Graph Dynamical Networks for Unsupervised Learning of Atomic Scale Dynamics in Materials

Understanding the dynamical processes that govern the performance of functional materials is essential for the design of next generation materials to tackle global energy and environmental challenges. Many of these processes involve the dynamics of individual atoms or small molecules in condensed phases, e.g. lithium ions in electrolytes, water molecules in membranes, molten atoms at interfaces, etc., which are difficult to understand due to the complexity of local environments. In this work, we develop graph dynamical networks, an unsupervised learning approach for understanding atomic scale dynamics in arbitrary phases and environments from molecular dynamics simulations. We show that important dynamical information can be learned for various multi-component amorphous material systems, which is difficult to obtain otherwise. With the large amounts of molecular dynamics data generated everyday in nearly every aspect of materials design, this approach provides a broadly useful, automated tool to understand atomic scale dynamics in material systems.Comment: 25 + 7 pages, 5 + 3 figure

Computational studies of ion transport in polymer electrolytes

Improving ionic conductivity and lithium mobility in polymer electrolytes is important for their practical use for battery electrolytes. In this study, a combination of molecular dynamics and Monte Carlo simulations was used to bring insight into lithium ion transport in poly(ethylene oxide) (PEO) with plasticizers and also next to alumina solid surface doped with lithium salt. The simulations were performed using a moderately high molecular weight polymer (Mn = 10,000 g/mol) at an EO:Li ratio of 15. For the plasticized system, the PEO with LiN(CF3SO 2)2 (LiTFSI) was mixed with 10 wt% plasticizers that included either cyclic ethylene carbonate (EC) or propylene carbonate (PC). Comparisons with an array of experiments showed a slight underestimation of the compared ionic conductivity, but within a factor of two, at most. With the addition of EC and PC plasticizers, the ionic conductivity increased a moderate degree with most of the increase due to faster TFSI anion motion, but not lithium cation. It was found that propylene carbonate formed complexes with the TFSI anion, in which lithium was an intermediary, creating moderate sized clusters. This formation allowed enhanced diffusion of lithium ions bound with TFSI ions, but this formation was offset by slower diffusion for lithium ions bound with ethylene oxide oxygens. Ethylene carbonate, on the other hand, showed no significant complexing with TFSI anion. The formation of this cluster, therefore, may be an avenue for increasing lithium diffusion but would likely require a plasticizer with stronger interactions with lithium than the carbonates studied. We also examined the influence of both acidic and basic alumina surfaces on the structure and lithium mobility in PEO with LiClO4 salts. The results showed the surface interacted with lithium salt anion in the acidic case via hydrogen bonding, which essentially freezes the lithium salt anion movement at the surface, yet a modest enhancement in lithium ion mobility was observed at low temperature

Computer simulations of single-ion BAB triblock copolymer electrolyte material for Lithium-polymer batteries

http://tartu.ester.ee/record=b2693136~S1*es

Diffusion and migration in polymer electrolytes

Mixtures of neutral polymers and lithium salts have the potential to serve as electrolytes in next-generation rechargeable Li-ion batteries. The purpose of this review is to expose the delicate interplay between polymer-salt interactions at the segmental level and macroscopic ion transport at the battery level. Since complete characterization of this interplay has only been completed in one system: mixtures of poly(ethylene oxide) and lithium bis(trifluoromethanesulfonyl)imide (PEO/LiTFSI), we focus on data obtained from this system. We begin with a discussion of the activity coefficient, followed by a discussion of six different diffusion coefficients: the Rouse motion of polymer segments is quantified by Dseg, the self-diffusion of cations and anions is quantified by Dself,+ and Dself,−, and the build-up of concentration gradients in electrolytes under an applied potential is quantified by Stefan-Maxwell diffusion coefficients, D0+, D0-, and D+-. The Stefan-Maxwell diffusion coefficients can be used to predict the velocities of the ions at very early times after an electric field is applied across the electrolyte. The surprising result is that D0- is negative in certain concentration windows. A consequence of this finding is that at these concentrations, both cations and anions are predicted to migrate toward the positive electrode at early times. We describe the controversies that surround this result. Knowledge of the Stefan-Maxwell diffusion coefficients enable prediction of the limiting current. We argue that the limiting current is the most important characteristic of an electrolyte. Excellent agreement between theoretical and experimental limiting current is seen in PEO/LiTFSI mixtures. What sequence of monomers that, when polymerized, will lead to the highest limiting current remains an important unanswered question. It is our hope that the approach presented in this review will guide the development of such polymers

