scholarly journals Pushing the boundaries of lithium battery research with atomistic modelling on different scales

2021 ◽  
Author(s):  
Lucy Morgan ◽  
Michael Mercer ◽  
Arihant Bhandari ◽  
Chao Peng ◽  
Mazharul M. Islam ◽  
...  
Keyword(s):  
Experimental Data ◽  
Electrode Materials ◽  
Predictive Accuracy ◽  
Computational Modelling ◽  
Critical Discussion ◽  
Structure Property ◽  
Design Strategies ◽  
Diverse Range ◽  
Atomistic Modelling ◽  
Atomistic Models

Abstract Computational modelling is a vital tool in the research of batteries and their component materials. Atomistic models are key to building truly physics-based models of batteries and form the foundation of the multiscale modelling chain, leading to more robust and predictive models. These models can be applied to fundamental research questions with high predictive accuracy. For example, they can be used to predict new behaviour not currently accessible by experiment, for reasons of cost, safety, or throughput. Atomistic models are useful for quantifying and evaluating trends in experimental data, explaining structure-property relationships, and informing materials design strategies and libraries. In this review, we showcase the most prominent atomistic modelling methods and their application to electrode materials, liquid and solid electrolyte materials, and their interfaces, highlighting the diverse range of battery properties that can be investigated. Furthermore, we link atomistic modelling to experimental data and higher scale models such as continuum and control models. We also provide a critical discussion on the outlook of these materials and the main challenges for future battery research.

(Invited) Improve Electrodes' Electrochemical Performance for HER and OER By Hydrogenation Treatment

2018 ◽  
Vol MA2018-01 (31) ◽  
pp. 1840-1840
Author(s):  
Xiaobo Chen
Keyword(s):  
Hydrogen Production ◽  
Large Scale ◽  
Electrode Materials ◽  
Scale Production ◽  
Structure Property ◽  
Large Scale Production ◽  
Property Performance ◽  
Splitting Process ◽  
New Discovery ◽  
Hydrogenation Treatment

Hydrogen production through electrolysis has been regarded as one of the most promising solutions for large-scale production of clean fuels. However, most electrodes have large overpotentials in the HER and OER reactions during the water splitting process. Many approaches and methods have been developed to enhance the electrodes' performance. Here, we would like to present our studies on the hydrogenation of various electrode materials for HER and OER applications. We aim to reveal the structure-property-performance relationship for those electrodes after hydrogenation treatment. We wish our work could provide useful information and will be honored if our work can inspire new discovery and finding in the related fields to advance our understanding and technologies for efficient hydrogen production through electrolysis.

scholarly journals Design Strategies toward Enhancing the Performance of Organic Electrode Materials in Metal-Ion Batteries

Chem ◽  
2018 ◽  
Vol 4 (12) ◽  
pp. 2786-2813 ◽  
Author(s):  
Yong Lu ◽  
Qiu Zhang ◽  
Lin Li ◽  
Zhiqiang Niu ◽  
Jun Chen
Keyword(s):  
Metal Ion ◽  
Electrode Materials ◽  
Design Strategies ◽  
Organic Electrode

scholarly journals Identification of different oxygen species in oxide nanostructures with 17O solid-state NMR spectroscopy

2015 ◽  
Vol 1 (1) ◽  
pp. e1400133 ◽  
Author(s):  
Meng Wang ◽  
Xin-Ping Wu ◽  
Sujuan Zheng ◽  
Li Zhao ◽  
Lei Li ◽  
...  
Keyword(s):  
Active Sites ◽  
Density Functional ◽  
Strong Dependence ◽  
Critical Role ◽  
Oxygen Species ◽  
Structure Property ◽  
Diverse Range ◽  
Oxygen Ions ◽  
Surface Sites ◽  
Nanostructured Oxides

