diff --git a/geometric/nifty.py b/geometric/nifty.py
index b6a8d60c..c5d82ea5 100644
--- a/geometric/nifty.py
+++ b/geometric/nifty.py
@@ -830,10 +830,12 @@ def createWorkQueue(wq_port, debug=True, name=package):
     if debug:
         work_queue.set_debug_flag('all')
     WORK_QUEUE = work_queue.WorkQueue(port=wq_port)
-    WORK_QUEUE.specify_name(name)
+    # LPW 2025-01-23 Commenting out the following line because it makes deleting the WQ no longer work.
+    # WORK_QUEUE.specify_name(name)
     # QYD: prefer the worker that is fastest in previous tasks
     # another choice is first-come-first serve: WORK_QUEUE_SCHEDULE_FCFS
-    WORK_QUEUE.specify_algorithm(work_queue.WORK_QUEUE_SCHEDULE_TIME)
+    # LPW 2025-01-23 Commenting out the following line because it makes deleting the WQ no longer work.
+    # WORK_QUEUE.specify_algorithm(work_queue.WORK_QUEUE_SCHEDULE_TIME)
     # QYD: We don't want to specify the following extremely long keepalive times
     # because they will prevent checking "dead" workers, causing the program to wait forever
     #WORK_QUEUE.specify_keepalive_timeout(8640000)
diff --git a/geometric/tests/test_terachem.py b/geometric/tests/test_terachem.py
index ca66b69e..e11bf3a2 100644
--- a/geometric/tests/test_terachem.py
+++ b/geometric/tests/test_terachem.py
@@ -118,14 +118,14 @@ def test_terachem_qmmm_openmm(self, localizer, workqueue):
         else:
             result = engine.calc_new(coords, 'run.tmp')['gradient']
         # Compare result
-        refgrad = np.array([[-0.0146181655,  0.0413077637, -0.0000000018],
-                            [-0.0035848878, -0.0059011543, -0.0092284233],
-                            [-0.0035848900, -0.0059011520,  0.0092284240],
-                            [ 0.0116421807, -0.0005882161, -0.0000000007],
-                            [ 0.0082058550, -0.0232158055,  0.0000000018],
-                            [-0.0016073291, -0.0027339830,  0.0043185120],
-                            [-0.0016073291, -0.0027339829, -0.0043185120],
-                            [ 0.0051545658, -0.0002334698, -0.0000000000]]).flatten()
+        refgrad = np.array([[-0.0087843182,  0.0248112145,  0.0000000045],
+                            [-0.0035052067, -0.0062861883, -0.0093217504],
+                            [-0.0035052036, -0.0062861880,  0.0093217464],
+                            [ 0.0118851362, -0.0009251753,  0.0000000006],
+                            [ 0.0071183928, -0.0200906153, -0.0000000012],
+                            [-0.0007386155,  0.0029989473, -0.0004150336],
+                            [-0.0007386155,  0.0029989474,  0.0004150337],
+                            [-0.0017315695,  0.0027790577, -0.0000000000]]).flatten()
         np.testing.assert_almost_equal(result, refgrad, decimal=6)
 
 def test_edit_tcin(localizer):