Ten-electron count rule for the binding of adsorbates on single-atom alloy catalysts

Single-atom alloys have recently emerged as highly active and selective alloy catalysts. Unlike pure metals, single-atom alloys escape the well-established conceptual framework developed nearly three decades ago for predicting catalytic performance. Although this offers the opportunity to explore so far unattainable chemistries, this leaves us without a simple guide for the design of single-atom alloys able to catalyse targeted reactions. Here, based on thousands of density functional theory calculations, we reveal a 10-electron count rule for the binding of adsorbates on the dopant atoms, usually the active sites, of single-atom alloy surfaces. A simple molecular orbital approach rationalizes this rule and the nature of the adsorbate-dopant interaction. In addition, our intuitive model can accelerate the rational design of single-atom alloy catalysts. Indeed, we illustrate how the unique insights provided by the electron count rule help identify the most promising dopant for an industrially relevant hydrogenation reaction, thereby reducing the number of potential materials by more than one order of magnitude.

The Interplay of Solvation and Polarization Effects on Ion Pairing in Nanoconfined Electrolytes

The nature of ion-ion interactions in electrolytes confined to nanoscale pores has important implications for energy storage and separation technologies. However, the physical effects dictating the structure of nanoconfined electrolytes remain debated. Here we employ machine-learning-based molecular dynamics simulations to investigate ion-ion interactions with density functional theory level accuracy in a prototypical confined electrolyte, aqueous NaCl within graphene slit pores. We find that the free energy of ion pairing in highly confined electrolytes deviates substantially from that in bulk solutions, observing a decrease in contact ion pairing but an increase in solvent-separated ion pairing. These changes arise from an interplay of ion solvation effects and graphene's electronic structure. Notably, the behavior observed from our first-principles-level simulations is not reproduced even qualitatively with the classical force fields conventionally used to model these systems. The insight provided in this work opens new avenues for predicting and controlling the structure of nanoconfined electrolytes.

Mesoscale Simulations Reveal How Salt Influences Clay Particles Agglomeration in Aqueous Dispersions

The aggregation of clay particles is an everyday phenomenon of scientific and industrial relevance. However, it is a complex multiscale process that depends delicately on the nature of the particle-particle and particle-solvent interactions. Toward understanding how to control such phenomena, a multiscale computational approach is developed, building from molecular simulations conducted at atomic resolution to calculate the potential of mean force (PMF) profiles in both pure and saline water environments. We document how it is possible to use such a model to develop a fundamental understanding concerning the mechanism of particle aggregation. For example, using molecular dynamics simulations conducted at the mesoscale in implicit solvents, it is possible to quantify the size and shape of clay aggregates as a function of system conditions. The approach is used to emphasize the role of salt concentration, which directly affects the potentials of the mean forces between kaolinite particles. While particle agglomeration in pure water yields large aggregates, the presence of sodium chloride in the aqueous brine leads instead to a large number of small aggregates. These results are consistent with macroscopic experimental observations, suggesting that the simulation protocol developed could be relevant for preventing pore blocking in heterogeneous porous matrixes.

First-principles spectroscopy of aqueous interfaces using machine-learned electronic and quantum nuclear effects

Vibrational spectroscopy is a powerful approach to visualising interfacial phenomena. However, extracting structural and dynamical information from vibrational spectra is a challenge that requires first-principles simulations, including non-Condon and quantum nuclear effects. We address this challenge by developing a machine-learning enhanced first-principles framework to speed up predictive modelling of infrared, Raman, and sum-frequency generation spectra. Our approach uses machine learning potentials that encode quantum nuclear effects to generate quantum trajectories using simple molecular dynamics efficiently. In addition, we reformulate bulk and interfacial selection rules to express them unambiguously in terms of the derivatives of polarisation and polarisabilities of the whole system and predict these derivatives efficiently using fully-differentiable machine learning models of dielectric response tensors. We demonstrate our framework's performance by predicting the IR, Raman, and sum-frequency generation spectra of liquid water, ice and the water-air interface by achieving near quantitative agreement with experiments at nearly the same computational efficiency as pure classical methods. Finally, to aid the experimental discovery of new phases of nanoconfined water, we predict the temperature-dependent vibrational spectra of monolayer water across the solid-hexatic-liquid phases transition.

