scholarly journals Mathematical Modeling of Cyclic Voltammogram Curves of Copper Deposition

2021 ◽  
Author(s):  
Shuvodeep De

The manufacturing of interconnects and the packaging of integrated circuits are achieved with electrodeposition of copper or other metals. In order to increase the rate of deposition, especially for the large features in packaging, forced convection is provided with certain agitation mechanisms. Although this reduces deposition time, it leads to non-uniform mass transport within each feature and between different features. Special organic additives are used in the solution during the process in order to tune the nucleation and growth of metal, as well as to modify the deposition rate and improve the uniformity. A mathematical model to describe the behavior of organic additives in conjugation with fluid flow and features of various geometry and dimensions is very much desired to facilitate chemistry and process development. In order to achieve this, the physiochemical kinetics of additive and their influence on the Cu deposition rate need to be described precisely. This presentation focuses on a method to extract the kinetic parameters describing the combined effect of multiple additives during copper deposition using rotating disk electrode (RDE). The one-dimensional steady state convection-diffusion equation for each of the chemical species including copper is solved by a semi-analytical method for a range of potentials. The boundary conditions of these differential equations are coupled on the surface of the RDE through the surface coverage of the absorbed species. The steady state of surface coverage of the species represents a dynamic equilibrium of three key processes i.e., adsorption, desorption, and consumption (incorporation). When equilibrium is achieved, the net rate of adsorption and desorption becomes equal to the rate of consumption. At each value of potential, the surface coverage of the additives is solved. At first, the solution is obtained with only one species known as suppressor and it was found that in a specific range of voltage and kinetic parameter multiple solutions of the surface coverage exist at same applied potential. This mathematically explains the S-shaped negative differential resistance (NDR) feature in experimental Cyclic Voltammogram (CV) curves. Figure 1 shows three such experimental S-shaped curves for different concentration of suppressors. The NDR region obtained in the theoretical CV curve is sensitive to the kinetic parameters of the additives. It is possible to match the theoretical and the experimental CV curves by optimizing the kinetic parameters. Determination of the kinetic parameters by particle swarm optimization using experimental data for multiple additive concentration will be discussed in detail in this talk.

2009 ◽  
Vol 1195 ◽  
Author(s):  
Jiajun Mao ◽  
Eric Eisenbraun ◽  
Vincent Omarjee ◽  
Clement Lanslot ◽  
Christian Dussarrat

AbstractWith the continuing scaling in device sizes, sputtered copper is not expected to achieve the conformality and surface coverage requirements to be an effective seed layer for electrochemical deposition in sub-32nm features. Additionally, the metallization demands of high aspect ratio TSVs in 3D-architectures pose similar challenges. In this work, a manufacturable low temperature Cu PE-ALD process has been developed employing a novel O and F-free precursor. The ALD process conditions are correlated with key film properties, including deposition rate, composition, step coverage, and resistivity. Additionally, the influence of precursor substituents on the deposition rate and preliminary integration performance are discussed.


2013 ◽  
Author(s):  
Edward Flach ◽  
Santiago Schnell

We are interested in finding the kinetic parameters of a chemical reaction. Previous methods for finding these parameters rely on the dynamic behaviour of the system. This means that the methods are time-sensitive and often rely on non-linear curve fitting. In the same manner as previous techniques, we consider the concentrations of chemicals in a reaction. However, we investigate the static behaviour of the reaction at dynamic equilibrium, or steady state. Here too, the chemical concentrations depend on the kinetic parameters of the reaction. In an open reaction, the static concentrations also depends on the rate of input of the source of reacting chemical. Controlling this input rate slides the steady state along a curve in concentration space. This curve is determined by the kinetic parameters. The plane of this curve is sufficient to find the kinetic parameters. The new method we propose uses only the steady state concentration values to determine the kinetic parameters of the reaction. These values are constant once dynamic equilibrium is achieved, and so can be read accurately. Readings can be repeated readily to reduce error. Thus this new technique is simple and could produce accurate kinetic parameter estimates.


Biochemistry ◽  
2010 ◽  
Vol 49 (49) ◽  
pp. 10421-10439 ◽  
Author(s):  
Jarrod B. French ◽  
Yana Cen ◽  
Tracy L. Vrablik ◽  
Ping Xu ◽  
Eleanor Allen ◽  
...  

1999 ◽  
Vol 274 (25) ◽  
pp. 17711-17717 ◽  
Author(s):  
Timothy J. Pickering ◽  
Scott Garforth ◽  
Jon R. Sayers ◽  
Jane A. Grasby

1984 ◽  
Vol 4 (6) ◽  
pp. 483-488 ◽  
Author(s):  
Nikolaus Kühn-Velten ◽  
Joachim Wolff ◽  
Wolfgang Staib

Kinetic parameters of 3β-hydroxysteroid dehydrogenase/isomerase, steroid-17α-monooxygenase, and steroid-17,20-lyase activities were estimated under steady-state conditions. Purified Leydig cells from rat testes were superfused with pregnenolone, progesterone, or 17α-hydroxyprogesterone. The Km values for both the monooxygenase- and the lyase-catalyzed reactions were by factors of five to ten higher if analyzed with the exogenously added substrate (0.98 and 0.65 μM, respectively) than if calculated from endogenous substrate derived from a precursor (0.10 and 0.13 μM, respectively). This discrepancy may be explained by different substrate partition between the intra- and extraceIJular spaces and by different substrate concentration at the active site of the respective enzyme, depending on whether the actual substrate is of exogenous or endogenous source.


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