scholarly journals Fast Fluoride Ion Conduction in Molecular Cation-Containing Compounds, NH4(Mg1-xLix)F3-x and (NH4)2(Mg1-xLix)F4-x

2021 ◽  
Author(s):  
Kota Motohashi ◽  
Yosuke Matsukawa ◽  
Takashi Nakamura ◽  
Yuta Kimura ◽  
Yoshiharu Uchimoto ◽  
...  
Keyword(s):  
Material Design ◽  
Fluoride Ion ◽  
Ion Conduction ◽  
Molecular Cation ◽  
Ion Conductivities ◽  
New Material ◽  
High Fluoride ◽  
Host Cation

Abstract Aiming development of the fast anion conductors, we proposed a new material design using flexible molecular cation as a host cation, and demonstrated it with fluoride ion conduction in NH4(Mg1-xLix)F3-x and (NH4)2(Mg1-xLix)F4-x. Relatively high fluoride ion conductivities of 4.8×10-5 S cm-1 and 8.4×10-6 S cm-1 were achieved at 323 K in (NH4)2(Mg0.85Li0.15)F3.85 and NH4(Mg0.9Li0.1)F2.9, respectively. Our findings suggest molecular cation-containing compounds can be attractive material groups for fast anion conductors.

High fluoride ion conduction and conductivity maxima in the glassy system PbF2MnF2Pb(PO3)2

1987 ◽  
Vol 24 (3) ◽  
pp. 253-257 ◽  
Author(s):  
A.R. Kulkarni ◽  
H.G.K. Sundar ◽  
C.A. Angell
Keyword(s):  
Fluoride Ion ◽  
Glassy System ◽  
Ion Conduction ◽  
High Fluoride

High fluoride-ion conductivity and fluoride-ion conductor−insulator transition in fluorinated hexagonal boron nitride

2021 ◽  
Vol 21 ◽  
pp. 100523
Author(s):  
Tsuyoshi Takami ◽  
Takashi Saito ◽  
Takashi Kamiyama ◽  
Katsumi Kawahara ◽  
Toshiharu Fukunaga ◽  
...  
Keyword(s):  
Boron Nitride ◽  
Hexagonal Boron Nitride ◽  
Insulator Transition ◽  
Ion Conductivity ◽  
Fluoride Ion ◽  
Ion Conductor ◽  
High Fluoride

scholarly journals Machine Learning-Based Detection of Graphene Defects with Atomic Precision

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Bowen Zheng ◽  
Grace X. Gu
Keyword(s):  
Machine Learning ◽  
Material Design ◽  
Thermal Vibration ◽  
Single Atom ◽  
Complex Data ◽  
Alternative Approach ◽  
Atomic Precision ◽  
Data Driven Approach ◽  
New Material ◽  
Domain Discretization

AbstractDefects in graphene can profoundly impact its extraordinary properties, ultimately influencing the performances of graphene-based nanodevices. Methods to detect defects with atomic resolution in graphene can be technically demanding and involve complex sample preparations. An alternative approach is to observe the thermal vibration properties of the graphene sheet, which reflects defect information but in an implicit fashion. Machine learning, an emerging data-driven approach that offers solutions to learning hidden patterns from complex data, has been extensively applied in material design and discovery problems. In this paper, we propose a machine learning-based approach to detect graphene defects by discovering the hidden correlation between defect locations and thermal vibration features. Two prediction strategies are developed: an atom-based method which constructs data by atom indices, and a domain-based method which constructs data by domain discretization. Results show that while the atom-based method is capable of detecting a single-atom vacancy, the domain-based method can detect an unknown number of multiple vacancies up to atomic precision. Both methods can achieve approximately a 90% prediction accuracy on the reserved data for testing, indicating a promising extrapolation into unseen future graphene configurations. The proposed strategy offers promising solutions for the non-destructive evaluation of nanomaterials and accelerates new material discoveries.

Neutron diffraction stufy of the high-fluoride-ion conductor, PbSnF4, prepared under an HF atmosphere

1994 ◽  
Vol 70-71 ◽  
pp. 253-258 ◽  
Author(s):  
R KANNO ◽  
K OHNO ◽  
H IZUMI ◽  
Y KAWAMOTO ◽  
T KAMIYAMA ◽  
...  
Keyword(s):  
Neutron Diffraction ◽  
Fluoride Ion ◽  
Ion Conductor ◽  
High Fluoride

scholarly journals Recent progress on exploring exceptionally high and anisotropic H+/OH− ion conduction in two-dimensional materials

2018 ◽  
Vol 9 (1) ◽  
pp. 33-43 ◽  
Author(s):  
Pengzhan Sun ◽  
Renzhi Ma ◽  
Takayoshi Sasaki
Keyword(s):  
Recent Progress ◽  
2D Materials ◽  
Two Dimensional ◽  
Ion Conduction ◽  
Recent Advances ◽  
Ion Conductivities ◽  
Two Dimensional Materials

