Classical Molecular Dynamics Research Articles

An examination of the performance of molecular dynamics force fields: Silicon and silicon dioxide reactive ion etching

Classical molecular dynamics (MD) simulations of plasma-surface interactions were performed of physical sputtering and reactive ion etching (RIE), with predictions based on several force fields. In this paper, we focus mainly on SiO2 but include some results for Si substrates as well. We compare predictions from these MD simulations to experimental studies of SiO2 physical sputtering (by Ar+ ions), RIE of Si, and RIE of SiO2 (both using F atoms and Ar+ ions). MD results using different published force fields are compared to reported yields from published vacuum beam experiments. The near-surface depth profiles predicted using different force fields are compared. One motivation for the present study is to document the nature and magnitude of differences in the predictions for selected systems and conditions of practical interest.

Ab initio electron-lattice downfolding: Potential energy landscapes, anharmonicity, and molecular dynamics in charge density wave materials

The interplay of electronic and nuclear degrees of freedom presents an outstanding problem in condensed matter physics and chemistry. Computational challenges arise especially for large systems, long time scales, in nonequilibrium, or in systems with strong correlations. In this work, we show how downfolding approaches facilitate complexity reduction on the electronic side and thereby boost the simulation of electronic properties and nuclear motion-in particular molecular dynamics (MD) simulations. Three different downfolding strategies based on constraining, unscreening, and combinations thereof are benchmarked against full density functional calculations for selected charge density wave (CDW) systems, namely 1H-TaS_22, 1T-TiSe_22, 1H-NbS_22, and a one-dimensional carbon chain. We find that the downfolded models can reproduce potential energy surfaces on supercells accurately and facilitate computational speedup in MD simulations by about five orders of magnitude in comparison to purely ab initio calculations. For monolayer 1H-TaS_22 we report classical and path integral replica exchange MD simulations, revealing the impact of thermal and quantum fluctuations on the CDW transition.

The Harmonic and Gaussian Approximations in the Potential Energy Landscape Formalism for Quantum Liquids.

The potential energy landscape (PEL) formalism has been used in the past to describe the behavior of classical low-temperature liquids and glasses. Here, we extend the PEL formalism to describe the behavior of liquids and glasses that obey quantum mechanics. In particular, we focus on the (i) harmonic and (ii) Gaussian approximations of the PEL, which have been commonly used to describe classical systems, and show how these approximations can be applied to quantum liquids/glasses. Contrary to the case of classical liquids/glasses, the PEL of quantum liquids is temperature-dependent, and hence, the main expressions resulting from approximations (i) and (ii) depend on the nature (classical vs quantum) of the system. The resulting theoretical expressions from the PEL formalism are compared with results from path-integral Monte Carlo (PIMC) simulations of a monatomic model liquid. In the PIMC simulations, every atom of the quantum liquid is represented by a ring-polymer. Our PIMC simulations show that at the local minima of the PEL (inherent structures, or IS), sampled over a wide range of temperatures and volumes, the ring-polymers are collapsed. This considerably facilitates the description of quantum liquids using the PEL formalism. Specifically, the normal modes of the ring-polymer system/quantum liquid at an IS can be calculated analytically if the normal modes of the classical liquid counterpart are known (as obtained, e.g., from classical MC or molecular dynamics simulations of the corresponding atomic liquid).

Membrane Permeation of Psychedelic Tryptamines by Dynamic Simulations.

Renewed scientific interest in psychedelic compounds represents one of the most promising avenues for addressing the current burden of mental health disorders. Classic psychedelics are a group of compounds that exhibit structural similarities to the naturally occurring neurotransmitter serotonin (5-HT). Acting on the 5-HT type 2A receptors (HT2ARs), psychedelics induce enduring neurophysiological changes that parallel their therapeutic psychological and behavioral effects. Recent preclinical evidence suggests that the ability of psychedelics to exert their action is determined by their ability to permeate the neuronal membrane to target a pool of intracellular 5-HT2ARs. In this computational study, we employ classical molecular dynamics simulations and umbrella sampling techniques to investigate the permeation behavior of 12 selected tryptamines and to characterize the interactions that drive the process. We aim at elucidating the impact of N-alkylation, indole ring substitution and positional modifications, and protonation on their membrane permeability. Dimethylation of the primary amine group and the introduction of a methoxy group at position 5 exhibited an increase in permeability. Moreover, there is a significant influence of positional substitutions on the indole groups, and the protonation of the molecules substantially increases the energy barrier at the center of the bilayer, making the compounds highly impermeable. All the information extracted from the trends predicted by the simulations can be applied in future drug design projects to develop psychedelics with enhanced activity.

