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.

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.

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.

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.

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).

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.

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.

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 and the lifetime of ion pairs τ using molecular dynamics simulations.

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.

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.

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.

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.

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.

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 CH.

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.

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.

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.