In situ growth optimization in focused electron-beam induced deposition

Abstract

We present the application of an evolutionary genetic algorithm for the in situ optimization of nanostructures that are prepared by focused electron-beam-induced deposition (FEBID). It allows us to tune the properties of the deposits towards the highest conductivity by using the time gradient of the measured in situ rate of change of conductance as the fitness parameter for the algorithm. The effectiveness of the procedure is presented for the precursor W(CO)6 as well as for post-treatment of Pt–C deposits, which were obtained by the dissociation of MeCpPt(Me)3. For W(CO)6-based structures an increase of conductivity by one order of magnitude can be achieved, whereas the effect for MeCpPt(Me)3 is largely suppressed. The presented technique can be applied to all beam-induced deposition processes and has great potential for a further optimization or tuning of parameters for nanostructures that are prepared by FEBID or related techniques.

Keywords

• electron beam induced deposition
• genetic algorithm
• nanotechnology
• tungsten