A Classical Molecular Dynamics Study of the Effect of the Atomic Force Microscope Tip Shape, Size and Deformation on the Tribological Properties of the Graphene/Au(111) Interface

Atomic force microscopes are used, besides their principal function as surface imaging tools, in the surface manipulation and measurement of interfacial properties. In particular, they can be modified to measure lateral friction forces that occur during the sliding of the tip against the underlying substrate. However, the shape, size, and deformation of the tips profoundly affect the measurements in a manner that is difficult to predict. In this work, we investigate the contribution of these effect to the magnitude of the lateral forces during sliding. The surface substrate is chosen to be a few-layer AB-stacked graphene surface, whereas the tip is initially constructed from face-centered cubic gold. In order to separate the effect of deformation from the shape, the rigid tips of three different shapes were considered first, namely, a cone, a pyramid and a hemisphere. The shape was seen to dictate all aspects of the interface during sliding, from temperature dependence to stick–slip behavior. Deformation was investigated next by comparing a rigid hemispherical tip to one of an identical shape and size but with all but the top three layers of atoms being free to move. The deformation, as also verified by an indentation analysis, occurs by means of the lower layers collapsing on the upper ones, thereby increasing the contact area. This collapse mitigates the friction force and decreases it with respect to the rigid tip for the same vertical distance. Finally, the size effect is studied by means of calculating the friction forces for a much larger hemispherical tip whose atoms are free to move. In this case, the deformation is found to be much smaller, but the stick–slip behavior is much more clearly seen.

Selective laser sintering of amorphous nanoparticles: Molecular dynamics simulations

The paper investigates the process of liquid-phase sintering of amorphous iron-based nanoparticles by the method of molecular dynamics simulations. The classical molecular dynamics package LAMMPS was used for modeling. Visual analysis of the atomic configurations of nanoparticles during their rapid cooling revealed the self-purification effect of the particles. Partial pair correlation functions and coordination number distribution functions were used to analyze the atomic structure of nanoparticles after sintering. As a result of the analysis of the main structural parameters, which were obtained using the specified functions, differences in the atomic composition and structure of the volume and surface of nanoparticles were established.

The study of the convergence conditions of the deep-learning method in the Li10GeP2S12 solid state electrolyte system

Abstract The ionic conductivity of solid-state electrolytes at room temperature is crucial for commercializing lithium-ion batteries with solid-state electrolytes. Ab initio methods encounter a challenge due to their substantial computational resource demands. Classical molecular dynamics methods, on the other hand, are suitable for large-scale systems with simulation times reaching the nanosecond scale. However, they rely on empirical parameters in force fields, limiting their use to systems with well-established and extensively validated parameters, which is a constraint in studying new materials. A simulation approach combines ab initio simulations and classical molecular dynamics. Deepmd-kit, a deep learning tool, trains a tailored force field model using ab initio simulation data for the target system. However, as an approximate method, its reliability must be compared with ab initio results. As a data-sensitive method, the amount of data required to achieve the desired accuracy varies for different systems and must be tested accordingly. This paper performs convergence training for system size and simulation time concerning Li10GeP2S12 solid-state electrolytes, establishing the convergence criteria for deep learning data in this system.

Vibrational Spectroscopy of YAlO3

Perovskites have long been materials of interest in solid‐state physics. Their structure leads them to exhibit various characteristics which have both theoretical and practical interest. Lattice dynamics can give a lot of insight into a material's nature such as phase transitions, thus the research presented here focuses on that, by doing a comprehensive vibrational and structural investigation of monocrystalline YAlO3 (YAP). Polarized Raman and infrared (IR) reflectance spectroscopy are used alongside ab initio and classical calculations. In the course of this work, complete Raman spectra have been obtained, confirming new vibrational modes, predicted by ab initio calculations but previously not observed experimentally. IR reflectance spectra have been obtained for the first time for this material. Classical molecular dynamics has been employed to calculate the phonon dispersion and density of states.

