Activation Energy−Activation Volume Master Plots for Ion Transport Behavior in Polymer Electrolytes and Supercooled Molten Salts

2005 ◽  
Vol 109 (35) ◽  
pp. 16567-16570 ◽  
Author(s):  
Malcolm D. Ingram ◽  
Corrie T. Imrie ◽  
Zlatka Stoeva ◽  
Steven J. Pas ◽  
Klaus Funke ◽  
...  
Keyword(s):  
Activation Energy ◽  
Ion Transport ◽  
Polymer Electrolytes ◽  
Molten Salts ◽  
Activation Volume ◽  
Transport Behavior ◽  
Master Plots ◽  
Energy Activation

Dendrites in Solid‐State Batteries: Ion Transport Behavior, Advanced Characterization, and Interface Regulation

2021 ◽  
pp. 2003250
Author(s):  
Zhenjiang Yu ◽  
Xueyan Zhang ◽  
Chuankai Fu ◽  
Han Wang ◽  
Ming Chen ◽  
...  
Keyword(s):  
Solid State ◽  
Ion Transport ◽  
Advanced Characterization ◽  
Transport Behavior ◽  
Solid State Batteries

Activation energy for alkaline-earth ion transport in low alkali aluminoborosilicate glasses

2013 ◽  
Vol 102 (8) ◽  
pp. 082904 ◽  
Author(s):  
Priyanka Dash ◽  
Eugene Furman ◽  
Carlo G. Pantano ◽  
Michael T. Lanagan
Keyword(s):  
Activation Energy ◽  
Ion Transport ◽  
Alkaline Earth

Towards constraining Mars' thermal evolution using machine learning

2021 ◽  
Author(s):  
Siddhant Agarwal ◽  
Nicola Tosi ◽  
Pan Kessel ◽  
Sebastiano Padovan ◽  
Doris Breuer ◽  
...  
Keyword(s):  
Activation Energy ◽  
Enrichment Factor ◽  
Activation Volume ◽  
Initial Conditions ◽  
Thermal Evolution ◽  
Diffusion Creep ◽  
Dynamic Simulations ◽  
Mixture Density ◽  
Lithospheric Thickness ◽  
Mantle Temperature

<p>The thermal evolution of terrestrial planets depends strongly on several parameters and initial conditions that are poorly constrained. Often, direct or indirect observables from planetary missions such as elastic lithospheric thickness, crustal thickness and duration of volcanism are inverted to infer the unknown parameter values and initial conditions. The non-uniqueness and non-linearity of this inversion necessitates a probabilistic inversion framework. However, due to the expensive nature of forward dynamic simulations of thermal convection , Markov Chain Monte Carlo methods are rarely used. To address this shortcoming, some studies have recently shown the effectiveness of Mixture Density Networks (MDN) (Bishop 1995) in being able to approximate the posterior probability using only the dataset of simulations run prior to the inversion (Meier et al. 2007, de Wit et al. 2013, Käufl et al. 2016, Atkins et al. 2016).</p><p>Using MDNs, we systematically isolate the degree to which a parameter can be constrained using different “present-day” synthetic observables from 6130 simulations for a Mars-like planet. The dataset – generated using the mantle convection code GAIA (Hüttig et al. 2013)- is the same as that used by Agarwal et al. (2020) for a surrogate modelling study.</p><p>The loss function used to optimize the MDN (log-likelihood) provides a single robust quantity that can be used to measure how well a parameter can be constrained. We test different numbers and combinations of observables (heat flux at the surface and core-mantle boundary, radial contraction, melt produced, elastic lithospheric thickness, and duration of volcanism) to constrain the following parameters: reference viscosity, activation energy and activation volume of the diffusion creep rheology, an enrichment factor for radiogenic elements in the crust, and initial mantle temperature. If all observables are available, reference viscosity can be constrained to within 32% of its entire range (10<sup>19</sup>−10<sup>22</sup> Pa s), crustal enrichment factor (1−50) to within 15%, activation energy (10<sup>5</sup>−5×10<sup>5</sup> J mol-1 ) to within 80%, and initial mantle temperature (1600−1800K) to within 39%. The additional availability of the full present-day temperature profile or parts of it as an observable tightens the constraints further. The activation volume (4×10<sup>-6</sup> −10×10<sup>-6</sup>  m<sup>3</sup> mol<sup>-1</sup>) cannot be constrained and requires research into new observables in space and time, as well as fields other than just temperature. Testing different levels of uncertainty (simulated using Gaussian noise) in the observables, we found that constraints on different parameters loosen at different rates, with initial temperature being the most sensitive. Finally, we present how the marginal MDN proposed by Bishop (1995) can be modified to model the joint probability for all parameters, so that  the inter-parameter correlations and the associated degeneracy can be capture, thereby providing a more comprehensive picture of all the evolution scenarios that fit given observational constraints.</p>

Non-solvating, side-chain polymer electrolytes as lithium single-ion conductors: synthesis and ion transport characterization

2020 ◽  
Vol 11 (2) ◽  
pp. 461-471 ◽  
Author(s):  
Jiacheng Liu ◽  
Phillip D. Pickett ◽  
Bumjun Park ◽  
Sunil P. Upadhyay ◽  
Sara V. Orski ◽  
...  
Keyword(s):  
Ion Transport ◽  
Dielectric Relaxation ◽  
Polymer Electrolytes ◽  
Transport Mechanism ◽  
Lithium Ion ◽  
Side Chain ◽  
Chain Polymer ◽  
Single Ion Conductors ◽  
Ion Conductors

Non-solvating, side-chain polymer electrolytes with more dissociable pendent anion chemistries exhibit a dielectric relaxation dominated lithium ion transport mechanism.

scholarly journals Molecular Dynamics Study of Ion Transport in Polymer Electrolytes of All-Solid-State Li-Ion Batteries

Micromachines ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1012
Author(s):  
Takuya Mabuchi ◽  
Koki Nakajima ◽  
Takashi Tokumasu
Keyword(s):  
Molecular Dynamics ◽  
Solid State ◽  
Ion Transport ◽  
Polyethylene Oxide ◽  
Polymer Electrolytes ◽  
Li Ion Batteries ◽  
Transport Mechanisms ◽  
Li Ion ◽  
Dynamics Simulations ◽  
The Relationship

Atomistic analysis of the ion transport in polymer electrolytes for all-solid-state Li-ion batteries was performed using molecular dynamics simulations to investigate the relationship between Li-ion transport and polymer morphology. Polyethylene oxide (PEO) and poly(diethylene oxide-alt-oxymethylene), P(2EO-MO), were used as the electrolyte materials, and the effects of salt concentrations and polymer types on the ion transport properties were explored. The size and number of LiTFSI clusters were found to increase with increasing salt concentrations, leading to a decrease in ion diffusivity at high salt concentrations. The Li-ion transport mechanisms were further analyzed by calculating the inter/intra-hopping rate and distance at various ion concentrations in PEO and P(2EO-MO) polymers. While the balance between the rate and distance of inter-hopping was comparable for both PEO and P(2EO-MO), the intra-hopping rate and distance were found to be higher in PEO than in P(2EO-MO), leading to a higher diffusivity in PEO. The results of this study provide insights into the correlation between the nanoscopic structures of ion solvation and the dynamics of Li-ion transport in polymer electrolytes.

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