Addressing Dynamics at Catalytic Heterogeneous Interfaces with DFT-MD: Anomalous Temperature Distributions from Commonly Used Thermostats

A charge calibration strategy for describing the charge transfer during the electrochemical elementary step

Constant potential modeling of electrocatalytic processes remains a significant challenge in the field of computational catalysis, primarily due to the difficulty in simultaneously considering the influence of constant potential conditions, explicit solvent environment, and the double-layer structure. In this work, we propose a charge calibration strategy for electrocatalytic processes. This strategy accounts for charge transfer in systems with explicit solvation and ions during constant-potential free energy modeling. In our strategy, interfacial counter-ions are employed to model the Helmholtz layer and determine the surface charge density, which defines the electrode potential. During the simulation of electrochemical reactions, extra charges are introduced/extracted to/from the system to compensate for electron transfer between the electrode and the reaction species and keep a constant surface charge density along the reaction profile. Our method showcases the impact of potential-dependent solvent reorganization on reaction kinetics and underscores the importance of constant potential kinetics. We anticipate that the strategy presented here will inspire further theoretical and experimental studies for electrochemistry interfaces.

Ductilization of 2.6-GPa alloys via short-range ordered interfaces and supranano precipitates

Higher strength and higher ductility are desirable for structural materials. However, ultrastrong alloys inevitably show decreased strain-hardening capacity, limiting their uniform elongation. We present a supranano (<10 nanometers) and short-range ordering design for grain interiors and grain boundary regions, respectively, in fine-grained alloys based on vanadium, cobalt, and nickel, with additions of tungsten, copper, aluminum, and boron. The pronounced grain boundary-related strengthening and ductilization mechanism is realized through segregation of the short-range ordering near the grain boundary. Furthermore, the supranano ordering with a larger size has an enhanced pinning effect for dislocations and stacking faults, multiplied and accumulated in grain interiors during plastic deformation. These mechanisms promote continuously increased flow stress until fracture of the alloy at 10% strain with 2.6-gigapascal tensile stress.

Expanded Negative Electrostatic Network-Assisted Seawater Oxidation and High-Salinity Seawater Reutilization

Coastal/offshore renewable energy sources combined with seawater splitting offer an attractive means for large-scale H2 electrosynthesis in the future. However, designing anodes proves rather challenging, as surface chlorine chemistry must be blocked, particularly at high current densities (J). Additionally, waste seawater with increased salinity produced after long-term electrolysis would impair the whole process sustainability. Here, we convert seawater to O2 selectively, on hydroxides, by building phytate-based expanded negative electrostatic networks (ENENs) with electrostatically repulsive capacities and higher negative charge coverage ranges than those of common inorganic polyatomic anions. With surface ENENs, even typically unstable CoFe hydroxides perform nicely toward alkaline seawater oxidation at activities of >1 A cm-2. CoFe hydroxides with phytate-based ENENs exhibit prolonged lifespans of 1000 h at J of 1 A cm-2 and 900 h at J of 2 A cm-2 and thus rival the best seawater oxidation anodes. Direct introduction of trace phytates to seawater weakens corrosion tendency on conventional CoFe hydroxides as well, extending the life of hydroxides by ∼28 times at J of 2 A cm-2. A wide range of materials all obtain prolonged lifetimes in the presence of ENENs, validating universal applicability. Mechanisms are studied using theoretical computations under working conditions and ex situ/in situ characterizations. We demonstrate a potentially viable way to sustainably reutilize high-salinity wastewater, which is a long-standing but neglected issue. Series-connected devices exhibit good resistance to low temperature operation and are more eco-friendly than current organic electrolyte-based energy storage devices.

Coalescence Mechanism Induced by Different Wetting States of Ti and Al Droplets on Rough Surfaces

There is currently increasing interest in droplet transportation and coalescence on rough surfaces. However, the relationship among wettability, coalescence mode, and substrate characteristics (roughness and nanopillar height) remains unclear. In this work, two coalescence modes, climbing coalescence and contacting coalescence, are first observed in the dynamic behaviors of Ti and Al droplets on rough substrates. Due to the nonsynchronized wetting state transition of the droplets, the coalescence mode with increasing substrate characteristics differs, transitioning from contacting coalescence to climbing coalescence and then returning to the contacting mode. In general, the mode of coalescence correlates closely with the respective wetting states. Typically, Ti and Al droplets coalesce in the contacting mode when they have the same wetting state, but if they have different wetting states, they coalesce in the climbing mode. Our results emphasize the complicated relationship between the surface structure and the wettability of droplets, which could provide insights into self-assembly, three-dimensional printing, and microfluidic devices.

