**In a few sentences,**
**the presentation of both**
**RMC and RDM methods**
**(personal views) :**

**RMC**

**The Reverse Monte Carlo
method (RMC) is now widely used for structural modelling.**

**RMC produces glass structure
models tending to the very best fit of diffraction data, almost in a systematical
way.**

**The composition and density
are required,**
**minimal/maximal interatomic
distances should be known, and**
**coordination numbers
are welcome when dealing with network glasses.**

**Model size involves at
least 1000 atoms.**

**Modelling may start from
random atomic positions.**

**In case of network glasses,
the building of a model satisfying the coordination constraint requirements
(for instance, a 4-connected three-dimensional network for SiO _{2}
or ZnCl_{2}) may become tedious and require a final by-hand intervention.**

**The models tend to present
non-requested features such as tetrahedra edge sharing, pending oxygen
atoms, exception to the expected coordination.**

**RDM**

**On the other hand, the
Rietveld for disordered material method (RDM) needs a crystal structure
as a starting mean model, so that the coordination constraints are respected
ab
initio.**

**Glasses or nanocrystalline
material diffraction data are fitted using microstrain effects on line
broadening.**

**Model size involves less
than 25 independent atoms of which the coordinates are refined.**

**The approach is controversial...**
**Describing glasses by
space groups different from P1...**

**Reconciling RMC and RDM
?**

**How to reconcile both
methods, that lead to quite different models, is the aim of this conference.**

**Is examined the behaviour
of RDM models, enlarged to nearly one thousand atoms or more (by multiplying
the cell edges), and submitted to limited random moves by the RMC method.**

**Three examples are presented
:**

**glassy SiO _{2},
ZnCl_{2} and NaPbM_{2}F_{9} (M = Fe, V), all previously
submitted to RMC and RDM modelling.**