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
2021 ◽  
pp. 117098
Author(s):  
Jian Luo ◽  
Binghui Deng ◽  
K. Deenamma Vargheese ◽  
Adama Tandia ◽  
Steven E. DeMartino ◽  
...  

2019 ◽  
Vol 73 (12) ◽  
pp. 972-982 ◽  
Author(s):  
Félix Musil ◽  
Michele Ceriotti

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.


1999 ◽  
Vol 578 ◽  
Author(s):  
T. Vegge ◽  
O. B. Pedersen ◽  
T. Leffers ◽  
K. W. Jacobsen

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.


2013 ◽  
Vol 5 (11) ◽  
pp. 1147-1154 ◽  
Author(s):  
C. Arcangeli ◽  
I. Borriello ◽  
G. Gianese ◽  
M. Celino ◽  
P. Morales

2004 ◽  
Vol 40 (4) ◽  
pp. 2143-2145 ◽  
Author(s):  
S. Mukherjee ◽  
D. Litvinov ◽  
S. Khizroev
Keyword(s):  

2000 ◽  
Vol 61 (4) ◽  
pp. 2806-2811 ◽  
Author(s):  
M. Kaukonen ◽  
R. M. Nieminen

2011 ◽  
Vol 94 (7) ◽  
pp. 2225-2229 ◽  
Author(s):  
Simon C. Middleburgh ◽  
David C. Parfitt ◽  
Paul R. Blair ◽  
Robin W. Grimes

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