Metal-water interface formation: Thermodynamics from ab initio molecular dynamics simulations

Metal-water interfaces are central to many electrochemical, (electro)catalytic, and materials science processes and systems. However, our current understanding of their thermodynamic properties is limited by the scarcity of accurate experimental and computational data and procedures. In this work, thermodynamic quantities for metal-water interface formation are computed for a range of FCC(111) surfaces (Pd, Pt, Au, Ag, Rh, and PdAu) through extensive density functional theory based molecular dynamics and the two-phase entropy model. We show that metal-water interface formation is thermodynamically favorable and that most metal surfaces studied in this work are completely wettable, i.e., have contact angles of zero. Interfacial water has higher entropy than bulk water due to the increased population of low-frequency translational modes. The entropic contributions also correlate with the orientational water density, and the highest solvation entropies are observed for interfaces with a moderately ordered first water layer; the entropic contributions account for up to ∼25% of the formation free energy. Water adsorption energy correlates with the water orientation and structure and is found to be a good descriptor of the internal energy part of the interface formation free energy, but it alone cannot satisfactorily explain the interfacial thermodynamics; the interface formation is driven by the competition between energetic and entropic contributions. The obtained results and insight can be used to develop, parameterize, and benchmark theoretical and computational methods for studying metal-water interfaces. Overall, our study yields benchmark-quality data and fundamental insight into the thermodynamic forces driving metal-water interface formation.

Emerging Atomistic Modeling Methods for Heterogeneous Electrocatalysis

Heterogeneous electrocatalysis lies at the center of various technologies that could help enable a sustainable future. However, its complexity makes it challenging to accurately and efficiently model at an atomic level. Here, we review emerging atomistic methods to simulate the electrocatalytic interface with special attention devoted to the components/effects that have been challenging to model, such as solvation, electrolyte ions, electrode potential, reaction kinetics, and pH. Additionally, we review relevant computational spectroscopy methods. Then, we showcase several examples of applying these methods to understand and design catalysts relevant to green hydrogen. We also offer experimental views on how to bridge the gap between theory and experiments. Finally, we provide some perspectives on opportunities to advance the field.

Aqueous alternating electrolysis prolongs electrode lifespans under harsh operation conditions

It is vital to explore effective ways for prolonging electrode lifespans under harsh electrolysis conditions, such as high current densities, acid environment, and impure water source. Here we report alternating electrolysis approaches that realize promptly and regularly repair/maintenance and concurrent bubble evolution. Electrode lifespans are improved by co-action of Fe group elemental ions and alkali metal cations, especially a unique Co2+-Na+ combo. A commercial Ni foam sustains ampere-level current densities alternatingly during continuous electrolysis for 93.8 h in an acidic solution, whereas such a Ni foam is completely dissolved in ~2 h for conventional electrolysis conditions. The work not only explores an alternating electrolysis-based system, alkali metal cation-based catalytic systems, and alkali metal cation-based electrodeposition techniques, and beyond, but demonstrates the possibility of prolonged electrolysis by repeated deposition-dissolution processes. With enough adjustable experimental variables, the upper improvement limit in the electrode lifespan would be high.

Modeling water transport properties in carbon nanotubes: Interplay between force-field flexibility and geometrical parameters

Modeling water and other liquids in computational simulations requires a large set of parameters. Many works have been devoted to finding new, improved water models, with almost all of them designed for bulk systems. Here, we use carbon nanotubes as a play model to investigate the effects of introducing flexibility in water force fields during molecular dynamics simulations of nanoconfined water. We explore six different models to show that viscosity, diffusion, and dipole orientation are vastly influenced by the flexibility and the family of force fields used. Particularly, we found the level of confinement (decreasing the nanotube's diameter) to increase discrepancies in the description of the dipole alignment. In smaller (10,10) nanotubes, the flexible version of the transferable intermolecular potential with three points (TIP3P/Fs) features a high directionality, while its rigid counterpart shows a more distributed dipole orientation. Both viscosity and diffusion are also extremely dependent on the force-field family, with the flexible version of the simple point charge (SPC/Fw) featuring the lower confidence interval.

Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation

Decades of nanotoxicology research have generated extensive and diverse data sets. However, data is not equal to information. The question is how to extract critical information buried in vast data streams. Here we show that artificial intelligence (AI) and molecular simulation play key roles in transforming nanotoxicity data into critical information, i.e., constructing the quantitative nanostructure (physicochemical properties)-toxicity relationships, and elucidating the toxicity-related molecular mechanisms. For AI and molecular simulation to realize their full impacts in this mission, several obstacles must be overcome. These include the paucity of high-quality nanomaterials (NMs) and standardized nanotoxicity data, the lack of model-friendly databases, the scarcity of specific and universal nanodescriptors, and the inability to simulate NMs at realistic spatial and temporal scales. This review provides a comprehensive and representative, but not exhaustive, summary of the current capability gaps and tools required to fill these formidable gaps. Specifically, we discuss the applications of AI and molecular simulation, which can address the large-scale data challenge for nanotoxicology research. The need for model-friendly nanotoxicity databases, powerful nanodescriptors, new modeling approaches, molecular mechanism analysis, and design of the next-generation NMs are also critically discussed. Finally, we provide a perspective on future trends and challenges.

Further cautionary tales on thermostatting in molecular dynamics: Energy equipartitioning and non-equilibrium processes in gas-phase simulations

Molecular dynamics (MD) simulations of gas-phase chemical reactions are typically carried out on a small number of molecules near thermal equilibrium by means of various thermostatting algorithms. Correct equipartitioning of kinetic energy among translations, rotations, and vibrations of the simulated reactants is critical for many processes occurring in the gas phase. As thermalizing collisions are infrequent in gas-phase simulations, the thermostat has to efficiently reach equipartitioning in the system during equilibration and maintain it throughout the actual simulation. Furthermore, in non-equilibrium simulations where heat is released locally, the action of the thermostat should not lead to unphysical changes in the overall dynamics of the system. Here, we explore issues related to both obtaining and maintaining thermal equilibrium in MD simulations of an exemplary ion-molecule dimerization reaction. We first compare the efficiency of global (Nosé-Hoover and Canonical Sampling through Velocity Rescaling) and local (Langevin) thermostats for equilibrating a system of flexible compounds and find that of these three only the Langevin thermostat achieves equipartition in a reasonable simulation time. We then study the effect of the unphysical removal of latent heat released during simulations involving multiple dimerization events. As the Langevin thermostat does not produce the correct dynamics in the free molecular regime, we only consider the commonly used Nosé-Hoover thermostat, which is shown to effectively cool down the reactants, leading to an overestimation of the dimerization rate. Our findings underscore the importance of thermostatting for the proper thermal initialization of gas-phase systems and the consequences of global thermostatting in non-equilibrium simulations.

Zooming into the Inner Helmholtz Plane of Pt(111)-Aqueous Solution Interfaces: Chemisorbed Water and Partially Charged Ions

The double layer on transition metals, i.e., platinum, features chemical metal-solvent interactions and partially charged chemisorbed ions. Chemically adsorbed solvent molecules and ions are situated closer to the metal surface than electrostatically adsorbed ions. This effect is described tersely by the concept of an inner Helmholtz plane (IHP) in classical double layer models. The IHP concept is extended here in three aspects. First, a refined statistical treatment of solvent (water) molecules considers a continuous spectrum of orientational polarizable states, rather than a few representative states, and non-electrostatic, chemical metal-solvent interactions. Second, chemisorbed ions are partially charged, rather than being electroneutral or having integral charges as in the solution bulk, with the coverage determined by a generalized, energetically distributed adsorption isotherm. The surface dipole moment induced by partially charged, chemisorbed ions is considered. Third, considering different locations and properties of chemisorbed ions and solvent molecules, the IHP is divided into two planes, namely, an AIP (adsorbed ion plane) and ASP (adsorbed solvent plane). The model is used to study how the partially charged AIP and polarizable ASP lead to intriguing double-layer capacitance curves that are different from what the conventional Gouy-Chapman-Stern model describes. The model provides an alternative interpretation for recent capacitance data of Pt(111)-aqueous solution interfaces calculated from cyclic voltammetry. This revisit brings forth questions regarding the existence of a pure double-layer region at realistic Pt(111). The implications, limitations, and possible experimental confirmation of the present model are discussed.

Surface functionalization of graphene nanosheet with poly (L-histidine) and its application in drug delivery: covalent vs non-covalent approaches

Nowadays, nanomaterials are increasingly being used as drug carriers in the treatment of different types of cancers. As a result, these applications make them attractive to researchers dealing with diagnosis and biomarkers discovery of the disease. In this study, the adsorption behavior of gemcitabine (GMC) on graphene nanosheet (GNS), in the presence and absence of Poly (L-histidine) (PLH) polymer is discussed using molecular dynamics (MD) simulation. The MD results revealed an increase in the efficiency and targeting of the drug when the polymer is covalently attached to the graphene substrate. In addition, the metadynamics simulation to investigate the effects of PLH on the adsorption capacity of the GNS, and explore the adsorption/desorption process of GMC on pristine and PLH- grafted GNS is performed. The metadynamics calculations showed that the amount of free energy of the drug in acidic conditions is higher (- 281.26 kJ/mol) than the free energy in neutral conditions (- 346.24 kJ/mol). Consequently, the PLH polymer may not only help drug adsorption but can also help in drug desorption in lower pH environments. Based on these findings, it can be said that covalent polymer bonding not only can help in the formation of a targeted drug delivery system but also can increase the adsorption capacity of the substrate.

