deletions | additions       diff --git a/workflow.tex b/workflow.tex  index 0fdf291..4f0339c 100644  --- a/workflow.tex  +++ b/workflow.tex 
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one can appeal to analogies, descriptors and machine learning .[ CITE NORMAN'S REVIEW ? arXiv:1601.00709 ].  Designing a proper strategy, thus requires an understanding of the nature of correlations in a given class  of materials. Irrespectively of the degree of correlation, it is natural to divide the workflow of materials design   into three different steps, of course, how to carrry carry  them out in practice will depend on the level of correlation. The  first, and most well-studied, is the calculation of the electronic structure, namely how to go 
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Successes include the prediction of a new compounds in the Ce-Ir-In  system~\cite{Fredeman_2011}. Notable failures, include elemental Pu, where non magnetic DFT  calculations underestimates the volume of the $\delta$ phase by more than 25$\%$  while magnetic calculations predict a large magnetic moment ($ 5 \Mu_B$ {\Mu}_B$  which is not observed experimentally). Notice however, that in spite of this failure, DFT + orbital polarization can predict the order of the structures.   However, for correlated materials,  we argue that extensions taking into account the effect of correlations on the