Multiscale In Silico Study of the Mechanism of Activation of the RtcB Ligase by the PTP1B Phosphatase.

Inositol-requiring enzyme 1 (IRE1) is a transmembrane sensor that is part of a trio of sensors responsible for controlling the unfolded protein response within the endoplasmic reticulum (ER). Upon the accumulation of unfolded or misfolded proteins in the ER, IRE1 becomes activated and initiates the cleavage of a 26-nucleotide intron from human X-box-containing protein 1 (XBP1). The cleavage is mediated by the RtcB ligase enzyme, which splices together two exons, resulting in the formation of the spliced isoform XBP1s. The XBP1s isoform activates the transcription of genes involved in ER-associated degradation to maintain cellular homeostasis. The catalytic activity of RtcB is controlled by the phosphorylation and dephosphorylation of three tyrosine residues (Y306, Y316, and Y475), which are regulated by the ABL1 tyrosine kinase and PTP1B phosphatase, respectively. This study focuses on investigating the mechanism by which the PTP1B phosphatase activates the RtcB ligase using a range of advanced in silico methods. Protein-protein docking identified key interacting residues between RtcB and PTP1B. Notably, the phosphorylated Tyr306 formed hydrogen bonds and salt bridge interactions with the "gatekeeper" residues Arg47 and Lys120 of the inactive PTP1B. Classical molecular dynamics simulation emphasized the crucial role of Asp181 in the activation of PTP1B, driving the conformational change from an open to a closed state of the WPD-loop. Furthermore, QM/MM-MD simulations provided insights into the free energy landscape of the dephosphorylation reaction mechanism of RtcB, which is mediated by the PTP1B phosphatase.

Theoretical multiscale study on the properties, aqueous solution behavior and biological impact of zinc oxide nanoparticles

The aim of this theoretical study is to describe the relationship between the structure and the physicochemical properties of zinc oxide nanoparticles (ZnO NPs) and Mn doped ZnO NPs to assess their toxicological impact. In order to do so, a multiscale modelling approach is applied. Different nanoparticles, as well as the mechanism(s) of nanoparticle aggregation and growing, are characterized in terms of size and shape considering electronic, surface, structural and topological properties via quantum mechanics simulations. To evaluate the toxicology impact of ZnO NPs in human health safety and their possible environmental impact, classical molecular dynamics simulations were carried out to study the interaction between the nanomaterials and biological target systems: a set of selected human proteins and model plasma membranes. Likewise, the simulation of nanoparticles dispersion in aqueous media along with water adsorption on their surfaces was conducted.The mayor findings may be summarized as: (i) the ZnO NPs from 12 to 96 (ZnO) units are characterized and their interaction energies, HOMO-LUMO gaps, superficial areas and volumes are reported; (ii) the (ZnO)12 NP and Zn11MnO12 NP are further characterized via their topological properties, vibrational spectra, PDOS and non-covalent interactions; (iii) the doping with Mn atoms is favourable. The interaction energies, HOMO-LUMO orbitals and gaps, PDOS, atomic charges, superficial areas and volumes are reported for NPs doped with up to 5 Mn atoms; (iv) high water affinity for ZnO NPs is reported with both quantum and classical calculations, v) (ZnO)12 NPs do not penetrate the cell membrane and (vi) the affinity energy of both ZnO and Mn doped NPs for human proteins is moderate.The reported results provide in-depth whole-chain studies of zinc oxide nanoparticles, which have been successfully applied for different technologies.

Fast crystal growth in deeply undercooled ZrTi melts.

We investigate the growth of crystals in Zr50Ti50 melts by classical molecular-dynamics simulations with an embedded atom method and a Stillinger-Weber potential model. Both models display fast solidification rates that can be captured by the transition state theory or the Ginzburg-Landau theory at small undercoolings. Fast crystal-growth rates are found to be affected by the pre-existing ordering in liquids, such as the body-centered cubic-like and icosahedral-like structures. The interface-induced ordering unveiled by the crystal-freezing method can explain the rate difference between these two models. However, these orderings fail to rationalize the temperature evolution of the growth rate at deep undercoolings. We correlate the growth kinetics with the detailed dynamical processes in liquids, finding the decoupling of hierarchic relaxation processes when collective motion emerges in supercooled liquids. We find that the growth kinetics is nondiffusive, but with a lower activation barrier corresponding to the structural relaxation or the cage-relative motion in ZrTi melts. These results explore a new relaxation mechanism for the fast growth rate in deeply undercooled liquids.

