Uncovering Local Correlations in Polymer Electrolytes by X-ray Scattering and Molecular Dynamics Simulations

Force Fields for High Concentration Aqueous KOH Solutions and Zincate Ions

Motivated by increasing interest in electrochemical devices that include highly alkaline electrolytes, we investigated two force fields for potassium hydroxide (KOH) at high concentrations in water. The "FNB" model uses the SPC/E water model, while the "FHM" model uses the TIP4P/2005 water model. We also developed parameters to describe zincate ions in these solutions. The density and viscosity of KOH using the FHM model are in better agreement with experiment than the values from the FNB model. Comparing the properties of the zincate solutions to the available experimental data, we find that both force fields agree reasonably well, although the FHM parameters give a better prediction of the viscosity. The developed force field parameters can be used in future simulations of zincate/KOH solutions in combination with other species of interest.

Backbone and Side Group Interchain Correlations Govern Wide-Angle X-ray Scattering of Poly(3-hexylthiophene)

Identifying the origin of scattering from polymer materials is crucial to infer structural features that can relate to functional properties. Here, we use our recently developed virtual-site coarse graining to accelerate atomistic simulations and show how various molecular features govern wide-angle X-ray scattering from a conjugated polymer, poly(3-hexylthiophene) (P3HT). The efficient molecular dynamics simulations can represent the structure and capture the emergence of crystalline order from amorphous melts upon cooling while retaining atomistic details of chain configurations. The scattering extracted from simulations shows good agreement with wide-angle X-ray scattering experiments. Amorphous P3HT exhibits broad scattering peaks: a high-q peak from interchain side-group correlations and a low-q peak from interchain backbone-backbone correlations. During amorphous to crystalline phase transitions, the distance between backbones along the side-group direction increases because of lack of interdigitation in the crystalline phase. Scattering from π-π stacking emerges only after crystallization takes place. Intrachain correlations contribute negligibly to the scattering from the amorphous and crystalline phases.

Solvation Structure of Methanol-in-Salt Electrolyte Revealed by Small-Angle X-ray Scattering and Simulations

The solvation structure of water-in-salt electrolytes was thoroughly studied, and two competing structures─anion solvated structure and anion network─were well-defined in recent publications. To further reveal the solvation structure in those highly concentrated electrolytes, particularly the influence of solvent, methanol was chosen as the solvent for this proposed study. In this work, small-angle X-ray scattering, small-angle neutron scattering, Fourier-transform infrared spectroscopy, and Raman spectroscopy were utilized to obtain the global and local structural information. With the concentration increment, the anion network formed by TFSI- became the dominant structure. Meanwhile, the hydrogen bonds among methanol were interrupted by the TFSI- anion and formed a new connection with them. Molecular dynamic simulations with two different force fields (GAFF and OPLS-AA) are tested, and GAFF agreed with synchrotron small-angle X-ray scattering/wide-angle X-ray scattering (SAXS/WAXS) results well and provided insightful information about molecular/ion scale solvation structure. This article not only deepens the understanding of the solvation structure in highly concentrated solutions, but more importantly, it provides additional strong evidence for utilizing SAXS/WAXS to validate molecular dynamics simulations.

Ion Solvation Cage Structure in Polymer Electrolytes Determined by Combining X-ray Scattering and Simulations

Solvation structure plays a crucial role in determining ion transport in electrolytes. We combine wide-angle X-ray scattering (WAXS) and molecular dynamics (MD) simulation to identify the solvation cage structure in two polymer electrolytes, poly(pentyl malonate) (PPM) and poly(ethylene oxide) (PEO) mixed with lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt. As the salt concentration increases, the amorphous halo in the pure polymers is augmented by an additional peak at low scattering angles. The location of this peak and its height are, however, different in the two electrolytes. By decoupling the total intensity into species contributions and mapping scattering peaks to position-space molecular correlations, we elucidate distinct origins of the additional peak. In PPM, it arises from long-range charge-ordering between solvation cages and anions, while in PEO it is dominated by correlations between anions surrounding the same cage. TFSI- ions are present in the PPM solvation cage, but expelled from the PEO solvation cage.

Molecular Origin of High Cation Transference in Mixtures of Poly(pentyl malonate) and Lithium Salt

The rational development of new electrolytes for lithium batteries rests on the molecular-level understanding of ion transport. We use molecular dynamics simulations to study the differences between a recently developed promising polymer electrolyte based on poly(pentyl malonate) (PPM) and the well-established poly(ethylene oxide) (PEO) electrolyte; LiTFSI is the salt used in both electrolytes. Cation transference is calculated by tracking the correlated motion of different species. The PEO solvation cage primarily contains 1 chain, resulting in strong correlations between Li⁺ and the polymer. In contrast, the PPM solvation cage contains multiple chains, resulting in weak correlations between Li⁺ and the polymer. This difference results in a high cation transference in PPM relative to PEO. Our comparative study suggests possible designs of polymer electrolytes with ion transport properties better than both PPM and PEO. The solvation cage of such a hypothetical polymer electrolyte is proposed based on insights from our simulations.

