Date Approved

11-3-2025

Embargo Period

11-3-2025

Document Type

Thesis

Degree Name

M.S. Materials Science and Engineering

Department

Physics

College

Henry M. Rowan College of Engineering

Advisor

James Newell, Ph.D.

Committee Member 1

Joseph Stanzione III, Ph.D.

Committee Member 2

Behrad Koohbor, Ph.D.

Keywords

deposition efficiency;mathematical modeling;Nylon 6;polymer cold spray;PVA;statistical modeling

Abstract

Cold spray (CS) is a promising additive manufacturing technique for various industries, including aerospace and automotive. However, the application of CS to polymers presents unique challenges due to their inherent properties and complex deposition mechanisms. This study addresses critical knowledge gaps in polymer cold spray processes, focusing on optimizing parameters for enhanced deposition of polyvinyl alcohol (PVA) and polyamide-6 (nylon 6). Through a comprehensive three-stage experimental approach, the effects of gas temperature, feed rate, standoff distance, gas pressure, raster speed, particle size, and crystallinity on deposition efficiency was investigated. Utilizing advanced design of experiments methodologies, including a response surface methodology, non-linear mathematical models were developed to predict and optimize cold spray parameters for polymeric systems. Our findings provide crucial insights into the interplay between process parameters and material properties, significantly advancing the understanding of polymer cold spray deposition. This research paves the way for improved polymer coating technologies, with far-reaching implications for lightweight, high-performance applications in critical industries.

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