Ion Transport in Polymer Electrolytes: Building New Bridges between Experiment and Molecular Simulation.

ConspectusPolymer electrolytes constitute a promising type of material for solid-state batteries. However, one of the bottlenecks for their practical implementation lies in the transport properties, often including restricted Li+ self-diffusion and conductivity and low cationic transference numbers. This calls for a molecular understanding of ion transport in polymer electrolytes in which molecular dynamics (MD) simulation can provide both new physical insights and quantitative predictions. Although efforts have been made in this area and qualitative pictures have emerged, direct and quantitative comparisons between experiment and simulation remain challenging because of the lack of a unified theoretical framework to connect them.In our work, we show that by computing the glass transition temperature (Tg) of the model system and using the normalized inverse temperature 1000/(T - Tg + 50), the Li+ self-diffusion coefficient can be compared quantitatively between MD simulations and experiments. This allows us to disentangle the effects of Tg and the polymer dielectric environment on ion conduction in polymer electrolytes, giving rise to the identification of an optimal solvating environment for fast ion conduction.Unlike Li+ self-diffusion coefficients and ionic conductivity, the transference number, which describes the fraction of current carried by Li+ ions, depends on the boundary conditions or the reference frame (RF). This creates a non-negligible gap when comparing experiment and simulation because the fluxes in the experimental measurements and in the linear response theory used in MD simulation are defined in different RFs. We show that by employing the Onsager theory of ion transport and applying a proper RF transformation, a much better agreement between experiment and simulation can be achieved for the PEO-LiTFSI system. This further allows us to derive the theoretical expression for the Bruce-Vincent transference number in terms of the Onsager coefficients and make a direct comparison to experiments. Since the Bruce-Vincent method is widely used to extract transference numbers from experimental data, this opens the door to calibrating MD simulations via reproducing the Bruce-Vincent transference number and using MD simulations to predict the true transference number.In addition, we also address several open questions here such as the time-scale effects on the ion-pairing phenomenon, the consistency check between different types of experiments, the need for more accurate force fields used in MD simulations, and the extension to multicomponent systems. Overall, this Account focuses on building new bridges between experiment and simulation for quantitative comparison, warnings of pitfalls when comparing apples and oranges, and clarifying misconceptions. From a physical chemistry point of view, it connects to concentrated solution theory and provides a unified theoretical framework that can maximize the power of MD simulations. Therefore, this Account will be useful for the electrochemical energy storage community at large and set examples of how to approach experiments from theory and simulation (and vice versa).

Understanding the patterns and health impact of indoor air pollutant exposures in Bradford, UK: a study protocol.

INTRODUCTION: Relative to outdoor air pollution, there is little evidence examining the composition and concentrations of indoor air pollution and its associated health impacts. The INGENIOUS project aims to provide the comprehensive understanding of indoor air pollution in UK homes. METHODS AND ANALYSIS: 'Real Home Assessment' is a cross-sectional, multimethod study within INGENIOUS. This study monitors indoor air pollutants over 2 weeks using low-cost sensors placed in three rooms in 300 Born in Bradford (BiB) households. Building audits are completed by researchers, and participants are asked to complete a home survey and a health and behaviour questionnaire, in addition to recording household activities and health symptoms on at least 1 weekday and 1 weekend day. A subsample of 150 households will receive more intensive measurements of volatile organic compound and particulate matter for 3 days. Qualitative interviews conducted with 30 participants will identify key barriers and enablers of effective ventilation practices. Outdoor air pollution is measured in 14 locations across Bradford to explore relationships between indoor and outdoor air quality. Data will be analysed to explore total concentrations of indoor air pollutants, how these vary with building characteristics, and whether they are related to health symptoms. Interviews will be analysed through content and thematic analysis. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the NHS Health Research Authority Yorkshire and the Humber (Bradford Leeds) Research Ethics Committee (22/YH/0288). We will disseminate findings using our websites, social media, publications and conferences. Data will be open access through the BiB, the Open Science Framework and the UK Data Service.

