In situ roughness monitoring of sputtered Pt thin film under dynamic turbulence using adaptive optics

Fuh, Yiin Kuen; Wang, Chia He

doi:10.1016/j.ijleo.2013.10.056

Cited by 3 publications

(2 citation statements)

References 21 publications

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“…It has been assumed that the on-line measurements of R kMC and Gr kMC are available from the process. In practice, such measurements can be collected using laser scattering combined with adaptive optics, as well as X-ray reflectivity. , Also, the assumption was made that any disturbances d ( t i ) that could impact thin film production by CVD could be detected on-line through the collected measurements. Thanks to the computational efficiency of the ANNs, the time-dependent profiles of T surf and X bulk could be adjusted in real time via the shrinking horizon NMPC framework to compensate for the perturbations.…”

Section: Results and Discussionmentioning

confidence: 99%

Artificial Neural Network Discrimination for Parameter Estimation and Optimal Product Design of Thin Films Manufactured by Chemical Vapor Deposition

Kimaev

Ricardez‐Sandoval

2020

J. Phys. Chem. C

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Industrial production of valuable chemical products often involves the manipulation of phenomena evolving at different temporal and spatial scales. Product properties can be captured accurately using computationally expensive stochastic multiscale models that explicitly consider the feedbacks between different scales. However, product design quality is often tampered by uncertainties affecting process operation. In this work, we used artificial neural networks (ANNs) to estimate an uncertain parameter, accurately predict product properties under uncertainty, and achieve orders-of-magnitude computational savings of a multiscale model of thin film formation by chemical vapor deposition. ANNs were trained using multiple realizations of the uncertain parameter to capture the behavior of the thin film’s two key microscale properties: roughness and growth rate. Next, mean square error and maximum likelihood estimation were used for parameter estimation and to find the ANN that could generate the closest predictions to the real-time measurements collected from the process in the presence of uncertainty. The chosen ANNs were employed to seek for the optimal operating conditions to enable the fabrication process to meet product quality specifications. ANNs are a promising technique for product property prediction and efficient decision making in the design of optimal operating conditions for chemical processes under uncertainty.

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Section: Results and Discussionmentioning

confidence: 99%

Artificial Neural Network Discrimination for Parameter Estimation and Optimal Product Design of Thin Films Manufactured by Chemical Vapor Deposition

Kimaev

Ricardez‐Sandoval

2020

J. Phys. Chem. C

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“…Copper and aluminum are often used to connect microelectronic and mechanical components [ 1 , 2 , 3 , 4 , 5 ], while silver is used in optical reflection components [ 6 , 7 , 8 ]. Gold is often used to produce the capacitance switch of Radio frequency Microelectromechanical Systems (RF MEMS) [ 9 ] and is utilized as the surface substrates of self-assembled molecular films [ 10 ], while platinum is commonly used for ferroelectric electrodes and high dielectric components [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

The Effects of Stresses and Interfaces on Texture Transformation in Silver Thin Films

et al. 2022

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Thin metal films are critical elements in nano- and micro-fabricated technologies. The texture orientation of thin films has a significant effect on applied devices. For Face-Centered Cubic (FCC) metal thin films, when the critical thickness is reached, the texture orientation can transform from (111) to (100) based on the model related to the balance between interfacial energy and strain energy. This research focused on the texture transformation of thin films under two conditions: (1) with or without an adhesion layer in the thin film and (2) with or without initial stress applied through a four-point bending load. In the experiment, two samples (silicon/silver and silicon/titanium/silver) were used to apply different initial stress/strain values and different annealing times. After annealing, an X-ray Diffractometer (XRD) was used to ascertain the preferred orientation of the thin films and the percentage of (111) and (100). Finally, Electron Back-Scattered Diffraction (EBSD) was used to observe the grain size of the thin films. The results showed that, regardless of the existence of an adhesion layer, texture transformation occurred, and this was relatively significant with Ti adhesion layers. Further, the initial stress was found to be small compared to the internal stress; thus, the initial stress imposed in the tests in this research was not significantly influenced by the texture transformation.

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Optical method for in situ monitoring of electrospinning process and porosity characterization of microporous membrane

Chen

Huang

Fuh

2017

J. Micro/Nanolith. MEMS MOEMS

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In situ roughness monitoring of sputtered Pt thin film under dynamic turbulence using adaptive optics

Cited by 3 publications

References 21 publications

Artificial Neural Network Discrimination for Parameter Estimation and Optimal Product Design of Thin Films Manufactured by Chemical Vapor Deposition

Artificial Neural Network Discrimination for Parameter Estimation and Optimal Product Design of Thin Films Manufactured by Chemical Vapor Deposition

The Effects of Stresses and Interfaces on Texture Transformation in Silver Thin Films

Optical method for in situ monitoring of electrospinning process and porosity characterization of microporous membrane

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