Coalescence behavior of fully submerged CO2 nanobubbles: A molecular dynamics based parametric study

Due to their extraordinarily extended lifetime and wide range of applications in numerous cutting-edge technologies and processes, nanobubbles have garnered a lot of attention in recent years. Nanobubble coalescence behavior is of crucial importance as it provides a clear indication of how stable these nanobubbles really are, which is vital for most nanobubble applications. The current study employs classical molecular dynamics simulation to investigate the coalescence dynamics of CO2 nanobubbles completely submerged in water. To draw a stark contrast, a comparison with air nanobubble coalescence is presented as well. It is observed that unlike air nanobubbles, CO2 nanobubbles have a tendency to hinder coalescence and do not fully coalesce into a single bubble in general. State of the entrapped gas inside the nanobubbles, electrostatic repulsion and large negative zeta-potential are the primary factors responsible for this nature. Coalescence neck growth and onset time are used to quantify the degree of partial coalescence. A compilation of findings and analysis for a total of 8 factors and 40 cases has been provided, demonstrating how CO2 nanobubble coalescence is influenced by many factors such as nanobubble size, surrounding pressure, temperature, the presence of air, and more. These parametric studies show that the degree of coalescence is tunable through adjustment of certain parameters. The parametric exploration of CO2 nanobubble coalescence behavior might serve as control strategies in various nanobubble driven processes.

What Happens to a Pyrrole Hemithioindigo Photoswitch Trapped in a Fluorescent Protein?

Artificial molecular photoswitches that can be reversibly controlled into different configurations by external light stimulation have broad application prospects in various fields, such as materials and chemical biology. Among them, the pyrrole hemithioindigo (PHT) photoswitch has a geometric structure similar to that of the fluorescent protein chromophore. What happens when the chromophore is replaced by PHT, and does it achieve similar functions to the original one? To answer these questions, we carried out ONIOM(QM/MM) and classical molecular dynamics studies on the photoisomerization mechanism and spectroscopic properties of PHT in the fluorescent protein. The results showed that in the protein environment, the fate of excited PHT is governed by the competition between fluorescence emission and hula-twist isomerization. Due to the strong steric hindrance effects caused by the interlacing residues in the protein that restrict the PHT conformation transformation, the cis-to-trans isomerization process of PHT needs to overcome a barrier of at least 4.9 kcal/mol; thus, fluorescence emission is more dominant in competition. It is also found that the intermolecular interaction between LYS67 and the carbonyl oxygen of PHT has a significant effect on the fluorescence emission. These results revealed the photochemical reaction mechanism of a light-driven molecular switch in the fluorescent protein and provided further theoretical support for the field of chemical biology.

Computational insight into the effect of alkyl chain length in tetraalkylammonium-based deep eutectic solvents

The effect of the increase in the alkyl chain length of cation on the properties of deep eutectic solvents based on ethylene glycol has been investigated employing classical molecular dynamics simulations. The change in the structural and dynamic properties in both the bulk and liquid–vapor interface is explored through various analyses. The interaction between the anion and the ethylene glycol increases with an increase in the alkyl chain length of the cation, as observed in the increase of the lifetime of the hydrogen bond formed between the two. The terminal carbon atoms are found to be closer to each other when the cation changes from tetraethylammonium to tetrabutylammonium. The cations are located closer to the interface, and the association of the alkyl chains becomes more significant with increased alkyl chain length, decreasing the surface tension values.

Roles of electrostatics and intermolecular electronic motions in the structural and spectroscopic features of hydrogen- and halogen-bonded systems

Abstract It is widely recognized that electrostatics plays a central role in the intermolecular interactions in condensed phases, as evidenced by the “electrostatics + Lennard-Jones” form of the potential functions that are commonly used in classical molecular dynamics simulations. Then, do we understand all about electrostatics in condensed phases? In this review, recent theoretical advances in relation to this topic will be discussed: (1) vibrational spectroscopic probing of the electrostatics in condensed phases, and (2) some phenomena affected by deviation from the scheme of isotropic fixed atomic partial charges, i.e., anisotropy and intermolecular transfer of electron distributions. A theoretical basis for better understanding on them and some theoretical models for practical calculations will be shown with some typical example cases of hydrogen- and halogen-bonded systems.