The limit of macroscopic homogeneous ice nucleation at the nanoscale

Nucleation in small volumes of water has garnered renewed interest due to the relevance of pore condensation and freezing under conditions of low partial pressures of water, such as in the upper troposphere. Molecular simulations can in principle provide insight on this process at the molecular scale that is challenging to achieve experimentally. However, there are discrepancies in the literature as to whether the rate in confined systems is enhanced or suppressed relative to bulk water at the same temperature and pressure. In this study, we investigate the extent to which the size of the critical nucleus and the rate at which it grows in thin films of water are affected by the thickness of the film. Our results suggest that nucleation remains bulk-like in films that are barely large enough accommodate a critical nucleus. This conclusion seems robust to the presence of physical confining boundaries. We also discuss the difficulties in unambiguously determining homogeneous nucleation rates in nanoscale systems, owing to the challenges in defining the volume. Our results suggest any impact on a film's thickness on the rate is largely inconsequential for present day experiments.

Origin of dielectric polarization suppression in confined water from first principles

It has long been known that the dielectric constant of confined water should be different from that in bulk. Recent experiments have shown that it is vanishingly small, however the origin of the phenomenon remains unclear. Here we used ab initio molecular dynamics simulations (AIMD) and AIMD-trained machine-learning potentials to understand water's structure and electronic properties underpinning this effect. For the graphene and hexagonal boron-nitride substrates considered, we find that it originates in the spontaneous anti-parallel alignment of the water dipoles in the first two water layers near the solid interface. The interfacial layers exhibit net ferroelectric ordering, resulting in an overall anti-ferroelectric arrangement of confined water. Together with constrained hydrogen-bonding orientations, this leads to much reduced out-of-plane polarization. Furthermore, we directly contrast AIMD and simple classical force-field simulations, revealing important differences. This work offers insight into a property of water that is critical in modulating surface forces, the electric-double-layer formation and molecular solvation, and shows a way to compute it.

Many-Body Methods for Surface Chemistry Come of Age: Achieving Consensus with Experiments

The adsorption energy of a molecule onto the surface of a material underpins a wide array of applications, spanning heterogeneous catalysis, gas storage, and many more. It is the key quantity where experimental measurements and theoretical calculations meet, with agreement being necessary for reliable predictions of chemical reaction rates and mechanisms. The prototypical molecule-surface system is CO adsorbed on MgO, but despite intense scrutiny from theory and experiment, there is still no consensus on its adsorption energy. In particular, the large cost of accurate many-body methods makes reaching converged theoretical estimates difficult, generating a wide range of values. In this work, we address this challenge, leveraging the latest advances in diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] to obtain accurate predictions for CO on MgO. These reliable theoretical estimates allow us to evaluate the inconsistencies in published temperature-programed desorption experiments, revealing that they arise from variations in employed pre-exponential factors. Utilizing this insight, we derive new experimental estimates of the (electronic) adsorption energy with a (more) precise pre-exponential factor. As a culmination of all of this effort, we are able to reach a consensus between multiple theoretical calculations and multiple experiments for the first time. In addition, we show that our recently developed cluster-based CCSD(T) approach provides a low-cost route toward achieving accurate adsorption energies. This sets the stage for affordable and reliable theoretical predictions of chemical reactions on surfaces to guide the realization of new catalysts and gas storage materials.

