Optimized molecular reconstruction procedure combining hybrid reverse Monte Carlo and molecular dynamics

How urban form impacts flooding

Urbanization and climate change are contributing to severe flooding globally, damaging infrastructure, disrupting economies, and undermining human well-being. Approaches to make cities more resilient to floods are emerging, notably with the design of flood-resilient structures, but relatively little is known about the role of urban form and its complexity in the concentration of flooding. We leverage statistical mechanics to reduce the complexity of urban flooding and develop a mean-flow theory that relates flood hazards to urban form characterized by the ground slope, urban porosity, and the Mermin order parameter which measures symmetry in building arrangements. The mean-flow theory presents a dimensionless flood depth that scales linearly with the urban porosity and the order parameter, with different scaling for disordered square- and hexagon-like forms. A universal scaling is obtained by introducing an effective mean chord length representative of the unobstructed downslope travel distance for flood water, yielding an analytical model for neighborhood-scale flood hazards globally. The proposed mean-flow theory is applied to probe city-to-city variations in flood hazards, and shows promising results linking recorded flood losses to urban form and observed rainfall extremes.

Microscopic Simulations of Electrochemical Double-Layer Capacitors

Electrochemical double-layer capacitors (EDLCs) are devices allowing the storage or production of electricity. They function through the adsorption of ions from an electrolyte on high-surface-area electrodes and are characterized by short charging/discharging times and long cycle-life compared to batteries. Microscopic simulations are now widely used to characterize the structural, dynamical, and adsorption properties of these devices, complementing electrochemical experiments and in situ spectroscopic analyses. In this review, we discuss the main families of simulation methods that have been developed and their application to the main family of EDLCs, which include nanoporous carbon electrodes. We focus on the adsorption of organic ions for electricity storage applications as well as aqueous systems in the context of blue energy harvesting and desalination. We finally provide perspectives for further improvement of the predictive power of simulations, in particular for future devices with complex electrode compositions.

How chemical defects influence the charging of nanoporous carbon supercapacitors

Nanoporous carbon texture makes fundamental understanding of the electrochemical processes challenging. Based on density functional theory (DFT) results, the proposed atomistic approach takes into account topological and chemical defects of the electrodes and attributes to them a partial charge that depends on the applied voltage. Using a realistic carbon nanotexture, a model is developed to simulate the ionic charge both at the surface and in the subnanometric pores of the electrodes of a supercapacitor. Before entering the smallest pores, ions dehydrate at the external surface of the electrodes, leading to asymmetric adsorption behavior. Ions in subnanometric pores are mostly fully dehydrated. The simulated capacitance is in qualitative agreement with experiments. Part of these ions remain irreversibly trapped upon discharge.

Ion desolvation and confinement are key physical processes in porous carbon-based supercapacitors undergoing charging and discharging cycles. We investigate electrolyte interactions between polarized porous carbon with subnanometer pore sizes and aqueous sodium chloride electrolyte, using molecular dynamics. Inspired by recent first-principles calculations, we develop a scheme accounting for chemical defects in electrodes where only the non-sp2 carbons species carry an extra negative charge (on the anode) and an extra positive charge (on the cathode) due to voltage polarization. This drives electrolyte species (ions and solvent molecules; water, in this work) to adsorb at the electrode surface and in subnanometric pores upon polarization. First, we observe an asymmetrical desolvation process of sodium and chloride ions at the external surface of the electrodes. The ionic distribution at the external surface of the electrodes is consistent with the Debye–Hückel electric potential equation and empirical trends observed for nonporous electrodes. In a second stage, we demonstrate that the nanoporosity of the electrodes is filled with ions and scarce water molecules and contributes to about 20% of the overall capacitance. A fraction of desolvated ions are irreversibly trapped in the core of electrodes during discharge. While maintaining the overall electroneutrality of the simulation cell, we find that anodes and cathodes do not carry the same amount of ions at all time steps, leading to charge imbalance.

Iterative reverse Monte Carlo and molecular statics for improved atomic structure modeling: a case study of zinc oxide grown by atomic layer deposition

Reverse Monte Carlo (RMC) modeling is a common method to derive atomic structure models of materials from experimental diffraction data. However, conventional RMC modeling does not impose energetic constraints and can produce non-physical local structures within the simulation volume. Although previous strategies have introduced energetic constraints during RMC modeling, these approaches have limitations in computational cost and physical accuracy. In this work, we periodically introduce molecular statics (MS) energy minimizations during RMC modeling in an iterative RMC-MS approach. We test this iterative RMC-MS approach using diffraction data collected by in operando high energy X-ray diffraction during atomic layer deposition of ZnO as a sample case. For MS relaxations we employ ReaxFF pair potentials previously established for ZnO. We find that RMC-MS and RMC provide equivalent agreement with experimental data, but RMC-MS structures are on average 0.6 eV per atom lower in energy and are more consistent with known ZnO atomic structure features. The iterative RMC-MS approach we report can accommodate large systems with minimal additional computational burden beyond a standard RMC simulation and can leverage established pair potentials for immediate application to study a wide range of materials.

Characterizing Structural Complexity in Disordered Carbons: From the Slit Pore to Atomistic Models

The reliable characterization of nanoporous carbons is critical to the design and optimization of their numerous applications; however, the vast majority of carbons in industrial use are highly disordered, with complex structures whose understanding has long challenged researchers. The idealized slit pore model represents the most commonly used approximation to a carbon nanopore; nevertheless, it has been only partially successful in predicting adsorption isotherms and fails significantly in predicting transport properties because of its inability to capture structural disorder and its effect on fluid accessibility. Atomistic modeling of the structure has much potential for overcoming this limitation, and among such approaches, hybrid reverse Monte Carlo simulation has emerged as the most attractive. This method reconstructs the structure of a carbon based on the fitting of its experimentally measured pair distribution function and appropriate properties such as porosity while minimizing the energy. The method is shown to be best implemented using a multistage strategy, with the first stage used to attain a deep minimum of the energy and subsequent stages to refine the structure based on the fitting of specific properties. Methods to determine the accessibility of gases based on the atomistic structure are outlined, and it is shown that energy barriers are very sensitive to small differences in the sizes of constrictions and pore entries. The ability to accurately predict macroscopic transport coefficients of adsorbates in nanoporous carbons appears to be the greatest limitation of such models. Overcoming this will require the fitting of properties more sensitive to long-range disorder than the currently used pair distribution and the use of a suitable multiscaling strategy, which is suggested as a future direction for advancing atomistic models. The inclusion of heteroatoms in the structure is also an important area requiring further attention, particularly in the development of computationally efficient force fields incorporating their interactions.

Realistic molecular model of kerogen's nanostructure

Despite kerogen's importance as the organic backbone for hydrocarbon production from source rocks such as gas shale, the interplay between kerogen's chemistry, morphology and mechanics remains unexplored. As the environmental impact of shale gas rises, identifying functional relations between its geochemical, transport, elastic and fracture properties from realistic molecular models of kerogens becomes all the more important. Here, by using a hybrid experimental-simulation method, we propose a panel of realistic molecular models of mature and immature kerogens that provide a detailed picture of kerogen's nanostructure without considering the presence of clays and other minerals in shales. We probe the models' strengths and limitations, and show that they predict essential features amenable to experimental validation, including pore distribution, vibrational density of states and stiffness. We also show that kerogen's maturation, which manifests itself as an increase in the sp(2)/sp(3) hybridization ratio, entails a crossover from plastic-to-brittle rupture mechanisms.