ADVANCED GRAPHENE SYNTHESIS FROM SOLID POLYCYCLIC AROMATIC HYDROCARBONS VIA A CONTROLLED-ENVIRONMENT CRUCIBLE TECHNIQUE
Abstract
Graphene, a two-dimensional material with exceptional electronic, mechanical, and thermal properties, holds immense promise for next-generation technologies. While various synthesis methods exist, challenges remain in achieving high-quality, large-area graphene reliably and cost-effectively. This article presents a novel approach for the synthesis of high-purity graphene from solid polycyclic aromatic hydrocarbons (PAHs) utilizing a sealed crucible technique. This method offers precise control over the precursor vapor environment, minimizing contamination and promoting uniform growth. We detail the experimental methodology, including precursor selection, crucible preparation, optimized growth parameters (temperature, pressure, duration), and comprehensive characterization techniques. Preliminary findings indicate the successful formation of few-layer, high-quality graphene films, as evidenced by Raman spectroscopy, scanning electron microscopy (SEM), and atomic force microscopy (AFM). The discussion delves into the potential growth mechanisms and compares this technique's advantages, such as simplicity, reduced gas consumption, and potential for direct growth on various substrates, against conventional methods. This controlled-environment crucible technique represents a promising avenue for scalable, high-quality graphene production, paving the way for its broader application in electronics, sensors, and energy storage devices.
Keywords
References
Similar Articles
- Dr. Arjun Mehta, Cognitive Diagnostics for Automated Enterprise Service Recovery Using Generative AI , International Journal of Next-Generation Engineering and Technology: Vol. 3 No. 05 (2026): Volume 03 Issue 05
- Dr. Maria Fernandes, Cyber-Enabled Modeling and Intelligent Decision Support in Human-Centric Industry 5.0 Practices , International Journal of Next-Generation Engineering and Technology: Vol. 3 No. 01 (2026): Volume 03 Issue 01
- Jean Claude Ndayizeye, Analyzing Unseen Customer Attributes with Innovative Cohort Identification Techniques , International Journal of Next-Generation Engineering and Technology: Vol. 3 No. 02 (2026): Volume 03 Issue 02
- Dr. Haruto Nakamura, Prof. Aiko Tanaka, A Framework-Based Analysis of Artificial Intelligence Tool Integration in Academic Writing and Its Effects on Critical Reasoning and Writing Competency in Malaysian Higher Education Faculty , International Journal of Next-Generation Engineering and Technology: Vol. 3 No. 08 (2026): Volume 03 Issue 08
You may also start an advanced similarity search for this article.