Process Parameter Optimization of Scanning Probe Lithography for Anodic Oxidation of Nanowire

REFERENCES

• Teuschler, T.; Mahr, K.; Miyaxaki, S.; Hundhausen, M.; Ley, L. Nanometer-scale field-induced oxidation of Si(111): H by a conducting-probe scanning force microscope: doping dependence and kinetics. Applied Physics Letters 1995, 67 (21), 3144–3146.
   Web of Science ®Google Scholar
• Gordon, A.E.; Fayfield, R.T.; Litfin, D.D.; Higman, T.K. Mechanisms of surface anodization produced by scanning probe microscopes. Journal of Vacuum Science & Technology B: Microelectronics and Nanometer Structures 1995, 13 (6), 2805–2808.
   Web of Science ®Google Scholar
• Stievenard, D.; Fontaine, P.A.; Bubois, E. Nanooxidation using a scanning probe microscope: An analytical model based on field induced oxidation. Applied Physics Letters 1997, 70 (24), 3272–3274.
   Web of Science ®Google Scholar
• Cabrera, N.; Mott, N.F. Theory of the oxidation of metals. Reports on Progress in Physics 1948, 12, 163–184.
   Web of Science ®Google Scholar
• Marchi, F.; Bouchiat, V.; Dallaporta, H.; Safarov, V.; Tonneau, D.; Doppelt, P. Growth of silicon oxide on hydrogenated silicon during lithography with an atomic force microscope. Journal of Vacuum Science & Technology B: Microelectronics and Nanometer Structures 1998, 16 (6), 2952–2956.
   Web of Science ®Google Scholar
• Garcia, R.; Calleja, M.; Rohrer, H. Pattering of silicon surfaces with noncontact atomic force microscope: Field-induced formation of nanometer-size water bridges. Journal of Applied Physics 1999, 86 (4), 1898–1903.
   Google Scholar
• Tello, M.; Garcia, R. Nano-oxidation of silicon surfaces: comparison of noncontact and contact atomic-force microscopy methods. Applied Physics Letters 2001, 79 (3), 424–426.
   Web of Science ®Google Scholar
• Singh, A.K.; Kumar, S.; Singh, V.P. Optimization of parameters using conductive powder in dielectric for EDM of super Co 605 with multiple quality characteristics. Materials and Manufacturing Processes 2014, 29 (3), 267–273.
   Web of Science ®Google Scholar
• Echrif, S.B.M.; Hrairi, M. Significant parameters for the surface roughness in incremental forming process. Materials and Manufacturing Processes 2014, 24 (6), 697–703.
   Web of Science ®Google Scholar
• Lu, D.; Antony, J. Optimization of multiple responses using a fuzzy-rule based inference system. International Journal of Production Research 2002, 40 (7), 1613–1625.
   Web of Science ®Google Scholar
• Lin, C.L. Use of the Taguchi method and grey relational analysis to optimize turning operations with multiple performance characteristics. Materials and Manufacturing Processes 2004, 19 (2), 209–220.
   Web of Science ®Google Scholar
• Kwak, T.S.; Suzuki, T.; Bae, W.B.; Uehara, Y.; Ohmori, H. Application of neural network and computer simulation to improve surface profile of injection molding optic lens. Journal of Materials Processing Technology 2005, 170 (1–2), 24–31.
   Web of Science ®Google Scholar
• El-Tamimi, A.M.; Soliman, M.S.; El Hossainy, T.M.; Muzher, J.A. Investigating the machinability of AISI 420 stainless steel using factorial design. Materials and Manufacturing Processes 2008, 23 (4), 419–426.
   Web of Science ®Google Scholar
• Kuar, A.S.; Acherjee, B.; Ganguly, D.; Mitra, S. Optimization of Nd:YAG laser parameters for microdrilling of alumina with multiquality characteristics via grey-Taguchi method. Materials and Manufacturing Processes 2012, 27 (3), 329–336.
   Web of Science ®Google Scholar
• Özek, C.; Çaydaş, U.; Ünal, E. A fuzzy model for predicting surface roughness in plasma arc cutting of AISI 4140 steel. Materials and Manufacturing Processes 2012, 27 (1), 95–102.
   Web of Science ®Google Scholar
• Muthuramalingam, T.; Mohan, B.; Rajadurai, A.; Saravanakumar, D. Monitoring and fuzzy control approach for efficient electrical discharge machining process. Materials and Manufacturing Processes 2014, 29 (3), 281–286.
   Web of Science ®Google Scholar
• Schmidt, A. Numerical prediction and sequential process optimization in sheet forming based on genetic algorithm. Materials and Manufacturing Processes 2011, 26 (3), 521–526.
   Web of Science ®Google Scholar
• Li, Z.; Wu, M.; Liu, T.; Wu, C.; Jiao, Z.; Zhao, B. Preparation of TiO2 nanowire gas nanosensor by AFM anode oxidation. Ultramicroscopy 2008, 108, 1334–1337.
   PubMed Web of Science ®Google Scholar
• Paravannoor, A.; Ranjusha, R.; Asha, A.M.; Vani, R.; Kalluri, S.; Subramanian, K.R.V.; Sivakumar, N.; Kim, T.N.; Nair, S.V.; Balakrishnan, A. Chemical and structural stability of porous thin film NiO nanowire based electrodes for supercapacitors. Chemical Engineering Journal 2013, 220, 360–366.
   Web of Science ®Google Scholar
• Neveling, D.P.; van den Heeverb, T.S.; Peroldb, W.J.; Dicks, L.M.T. A nanoforce ZnO nanowire-array biosensor for the detection and quantification of immunoglobulins. Sensors and Actuators B: Chemical 2014, 203, 102–110.
   Web of Science ®Google Scholar