouin zone. This finding provides a pathway to engineering optoelectronic graphene devices, while maintaining the outstanding electrical properties of graphene.
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The atomic configuration of graphene edges significantly influences the various properties of graphene nanostructures, and realistic device fabrication requires precise engineering of graphene edges. However, the imaging and analysis of the intrinsic nature of graphene edges can be illusive due to contamination problems and measurement-induced structural changes to graphene edges. In this issue of ACS Nano, He et al. report an in situ heating experiment in aberration-corrected transmission electron microscopy to elucidate the temperature dependence of graphene edge termination at the atomic scale. They revealed that graphene edges predominantly have zigzag terminations below 400 °C, while above 600 °C, the edges are dominated by armchair and reconstructed zigzag edges. This report brings us one step closer to the true nature of graphene edges. In this Perspective, we outline the present understanding, issues, and future challenges faced in the field of graphene-edge-based nanodevices.