Vapor Deposition of TiO<sub>2</sub>

Yokozawa, M.; Iwasa, Hitoo; Teramoto, I.

doi:10.1143/jjap.7.96

Cited by 78 publications

(28 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Oxygen lowered the temperature of the thermal decomposition of the titanium precursor. [37,39] The experiments without oxygen are more relevant to ALD because, in this process, only an inert carrier gas is present during the metal precursor pulse. Therefore, only experiments carried out without reactive gases are considered in the following discussion.…”

Section: Resultsmentioning

confidence: 99%

Reaction Mechanism Studies on Titanium Isopropoxide–Water Atomic Layer Deposition Process

Rahtu¹,

Ritala²

2002

Chem. Vap. Deposition

133

137

View full text Add to dashboard Cite

Reaction mechanisms between titanium isopropoxide and deuterated water in the atomic layer deposition (ALD) of TiO 2 at 150±350 C were studied using a quartz crystal microbalance (QCM) and a quadrupole mass spectrometer (QMS). The temperature had no marked effect on the total amount of the main gaseous by-product (CH 3 ) 2 CHOD. At 150±250 C, about half of the ligands were released in reactions with surface hydroxyl groups during the Ti(OCH(CH 3 ) 2 ) 4 pulse, and the other half during the water pulse. At higher temperatures, Ti(OCH(CH 3 ) 2 ) 4 began to thermally decompose, thus affecting the growth mechanism. The results were compared with earlier CVD and ALD studies.

show abstract

Section: Resultsmentioning

confidence: 99%

Reaction Mechanism Studies on Titanium Isopropoxide–Water Atomic Layer Deposition Process

Rahtu¹,

Ritala²

2002

Chem. Vap. Deposition

133

137

View full text Add to dashboard Cite

show abstract

“…The second partial derivative is computed individually for each of the unknown parameters to be estimated. For the three unknown parameters in (13), the partial derivatives are as follows: (19) (20)…”

Section: Hybrid Neural Network Modelingmentioning

confidence: 99%

Semi-empirical neural network modeling of metal-organic chemical vapor deposition

Nami

Misman

Erbil

et al. 1997

IEEE Trans. Semicond. Manufact.

View full text Add to dashboard Cite

Metal-organic chemical vapor deposition (MOCVD)is an important technique for growing thin films with various applications in electronics and optics. The development of accurate and efficient MOCVD process models is therefore desirable, since such models can be instrumental in improving process control in a manufacturing environment. This paper presents a semiempirical MOCVD model based on "hybrid" neural networks. The model is constructed by characterizing the MOCVD of titanium dioxide (TiO 2 ) films through the measurement of deposition rate over a range of deposition conditions by a statistically designed experiment in which susceptor and source temperature, flow rate of the carrier gas for the precursor and chamber pressure are varied. A modified backpropagation neural network is then trained on the experimental data to determine the value of the adjustable parameters in an analytical expression for the TiO2 deposition rate. In so doing, a general purpose methodology for deriving semi-empirical neural process models which take into account prior knowledge of the underlying process physics is developed.

show abstract

“…TiO 2 films can be prepared by several techniques, e.g. by sol-gel routes [4], vapour deposition [5], sputtering [6] or electrodeposition [7][8][9][10][11][12][13][14][15]. Electrodeposition of semiconductor oxides, especially ZnO, has been well investigated during the last years [16,17].…”

Section: Introductionmentioning

confidence: 99%

Efficiency improvement of dye-sensitized solar cells based on electrodeposited TiO2 films by low temperature post-treatment

Wessels

Wark

Oekermann

2010

Electrochimica Acta

View full text Add to dashboard Cite

Vapor Deposition of TiO₂

Cited by 78 publications

References 2 publications

Reaction Mechanism Studies on Titanium Isopropoxide–Water Atomic Layer Deposition Process

Reaction Mechanism Studies on Titanium Isopropoxide–Water Atomic Layer Deposition Process

Semi-empirical neural network modeling of metal-organic chemical vapor deposition

Efficiency improvement of dye-sensitized solar cells based on electrodeposited TiO2 films by low temperature post-treatment

Contact Info

Product

Resources

About

Vapor Deposition of TiO2

Cited by 78 publications

References 2 publications

Reaction Mechanism Studies on Titanium Isopropoxide–Water Atomic Layer Deposition Process

Reaction Mechanism Studies on Titanium Isopropoxide–Water Atomic Layer Deposition Process

Semi-empirical neural network modeling of metal-organic chemical vapor deposition

Efficiency improvement of dye-sensitized solar cells based on electrodeposited TiO2 films by low temperature post-treatment

Contact Info

Product

Resources

About

Vapor Deposition of TiO₂