生成一个KPOINTS收敛性测试脚本
时间: 2024-10-15 09:09:52 浏览: 4
在DFT(Density Functional Theory)计算中,KPOINTS文件用于指定电子波函数在晶格点集上采样的密度,对最终结果的准确性和计算效率有很大影响。对于KPOINTS的收敛性测试,通常需要编写一个脚本来迭代改变K点网格,比较各步的结果,直到达到预期的精度标准。这里是一个简单的Python脚本示例,基于VASP(Vienna Ab initio Simulation Package)的kpoints convergence testing:
```python
# 导入必要的库
from ase.io import read
from vaspkit.kpoints import get_kpoint_convergence
# 读取结构文件
structure = read('POSCAR')
# 设置起始和结束的K点网格,以及步长
start_grid = [5, 5, 5]
end_grid = [30, 30, 30]
step = 5
# 定义测试函数
def test_kpoints(kpoints):
# 运行vasp并获取总能量
energy = run_vasp_with_kpoints(structure, kpoints)
return energy
# 开始测试
for i in range(start_grid[0], end_grid[0] + step, step):
for j in range(start_grid[1], end_grid[1] + step, step):
for k in range(start_grid[2], end_grid[2] + step, step):
num_points = (i, j, k)
converged_energy = test_kpoints(num_points)
print(f"Grid size: {num_points}, Energy: {converged_energy}")
#
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