Recent Advances in Post-Lithium Ion Batteries

Lithium ion batteries (LIBs) are efficient storage systems for portable electronic devices, electrical power grids, and electrified transportation due to their high-energy density and low maintenance requirements. After their launch into the market in 1990s, they immediately became the dominant technology for portable systems. The development of LiBs for electric drive vehicles has been, in contrast, rather incremental. There are several critical issues, such as an energy density, system safety, cost, and environmental impact of the battery production processes, that remain challenges in the automotive field. In order to strengthen the LiB’s competitiveness and affordability in vehicle technology, the necessity of game-changer batteries is urgent. Recently, a novel approach going beyond Li batteries has become rapidly established. Several new chemistries have been proposed, leading to better performances in terms of energy density, long-life storage capability, safety, and sustainability. However, several challenges, such as a thorough understanding of mechanisms, cell design, long-term durability, and safety issues, have not yet been fully addressed. This book collects some recent developments and emerging trends in the field of “post-lithium” batteries, covering both fundamental and applied aspects of next-generation batterie

Thermal Conductivity of Carbon Nanotubes and their Polymer Nanocomposites: A Review

Thermally conductive polymer composites offer new possibilities for replacing metal parts in several applications, including power electronics, electric motors and generators, heat exchangers, etc., thanks to the polymer advantages such as light weight, corrosion resistance and ease of processing. Current interest to improve the thermal conductivity of polymers is focused on the selective addition of nanofillers with high thermal conductivity. Unusually high thermal conductivity makes carbon nanotube (CNT) the best promising candidate material for thermally conductive composites. However, the thermal conductivities of polymer/CNT nanocomposites are relatively low compared with expectations from the intrinsic thermal conductivity of CNTs. The challenge primarily comes from the large interfacial thermal resistance between the CNT and the surrounding polymer matrix, which hinders the transfer of phonon dominating heat conduction in polymer and CNT. This article reviews the status of worldwide research in the thermal conductivity of CNTs and their polymer nanocomposites. The dependence of thermal conductivity of nanotubes on the atomic structure, the tube size, the morphology, the defect and the purification is reviewed. The roles of particle/polymer and particle/particle interfaces on the thermal conductivity of polymer/CNT nanocomposites are discussed in detail, as well as the relationship between the thermal conductivity and the micro- and nano-structure of the composite

Kinetically Controlled Synthesis of Triblock Copolymer Stabilized Gold Nanoparticles

Concerns for the environmental and economic impact of organic solvents in gold nanoparticle synthesis have motivated the search for more environmentally benign alternatives. One viable approach is the synthesis of AuNPs from tetrachloroauric(III) acid (HAuCl4) using triblock copolymers (TBPs). However, a major challenge of using TBPs is the heterogeneous nature of the formed nanocrystals. Establishing control over AuNP size and shape requires a detailed mechanistic understanding of precursor reduction and nanoparticle growth. By using mixtures of TBPs (L31 and F68), a more flexible method to tune AuNP size and shape is demonstrated. This is achieved by adjusting the TBP/Au(III) ratio and the concentrations of seed citrate-stabilized AuNPs. Kinetic models are used to explain why L31 inhibits the rate of AuNP formation and growth. Experimental evidence of sigmoidal growth kinetics, early time bimodal gold nanoparticle size distributions, and polycrystallinity suggest that aggregative AuNP growth is an important mechanism