Considerably Increased Dynamics of CO-Water Complexes over CO and Water Alone

Solvents are increasingly known to influence chemical reactivity. However, the microscopic origin of solvent effects is scarcely understood, particularly at the individual molecule level. To shed light on this, we explored a well-defined model system of water (D₂O) and carbon monoxide on a single-crystal copper surface with time-lapsed low-temperature scanning tunneling microscopy (STM) and ab initio calculations. Through detailed measurements on a time scale of minutes to hours at the limit of single-molecule solvation, we find that at cryogenic temperatures CO-D₂O complexes are more mobile than individual CO or water molecules. We also obtain detailed mechanistic insights into the motion of the complex. In diffusion-limited surface reactions, such a solvent-triggered increase in mobility would substantially increase the reaction yield.

pH-dependent water permeability switching and its memory in MoS2 membranes

Intelligent transport of molecular species across different barriers is critical for various biological functions and is achieved through the unique properties of biological membranes1-4. Two essential features of intelligent transport are the ability to (1) adapt to different external and internal conditions and (2) memorize the previous state5. In biological systems, the most common form of such intelligence is expressed as hysteresis6. Despite numerous advances made over previous decades on smart membranes, it remains a challenge to create a synthetic membrane with stable hysteretic behaviour for molecular transport7-11. Here we demonstrate the memory effects and stimuli-regulated transport of molecules through an intelligent, phase-changing MoS2 membrane in response to external pH. We show that water and ion permeation through 1T' MoS2 membranes follows a pH-dependent hysteresis with a permeation rate that switches by a few orders of magnitude. We establish that this phenomenon is unique to the 1T' phase of MoS2, due to the presence of surface charge and exchangeable ions on the surface. We further demonstrate the potential application of this phenomenon in autonomous wound infection monitoring and pH-dependent nanofiltration. Our work deepens understanding of the mechanism of water transport at the nanoscale and opens an avenue for the development of intelligent membranes.

Hydration at Highly Crowded Interfaces

Understanding the molecular and electronic structure of solvated ions at surfaces requires an analysis of the interactions between the surface, the ions, and the solvent environment on equal footing. Here, we tackle this challenge by exploring the initial stages of Cs^{+} hydration on a Cu(111) surface by combining experiment and theory. Remarkably, we observe "inside-out" solvation of Cs^{+} ions, i.e., their preferential location at the perimeter of the water clusters on the metal surface. In addition, water-Cs complexes containing multiple Cs^{+} ions are observed to form at these surfaces. Established models based on maximum ion-water coordination and conventional solvation models cannot account for this situation, and the complex interplay of microscopic interactions is the key to a fundamental understanding.

Medium-density amorphous ice

Amorphous ices govern a range of cosmological processes and are potentially key materials for explaining the anomalies of liquid water. A substantial density gap between low-density and high-density amorphous ice with liquid water in the middle is a cornerstone of our current understanding of water. However, we show that ball milling "ordinary" ice Ih at low temperature gives a structurally distinct medium-density amorphous ice (MDA) within this density gap. These results raise the possibility that MDA is the true glassy state of liquid water or alternatively a heavily sheared crystalline state. Notably, the compression of MDA at low temperature leads to a sharp increase of its recrystallization enthalpy, highlighting that H₂O can be a high-energy geophysical material.

Classical Quantum Friction at Water-Carbon Interfaces

Friction at water-carbon interfaces remains a major puzzle with theories and simulations unable to explain experimental trends in nanoscale waterflow. A recent theoretical framework─quantum friction (QF)─proposes to resolve these experimental observations by considering nonadiabatic coupling between dielectric fluctuations in water and graphitic surfaces. Here, using a classical model that enables fine-tuning of the solid's dielectric spectrum, we provide evidence from simulations in general support of QF. In particular, as features in the solid's dielectric spectrum begin to overlap with water's librational and Debye modes, we find an increase in friction in line with that proposed by QF. At the microscopic level, we find that this contribution to friction manifests more distinctly in the dynamics of the solid's charge density than that of water. Our findings suggest that experimental signatures of QF may be more pronounced in the solid's response rather than liquid water's.

Stick or Spill? Scaling Relationships for the Binding Energies of Adsorbates on Single-Atom Alloy Catalysts

Single-atom alloy catalysts combine catalytically active metal atoms, present as dopants, with the selectivity of coinage metal hosts. Determining whether adsorbates stick at the dopant or spill over onto the host is key to understanding catalytic mechanisms on these materials. Despite a growing body of work, simple descriptors for the prediction of spillover energies (SOEs), i.e., the relative stability of an adsorbate on the dopant versus the host site, are not yet available. Using Density Functional Theory (DFT) calculations on a large set of adsorbates, we identify the dopant charge and the SOE of carbon as suitable descriptors. Combining them into a linear surrogate model, we can reproduce DFT-computed SOEs within 0.06 eV mean absolute error. More importantly, our work provides an intuitive theoretical framework, based on the concepts of electrostatic interactions and covalency, that explains SOE trends and can guide the rational design of future single-atom alloy catalysts.