Decoding Polymer Architecture Effect on Ion Clustering, Chain Dynamics, and Ionic Conductivity in Polymer Electrolytes

Poly(ethylene oxide) (PEO)-based polymer electrolytes are a promising class of materials for use in lithium-ion batteries due to their high ionic conductivity and flexibility. In this study, the effects of polymer architecture including linear, star, and hyperbranched and salt (lithiumbis(trifluoromethanesulfonyl)imide (LiTFSI)) concentration on the glass transition (T _g), microstructure, phase diagram, free volume, and bulk viscosity, all of which play a significant role in determining the ionic conductivity of the electrolyte, have been systematically studied for PEO-based polymer electrolytes. The branching of PEO widens the liquid phase toward lower salt concentrations, suggesting decreased crystallization and improved ion coordination. At high salt loadings, ion clustering is common for all electrolytes, yet the cluster size and distribution appear to be strongly architecture-dependent. Also, the ionic conductivity is maximized at a salt concentration of [Li/EO ≈ 0.085] for all architectures, and the highly branched polymers displayed as much as three times higher ionic conductivity (with respect to the linear analogue) for the same total molar mass. The architecture-dependent ionic conductivity is attributed to the enhanced free volume measured by positron annihilation lifetime spectroscopy. Interestingly, despite the strong architecture dependence of ionic conductivity, the salt addition in the highly branched architectures results in accelerated yet similar monomeric friction coefficients for these polymers, offering significant potential toward decoupling of conductivity from segmental dynamics of polymer electrolytes, leading to outstanding battery performance.

Elucidating the Molecular Origins of the Transference Number in Battery Electrolytes Using Computer Simulations

The rate at which rechargeable batteries can be charged and discharged is governed by the selective transport of the working ions through the electrolyte. Conductivity, the parameter commonly used to characterize ion transport in electrolytes, reflects the mobility of both cations and anions. The transference number, a parameter introduced over a century ago, sheds light on the relative rates of cation and anion transport. This parameter is, not surprisingly, affected by cation-cation, anion-anion, and cation-anion correlations. In addition, it is affected by correlations between the ions and neutral solvent molecules. Computer simulations have the potential to provide insights into the nature of these correlations. We review the dominant theoretical approaches used to predict the transference number from simulations by using a model univalent lithium electrolyte. In electrolytes of low concentration, one can obtain a quantitative model by assuming that the solution is made up of discrete ion-containing clusters-neutral ion pairs, negatively and positively charged triplets, neutral quadruplets, and so on. These clusters can be identified in simulations using simple algorithms, provided their lifetimes are sufficiently long. In concentrated electrolytes, more clusters are short-lived and more rigorous approaches that account for all correlations are necessary to quantify transference. Elucidating the molecular origin of the transference number in this limit remains an unmet challenge.

Microscopic Insight into the Structure-Processing-Property Relationships of Core-Shell Structured Dialcohol Cellulose Nanoparticles

In the quest to develop sustainable and environmentally friendly materials, cellulose is a promising alternative to synthetic polymers. However, native cellulose, in contrast to many synthetic polymers, cannot be melt-processed with traditional techniques because, upon heating, it degrades before it melts. One way to improve the thermoplasticity of cellulose, in the form of cellulose fibers, is through chemical modification, for example, to dialcohol cellulose fibers. To better understand the importance of molecular interactions during melt processing of such modified fibers, we undertook a molecular dynamics study of dialcohol cellulose nanocrystals with different degrees of modification. We investigated the structure of the nanocrystals as well as their interactions with a neighboring nanocrystal during mechanical shearing, Our simulations showed that the stress, interfacial stiffness, hydrogen-bond network, and cellulose conformations during shearing are highly dependent on the degree of modification, water layers between the crystals, and temperature. The melt processing of dialcohol cellulose with different degrees of modification and/or water content in the samples was investigated experimentally by fiber extrusion with water used as a plasticizer. The melt processing was easier when increasing the degree of modification and/or water content in the samples, which was in agreement with the conclusions derived from the molecular modeling. The measured friction between the two crystals after the modification of native cellulose to dialcohol cellulose, in some cases, halved (compared to native cellulose) and is also reduced with increasing temperature. Our results demonstrate that molecular modeling of modified nanocellulose fibers can provide fundamental information on the structure-property relationships of these materials and thus is valuable for the development of new cellulose-based biomaterials.

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.