PiNNwall: Heterogeneous Electrode Models from Integrating Machine Learning and Atomistic Simulation.

Electrochemical energy storage always involves the capacitive process. The prevailing electrode model used in the molecular simulation of polarizable electrode-electrolyte systems is the Siepmann-Sprik model developed for perfect metal electrodes. This model has been recently extended to study the metallicity in the electrode by including the Thomas-Fermi screening length. Nevertheless, a further extension to heterogeneous electrode models requires introducing chemical specificity, which does not have any analytical recipes. Here, we address this challenge by integrating the atomistic machine learning code (PiNN) for generating the base charge and response kernel and the classical molecular dynamics code (MetalWalls) dedicated to the modeling of electrochemical systems, and this leads to the development of the PiNNwall interface. Apart from the cases of chemically doped graphene and graphene oxide electrodes as shown in this study, the PiNNwall interface also allows us to probe polarized oxide surfaces in which both the proton charge and the electronic charge can coexist. Therefore, this work opens the door for modeling heterogeneous and complex electrode materials often found in energy storage systems.

Bruce-Vincent transference numbers from molecular dynamics simulations.

Transference number is a key design parameter for electrolyte materials used in electrochemical energy storage systems. However, the determination of the true transference number from experiments is rather demanding. On the other hand, the Bruce-Vincent method is widely used in the lab to approximately measure transference numbers of polymer electrolytes, which becomes exact in the limit of infinite dilution. Therefore, theoretical formulations to treat the Bruce-Vincent transference number and the true transference number on an equal footing are clearly needed. Here, we show how the Bruce-Vincent transference number for concentrated electrolyte solutions can be derived in terms of the Onsager coefficients, without involving any extrathermodynamic assumptions. By demonstrating it for the case of poly(ethylene oxide)-lithium bis(trifluoromethane)sulfonimide system, this work opens the door to calibrating molecular dynamics (MD) simulations via reproducing the Bruce-Vincent transference number and using MD simulations as a predictive tool for determining the true transference number.

Transference Number in Polymer Electrolytes: Mind the Reference-Frame Gap.

The transport coefficients, in particular the transference number, of electrolyte solutions are important design parameters for electrochemical energy storage devices. The recent observation of negative transference numbers in PEO-LiTFSI under certain conditions has generated much discussion about its molecular origins, by both experimental and theoretical means. However, one overlooked factor in these efforts is the importance of the reference frame (RF). This creates a non-negligible gap when comparing experiment and simulation because the fluxes in the experimental measurements of transport coefficients and in the linear response theory used in the molecular dynamics simulation are defined in different RFs. In this work, we show that, by applying a proper RF transformation, a much improved agreement between experimental and simulation results can be achieved. Moreover, it is revealed that the anion mass and the anion-anion correlation, rather than ion aggregates, play a crucial role for the reported negative transference numbers.

Training algorithm matters for the performance of neural network potential: A case study of Adam and the Kalman filter optimizers.

One hidden yet important issue for developing neural network potentials (NNPs) is the choice of training algorithm. In this article, we compare the performance of two popular training algorithms, the adaptive moment estimation algorithm (Adam) and the extended Kalman filter algorithm (EKF), using the Behler-Parrinello neural network and two publicly accessible datasets of liquid water [Morawietz et al., Proc. Natl. Acad. Sci. U. S. A. 113, 8368-8373, (2016) and Cheng et al., Proc. Natl. Acad. Sci. U. S. A. 116, 1110-1115, (2019)]. This is achieved by implementing EKF in TensorFlow. It is found that NNPs trained with EKF are more transferable and less sensitive to the value of the learning rate, as compared to Adam. In both cases, error metrics of the validation set do not always serve as a good indicator for the actual performance of NNPs. Instead, we show that their performance correlates well with a Fisher information based similarity measure.

Molecular dynamics simulation of extension-induced crystallization of branched bimodal HDPE: Unraveling the effects of short-chain branches.

