the test structures were fabricated on a p - doped silicon substrate 
 with a 1.6 m thermal oxide layer . the structures are cavities 
 with diameters between 3 and 20 m with circular , square , and 
 rectangular geometry . they were etched 1.4 m deep into the 
 sio2 layer using a photoresist mask and an ar- and chf3-based reactive - ion - etching ( rie ) process using 200 mw and 
 40 mtorr for a vertical etch profile . the monolayer graphene samples 
 were grown by chemical - vapor deposition ( cvd ) in a 4 in . cold walled 
 reactor ( aixtron bm ) using copper ( cu ) foil as the growth substrate . cu surface pretreatment and high - temperature annealing were performed 
 before the graphene growth . after the synthesis , a semidry 
 proprietary transfer process using pmma as the supporting layer was 
 used to suspend the monolayer graphene onto the cavities . the supporting 
 polymer was removed by annealing the sample at 450 c for 2h 
 in n2 atmosphere . finally , the graphene samples were annealed 
 at a temperature of 450 c to minimize residues formed by processing .
graphene 
 has extraordinary mechanical and electronic properties , making it 
 a promising material for membrane - based nanoelectromechanical systems 
 ( nems ) . here 
 , chemical - vapor - deposited graphene is transferred onto 
 target substrates to suspend it over cavities and trenches for pressure - sensor 
 applications . 
 the development of such devices requires suitable metrology 
 methods , i.e. , large - scale characterization techniques , to confirm 
 and analyze successful graphene transfer with intact suspended graphene 
 membranes . 
 we propose fast and noninvasive raman spectroscopy mapping 
 to distinguish between free - standing and substrate - supported graphene , 
 utilizing the different strain and doping levels . 
 the technique is 
 expanded to combine two - dimensional area scans with cross - sectional 
 raman spectroscopy , resulting in three - dimensional raman tomography 
 of membrane - based graphene nems . 
 the potential of raman tomography 
 for in - line monitoring is further demonstrated with a methodology 
 for automated data analysis to spatially resolve the material composition 
 in micrometer - scale integrated devices , including free - standing and 
 substrate - supported graphene . 
 raman tomography may be applied to devices 
 composed of other two - dimensional materials as well as silicon micro- 
 and nanoelectromechanical systems .