diff --git a/bind/G4Calo.py b/bind/G4Calo.py
index 07cf48e..a57e0b0 100644
--- a/bind/G4Calo.py
+++ b/bind/G4Calo.py
@@ -328,6 +328,27 @@ def _run_mini_batch(
     df = G4System.run_batch(nEvents, particleSpec, minEnergy_GeV, maxEnergy_GeV,"")
     return df
 
+def _run_mini_batch_silent(*args, **kwargs):
+    import sys
+    # Redirect stdout and stderr to silence the output
+    devnull = open(os.devnull, 'w')
+    original_stdout = sys.stdout
+    original_stderr = sys.stderr
+    sys.stdout = devnull
+    sys.stderr = devnull
+
+    try:
+        return _run_mini_batch(*args, **kwargs)  # Call your actual function
+    except Exception as e:
+        # Restore original stdout and stderr if an exception occurs
+        sys.stdout = original_stdout
+        sys.stderr = original_stderr
+        raise e
+    finally:
+        # Restore original stdout and stderr
+        sys.stdout = original_stdout
+        sys.stderr = original_stderr
+        devnull.close()
 
 
 def run_batch(
@@ -356,7 +377,7 @@ def run_batch(
 
     #use a multiprocessing pool to run the mini batches in parallel
     with multiprocessing.Pool(nCores) as pool:
-        dfs = pool.starmap(_run_mini_batch, [(gd, nevents[i], particleSpec, minEnergy_GeV, maxEnergy_GeV, i) for i in range(nCores)])
+        dfs = pool.starmap(_run_mini_batch_silent, [(gd, nevents[i], particleSpec, minEnergy_GeV, maxEnergy_GeV, i) for i in range(nCores)])
 
     return pd.concat(dfs)