An overview of recent advances in measuring and understanding the exceptionally high and anisotropic H+/OH− ion conductivities of representative 2D materials.

scholarly journals The Attitude of Economic Students and Lecturers toward Economic English Material Based on Shariah Economy System

2017 ◽  
Vol 8 (4) ◽  
pp. 697
Author(s):  
Syamsul Una ◽  
Djamiah Husain ◽  
Abd. Halim
Keyword(s):  
Survey Research ◽  
Teaching And Learning ◽  
Positive Attitude ◽  
Material Design ◽  
Learning Material ◽  
New Material ◽  
Academic Year ◽  
Economy System

This research aimed to investigate Economic students and lecturers’ attitude toward economic English material based on shariah economy system. The material was the new material design that combined economic English in general and shariah economy concept in a teaching and learning material. This research is survey research. It was held at Economy Faculty of Dayanu Ikhsanuddin University Baubau Indonesia in 2015/2016 academic year. This research was limited to analyze both Economic students and lecturers’ attitude toward economic English material based on shariah economy system. The Participants of the study were 100 Economic students and 20 Economic lecturers. The instruments used were questionnaire and interview. All participants were invited to respond to questionnaires. And they then participated in follow-up interviews. The results of the study showed that the main score of students’ attitude was 42.24 and lecturers’ attitude was 41.50. From the main above indicated that both Economic students and lecturers had positive attitude toward economic English material based on shariah economy system.

scholarly journals Development of a Material Design Space for 4D-Printed Bio-Inspired Hygroscopically Actuated Bilayer Structures with Unequal Effective Layer Widths

Biomimetics ◽  
2021 ◽  
Vol 6 (4) ◽  
pp. 58
Author(s):  
Friederike Krüger ◽  
Rebecca Thierer ◽  
Yasaman Tahouni ◽  
Renate Sachse ◽  
Dylan Wood ◽  
...  
Keyword(s):  
Design Space ◽  
Solution Space ◽  
Material Design ◽  
Material Behavior ◽  
Beam Deflection ◽  
Fused Filament Fabrication ◽  
Young’S Moduli ◽  
New Material ◽  
Linear Material ◽  
Production Errors

(1) Significance of geometry for bio-inspired hygroscopically actuated bilayer structures is well studied and can be used to fine-tune curvatures in many existent material systems. We developed a material design space to find new material combinations that takes into account unequal effective widths of the layers, as commonly used in fused filament fabrication, and deflections under self-weight. (2) For this purpose, we adapted Timoshenko’s model for the curvature of bilayer strips and used an established hygromorphic 4D-printed bilayer system to validate its ability to predict curvatures in various experiments. (3) The combination of curvature evaluation with simple, linear beam deflection calculations leads to an analytical solution space to study influences of Young’s moduli, swelling strains and densities on deflection under self-weight and curvature under hygroscopic swelling. It shows that the choice of the ratio of Young’s moduli can be crucial for achieving a solution that is stable against production errors. (4) Under the assumption of linear material behavior, the presented development of a material design space allows selection or design of a suited material combination for application-specific, bio-inspired bilayer systems with unequal layer widths.

Nanoscale element behavior in a continuum

2020 ◽  
Vol 27 (4) ◽  
pp. 1033-1041
Author(s):  
Sungsook Ahn ◽  
Sang Joon Lee
Keyword(s):  
Thin Sheet ◽  
Material Design ◽  
Point Of View ◽  
Model Systems ◽  
Internal Source ◽  
Soft Condensed Matter ◽  
Stimuli Responsive ◽  
Electrical Devices ◽  
New Material ◽  
Line Patterns

Patterns in materials are not just decoration but also important for function. In view of this, the dynamics of patterning procedures in materials has been investigated as an important developmental procedure. In this study, nanoscale components in a continuum are traced in terms of natural patterning procedures. Externally applied compressive or extensive forces to an elastic thin sheet commonly induce an orientated lateral line pattern. From a nanoscale element point of view, the dynamics of natural arrangements, forming anisotropic patterns in preference to isotropy, still remains unclear. In this study, new developmental procedures for line patterns are suggested by stimuli-responsive viscoelastic nanocomposite network model systems. Forces originating from an internal source without directional orientation generate lines in preference to isotropic patterns. With repeated, non-oriented (or isotropic) and self-modulated strain variations, stress is accumulated to drive anisotropic orientations and further lines. The anisotropic elemental arrangement is justified by the equilibrium between the short-range attraction and long-range repulsion from a bottom-up viewpoint. This study suggests a new material design methodology that is useful for electrical devices, biomedical devices and other patterned soft condensed matter in conjunction with line patterns typically generated in a broad range of viscoelastic materials.

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