Effects of pectin and temperature on the diffusion of ions and water in saltwater membranes

In this study, we investigate the structural and dynamical characteristics of the biopolymer pectin, exploring its impact on ion transport, diffusion activation energy, and relaxation timescales within a saltwater environment (100 mM NaCl (aq.)) using classical molecular dynamics (MD) simulations. Our analysis of radial distribution functions (g(r)) reveals a notable preference of Na+ ions to interact more extensively with pectin compared to Cl– ions. Moreover, we observe slight variations in the strength of inter-ion interactions, with a modest decrease in ion-pectin interaction strength with increased pectin loading. Additionally, our findings indicate that sodium exhibits the lowest diffusion coefficient due to the presence of significant energy barriers among Na+, Cl–, and water molecules, following the sequence: D(water) > D(Cl–) > D(Na+) at any pectin loading and temperature conditions within pectin-saltwater membranes. Furthermore, our study demonstrates that viscosity, ion-pair relaxation timescales and ion-cage relaxation timescales exhibit monotonic increases with pectin loading while displaying the opposite trend with temperature. Overall, our simulations strongly endorse the use of biopolymer pectin as a highly promising and innovative option for a wide range of industrial applications, including flexible hydrogel electrolytes and saline water treatment.

Atomistic Computer Simulations of Uranyl Adsorption on Hydrated Illite and Smectite Surfaces

A quantitative understanding of the molecular-scale mechanisms of radionuclide sorption on different clay minerals is crucial for the development and safe implementation of geological nuclear waste disposal technologies. We apply classical molecular dynamics (MD) computer simulations to study the adsorption of uranyl on the external basal surfaces of two typical clay models. In the illite model, negative charge is primarily localized in the tetrahedral sheets, while in the lower-charge smectite model, the isomorphic substitutions are introduced in the octahedral sheet. The comparison of atomic density distributions at the clay surfaces and adsorption-free energies profiles as a function of distance from these surfaces demonstrates that overall U behavior at the basal clay surface is quite similar for illite and smectite. Uranyl is sorbed as a mixture of outer-sphere aqua complexes [UO2(H2O)5]2+ and hydrolyzed aqua complexes [UO2(H2O)4–5OH]+ on both surfaces. The structural and compositional differences between the models do not greatly affect the uranyl’s nearest coordination environment and are mainly reflected in the specific localization and orientation of the uranyl ions at both surfaces and in the magnitude of the adsorption-free energies. The observed quantitative characteristics of uranyl interactions with illite and smectite surfaces will help to better understand U behavior during the sorption process on clay minerals for the entire range of mixed-layer illite–smectite structures. A comparison of two versions of the ClayFF force field in the simulations made it possible to more accurately and quantitatively evaluate some subtle features of the uranyl–clay interactions and to obtain a more precise composition of uranyl complex with the modified ClayFF force field (ClayFF-MOH).

A data-guided approach for the evaluation of zeolites for hydrogen storage with the aid of molecular simulations.

