XRD Analysis of Cu-Al Interconnect Intermetallic Compound in an Annealed Micro-Chip

Chua, Kok Yau; Hng, May Ting; Lee, Cher Chia; Anand, T. Joseph Sahaya

doi:10.4028/www.scientific.net/amr.620.166

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…According to Qi et al [17], the diffraction peak of the GO was around 10 • , but this peak disappeared in the compound, indicating that the GO was reduced to reduced graphene oxide (Figure 4a). XRD revealed that the main component was Fe 0 , with a diffraction peak observed at 2θ of 44.6 • , and also contained α-Fe 3 O 4 components, with diffraction peaks at 65.0 • and 35.5 • and a characteristic peak at 2θ of 23.8 • CuO [31,32]. Figure 4 shows that there was no excess impurity peak on the surface of the prepared rGO/Fe/Cu, which indicated that the purity of the rGO/Fe/Cu prepared by this method was high.…”

Section: Resultsmentioning

confidence: 99%

Binary Dye Removal from Simulated Wastewater Using Reduced Graphene Oxide Loaded with Fe-Cu Bimetallic Nanocomposites Combined with an Artificial Neural Network

Xin

Xiang

et al. 2021

Materials

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Reduced graphene oxide loaded with an iron-copper nanocomposite was prepared in this study, using graphene oxide as a carrier and ferrous sulfate, copper chloride and sodium borohydride as raw materials. The obtained material was prepared for eliminating hazardous dye carmine and the binary dye mixture of carmine and Congo red. The process of carmine dye removal by the nanocomposite was modeled and optimized through response surface methodology and artificial intelligence (artificial neural network–particle swarm optimization and artificial neural network–genetic algorithm) based on single-factor experiments. The results demonstrated that the surface area of the nanocomposite was 41.255 m2/g, the pore size distribution was centered at 2.125 nm, and the saturation magnetization was up to 108.33 emu/g. A comparison of the material before and after the reaction showed that the material could theoretically be reused three times. The absolute error between the predicted and experimental values derived by using artificial neural network–particle swarm optimization was the smallest, indicating that this model was suitable to remove carmine from simulated wastewater. The dose factor was the key factor in the adsorption process. This process could be described with the pseudo-second-order kinetic model, and the maximum adsorption capacity was 1848.96 mg/g. The removal rate of the mixed dyes reached 96.85% under the optimal conditions (the dosage of rGO/Fe/Cu was 20 mg, the pH was equal to 4, the initial concentration of the mixed dyes was 500 mg/L, and the reaction time was 14 min), reflecting the excellent adsorption capability of the material.

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Section: Resultsmentioning

confidence: 99%

Binary Dye Removal from Simulated Wastewater Using Reduced Graphene Oxide Loaded with Fe-Cu Bimetallic Nanocomposites Combined with an Artificial Neural Network

Xin

Xiang

et al. 2021

Materials

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“…In FIB, a thin lamella with dimension 10µm x 10µm x 0.1µm was extracted from the peripheral bonding interface consisting Si, Al bond pad and Cu ball bond. Equipments and process parameters used in these processes were similar to that of [3,8], except that the bonding temperatures evaluated in this work was 100°C and the location of lamella extraction was performed at the high stress region. Lamellas were then inspected by FEI TECNAI G 2 F20 system which is capable for Transmission Electron Microscope (TEM)/Scanning TEM (STEM) imaging with high angle annular dark field (HAADF) feature and line scan Energy Dispersive X-ray (EDX).…”

Section: Methodsmentioning

confidence: 99%

“…The annealing condition for Thermosonic Cu-Al system is commonly referring to High Temperature Storage (HTS), i.e. a standard annealing or aging process (typical temperature of 175°C) for assessing the long term reliability performance of the component in micro-electronics industry [8]. The common belief is that the IMC formation at the bonding interface is highly correlated to the reliability of the bonding and thus that of the component.…”

Section: Introductionmentioning

confidence: 99%

Micro-Structural Studies of Thermosonic Cu-Al Bonding Interface

Anand

Yau

Jalar

2014

AMR

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Thermosonic Copper (Cu) wire interconnection has been under an extensive research and development to replace expensive Gold (Au) wire material in the semiconductor industry. However, a reliability concern is raised due to void formation at the bonding interface of Copper wire-Aluminum bond pad (Cu-Al) after High Temperature Storage (HTS) annealing condition. It is believed that the Intermetallic Compound (IMC) layer growth and evolution lead to a volumetric shrinkage which in turn results in the void formation. Annealing conditions influence the development of the IMC at the bonding interface which is related to the bonding reliability. In this work, the effects of annealing toward the micro-structure and IMC growth at the bonding interface were evaluated using Scanning Transmission Electron Microscope equipped with Energy Dispersive X-ray analysis. In the as-synthesized sample bonded at 100°C, an inhomogeneous IMC formation dominated by grain boundary diffusion was observed. After High Temperature Storage of 1000 hours, the consumption of the Al bond pad resulted in the formation of irregular IMC layers. The variation of phases existed in a localized region was believed due to simultaneous growth of IMC by both grain boundary and volume diffusions. Moreover, the diffusion of Cu into Si was observed. This resulted in the formation of the mixture of Si + η phases in the affected sea region.

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Microstructural and mechanical analysis of Cu and Au interconnect on various bond pads

Anand

Yau

Leong

et al. 2013

Current Applied Physics

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XRD Analysis of Cu-Al Interconnect Intermetallic Compound in an Annealed Micro-Chip

Cited by 4 publications

References 15 publications

Binary Dye Removal from Simulated Wastewater Using Reduced Graphene Oxide Loaded with Fe-Cu Bimetallic Nanocomposites Combined with an Artificial Neural Network

Binary Dye Removal from Simulated Wastewater Using Reduced Graphene Oxide Loaded with Fe-Cu Bimetallic Nanocomposites Combined with an Artificial Neural Network

Micro-Structural Studies of Thermosonic Cu-Al Bonding Interface

Microstructural and mechanical analysis of Cu and Au interconnect on various bond pads

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