Liquid-Liquid Phase Transition in Metallic Droplets

We report theoretical evidence of the substrate-induced liquid-liquid phase transition (LLPT) behaviors in a single Al droplet and Ti-Al droplets. The Al droplet can produce an LLPT induced by substrates in part, forming a special three-layer structure. However, the introduction of a Ti droplet can promote the LLPT in an Al droplet. Al and Ti droplets do not coalesce into a homogeneously mixed droplet but produce the ordered liquid films. The substrate-induced LLPT in the Al droplet is characterized by the transition from the disordered to ordered structure. Results indicate that the substrate and the Ti droplet are the driving forces to promote the LLPT. The LLPT of the Ti-Al droplets in the wedge-shaped substrate is also observed, indicating that the confined Ti-Al droplets are more likely to undergo an LLPT.

Zeolite-confined subnanometric PtSn mimicking mortise-and-tenon joinery for catalytic propane dehydrogenation

Heterogeneous catalysts are often composite materials synthesized via several steps of chemical transformation, and thus the atomic structure in composite is a black-box. Herein with machine-learning-based atomic simulation we explore millions of structures for MFI zeolite encapsulated PtSn catalyst, demonstrating that the machine-learning enhanced large-scale potential energy surface scan offers a unique route to connect the thermodynamics and kinetics within catalysts' preparation procedure. The functionalities of the two stages in catalyst preparation are now clarified, namely, the oxidative clustering and the reductive transformation, which form separated Sn₄O₄ and PtSn alloy clusters in MFI. These confined clusters have high thermal stability at the intersection voids of MFI because of the formation of "Mortise-and-tenon Joinery". Among, the PtSn clusters with high Pt:Sn ratios (>1:1) are active for propane dehydrogenation to propene, ∼10³ in turnover-of-frequency greater than conventional Pt₃Sn metal. Key recipes to optimize zeolite-confined metal catalysts are predicted.

Structural dynamics of Ru clusters during nitrogen dissociation in ammonia synthesis

The dynamic evolution of catalyst structures greatly influences the reactivity, especially sub-nanometer clusters, exhibiting complex configurational fluctuation. In the present work, we study the structural dynamics of a Ru₁₉ cluster during the dissociation of N₂ and calculate the reaction free energies using ab initio molecular dynamics (AIMD). Our AIMD calculation predicts a peak-shaped reaction entropy curve due to the adsorption-induced phase transition of the Ru₁₉ cluster. The low melting points of sub-nanometer clusters make it possible to activate N₂ at low temperatures. This work demonstrates that the dynamic changes of cluster structures have a non-negligible effect on reaction free energy and offer an opportunity for achieving ammonia synthesis under mild conditions.

Modeling Operando Electrochemical CO2 Reduction

Since the seminal works on the application of density functional theory and the computational hydrogen electrode to electrochemical CO₂ reduction (eCO₂R) and hydrogen evolution (HER), the modeling of both reactions has quickly evolved for the last two decades. Formulation of thermodynamic and kinetic linear scaling relationships for key intermediates on crystalline materials have led to the definition of activity volcano plots, overpotential diagrams, and full exploitation of these theoretical outcomes at laboratory scale. However, recent studies hint at the role of morphological changes and short-lived intermediates in ruling the catalytic performance under operating conditions, further raising the bar for the modeling of electrocatalytic systems. Here, we highlight some novel methodological approaches employed to address eCO₂R and HER reactions. Moving from the atomic scale to the bulk electrolyte, we first show how ab initio and machine learning methodologies can partially reproduce surface reconstruction under operation, thus identifying active sites and reaction mechanisms if coupled with microkinetic modeling. Later, we introduce the potential of density functional theory and machine learning to interpret data from Operando spectroelectrochemical techniques, such as Raman spectroscopy and extended X-ray absorption fine structure characterization. Next, we review the role of electrolyte and mass transport effects. Finally, we suggest further challenges for computational modeling in the near future as well as our perspective on the directions to follow.