Nanostructured oxides find multiple uses in a diverse range of applications including catalysis, energy storage, and environmental management, their higher surface areas, and, in some cases, electronic properties resulting in different physical properties from their bulk counterparts. Developing structure-property relations for these materials requires a determination of surface and subsurface structure. Although microscopy plays a critical role owing to the fact that the volumes sampled by such techniques may not be representative of the whole sample, complementary characterization methods are urgently required. We develop a simple nuclear magnetic resonance (NMR) strategy to detect the first few layers of a nanomaterial, demonstrating the approach with technologically relevant ceria nanoparticles. We show that the 17O resonances arising from the first to third surface layer oxygen ions, hydroxyl sites, and oxygen species near vacancies can be distinguished from the oxygen ions in the bulk, with higher-frequency 17O chemical shifts being observed for the lower coordinated surface sites. H217O can be used to selectively enrich surface sites, allowing only these particular active sites to be monitored in a chemical process. 17O NMR spectra of thermally treated nanosized ceria clearly show how different oxygen species interconvert at elevated temperature. Density functional theory calculations confirm the assignments and reveal a strong dependence of chemical shift on the nature of the surface. These results open up new strategies for characterizing nanostructured oxides and their applications.

scholarly journals From atomistic interfaces to dendritic patterns

2018 ◽  
Vol 376 (2113) ◽  
pp. 20170210 ◽  
Author(s):  
P. K. Galenko ◽  
D. V. Alexandrov
Keyword(s):  
Computational Modelling ◽  
Experimental Tests ◽  
Theoretical Models ◽  
Boundary Integral ◽  
Transport Processes ◽  
Atomic Scale ◽  
Theme Issue ◽  
Two Phase ◽  
Field Methods ◽  
Atomistic Modelling

Transport processes around phase interfaces, together with thermodynamic properties and kinetic phenomena, control the formation of dendritic patterns. Using the thermodynamic and kinetic data of phase interfaces obtained on the atomic scale, one can analyse the formation of a single dendrite and the growth of a dendritic ensemble. This is the result of recent progress in theoretical methods and computational algorithms calculated using powerful computer clusters. Great benefits can be attained from the development of micro-, meso- and macro-levels of analysis when investigating the dynamics of interfaces, interpreting experimental data and designing the macrostructure of samples. The review and research articles in this theme issue cover the spectrum of scales (from nano- to macro-length scales) in order to exhibit recently developing trends in the theoretical analysis and computational modelling of dendrite pattern formation. Atomistic modelling, the flow effect on interface dynamics, the transition from diffusion-limited to thermally controlled growth existing at a considerable driving force, two-phase (mushy) layer formation, the growth of eutectic dendrites, the formation of a secondary dendritic network due to coalescence, computational methods, including boundary integral and phase-field methods, and experimental tests for theoretical models—all these themes are highlighted in the present issue. This article is part of the theme issue ‘From atomistic interfaces to dendritic patterns’.

scholarly journals A structural and kinetic survey of GH5_4 endoglucanases reveals determinants of broad substrate specificity and opportunities for biomass hydrolysis

2020 ◽  
Vol 295 (51) ◽  
pp. 17752-17769
Author(s):  
Evan M. Glasgow ◽  
Elias I. Kemna ◽  
Craig A. Bingman ◽  
Nicole Ing ◽  
Kai Deng ◽  
...  
Keyword(s):  
Substrate Specificity ◽  
Protein Design ◽  
Plant Biomass ◽  
Catalytic Efficiency ◽  
Structural Features ◽  
Glycoside Hydrolases ◽  
Design Strategies ◽  
Biomass Hydrolysis ◽  
Diverse Range ◽  
Broad Specificity

Broad-specificity glycoside hydrolases (GHs) contribute to plant biomass hydrolysis by degrading a diverse range of polysaccharides, making them useful catalysts for renewable energy and biocommodity production. Discovery of new GHs with improved kinetic parameters or more tolerant substrate-binding sites could increase the efficiency of renewable bioenergy production even further. GH5 has over 50 subfamilies exhibiting selectivities for reaction with β-(1,4)–linked oligo- and polysaccharides. Among these, subfamily 4 (GH5_4) contains numerous broad-selectivity endoglucanases that hydrolyze cellulose, xyloglucan, and mixed-linkage glucans. We previously surveyed the whole subfamily and found over 100 new broad-specificity endoglucanases, although the structural origins of broad specificity remained unclear. A mechanistic understanding of GH5_4 substrate specificity would help inform the best protein design strategies and the most appropriate industrial application of broad-specificity endoglucanases. Here we report structures of 10 new GH5_4 enzymes from cellulolytic microbes and characterize their substrate selectivity using normalized reducing sugar assays and MS. We found that GH5_4 enzymes have the highest catalytic efficiency for hydrolysis of xyloglucan, glucomannan, and soluble β-glucans, with opportunistic secondary reactions on cellulose, mannan, and xylan. The positions of key aromatic residues determine the overall reaction rate and breadth of substrate tolerance, and they contribute to differences in oligosaccharide cleavage patterns. Our new composite model identifies several critical structural features that confer broad specificity and may be readily engineered into existing industrial enzymes. We demonstrate that GH5_4 endoglucanases can have broad specificity without sacrificing high activity, making them a valuable addition to the biomass deconstruction toolset.

