Microscopic interactions in CuGeO 3 and organic Spin-Peierls systems deduced from their pretransitional lattice fluctuations

2001 ◽  
Vol 20 (3) ◽  
pp. 321-333 ◽  
Author(s):  
J.-P. Pouget
Keyword(s):  
Microscopic Interactions ◽  
Lattice Fluctuations

scholarly journals Graph neural networks for an accurate and interpretable prediction of the properties of polycrystalline materials

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Minyi Dai ◽  
Mehmet F. Demirel ◽  
Yingyu Liang ◽  
Jia-Mian Hu
Keyword(s):  
Neural Network ◽  
Network Architecture ◽  
Polycrystalline Materials ◽  
Feed Forward Neural Network ◽  
Microscopic Interactions ◽  
Physical Interactions ◽  
Graph Neural Networks ◽  
Individual Grains ◽  
Physical Features ◽  
Machine Learning Models

AbstractVarious machine learning models have been used to predict the properties of polycrystalline materials, but none of them directly consider the physical interactions among neighboring grains despite such microscopic interactions critically determining macroscopic material properties. Here, we develop a graph neural network (GNN) model for obtaining an embedding of polycrystalline microstructure which incorporates not only the physical features of individual grains but also their interactions. The embedding is then linked to the target property using a feed-forward neural network. Using the magnetostriction of polycrystalline Tb0.3Dy0.7Fe2 alloys as an example, we show that a single GNN model with fixed network architecture and hyperparameters allows for a low prediction error of ~10% over a group of remarkably different microstructures as well as quantifying the importance of each feature in each grain of a microstructure to its magnetostriction. Such a microstructure-graph-based GNN model, therefore, enables an accurate and interpretable prediction of the properties of polycrystalline materials.

Lattice fluctuations and inhomogeneous charge states of high-Tcsuperconductors

2002 ◽  
Vol 15 (3) ◽  
pp. 439-445 ◽  
Author(s):  
N L Saini ◽  
H Oyanagi ◽  
Ziyu Wu ◽  
A Bianconi
Keyword(s):  
Charge States ◽  
Lattice Fluctuations

scholarly journals Quantum lattice fluctuations and luminescence inC60

1993 ◽  
Vol 47 (7) ◽  
pp. 3975-3978 ◽  
Author(s):  
Barry Friedman ◽  
Kikuo Harigaya
Keyword(s):  
Quantum Lattice ◽  
Lattice Fluctuations

Microscopic interactions between ivermectin and key human and viral proteins involved in SARS-CoV-2 infection

2021 ◽  
Author(s):  
Antonio Francés-Monerris ◽  
Cristina Garcia Iriepa ◽  
Isabel Iriepa ◽  
Cécilia Hognon ◽  
Tom Miclot ◽  
...  
Keyword(s):  
Viral Proteins ◽  
Infection Cycle ◽  
Chemical Structures ◽  
Microscopic Interactions

The identification of suitable chemical structures able to effectively bind to the human/viral proteins involved in the SARS-CoV-2 infection cycle is crucial to fight this pathogen. Here we conduct a...

Using Quantum Agent-Based Simulation to Model Social Networks

2011 ◽  
pp. 42-54
Author(s):  
C. Bisconti ◽  
A. Corallo ◽  
M. De Maggio ◽  
F. Grippa ◽  
S. Totaro
Keyword(s):  
Social Networks ◽  
Quantum Mechanics ◽  
Quantum Physics ◽  
Business Processes ◽  
Social Dynamics ◽  
Social Systems ◽  
Many Body ◽  
Agent Based ◽  
Microscopic Interactions ◽  
The Many

This research aims to apply models extracted from the many-body quantum mechanics to describe social dynamics. It is intended to draw macroscopic characteristics of organizational communities starting from the analysis of microscopic interactions with respect to the node model. In this chapter, the authors intend to give an answer to the following question: which models of the quantum physics are suitable to represent the behaviour and the evolution of business processes? The innovative aspects of the project are related to the application of models and methods of the quantum mechanics to social systems. In order to validate the proposed mathematical model, the authors intend to define an open-source platform able to model nodes and interactions within a network, to visualize the macroscopic results through a digital representation of the social networks.

Hydration States of Cholinium Phosphate-Type Ionic Liquids as a Function of Water Content

2019 ◽  
Vol 72 (5) ◽  
pp. 392 ◽  
Author(s):  
Yohsuke Nikawa ◽  
Seiji Tsuzuki ◽  
Hiroyuki Ohno ◽  
Kyoko Fujita
Keyword(s):  
Ionic Liquids ◽  
Water Content ◽  
Alkyl Chain ◽  
Hydroxyl Group ◽  
Water Molecules ◽  
Hydroxyl Groups ◽  
Ion Structure ◽  
Activity Measurements ◽  
Microscopic Interactions ◽  
Dynamics Simulations

We investigated the hydration states of cholinium phosphate-type ionic liquids (ILs) in relation to ion structure, focusing on the influence of the hydroxyl group of the cation and the alkyl chain length of the anion. Water activity measurements provided information on the macroscopic hydration states of the hydrated ILs, while NMR measurements and molecular dynamics simulations clearly showed the microscopic interactions and coordination of the water molecules. The hydrogen bonding networks in these ILs were influenced by the anion structure and water content, and the mobility of water molecules was influenced by the number of hydroxyl groups in the cation and anion.

Metallic states induced by quantum lattice fluctuations

2019 ◽  
Vol 99 (3) ◽  
Author(s):  
Norikazu Tomita ◽  
Akira Takahashi
Keyword(s):  
Quantum Lattice ◽  
Lattice Fluctuations
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