Atomic-scale modeling of radiation damage by SAS

JOM ◽  
1996 ◽  
Vol 48 (12) ◽  
pp. 38-41 ◽  
Author(s):  
H. L. Heinisch
Keyword(s):  
Radiation Damage ◽  
Atomic Scale ◽  
Scale Modeling

Atomic-scale modeling of crack branching in oxide glass

2021 ◽  
pp. 117098
Author(s):  
Jian Luo ◽  
Binghui Deng ◽  
K. Deenamma Vargheese ◽  
Adama Tandia ◽  
Steven E. DeMartino ◽  
...  
Keyword(s):  
Atomic Scale ◽  
Oxide Glass ◽  
Crack Branching ◽  
Scale Modeling

Interaction of gas molecules with crystalline polymer separation membranes: Atomic-scale modeling and first-principles calculations

2011 ◽  
Vol 384 (1-2) ◽  
pp. 176-183 ◽  
Author(s):  
Yanting Wang ◽  
Sergey N. Rashkeev ◽  
John R. Klaehn ◽  
Christopher J. Orme ◽  
Eric S. Peterson
Keyword(s):  
First Principles ◽  
Crystalline Polymer ◽  
Atomic Scale ◽  
First Principles Calculations ◽  
Separation Membranes ◽  
Scale Modeling ◽  
Gas Molecules ◽  
Polymer Separation

Renormalization Plus Convolution Method for Atomic-Scale Modeling of Electrical and Thermal Transport in Nanowires

Nano Letters ◽  
2008 ◽  
Vol 8 (12) ◽  
pp. 4205-4209 ◽  
Author(s):  
Chumin Wang ◽  
Fernando Salazar ◽  
Vicenta Sánchez
Keyword(s):  
Thermal Transport ◽  
Atomic Scale ◽  
Scale Modeling ◽  
Convolution Method

scholarly journals Machine Learning at the Atomic Scale

2019 ◽  
Vol 73 (12) ◽  
pp. 972-982 ◽  
Author(s):  
Félix Musil ◽  
Michele Ceriotti
Keyword(s):  
Machine Learning ◽  
Short Review ◽  
Atomic Scale ◽  
Structure Property ◽  
Computationally Efficient ◽  
Property Relations ◽  
Scale Modeling ◽  
Phase Systems ◽  
Scale Properties ◽  
Physical Phenomena

Statistical learning algorithms are finding more and more applications in science and technology. Atomic-scale modeling is no exception, with machine learning becoming commonplace as a tool to predict energy, forces and properties of molecules and condensed-phase systems. This short review summarizes recent progress in the field, focusing in particular on the problem of representing an atomic configuration in a mathematically robust and computationally efficient way. We also discuss some of the regression algorithms that have been used to construct surrogate models of atomic-scale properties. We then show examples of how the optimization of the machine-learning models can both incorporate and reveal insights onto the physical phenomena that underlie structure–property relations.

Atomic-Scale Modeling of the Annihilation of Jogged Screw Dislocation Dipoles

1999 ◽  
Vol 578 ◽  
Author(s):  
T. Vegge ◽  
O. B. Pedersen ◽  
T. Leffers ◽  
K. W. Jacobsen
Keyword(s):  
Molecular Dynamics ◽  
Screw Dislocation ◽  
Atomic Scale ◽  
Atomistic Simulations ◽  
Elastic Band ◽  
Screw Dislocations ◽  
Scale Modeling ◽  
Band Method

AbstractUsing atomistic simulations we investigate the annihilation of screw dislocation dipoles in Cu. In particular we determine the influence of jogs on the annihilation barrier for screw dislocation dipoles. The simulations involve energy minimizations, molecular dynamics, and the Nudged Elastic Band method. We find that jogs on screw dislocations substantially reduce the annihilation barrier, hence leading to an increase in the minimum stable dipole height.

Organic Functionalization of Metal Oxide Surfaces: An Atomic Scale Modeling Approach

2013 ◽  
Vol 5 (11) ◽  
pp. 1147-1154 ◽  
Author(s):  
C. Arcangeli ◽  
I. Borriello ◽  
G. Gianese ◽  
M. Celino ◽  
P. Morales
Keyword(s):  
Metal Oxide ◽  
Atomic Scale ◽  
Oxide Surfaces ◽  
Metal Oxide Surfaces ◽  
Organic Functionalization ◽  
Modeling Approach ◽  
Scale Modeling

Atomic-Scale Modeling of Nanoconstrictions

2004 ◽  
Vol 40 (4) ◽  
pp. 2143-2145 ◽  
Author(s):  
S. Mukherjee ◽  
D. Litvinov ◽  
S. Khizroev
Keyword(s):  
Atomic Scale ◽  
Scale Modeling
Sign in / Sign up

Export Citation Format

Share Document