A Combinatorial Study of Thin-Film Process Variables Using Microhotplates

Abstract

A major goal of materials research over the past two decades has been the development of high-throughput methods for rapid discovery and optimization of processing routes. These methods rely on highly parallel materials synthesis to efficiently create libraries wherein at least one processing parameter has been systematically varied. Here, we demonstrate a method of using an array of microelectromechanical-systems (MEMS)-based microhotplates in the high-throughput optimization of a chemical vapor deposition (CVD) process. Electrical and thermal processing variables are independently controlled at each element of the array, both during and after deposition. In the experiment described, SnO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> films were deposited on the microhotplates at 375°C or 500°C, with pulsed or continuous heating, and with voltage applied or not applied to the films. A 16-element microhotplate array was used, thus allowing a repeated two-level full factorial exploration of the experimental space. After deposition, sputter depth profile via X-ray photoelectron spectroscopy was used to determine the deposition rate of the films. Statistical modeling then determined the main effects and interaction effects of the growth conditions. Although applied here to the growth rate during CVD, the technology described is generally applicable for high-throughput study of the effects of thermal and electrical processing steps in thin-film manufacture.