scholarly journals Direct H-He chemical association in superionic FeO2H2He at Deep-Earth conditions

2021 ◽  
Author(s):  
Jurong Zhang ◽  
Hanyu Liu ◽  
Yanming Ma ◽  
Changfeng Chen
Keyword(s):  
Ab Initio Molecular Dynamics ◽  
Quaternary Compound ◽  
Fundamental Interest ◽  
Structure Search ◽  
Wide Range ◽  
Celestial Bodies ◽  
Formation And Evolution ◽  
Dynamics Simulations ◽  
Chemical Association ◽  
Promising Avenue

Abstract Hydrogen and helium were known to play crucial roles in geological and astrophysical environments; however, they are inert toward each other across wide pressure-temperature (P-T). Given their prominent presence and influence on the formation and evolution of celestial bodies, it is of fundamental interest to explore the nature of interactions between hydrogen and helium. Using an advanced crystal structure search method, we have identified a quaternary compound FeO2H2He stabilized in a wide range of P-T conditions. Ab initio molecular dynamics simulations further reveal a novel superionic state of FeO2H2He hosting liquid-like diffusive hydrogen in the FeO2He sublattice, creating a conducive environment for H-He chemical association, at P-T conditions corresponding to the Earth's lowest mantle regions. This surprising chemically facilitated coalescence of otherwise immiscible molecular species highlights a promising avenue for exploring this long-sought but hitherto unattainable state of matter. This finding raises strong prospects for exotic H-He mixtures inside Earth and possibly also in other astronomical bodies.

scholarly journals Unsupervised discovery of solid-state lithium ion conductors

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Ying Zhang ◽  
Xingfeng He ◽  
Zhiqian Chen ◽  
Qiang Bai ◽  
Adelaide M. Nolan ◽  
...  
Keyword(s):  
Solid State ◽  
Unsupervised Learning ◽  
Lithium Ion ◽  
Functional Materials ◽  
Ab Initio Molecular Dynamics ◽  
Property Data ◽  
Wide Range ◽  
Dynamics Simulations ◽  
Lithium Ion Conductors ◽  
Ion Conductors

AbstractAlthough machine learning has gained great interest in the discovery of functional materials, the advancement of reliable models is impeded by the scarcity of available materials property data. Here we propose and demonstrate a distinctive approach for materials discovery using unsupervised learning, which does not require labeled data and thus alleviates the data scarcity challenge. Using solid-state Li-ion conductors as a model problem, unsupervised materials discovery utilizes a limited quantity of conductivity data to prioritize a candidate list from a wide range of Li-containing materials for further accurate screening. Our unsupervised learning scheme discovers 16 new fast Li-conductors with conductivities of 10−4–10−1 S cm−1 predicted in ab initio molecular dynamics simulations. These compounds have structures and chemistries distinct to known systems, demonstrating the capability of unsupervised learning for discovering materials over a wide materials space with limited property data.

General Trend of Negative Transference Number in Li Salt/Ionic Liquid Mixtures

2019 ◽  
Author(s):  
Nicola Molinari ◽  
Jonathan P. Mailoa ◽  
Boris Kozinsky
Keyword(s):  
Ionic Liquid ◽  
Transference Number ◽  
Liquid Mixtures ◽  
Single Linkage ◽  
Self Diffusion ◽  
Wide Range ◽  
Single Linkage Cluster ◽  
Concentrated Solution ◽  
The One ◽  
Dynamics Simulations

We show that strong cation-anion interactions in a wide range of lithium-salt/ionic liquid mixtures result in a negative lithium transference number, using molecular dynamics simulations and rigorous concentrated solution theory. This behavior fundamentally deviates from the one obtained using self-diffusion coefficient analysis and agrees well with experimental electrophoretic NMR measurements, which accounts for ion correlations. We extend these findings to several ionic liquid compositions. We investigate the degree of spatial ionic coordination employing single-linkage cluster analysis, unveiling asymmetrical anion-cation clusters. Additionally, we formulate a way to compute the effective lithium charge that corresponds to and agrees well with electrophoretic measurements and show that lithium effectively carries a negative charge in a remarkably wide range of chemistries and concentrations. The generality of our observation has significant implications for the energy storage community, emphasizing the need to reconsider the potential of these systems as next generation battery electrolytes.<br>

scholarly journals Polymer cyclization for the emergence of hierarchical nanostructures