DMC-ICE13: ambient and high pressure polymorphs of ice from Diffusion Monte Carlo and Density Functional Theory

Ice is one of the most important and interesting molecular crystals exhibiting a rich and evolving phase diagram. Recent discoveries mean that there are now twenty distinct polymorphs; a structural diversity that arises from a delicate interplay of hydrogen bonding and van der Waals dispersion forces. This wealth of structures provides a stern test of electronic structure theories, with Density Functional Theory (DFT) often not able to accurately characterise the relative energies of the various ice polymorphs. Thanks to recent advances that enable the accurate and efficient treatment of molecular crystals with Diffusion Monte Carlo (DMC), we present here the DMC-ICE13 dataset; a dataset of lattice energies of 13 ice polymorphs. This dataset encompasses the full structural complexity found in the ambient and high-pressure molecular ice polymorphs and when experimental reference energies are available our DMC results deliver sub-chemical accuracy. Using this dataset we then perform an extensive benchmark of a broad range of DFT functionals. Of the functionals considered, we find revPBE-D3 and RSCAN to reproduce reference absolute lattice energies with the smallest error, whilst optB86b-vdW and SCAN+rVV10 have the best performance on the relative lattice energies. Our results suggest that a single functional achieving reliable performance for all phases is still missing, and that care is needed in the selection of the most appropriate functional for the desired application.The insights obtained here may also be relevant to liquid water and other hydrogen bonded and dispersion bonded molecular crystals.

Water Flow in Single-Wall Nanotubes: Oxygen Makes It Slip, Hydrogen Makes It Stick

Experimental measurements have reported ultrafast and radius-dependent water transport in carbon nanotubes which are absent in boron nitride nanotubes. Despite considerable effort, the origin of this contrasting (and fascinating) behavior is not understood. Here, with the aid of machine learning-based molecular dynamics simulations that deliver first-principles accuracy, we investigate water transport in single-wall carbon and boron nitride nanotubes. Our simulations reveal a large, radius-dependent hydrodynamic slippage on both materials, with water experiencing indeed a ≈5 times lower friction on carbon surfaces compared to boron nitride. Analysis of the diffusion mechanisms across the two materials reveals that the fast water transport on carbon is governed by facile oxygen motion, whereas the higher friction on boron nitride arises from specific hydrogen-nitrogen interactions. This work not only delivers a clear reference of quantum mechanical accuracy for water flow in single-wall nanotubes but also provides detailed mechanistic insight into its radius and material dependence for future technological application.

Observation and Characterization of Dicarbonyls on a RhCu Single-Atom Alloy

Dicarbonyl species are ubiquitous on Rh/oxide catalysts and are known to form on Rh⁺ centers. However, dicarbonyl species have never been directly observed on single-atom alloys (SAAs) where the active site is metallic. Herein, using surface science and theoretical modeling, we provide evidence of dicarbonyl species at isolated Rh sites on a RhCu(100) SAA. This approach not only enables us to directly visualize dicarbonyl species at Rh sites but also demonstrates that the transition between the mono- and dicarbonyl configuration can be achieved by changing surface temperature and CO pressure. Density functional theory calculations further support the mono- and dicarbonyl assignments and provide evidence that these species should be stable on other SAA combinations. Together, these results provide a picture of the structure and energetics of both the mono- and dicarbonyl configurations on the RhCu(100) SAA surface and should aid with IR assignments on SAA nanoparticle catalysts.