Bimodal HDPE models were designed for extension-induced crystallization imitating the architecture of industrial bimodal HDPE copolymerized with ethylene and 1-butene, 1-hexene, or 1-octene. Crystallites of bimodal HDPE experienced the emergence of precursors, shish nuclei, and lamellae. The compact conformation of branched polymers impeded the rolling-over, deposition, and folding of chains on the substrate, and thus the formation of nuclei and lamella. Moreover, this retardation was intensified with the rising branch density and length, causing a depression of crystallinity and an increment of tie-chains concentration. Besides, when branches were all located on long chains, the compact conformation enlarged the resistance to the disentanglement of main chains, thus relatively fewer branched long chains were involved in the precursors or nuclei, resulting in the attenuation of lamella formation. Furthermore, for ethyl branched polymers, the coexistent orthorhombic and monoclinic crystallites were built up, and a few expanded monoclinic cells occurred for butyl branches because of the larger butyl reeling into lamella, while hexagonal crystals were created for ethyl/1-hexyl copolymers because of cocrystallization. Additionally, relative to ethyl, larger butyl and hexyl were preferential to be repelled outside crystals to form tie-chains, and hexyl branched polymers acquired relatively fewer tie-chains because of hexagonal eutectoid.

Importance of the Ion-Pair Lifetime in Polymer Electrolytes.

Ion pairing is commonly considered as a culprit for the reduced ionic conductivity in polymer electrolyte systems. However, this simple thermodynamic picture should not be taken literally, as ion pairing is a dynamical phenomenon. Here we construct model poly(ethylene oxide)-bis(trifluoromethane)sulfonimide lithium salt systems with different degrees of ion pairing by tuning the solvent polarity and examine the relation between the cation-anion distinct conductivity σ+-d and the lifetime of ion pairs τ+- using molecular dynamics simulations. It is found that there exist two distinct regimes where σ+-d scales with 1/τ+- and τ+-, respectively, and the latter is a signature of longer-lived ion pairs that contribute negatively to the total ionic conductivity. This suggests that ion pairs are kinetically different depending on the solvent polarity, which renders the ion-pair lifetime highly important when discussing its effect on ion transport in polymer electrolyte systems.

Mass dose rates of particle-bound organic pollutants in the human respiratory tract: Implications for inhalation exposure and risk estimations.

To date, little is known about the effective doses of airborne particulate matter (PM) and PM-bound hazardous organic components to the human respiratory tract (HRT). In the light of this, here we provide particle mass dose rates (dose per hour of exposure) of PM and a suite of PM-bound hazardous organic compounds in the HRT for two population age groups (adults & children). More specifically, the mass dose rates of PM and PM-bound polycyclic aromatic hydrocarbons (PAHs), nitrated-PAH (NPAHs), polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs) and polybrominated diphenyl ethers (PBDEs) were estimated at two urban sites using a multiple path particle dosimetry model. We find that, in most cases, the total mass doses are following similar variations across sites and seasons as their ambient total concentrations, however their distribution in the HRT is a function of the particle size distributions and the physiological parameters of each age group. More specifically, the majority of the deposited mass of PM and all the chemical components investigated was accumulated in the upper airways instead of the lungs. We further show that children, due to their different physiology, are more susceptible and receive larger fraction of the total mass doses in the deepest parts of the lungs compared to the adults' group. Comparing the traditional method for estimating the inhalation risk, which is based on the ambient concentration of pollutants, and a modified version using the mass dose in the HRT, we find that the former may overestimate the reported risks. The results presented here provide a novel dataset composed by previously undetermined doses of hazardous airborne particulate organic components in the HRT and demonstrate that alternative health risk estimation approaches may capture some variabilities that are traditionally overlooked.

Mechanistic investigation of zinc-promoted silylation of phenylacetylene and chlorosilane: a combined experimental and computational study.

