diff --git a/openmmml/models/macepotential.py b/openmmml/models/macepotential.py
index 0cf1397..03b2077 100644
--- a/openmmml/models/macepotential.py
+++ b/openmmml/models/macepotential.py
@@ -283,13 +283,6 @@ def __init__(
                 self.register_buffer("batch", torch.zeros(nodeAttrs.shape[0], dtype=torch.long, requires_grad=False))
                 self.register_buffer("pbc", torch.tensor([periodic, periodic, periodic], dtype=torch.bool, requires_grad=False))
 
-                self.inputDict = {
-                    "ptr": self.ptr,
-                    "node_attrs": self.node_attrs,
-                    "batch": self.batch,
-                    "pbc": self.pbc,
-                }                    
-
             def _getNeighborPairs(
                 self, positions: torch.Tensor, cell: Optional[torch.Tensor]
             ) -> Tuple[torch.Tensor, torch.Tensor]:
@@ -369,12 +362,19 @@ def forward(
                 edgeIndex, shifts = self._getNeighborPairs(positions, cell)
 
                 # Update input dictionary.
-                self.inputDict["positions"] = positions
-                self.inputDict["edge_index"] = edgeIndex
-                self.inputDict["shifts"] = shifts
+                inputDict = {
+                    "ptr": self.ptr,
+                    "node_attrs": self.node_attrs,
+                    "batch": self.batch,
+                    "pbc": self.pbc,
+                    "positions": positions,
+                    "edge_index": edgeIndex,
+                    "shifts": shifts,
+                    "cell": cell if cell is not None else torch.zeros(3, 3, dtype=self.dtype),
+                }                    
 
                 # Predict the energy.
-                energy = self.model(self.inputDict, compute_force=False)[
+                energy = self.model(inputDict, compute_force=False)[
                     self.returnEnergyType
                 ]