(574f) Group Contribution Method for Atomic Layer Deposition Based on Adsorbate Solid Solution Theory for Computer Aided Design of Novel Materials and Nanostructures | AIChE

(574f) Group Contribution Method for Atomic Layer Deposition Based on Adsorbate Solid Solution Theory for Computer Aided Design of Novel Materials and Nanostructures


Shahmohammadi, M. - Presenter, University of Illinois At Chicago
Takoudis, C. G., University of Illinois at Chicago
Diwekar, U., Vishwamitra Research Institute /stochastic Rese
Mukherjee, R., VRI-CUSTOM
Nanomaterials and nanostructures with multi-functional properties found widespread applications such as electronics, optics, and coatings that can be fabricated using Atomic Layer Deposition (ALD). This is a gas phase process which deposits conformal and pinhole-free thin films of metal oxides on a substrate. A precursor is used in this process which has limited capacities. Precursors, which are normally a metal surrounded by organic functional groups, chemisorb on the substrate or reacts with the surface sites and with each other. They subsequently desorb from the surface after completion of reaction. The precursors will then proceed to react with other unreacted surface areas and produce a very conformal deposition (1). The objective of this work is to develop a computational tool for the design of novel precursor materials with enhanced properties using adsorbate solid solution theory (ASST) (2) without conducting experiments that are expensive and time consuming. The process is carried out in two stages. In this work, we apply the ASST to derive Group Contribution method (GCM) for the ALD process. This group contribution method deriving interaction parameters for the UNIFAC based GCM. The precursor material used in previous ALD experiments is divided into functional groups. Based on the experiments, the isotherms are calculated and used to find the group interaction parameters using optimization methods. The efficient ant colony optimization (EACO) algorithm is the method used for optimization (3). With the estimated properties, Computer-Aided Molecular Design (CAMD), which is reverse of GCM where optimization is used to design new chemicals, generates a list of new materials which have enhanced properties In this way, novel materials for ALD will be designed (4,5). In this stage, combinatorial optimization is used to maximize the desired properties within the structural constraints of a precursor. The properties of the novel designed materials will be tested experimentally. Characterization of the thin films produced by ALD with designed precursors will help us to optimize the materials in the best way. In this way, one is able to design the exact materials which are needed for specific applications.


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  4. Mukherjee R, Gebreslassie B, Diwekar UM. Design of novel polymeric adsorbents for metal ion removal from water using computer-aided molecular design. Clean Technol Environ Policy [Internet]. Springer Berlin Heidelberg; 2016; Available from: "http://dx.doi.org/10.1007/s10098-016-1236-6
  5. Siliang Chang, Sathees Kannan Selvaraj, Yoon-Young Choi, Seungbum Hong, Serge M. Nakhmanson, Christos G. Takoudis. "Atomic layer deposition of environmentally benign SnTiOx as a potential ferroelectric material." Journal of Vacuum Science & Technology A 34, no. 1 (2016): 01A119