Long-Range Ionic and Short-Range Hydration Effects Govern Strongly Anisotropic Clay Nanoparticle Interactions

The aggregation of clay particles in aqueous solution is a ubiquitous everyday process of broad environmental and technological importance. However, it is poorly understood at the all-important atomistic level since it depends on a complex and dynamic interplay of solvent-mediated electrostatic, hydrogen bonding, and dispersion interactions. With this in mind, we have performed an extensive set of classical molecular dynamics simulations (included enhanced sampling simulations) on the interactions between model kaolinite nanoparticles in pure and salty water. Our simulations reveal highly anisotropic behavior, in which the interaction between the nanoparticles varies from attractive to repulsive depending on the relative orientation of the nanoparticles. Detailed analysis reveals that at large separation (>1.5 nm), this interaction is dominated by electrostatic effects, whereas at smaller separations, the nature of the water hydration structure becomes critical. This study highlights an incredible richness in how clay nanoparticles interact, which should be accounted for in, for example, coarse-grained models of clay nanoparticle aggregation.

The role of structural order in heterogeneous ice nucleation

The freezing of water into ice is a key process that is still not fully understood. It generally requires an impurity of some description to initiate the heterogeneous nucleation of the ice crystals. The molecular structure, as well as the extent of structural order within the impurity in question, both play an essential role in determining its effectiveness. However, disentangling these two contributions is a challenge for both experiments and simulations. In this work, we have systematically investigated the ice-nucleating ability of the very same compound, cholesterol, from the crystalline (and thus ordered) form to disordered self-assembled monolayers. Leveraging a combination of experiments and simulations, we identify a “sweet spot” in terms of the surface coverage of the monolayers, whereby cholesterol maximises its ability to nucleate ice (which remains inferior to that of crystalline cholesterol) by enhancing the structural order of the interfacial water molecules. These findings have practical implications for the rational design of synthetic ice-nucleating agents.

The freezing of water into ice is still not fully understood. Here, we investigate the role of structural disorder within the biologically relevant impurities that facilitate this fundamental phase transition.

Can molecular simulations reliably compare homogeneous and heterogeneous ice nucleation?

In principle, the answer to the posed titular question is undoubtedly "yes." But in practice, requisite reference data for homogeneous systems have been obtained with a treatment of intermolecular interactions that is different from that typically employed for heterogeneous systems. In this article, we assess the impact of the choice of truncation scheme when comparing water in homogeneous and inhomogeneous environments. Specifically, we use explicit free energy calculations and a simple mean field analysis to demonstrate that using the "cut-and-shift" version of the Lennard-Jones potential (common to most simple point charge models of water) results in a systematic increase in the melting temperature of ice I_h. In addition, by drawing an analogy between a change in cutoff and a change in pressure, we use existing literature data for homogeneous ice nucleation at negative pressures to suggest that enhancements due to heterogeneous nucleation may have been overestimated by several orders of magnitude.

General embedded cluster protocol for accurate modeling of oxygen vacancies in metal-oxides

The O vacancy (Ov) formation energy, EOv, is an important property of a metal-oxide, governing its performance in applications such as fuel cells or heterogeneous catalysis. These defects are routinely studied with density functional theory (DFT). However, it is well-recognized that standard DFT formulations (e.g., the generalized gradient approximation) are insufficient for modeling the Ov, requiring higher levels of theory. The embedded cluster method offers a promising approach to compute EOv accurately, giving access to all electronic structure methods. Central to this approach is the construction of quantum(-mechanically treated) clusters placed within suitable embedding environments. Unfortunately, current approaches to constructing the quantum clusters either require large system sizes, preventing application of high-level methods, or require significant manual input, preventing investigations of multiple systems simultaneously. In this work, we present a systematic and general quantum cluster design protocol that can determine small converged quantum clusters for studying the Ov in metal-oxides with accurate methods, such as local coupled cluster with single, double, and perturbative triple excitations. We apply this protocol to study the Ov in the bulk and surface planes of rutile TiO2 and rock salt MgO, producing the first accurate and well-converged determinations of EOv with this method. These reference values are used to benchmark exchange–correlation functionals in DFT, and we find that all the studied functionals underestimate EOv, with the average error decreasing along the rungs of Jacob’s ladder. This protocol is automatable for high-throughput calculations and can be generalized to study other point defects or adsorbates.

