The blog ran on blogofile for many years, and that software is long past maintained. The 623 posts written with it are still at their original addresses, with their original look, in the archive. New posts live here under /posts/.

Posts are Quarto documents (.qmd) or Jupyter notebooks (.ipynb). Code runs on my machine when I render, and the results are saved with the post, so the site builds without re-running anything.

A small example

Here is the first-order reaction in a batch reactor, , solved numerically and compared with the analytical solution.

import numpy as np
from scipy.integrate import solve_ivp

k = 0.23   # 1/min
Ca0 = 2.0  # mol/L

sol = solve_ivp(lambda t, Ca: -k * Ca, (0, 20), [Ca0], dense_output=True)
t = np.linspace(0, 20, 200)
Ca = sol.sol(t)[0]

print(f"C_A(20 min) = {Ca[-1]:.4f} mol/L (exact {Ca0 * np.exp(-k * 20):.4f})")

C_A(20 min) = 0.0201 mol/L (exact 0.0201)

import matplotlib.pyplot as plt

fig, ax = plt.subplots(figsize=(6, 3.5))
ax.plot(t, Ca, label="solve_ivp")
ax.plot(t[::15], Ca0 * np.exp(-k * t[::15]), "o", label="exact")
ax.set_xlabel("t (min)")
ax.set_ylabel("$C_A$ (mol/L)")
ax.legend()
plt.tight_layout()

Figure 1 shows the two agree. Equations, figures and cross-references all come from Quarto, and code blocks have a copy button.

A notebook in posts/<slug>/index.ipynb is a post. Quarto renders it from the outputs already saved in the notebook and does not run it, so code that needs a GPU, a DFT code or a license still works here. Write the post in org-mode and export it with ox-ipynb, or write it in Jupyter directly.

import numpy as np

# Arrhenius rate constants
Ea = 75e3   # J/mol
A = 1e13    # 1/s
R = 8.314
T = np.array([300, 400, 500, 600])
k = A * np.exp(-Ea / (R * T))
for Ti, ki in zip(T, k):
    print(f'{Ti} K: k = {ki:.3e} 1/s')

300 K: k = 8.727e-01 1/s
400 K: k = 1.606e+03 1/s
500 K: k = 1.461e+05 1/s
600 K: k = 2.954e+06 1/s

The rate constant goes up by more than six orders of magnitude between 300 K and 600 K.