The zinc-promoted silylation method is of great importance to synthesize high-performance silicon-containing arylacetylene (PSA) resins in the industry. However, it is difficult to eliminate the accompanied by-product of terminal alkenes due to the lack of mechanistic understanding of the silylation. The initiation of zinc-promoted silylation is facilitated by the interaction between zinc and phenylacetylene. Our DFT calculations indicated that the intermolecular hydrogen transfer of phenylacetylene follows an ionic pathway, which generates a phenylacetylene anion and the corresponding alkene moieties on the zinc surface. The styrene by-product is observed in this stage, with its alkene moieties desorbing as radicals into the solvent under the high reaction temperature. Three possible intermediates of surface phenylacetylene anions were proposed including PhC[triple bond, length as m-dash]C-Zn, PhC[triple bond, length as m-dash]CZnCl, and (PhC[triple bond, length as m-dash]C)2Zn. These carbanion-zinc intermediates undergo an SN2 reaction with Me3SiCl to afford the alkynylsilane on the zinc surface, which is calculated to be the rate-determining step for the zinc-promoted silylation reaction.

Role of Viscosity in Deviations from the Nernst-Einstein Relation.

Deviations from the Nernst-Einstein relation are commonly attributed to ion-ion correlation and ion pairing. Despite the fact that these deviations can be quantified by either experimental measurements or molecular dynamics simulations, there is no rule of thumb to tell the extent of deviations. Here, we show that deviations from the Nernst-Einstein relation are proportional to the inverse viscosity by exploring the finite-size effect on transport properties under periodic boundary conditions. This conclusion is in accord with the established experimental results of ionic liquids.

PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials.

Atomic neural networks (ANNs) constitute a class of machine learning methods for predicting potential energy surfaces and physicochemical properties of molecules and materials. Despite many successes, developing interpretable ANN architectures and implementing existing ones efficiently are still challenging. This calls for reliable, general-purpose, and open-source codes. Here, we present a python library named PiNN as a solution toward this goal. In PiNN, we designed a new interpretable and high-performing graph convolutional neural network variant, PiNet, as well as implemented the established Behler-Parrinello neural network. These implementations were tested using datasets of isolated small molecules, crystalline materials, liquid water, and an aqueous alkaline electrolyte. PiNN comes with a visualizer called PiNNBoard to extract chemical insight "learned" by ANNs. It provides analytical stress tensor calculations and interfaces to both the atomic simulation environment and a development version of the Amsterdam Modeling Suite. Moreover, PiNN is highly modularized, which makes it useful not only as a standalone package but also as a chain of tools to develop and to implement novel ANNs. The code is distributed under a permissive BSD license and is freely accessible at https://github.com/Teoroo-CMC/PiNN/ with full documentation and tutorials.

Temperature effects on the ionic conductivity in concentrated alkaline electrolyte solutions.

Alkaline electrolyte solutions are important components in rechargeable batteries and alkaline fuel cells. As the ionic conductivity is thought to be a limiting factor in the performance of these devices, which are often operated at elevated temperatures, its temperature dependence is of significant interest. Here we use NaOH as a prototypical example of alkaline electrolytes, and for this system we have carried out reactive molecular dynamics simulations with an experimentally verified high-dimensional neural network potential derived from density-functional theory calculations. It is found that in concentrated NaOH solutions elevated temperatures enhance both the contributions of proton transfer to the ionic conductivity and deviations from the Nernst-Einstein relation. These findings are expected to be of practical relevance for electrochemical devices based on alkaline electrolyte solutions.

Dominant Effects of Short-Chain Branching on the Initial Stage of Nucleation and Formation of Tie Chains for Bimodal Polyethylene as Revealed by Molecular Dynamics Simulation.