How do interfaces alter the dynamics of supercooled water?

The structure of liquid water in the proximity of an interface can deviate significantly from that of bulk water, with surface-induced structural perturbations typically converging to bulk values at about ∼1 nm from the interface. While these structural changes are well established it is, in contrast, less clear how an interface perturbs the dynamics of water molecules within the liquid. Here, through an extensive set of molecular dynamics simulations of supercooled bulk and interfacial water films and nano-droplets, we observe the formation of persistent, spatially extended dynamical domains in which the average mobility varies as a function of the distance from the interface. This is in stark contrast with the dynamical heterogeneity observed in bulk water, where these domains average out spatially over time. We also find that the dynamical response of water to an interface depends critically on the nature of the interface and on the choice of interface definition. Overall these results reveal a richness in the dynamics of interfacial water that opens up the prospect of tuning the dynamical response of water through specific modifications of the interface structure or confining material.

Rapid Water Diffusion at Cryogenic Temperatures through an Inchworm-like Mechanism

Water diffusion across the surfaces of materials is of importance to disparate processes such as water purification, ice formation, and more. Despite reports of rapid water diffusion on surfaces the molecular level, details of such processes remain unclear. Here, with scanning tunneling microscopy, we observe structural rearrangements and diffusion of water trimers at unexpectedly low temperatures (<10 K) on a copper surface, temperatures at which water monomers or other clusters do not diffuse. Density functional theory calculations reveal a facile trimer diffusion process involving transformations between elongated and almost cyclic conformers in an inchworm-like manner. These subtle intermolecular reorientations maintain an optimal balance of hydrogen-bonding and water-surface interactions throughout the process. This work shows that the diffusion of hydrogen-bonded clusters can occur at exceedingly low temperatures without the need for hydrogen bond breakage or exchange; findings that will influence Ostwald ripening of ice nanoclusters and hydrogen bonded clusters in general.

Water/oil interfacial tension reduction - an interfacial entropy driven process

The interfacial tension (IFT) of a fluid-fluid interface plays an important role in a wide range of applications and processes. When low IFT is desired, surface active compounds (e.g. surfactants) can be added to the system. Numerous attempts have been made to relate changes in IFT arising from such compounds to the specific nature of the interface. However, the IFT is controlled by an interplay of factors such as temperature and molecular structure of surface-active compounds, which make it difficult to predict IFT as those conditions change. In this study, we present the results from molecular dynamics simulations revealing the specific role surfactants play in IFT. We find that, in addition to reducing direct contact between the two fluids, surfactants serve to increase the disorder at the interface (related to interfacial entropy) and consequently reduce the water/oil IFT, especially when surfactants are present at high surface density. Our results suggest that surfactants that yield more disordered interfacial films (e.g. with flexible and/or unsaturated tails) reduce the water/oil IFT more effectively than surfactants which yield highly ordered interfacial films. Our results shed light on some of the factors that control IFT and could have important practical implications in industrial applications such as the design of cosmetics, food products, and detergents.

Periodic Trends in Adsorption Energies around Single-Atom Alloy Active Sites

Single-atom alloys (SAAs) make up a special class of alloy surface catalysts that offer well-defined, isolated active sites in a more inert metal host. The dopant sites are generally assumed to have little or no influence on the properties of the host metal, and transport of chemical reactants and products to and from the dopant sites is generally assumed to be facile. Here, by performing density functional theory calculations and surface science experiments, we identify a new physical effect on SAA surfaces, whereby adsorption is destabilized by ≤300 meV on host sites within the perimeter of the reactive dopant site. We identify periodic trends for this behavior and demonstrate a zone of exclusion around the reactive sites for a range of adsorbates and combinations of host and dopant metals. Experiments confirm an increased barrier for diffusion of CO toward the dopant on a RhCu SAA. This effect offers new possibilities for understanding and designing active sites with tunable energetic landscapes surrounding them.