This study employs a data-guided approach to evaluate zeolites for hydrogen storage, utilizing molecular simulations. The development of efficient and practical hydrogen storage materials is crucial for advancing clean energy technologies. Zeolites have shown promise as potential candidates due to their unique porous structure and tunable properties. However, the selection and design of suitable zeolites for hydrogen storage remain challenging. Therefore, this work aims to address this materials science question by utilizing molecular simulations and data-guided approaches to evaluate zeolites' performance for hydrogen storage. The results obtained from this study provide valuable insights into the evaluation of zeolites for hydrogen storage. Through molecular simulations, we analyze the adsorption behavior of hydrogen molecules in various zeolite structures. The performance of different zeolite frameworks in terms of hydrogen storage capacity, adsorption energy, and diffusion properties is assessed. Linde type A zeolite (LTA) had the highest capacity with a hydrogen capacity of 4.8wt% out of the 233 investigated zeolites. Furthermore, we investigate the influence of different factors such as mass (M), density (D), helium void fraction (HVF), accessible pore volume (APV), gravimetric surface area (GSA), and largest overall cavity diameter (Di) on the hydrogen storage performance of zeolites. The results show that Di, D, and M have a negative effect on the percentage weight capacity, while GSA and VSA have the highest positive contribution to the percentage weight. This study, therefore, provides new insights into the factors that affect their hydrogen storage capacity by exhibiting the importance of considering multiple factors when evaluating the performance of zeolites and demonstrates the potential of combining different computational methods to provide a more comprehensive understanding of materials. The current study contributes to the understanding of zeolite-based materials for hydrogen storage applications, aiding in the development of more efficient and practical hydrogen storage systems. Computational techniques were employed to investigate the hydrogen storage properties of zeolites. Molecular simulations were performed using classical force fields and molecular dynamics methods. The calculations were carried out at a force field level of theory with the GGA functional. To accurately capture the thermodynamics and kinetics of hydrogen adsorption, enhanced sampling techniques such as Monte Carlo simulations and molecular dynamics with metadynamics were utilized. We employed Grand Canonical Monte Carlo (GCMC) simulations to model hydrogen adsorption in zeolite structures for hydrogen storage. Our approach involved performing a substantial number of Monte Carlo steps (10,000) to ensure system equilibration and precise results. We defined a cutoff distance for particle interactions as 12.5 Ǻ and considered 0.000e framework charge per cell and 0.000e sorbate charge in energy calculations. The choice of an appropriate simulation cell size (50 × 50 × 50) Ǻ was crucial, mirroring real-world conditions. We specified lower and upper fugacity values (1 to 10atm) to capture the range of gas pressures in the simulations. These methodical steps collectively enabled us to accurately model hydrogen adsorption within zeolites, forming the core of our hydrogen storage evaluation. In this research, we utilized DFT calculations to thoroughly investigate the interactions between zeolites and hydrogen. We employed pseudopotentials to describe electron behavior in zeolite systems, choosing them in line with DFT norms and basis set compatibility. Our simulation cell design replicated zeolite periodicity and eliminated boundary effects. Pre-geometry optimization was performed with HyperChem29, ensuring stable conformations with strict convergence criteria. We utilized 6-31 + G(d) and LanL2DZ basis sets for light and heavy atoms, aligning with field standards for computational efficiency and precision. A machine learning algorithm was used to rank the importance of various structural features such as mass (M), density (D), helium void fraction (HVF), accessible pore volume (APV), gravimetric surface area (GSA), and largest overall cavity diameter (Di) and how they affect the capacity of the zeolites. Machine learning analysis was performed with the Scikit-learn library, an open-source Python tool. We employed a range of machine learning models, including SVMs, random forests, and neural networks, primarily for data analysis and feature extraction. Pearson correlation analysis, a classical statistical technique, was used to evaluate linear relationships between variables and assess the strength and direction of these relationships. It served as a complementary tool to understand the interplay of variables in our dataset, distinguishing it from machine learning algorithms. Further quantum chemical calculations were also performed to calculate the adsorption energy, global reactivity electronic descriptors, and natural bond orbital analysis in order to provide insights into the interaction of the zeolites with hydrogen. The simulations and data analysis were performed using BIOVIA material studio software, Gaussian, and Origin Pro software.

Practical classical molecular dynamics simulations for low-temperature plasma processing: a review

Practical classical molecular dynamics simulations for low-temperature plasma processing: a review

Cation Modifies Interfacial Water Structures on Platinum during Alkaline Hydrogen Electrocatalysis.

The molecular details of an electrocatalytic interface play an essential role in the production of sustainable fuels and value-added chemicals. Many electrochemical reactions exhibit strong cation-dependent activities, but how cations affect reaction kinetics is still elusive. We report the effect of cations (K+, Li+, and Ba2+) on the interfacial water structure using second-harmonic generation (SHG) and classical molecular dynamics (MD) simulation. The second- (χH2O(2)) and third-order (χH2O(3)) optical susceptibilities of water on Pt are smaller in the presence of Ba2+ compared to those of K+, suggesting that cations can affect the interfacial water orientation. MD simulation reproduces experimental SHG observations and further shows that the competition between cation hydration and interfacial water alignment governs the net water orientation. The impact of cations on interfacial water supports a cation hydration-mediated mechanism for hydrogen electrocatalysis; i.e., the reaction occurs via water dissociation followed by cation-assisted hydroxide/water exchange on Pt. Our study highlights the role of interfacial water in electrocatalysis and how innocent additives (such as cations) can affect the local electrochemical environment.