diff --git a/examples/Fragmentation/Fragmentation_Movie.py b/examples/Fragmentation/Fragmentation_Movie.py
index adb37d371..b60dbc1db 100755
--- a/examples/Fragmentation/Fragmentation_Movie.py
+++ b/examples/Fragmentation/Fragmentation_Movie.py
@@ -166,7 +166,7 @@ def encounter_combiner(sim):
     enc = enc.sel(time=tgood)
 
     # The following will combine the two datasets along the time dimension, sort the time dimension, and then fill in any time gaps with interpolation
-    ds = xr.combine_nested([data,enc],concat_dim='time').sortby("time").chunk(dict(time=-1)).interpolate_na(dim="time", method="akima")
+    ds = xr.combine_nested([data,enc],concat_dim='time').sortby("time").interpolate_na(dim="time", method="akima")
     
     # Rename the merged Target body so that their data can be combined
     tname=[n for n in ds['name'].data if names[0] in n]
@@ -359,7 +359,7 @@ def vec_props(self, c):
         minimum_fragment_gmass = 0.01 * body_Gmass[style][1] 
         gmtiny = 0.10 * body_Gmass[style][1] 
         sim.set_parameter(collision_model="fraggle", encounter_save="both", gmtiny=gmtiny, minimum_fragment_gmass=minimum_fragment_gmass, nfrag_reduction=nfrag_reduction[style])
-        sim.run(dt=5e-4, tstop=tstop[style], istep_out=1, dump_cadence=0, dask=False)
+        sim.run(dt=5e-4, tstop=tstop[style], istep_out=1, dump_cadence=0)
 
         print("Generating animation")
         anim = AnimatedScatter(sim,movie_filename,movie_titles[style],style,nskip=1)
diff --git a/src/fraggle/fraggle_util.f90 b/src/fraggle/fraggle_util.f90
index d1327d723..92bbb4aba 100644
--- a/src/fraggle/fraggle_util.f90
+++ b/src/fraggle/fraggle_util.f90
@@ -175,15 +175,16 @@ module subroutine fraggle_util_set_mass_dist(self, param)
 
             ! The mass will be distributed evenly in logspace between the second-largest remnant and the minimum mass
             ! Use Newton's method solver to get the logspace slope of the mass function
-            Mrat = mremaining / min_mfrag
+            Mrat = (mremaining + Mslr) / Mslr
             nrem = nfrag - 2
-            x0 = 1.0_DP + 100*epsilon(1.0_DP)
+            x0 = 1.0_DP - 100*epsilon(1.0_DP)
             x1 = Mrat**(1.0/nrem)
             do j = 1, MAXLOOP 
                y0 = Mrat - (1.0_DP - x0**nrem)/(1.0_DP - x0)
                y1 = Mrat - (1.0_DP - x1**nrem)/(1.0_DP - x1)
                if (y0*y1 < 0.0_DP) exit
                x1 = x1 * 1.6_DP
+               x0 = x0 / 1.6_DP
             end do
 
             ! Find the mass scaling factor with bisection
@@ -214,11 +215,11 @@ module subroutine fraggle_util_set_mass_dist(self, param)
 
             Mslr = impactors%mass_dist(iMslr)
             mass(iMslr) = Mslr
-            mfrag = min_mfrag
+            mfrag = Mslr 
             do i = iMrem,nfrag
+               mfrag = mfrag * mscale
                mass(i) = mfrag
                mremaining = mremaining - mfrag
-               mfrag = max(mfrag * mscale, min_mfrag)
             end do
 
             ! There may still be some small residual due to round-off error. If so, simply add it to the last bin of the mass distribution.