Characterization of copper etching process on micro leadless land grid array (ゼLLGA) via design of experiments approach

In this work, we characterized the wet chemical atomic layer etching of an InGaAs surface by using various surface analysis methods. For this etching process, H2O2 was used to create a self-limiting oxide layer. Oxide removal was studied for both HCl and NH4OH solutions. Less In oxide tended to remain after the HCl treatment than after the NH4OH treatment, so the combination of H2O2 and HCl is suitable for wet chemical atomic layer etching. In addition, we found that repetition of this etching process does not impact on the oxide amount, surface roughness, and interface state density. Thus, nanoscale etching of InGaAs with no impact on the surface condition is possible with this method.

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Surface characterization of patterning on MgO single crystals using wet chemical etching process to advance MEMS devices

Journal of Micromechanics and Microengineering ◽

10.1088/1361-6439/ab504d ◽

2019 ◽

Vol 30 (1) ◽

pp. 015001

Author(s):

Jia Liu ◽

Pianggang Jia ◽

Xiaoyong Chen ◽

Ting Liang ◽

Hao Liu ◽

...

Keyword(s):

Single Crystals ◽

Chemical Etching ◽

Surface Characterization ◽

Etching Process ◽

Mems Devices ◽

Wet Chemical ◽

Wet Chemical Etching

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Simultaneous Hierarchical and Multi-Level Optimization for Material Characterization and Design of Experiments

Volume 2: 27th Computers and Information in Engineering Conference, Parts A and B ◽

10.1115/detc2007-35470 ◽

2007 ◽

Cited By ~ 1

Author(s):

John G. Michopoulos ◽

Tomonari Furukawa ◽

John C. Hermanson ◽

Samuel G. Lambrakos

Keyword(s):

Design Of Experiments ◽

Material Characterization ◽

Performance Metrics ◽

Loading Path ◽

Optimization Approach ◽

Material System ◽

Objective Functions ◽

Uniqueness Of Solutions ◽

Mechatronic Systems

A hierarchical algorithmic and computational scheme based on a staggered design optimization approach is presented. This scheme is structured for unique characterization of many continuum systems and their associated datasets of experimental measurements related to their response characteristics. This methodology achieves both online (real-time) and offline design of optimum experiments required for characterization of the material system under consideration, while also achieving a constitutive characterization of the system. The approach assumes that mechatronic systems are available for exposing specimens to multidimensional loading paths and for the acquisition of data associated with stimulus and response behavior. Material characterization is achieved by minimizing the difference between system responses that are measured experimentally and predicted based on model representation. The performance metrics of the material characterization process are used to construct objective functions for the design of experiments at a higher-level optimization. The distinguishability and uniqueness of solutions that characterize the system are used as two of many possible measures adopted for construction of objective functions required for design of experiments. Finally, a demonstration of the methodology is presented that considers the best loading path of a two degree-of-freedom loading machine for characterization of the linear elastic constitutive response of anisotropic materials.

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