Defect-Dependent Corrugation in Graphene

Graphene's intrinsically corrugated and wrinkled topology fundamentally influences its electronic, mechanical, and chemical properties. Experimental techniques allow the manipulation of pristine graphene and the controlled production of defects which allows one to control the atomic out-of-plane fluctuations and thus tune graphene's properties. Here, we perform large scale machine learning-driven molecular dynamics simulations to understand the impact of defects on the structure of graphene. We find that defects cause significantly higher corrugation leading to a strongly wrinkled surface. The magnitude of this structural transformation strongly depends on the defect concentration and specific type of defect. Analyzing the atomic neighborhood of the defects reveals that the extent of these morphological changes depends on the preferred geometrical orientation and the interactions between defects. While our work highlights that defects can strongly affect graphene's morphology, it also emphasizes the differences between distinct types by linking the global structure to the local environment of the defects.

First-principles design of a single-atom–alloy propane dehydrogenation catalyst

Nanoparticles of rhodium dispersed on metal oxides are generally poor catalysts for alkane dehydrogenation because the reactants bind too strongly to the metal. Hannagan et al. performed first-principle calculations indicating that single rhodium atoms in a copper surface should be stable and selective for conversion of propane to propene and hydrogen. Model studies of single rhodium atoms embedded in a copper (111) surface revealed a very high selectivity to propene and high resistance to the formation of surface carbon that would deactivate the catalyst.

Science , abg8389, this issue p. 1444

Microscopic Kinetics Pathway of Salt Crystallization in Graphene Nanocapillaries

The fundamental understanding of crystallization, in terms of microscopic kinetic and thermodynamic details, remains a key challenge in the physical sciences. Here, by using in situ graphene liquid cell transmission electron microscopy, we reveal the atomistic mechanism of NaCl crystallization from solutions confined within graphene cells. We find that rock salt NaCl forms with a peculiar hexagonal morphology. We also see the emergence of a transitory graphitelike phase, which may act as an intermediate in a two-step pathway. With the aid of density functional theory calculations, we propose that these observations result from a delicate balance between the substrate-solute interaction and thermodynamics under confinement. Our results highlight the impact of confinement on both the kinetics and thermodynamics of crystallization, offering new insights into heterogeneous crystallization theory and a potential avenue for materials design.

Interplay of structural and dynamical heterogeneity in the nucleation mechanism in Ni

Gaining fundamental understanding of crystal nucleation processes in metal alloys is crucial for the development and design of high-performance materials with targeted properties. Yet, crystallizationis a complex non-equilibrium process and,...

Hydration of NH_{4}^{+} in Water: Bifurcated Hydrogen Bonding Structures and Fast Rotational Dynamics

Understanding the hydration and diffusion of ions in water at the molecular level is a topic of widespread importance. The ammonium ion (NH_{4}^{+}) is an exemplar system that has received attention for decades because of its complex hydration structure and relevance in industry. Here we report a study of the hydration and the rotational diffusion of NH_{4}^{+} in water using ab initio molecular dynamics simulations and quantum Monte Carlo calculations. We find that the hydration structure of NH_{4}^{+} features bifurcated hydrogen bonds, which leads to a rotational mechanism involving the simultaneous switching of a pair of bifurcated hydrogen bonds. The proposed hydration structure and rotational mechanism are supported by existing experimental measurements, and they also help to rationalize the measured fast rotation of NH_{4}^{+} in water. This study highlights how subtle changes in the electronic structure of hydrogen bonds impacts the hydration structure, which consequently affects the dynamics of ions and molecules in hydrogen bonded systems.

Strain Relief during Ice Growth on a Hexagonal Template

Heterogeneous ice nucleation at solid surfaces impacts many areas of science, from environmental processes, such as precipitation, to microbiological systems and food processing, but the microscopic mechanisms underpinning nucleation remain unclear. Discussion of ice growth has often focused around the role of the surface in templating the structure of water, forcing the first layer to adopt the registry of the underlying substrate rather than that of ice. To grow a thick ice film, water in the first few ice layers must accommodate this strain, but understanding how this occurs requires detailed molecular-scale information that is lacking. Here we combine scanning tunneling microscopy, low-energy electron diffraction, and work-function measurements with electronic structure calculations to investigate the initial stages of ice growth on a Pt alloy surface, having a lattice spacing 6% larger than ice. Although the first layer of water forms a strictly commensurate hexagonal network, this behavior does not extend to the second layer. Instead, water forms a 2D structure containing extended defect rows made from face-sharing pentamer and octamer rings. The defect rows allow the majority of second-layer water to remain commensurate with the solid surface while compensating lateral strain by increasing the water density close to that of an ice surface. The observation of octamer-pentamer rows in ice films formed on several surfaces suggests that the octamer-pentamer defect motif acts as a flexible strain relief mechanism in thin ice films, providing a mechanism that is not available during the growth of strained films in other materials, such as semiconductors.

