(406d) Optimal Design of Novel Precursor Material Using Camd for Enhanced Growth Kinetics of ALD | AIChE

(406d) Optimal Design of Novel Precursor Material Using Camd for Enhanced Growth Kinetics of ALD

Authors 

Shahmohammadi, M. - Presenter, University of Illinois At Chicago
Takoudis, C. G., University of Illinois at Chicago
Diwekar, U., Vishwamitra Research Institute /stochastic Rese
Optimal design of novel precursor material using CAMD for enhanced growth kinetics of ALD

Rajib Mukherjee1,2, Mina Shahmohammadi3, Christos G. Takoudis3,4, Urmila M. Diwekar2, 4*

  1. Department of Chemical Engineering, University of Texas Permian Basin, Odessa, TX 79762
  2. Vishwamitra Research Institute, Crystal Lake, Illinois, 60012
  3. Department of Chemical Engineering, University of Illinois at Chicago, Chicago, Illinois 60607
  4. Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois 60607

*Corresponding: urmila@vri-custom.org

Abstract

Atomic Layer Deposition (ALD) is a promising technique in which deposition of thin films takes place on a substrate through sequential and self-limiting surface reactions. A precursor used in this process chemisorbs on the substrate and part of the molecule subsequently desorbs from the surface after completion of the reaction leaving behind deposition of metal and metal oxides on the substrate. Precursor chemisorption on the substrate leads to a self-limiting process and it eventually results in films with desired thickness at Ångström length scale. In order to design an ALD experiment, one should decide on precursor(s) based on the ALD conditions (i.e., bubbler and reactor temperatures, pressure, gas flow, etc.) and likely applications of the final film. It is practically impossible to carry out a huge number of ALD experiments using numerous precursors and deposition conditions in order to find the optimum one depending on the applications of interest. Moreover, only existing precursors can be tested for experiments. In this work, we will present development of novel titanium precursors from the thermodynamic model of adsorption as in Adsorbate solid solution theory (ASST) using Computer Aided Molecular Design (CAMD) [1]. Three different functional groups are used for the experiment, the thermodynamic properties of which are obtained through group contribution method (GCM) [2]. Each functional group is allowed to vary from 0 to 20 times. Since this results in combinatorial explosion of alternatives, a combinatorial optimization method is applied using novel efficient ant colony optimization (EACO) algorithm [3]. This is the first time CAMD is being applied to design precursor materials for ALD. The ALD growth kinetics is used as an objective of optimization and a solution is validated with thermodynamic constraints. From our simulation, 41 different novel precursor molecular structures are generated with growth rates ranging from 1.23 Å/cycle to as high as 1.65 Å/cycle. Thus, several of these novel precursors have shown growth rates higher than the known titanium precursors [4]. Temperature as a variable with wide range of limits between 300 K and 600 K is used for our simulation. ALD growth rate is found to be a function of the combination of the precursor functional groups as well as temperature with a complex correlation among them.

Keywords: Atomic Layer Deposition, Computer-Aided Molecular Design, Group Contribution Method, Adsorbate Solid Solution Theory, ALD growth kinetics

[1] Berti, C., Ulbig, P., Burdorf, A., Seippel, J., Schulz, S., 1999. Correlation and prediction of liquid-phase adsorption on zeolites using group contributions based on adsorbate-solid solution theory. Langmuir 15, 6035–6042. https://doi.org/10.1021/la981415p

[2] M. Shahmohammadi, R. Mukherjee, C.G., Takoudis, U.M., Diwekar, 2019, “Optimal Design of Novel Precursors Materials for the Atomic Layer Deposition. Part 1: Group Contribution Method”, In preparation

[3] Gebreslassie, B. H., & Diwekar, U. M. (2015). Efficient ant colony optimization for computer aided molecular design: Case study solvent selection problem. Computers & Chemical Engineering, 78, 1-9.

[4] R. Mukherjee, M. Shahmohammadi, C.G., Takoudis, U.M., Diwekar, 2019, “Optimal Design of Novel Precursor Materials for Atomic Layer Deposition. Part 2: Computer-Aided Molecular Design”, In preparation