diff --git a/papers/joss/design_plots.py b/papers/joss/design_plots.py
index 50a958518..9b70bed8c 100644
--- a/papers/joss/design_plots.py
+++ b/papers/joss/design_plots.py
@@ -1,5 +1,12 @@
-# A script to generate design optimisation plots for the JOSS paper.
+"""
+A script to generate design optimisation plots for the JOSS paper.
 
+NOTE: The design optimisation plots that appear in Figure 8 of the paper were
+unfortunately generated with a bug in simulator._create_experiment_simulation().
+PR 857 fixed and replaced this function with simulator.create_simulation() in
+January 2026. The two design plots in figures/individual and one in
+figures/combined were updated in PR 966, July 2026.
+"""
 
 import numpy as np
 import pybamm
@@ -43,7 +50,6 @@
         - Parameter("Positive electrode active material volume fraction"),
         "Cell mass [kg]": pybop.pybamm.cell_mass(),
     },
-    check_already_exists=False,
 )
 
 # Fitting parameters
diff --git a/papers/joss/figures/combined/design.pdf b/papers/joss/figures/combined/design.pdf
index 988e7a4d3..bc339c7f9 100644
Binary files a/papers/joss/figures/combined/design.pdf and b/papers/joss/figures/combined/design.pdf differ
diff --git a/papers/joss/figures/individual/design_gravimetric.pdf b/papers/joss/figures/individual/design_gravimetric.pdf
index de0dddbe7..923269ded 100644
Binary files a/papers/joss/figures/individual/design_gravimetric.pdf and b/papers/joss/figures/individual/design_gravimetric.pdf differ
diff --git a/papers/joss/figures/individual/design_prediction.pdf b/papers/joss/figures/individual/design_prediction.pdf
index 15237a3b4..17ec36188 100644
Binary files a/papers/joss/figures/individual/design_prediction.pdf and b/papers/joss/figures/individual/design_prediction.pdf differ
diff --git a/papers/joss/param_plots.py b/papers/joss/param_plots.py
index 975217908..6db6eecca 100644
--- a/papers/joss/param_plots.py
+++ b/papers/joss/param_plots.py
@@ -1,5 +1,6 @@
-# A script to generate parameterisation plots for the JOSS paper.
-
+"""
+A script to generate parameterisation plots for the JOSS paper.
+"""
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -455,6 +456,7 @@
             optim.optimiser.b1 = 0.85
             optim.optimiser.b2 = 0.9
             optim.optimiser.lam = 0.005
+            optim.optimiser._alpha = np.asarray([1.0, 0.22222222])  # noqa: SLF001  # retain the initial step size used for paper
         if optimiser is pybop.GradientDescent:
             optim.optimiser.set_learning_rate(eta=[11, 4.5])