如何在反应引导中绘制极区图？

在反应引导中，绘制极区图是一种常用的可视化方法，用于解释和表达反应性能。下面介绍如何在反应引导中绘制极区图。

步骤

1. 导入必要的模块。

import numpy as np
import matplotlib.pyplot as plt

2. 准备反应数据。

reactants = ['CH4', 'CO2', 'H2O']
products = ['CO', 'H2']
rates = [1.0, 0.5, 0.25, 0.1, 0.05]

3. 计算反应级别。

n_reactants = len(reactants)
n_products = len(products)
levels = [n_products - n_reactants + np.sum(coefficients) for coefficients in coefficients_array]

4. 计算反应速率常数。

k = 0.01
temperature = 500
multiplier = np.exp(-1.0 / (8.314 * temperature))
rate_constants = [k * multiplier ** level for level in levels]

5. 计算极区图坐标。

x = [np.sum([reactants.index(reactant) * coefficients[i] for i, reactant in enumerate(reactants)]) for coefficients in coefficients_array]
y = [np.sum([products.index(product) * coefficients[i] for i, product in enumerate(products)]) for coefficients in coefficients_array]

6. 绘制极区图。

fig = plt.figure(figsize=(5, 5))
ax = fig.add_subplot(111, projection='polar')

for i in range(len(rates)):
    ax.plot([y[i], y[i]], [0, -x[i]], color='k')
    ax.plot([y[i], y[i]+2*np.pi/3], [-x[i], -x[i]-2*np.pi/3], color='k')
    ax.plot([y[i], y[i]-2*np.pi/3], [-x[i], -x[i]+2*np.pi/3], color='k')

ax.set_ylim(-np.pi/2, 0)
ax.set_yticks([-np.pi/2, -np.pi/3, -np.pi/6, 0])
ax.set_yticklabels([r'$\frac{\pi}{2}$', r'$\frac{\pi}{3}$', r'$\frac{\pi}{6}$', r'$0$'])
ax.set_xticks(np.linspace(0, 2*np.pi, 6, endpoint=False))
ax.set_xticklabels(products+reactants)

plt.show()

结语

绘制极区图可以更直观地反映反应性能，这对于研究反应机理以及优化反应过程具有重要意义。以上就是在反应引导中绘制极区图的方法，希望对你有所帮助。