The molecular mechanism of short-chain branching (SCB), especially the effects of methylene sequence length (MSL) and short-chain branching distribution (SCBD) on the initial stage of nucleation, the crystallization process, and particularly the tie chain formation process of bimodal polyethylene (BPE), were explored using molecular dynamics simulation. This work constructed two kinds of BPE models in accordance with commercial BPE pipe resins: SCB incorporated in the long chain or in the short chains. The initial stage of nucleation was determined by the MSL of the system, as the critical MSL for a branched chain to nucleate is about 60 CH2. SCB incorporated in the long chain led to a delay of the initial stage of nucleation relative to the case of SCB incorporated in the short chains. The increase of branch length could accelerate the delay to nucleation. The location of short chain relative to the long chain depended on the MSL of the short chain. As the MSL of the system decreased, the crystallinity decreased, while the tie chains concentration increased. The tie chains concentration of the BPE model with branches incorporated in the long chain was higher than that with branches incorporated in the short chain.

Molecular dynamics simulation of shish-kebab crystallization of polyethylene: Unraveling the effects of molecular weight distribution.

By means of molecular dynamics simulations, extensional flow was performed on five polyethylene models with different molecular weight distributions (MWDs) precisely designed in view of Grubbs, metallocene, Ziegler-Natta, and chromium-based catalysts, while ignoring the sequence distributions of short branches to shed light on the molecular mechanism of MWD on shish-kebab formation. The formation of shish-kebab crystallites can be divided into three stages: the emergence of precursors, evolution from precursors to shish nuclei, and the formation of lamellar crystallites. The results demonstrated that the precursors initiated from trans-rich segments with local order and minor crystallinity grew into large shish nuclei and eventually evolved into lamellae. There were more inconsecutively trans-state bonds occurring in long chains rather than in short chains, which promoted an easier transformation from precursors to shish nuclei. Therefore, broader MWDs make positive contributions to the formation of shish nuclei, increase the crystallization speed, and the generation of a more regular, compact, and thicker lamella with less tie molecule fractions, while the final crystallinity is independent of MWD.

A unified model of Grignard reagent formation.

Grignard reagents are among the most fundamental reagents in organic synthesis, yet studies have hitherto failed to fully explain the selectivity and kinetics of Grignard reagent formation (GRF). The present study provides new insights into the intermediates and pathways of GRF using density functional theory (DFT) calculations. Potential energy surfaces of RX dissociation along different directions reveal the origin of configuration retention of alkenyl and aromatic halides. Radical intermediates participate solely in the dissociation stage, and depend on the geometry of the reactant halide. Dissociation of organic halides yields stabilized surface anions, and the rest of the reaction is ionic in nature. MgX+/RMg+ were proposed as the key intermediates of Mg leaving from the surface in the self-activation of GRF, which explains the accelerated kinetics upon addition of RMgX or MgX2. The intermediacy of the cations was supported by a simple electrochemical experiment. To the best of our knowledge, this is the first unified ionic model (I-model) developed for resolving the controversial issues of GRF.

Molecular dynamics study of the isothermal crystallization mechanism of polyethylene chain: the combined effects of chain length and temperature.

A molecular level understanding of the polyethylene (PE) crystallization process was elucidated by molecular dynamics simulation of three states, with varying chain length and temperature. The process can be classified into the following three states: (1) nucleation controlled state, (2) competitive state of crystal growth process and new nuclei formation, and (3) crystal growth controlled state, which could be quantified by the evolution of nuclei number. With increasing chain length, two phenomena occur: the single crystallization mechanism changes from state (1) to (3), and the crystal size increases while the b/a axial ratio in the lateral surface decreases. These changes can be explained from a thermodynamic point of view, in that the van der Waals (vdW) interaction per CH2 unit is strengthened and more nucleation sites are generated for longer chain. Size effect (meaning different surface fractions when the chain collapses into a globule) was an important factor determining vdW energy per unit and the crystallization states of a single PE chain. On the other hand, the crystallization states were independent of chain length for short chains systems with the same size effect. In both conditions, a long chain generates multi-crystal domains, and a short chain prefers a single crystal domain. Our results not only provide molecular level evidence for crystallization states but also clarify the influence of chain length on the crystallization process.