Anomalously Low Barrier for Water Dimer Diffusion on Cu(111)

A molecular-scale description of water and ice is important in fields as diverse as atmospheric chemistry, astrophysics, and biology. Despite a detailed understanding of water and ice structures on a multitude of surfaces, relatively little is known about the kinetics of water motion on surfaces. Here, we report a detailed study on the diffusion of water monomers and the formation and diffusion of water dimers through a combination of time-lapse low-temperature scanning tunnelling microscopy experiments and first-principles electronic structure calculations on the atomically flat Cu(111) surface. On the basis of an unprecedented long-time study of individual water monomers and dimers over days, we establish rates and mechanisms of water monomer and dimer diffusion. Interestingly, we find that the monomer and the dimer diffusion barriers are similar, despite the significantly larger adsorption energy of the dimer. This is thus a violation of the rule of thumb that relates diffusion barriers to adsorption energies, an effect that arises because of the directional and flexible hydrogen bond within the dimer. This flexibility during diffusion should also be relevant for larger water clusters and other hydrogen-bonded adsorbates. Our study stresses that a molecular-scale understanding of the initial stages of ice nanocluster formation is not possible on the basis of static structure investigations alone.

Physisorption of Water on Graphene: Subchemical Accuracy from Many-Body Electronic Structure Methods

Wet carbon interfaces are ubiquitous in the natural world and exhibit anomalous properties, which could be exploited by emerging technologies. However, progress is limited by lack of understanding at the molecular level. Remarkably, even for the most fundamental system (a single water molecule interacting with graphene), there is no consensus on the nature of the interaction. We tackle this by performing an extensive set of complementary state-of-the-art computer simulations on some of the world's largest supercomputers. From this effort a consensus on the water-graphene interaction strength has been obtained. Our results have significant impact for the physical understanding, as they indicate that the interaction is weaker than predicted previously. They also pave the way for more accurate and reliable studies of liquid water at carbon interfaces.

Adsorption Behavior of Organic Molecules: A Study of Benzotriazole on Cu(111) with Spectroscopic and Theoretical Methods

The adsorption of organic molecules on solid substrates is important to applications in fields such as catalysis, photovoltaics, corrosion inhibition, adhesion, and sensors. The molecular level description of the surface-molecule interaction and of the adsorption structures in these complex systems is crucial to understand their properties and function. Here, we present an investigation of one such system, benzotriazole (BTAH) on single-crystal Cu(111) in vacuum conditions. BTAH is the most widely used corrosion inhibitor for copper and thus a molecule of great industrial relevance. We show that the co-application of a wide range of spectroscopic techniques with theoretical methods provides unique insight in the description of the atomistic details of the adsorbed structures. Specifically, spectroscopic photoemission, absorption, and standing wave experiments combined with ab initio computational modeling allowed us to identify that benzotriazole forms overlayers of intact BTAH when deposited at low temperature, and it dissociates into BTA and H at room temperature and above. The dissociated molecule then forms complex structures of mixed chains and dimers of BTA bound to copper adatoms. Our work also reveals that copper adatoms at low concentrations, such as the theoretically predicted superstructures, cannot be resolved by means of current X-ray photoelectron spectroscopy as the modeled Cu 2p spectra are practically indistinguishable from those for a Cu surface without adatoms. Overall this study significantly deepens understanding of BTAH on Cu, a system studied for more than 50 years, and it highlights the benefits of combining spectroscopic and computational methods to obtain a complete picture of a complex adsorption system.