Comparing Predictive Accuracy and Computational Costs for Viscoelastic Modeling of Spinal Cord Tissues

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Nicole L. Ramo ◽  
Kevin L. Troyer ◽  
Christian M. Puttlitz
Keyword(s):  
Experimental Data ◽  
Spinal Cord ◽  
Mechanical Response ◽  
Predictive Accuracy ◽  
Material Model ◽  
Loading Conditions ◽  
Nonlinear Viscoelastic ◽  
Arbitrary Loading ◽  
Linear Viscoelastic ◽  
Viscoelastic Modeling

Abstract The constitutive equation used to characterize and model spinal tissues can significantly influence the conclusions from experimental and computational studies. Therefore, researchers must make critical judgments regarding the balance of computational efficiency and predictive accuracy necessary for their purposes. The objective of this study is to quantitatively compare the fitting and prediction accuracy of linear viscoelastic (LV), quasi-linear viscoelastic (QLV), and (fully) nonlinear viscoelastic (NLV) modeling of spinal-cord-pia-arachnoid-construct (SCPC), isolated cord parenchyma, and isolated pia-arachnoid-complex (PAC) mechanics in order to better inform these judgements. Experimental data collected during dynamic cyclic testing of each tissue condition were used to fit each viscoelastic formulation. These fitted models were then used to predict independent experimental data from stress-relaxation testing. Relative fitting accuracy was found not to directly reflect relative predictive accuracy, emphasizing the need for material model validation through predictions of independent data. For the SCPC and isolated cord, the NLV formulation best predicted the mechanical response to arbitrary loading conditions, but required significantly greater computational run time. The mechanical response of the PAC under arbitrary loading conditions was best predicted by the QLV formulation.

Structure property relationships in core-shell BaTiO3–LiF ceramics

1993 ◽  
Vol 8 (4) ◽  
pp. 871-879 ◽  
Author(s):  
C.A. Randall ◽  
S.F. Wang ◽  
D. Laubscher ◽  
J.P. Dougherty ◽  
W. Huebner
Keyword(s):  
Experimental Data ◽  
Dielectric Properties ◽  
Dielectric Property ◽  
Potential Application ◽  
Microstructural Development ◽  
Core Shell ◽  
Structure Property ◽  
The Core ◽  
Structure Property Relationships ◽  
Multilayer Capacitors

A sintering, microstructural development and dielectric property study of BaTiO3–LiF ceramics was performed to assess the potential application of low-fired multilayer capacitors. Not only does LiF allow for sintering below 1000 °C, it also allows for the manipulation of dielectric properties and interfaces within BaTiO3–LiF ceramics. Using mixing laws, a model of the dielectric properties of the core-shell microstructures is presented that agrees well with the observed experimental data.

scholarly journals Langasite Family Midinfrared Nonlinear Optical Oxide Materials: Structure, Property, and Applications

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Haichao Lan ◽  
Fei Liang ◽  
Zheshuai Lin ◽  
Haohai Yu ◽  
Huaijin Zhang ◽  
...  
Keyword(s):  
Experimental Data ◽  
Metal Oxides ◽  
High Performance ◽  
Nonlinear Optical ◽  
Damage Threshold ◽  
Laser Damage Threshold ◽  
Laser Damage ◽  
Oxide Materials ◽  
Structure Property ◽  
Nlo Materials

Midinfrared (IR) nonlinear optical (NLO) materials with high performance are vital in important technological applications in many civil and military fields. Very recently, langasite family compounds have attracted much attention due to their wide transparency to mid-IR region and ultrahigh laser damage threshold (LDT). In this brief review, three important compounds—LGS, LGN, and LGT—are investigated and analyzed based on available experimental data. The electrooptical (EO) Q-switch and mid-IR OPO applications are summarized in detail. Finally, promising search directions for new metal oxides that have good mid-IR NLO performances are discussed.

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