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Chaojian Chen ◽  
Manjesh Kumar Singh ◽  
Katrin Wunderlich ◽  
Sean Harvey ◽  
Colette J. Whitfield ◽  
...  
Keyword(s):  
Self Assembly ◽  
Three Dimensional ◽  
Hierarchical Structures ◽  
Structural Similarity ◽  
Vital Role ◽  
Nanomaterial Synthesis ◽  
Wide Range ◽  
Linear Poly ◽  
Polymer Folding ◽  
Dynamics Simulations

AbstractThe creation of synthetic polymer nanoobjects with well-defined hierarchical structures is important for a wide range of applications such as nanomaterial synthesis, catalysis, and therapeutics. Inspired by the programmability and precise three-dimensional architectures of biomolecules, here we demonstrate the strategy of fabricating controlled hierarchical structures through self-assembly of folded synthetic polymers. Linear poly(2-hydroxyethyl methacrylate) of different lengths are folded into cyclic polymers and their self-assembly into hierarchical structures is elucidated by various experimental techniques and molecular dynamics simulations. Based on their structural similarity, macrocyclic brush polymers with amphiphilic block side chains are synthesized, which can self-assemble into wormlike and higher-ordered structures. Our work points out the vital role of polymer folding in macromolecular self-assembly and establishes a versatile approach for constructing biomimetic hierarchical assemblies.

scholarly journals Proton Transport Mechanism and Pathways in the Superprotonic Phase of M3H(AO4)2 Solid Acids from Ab Initio Molecular Dynamics Simulations

2021 ◽  
Author(s):  
Boris Merinov ◽  
Sergey Morozov
Keyword(s):  
Molecular Dynamics ◽  
Ab Initio ◽  
Proton Transport ◽  
Transport Mechanism ◽  
Solid Acids ◽  
Ab Initio Molecular Dynamics ◽  
Theoretical Studies ◽  
Dynamics Simulations ◽  
Experimental And Theoretical Studies ◽  
Superprotonic Phase

The proton transport mechanism in superprotonic phases of solid acids is a subject of experimental and theoretical studies for a number of years. Despite this, details of the mechanism still...

scholarly journals OH− and H3O+ Diffusion in Model AEMs and PEMs at Low Hydration: Insights from Ab Initio Molecular Dynamics

Membranes ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 355
Author(s):  
Tamar Zelovich ◽  
Mark E. Tuckerman
Keyword(s):  
Molecular Dynamics ◽  
Fuel Cell ◽  
Ab Initio ◽  
Cost Effective ◽  
Clean Energy ◽  
Proton Exchange ◽  
Ab Initio Molecular Dynamics ◽  
Anion Exchange Membranes ◽  
Diffusion Mechanisms ◽  
Dynamics Simulations

Fuel cell-based anion-exchange membranes (AEMs) and proton exchange membranes (PEMs) are considered to have great potential as cost-effective, clean energy conversion devices. However, a fundamental atomistic understanding of the hydroxide and hydronium diffusion mechanisms in the AEM and PEM environment is an ongoing challenge. In this work, we aim to identify the fundamental atomistic steps governing hydroxide and hydronium transport phenomena. The motivation of this work lies in the fact that elucidating the key design differences between the hydroxide and hydronium diffusion mechanisms will play an important role in the discovery and determination of key design principles for the synthesis of new membrane materials with high ion conductivity for use in emerging fuel cell technologies. To this end, ab initio molecular dynamics simulations are presented to explore hydroxide and hydronium ion solvation complexes and diffusion mechanisms in the model AEM and PEM systems at low hydration in confined environments. We find that hydroxide diffusion in AEMs is mostly vehicular, while hydronium diffusion in model PEMs is structural. Furthermore, we find that the region between each pair of cations in AEMs creates a bottleneck for hydroxide diffusion, leading to a suppression of diffusivity, while the anions in PEMs become active participants in the hydronium diffusion, suggesting that the presence of the anions in model PEMs could potentially promote hydronium diffusion.

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