Treffer: MC-Cluster: a Monte Carlo simulation for nanoparticle

Title:
MC-Cluster: a Monte Carlo simulation for nanoparticle
Contributors:
Sharapa, Dmitry I., Sireci, Enrico, Plessow, Philipp N.
Publisher Information:
Karlsruhe Institute of Technology
Publication Year:
2025
Document Type:
dataset
File Description:
application/x-tar
Language:
unknown
DOI:
10.35097/pqmqcrq4h47eucz5
Rights:
info:eu-repo/semantics/openAccess ; Other ; GNU Affero General Public License.
Accession Number:
edsbas.FBC55C40
Database:
BASE

Weitere Informationen

This Monte-Carlo simulation simulates nanoparticles at different temperatures. By applying a simulated annealing protocol, the user can find the most stable, entropically realistic structure of a nanoparticle. ; Simple energy model The energy input is a simple mapping of coordination number to energy in eV. The input can be a direct mapping of every coordination number to a distinct energy. Alternatively, a linear energy increase with coordination number can be used, which speeds up the simulation. High performance By using a simple energy model, the simulation can perform up to 10^11 iterations in one day. With a linear coordination number to energy mapping it can reach up to 10^12 iterations in one day. This allows for the simulation of larger nanoparticles. Multithreaded The code allows for as many parallel simulations as cores available on the computing node. This enables the user to obtain a statistically relevant ensemble of low-energy structures. Adding parallel simulations has negligible increase in required RAM. Track the Simulation using the .xyz-format Throughout the simulation it is possible to track the energy and save snapshots of the particle. Furthermore the particle with the lowest energy will be saved as an .xyz-file. Support The simulation can simulate the effect a support can have on the particle. A monometallic support can be created by giving a vector that is orthogonal to the support pane. Usage Requirements Rust Python used version 3.11.10 ASE used version: ase-3.22.1 Install from git git clone git@github.com:T-136/MC-Cluster.git Build the binary Build the program with: cargo build -r After the build step is complete the compiled program can be found in your project folder under "./target/release/mc". Run the simulation ./target/release/MC-Cluster -a Pt,1000 --support Al,1,1,1 -t 1000 -i 1e7 -r 0-1 --e-cn ./example_data/cn_input_example.json -o 9/10 -g ./example_data/303030-grid --support-e 0 --xyz-trajectory Use "-h" or "--help" to see the available flags and how to use them. -s, ...