A Green Approach for Photometric Determination of Copper β-Resorcylate in Double Base Solid Propellants

Publish Year: 1400
نوع سند: مقاله ژورنالی
زبان: English
View: 248

This Paper With 9 Page And PDF Format Ready To Download

  • Certificate
  • من نویسنده این مقاله هستم

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این Paper:

شناسه ملی سند علمی:

JR_CHM-5-6_007

تاریخ نمایه سازی: 1 آبان 1400

Abstract:

This paper describes the applicability of micellar media instead of extraction steps with toxic solvents for direct determination of copper beta-resorcylate as burning rate catalyst in double base propellant (DB propellant). The method is based on a simple and safe sample preparation of DB propellant, and then complex formation of copper ion with Diethyldithiocarbamate (DDTC) in the presence of sodium dodecyl sulfate (SDS) as a micellar media. Under optimal conditions, at λmax= ۴۴۵ nm, the calibration graph was linear in the range of ۰.۲۵-۴.۵ µg mL-۱ for copper with detection limits ۰.۱۲۵ µg mL-۱. The validity of the method was evaluated by means of the data statistical analysis. For this purpose, the method was applied to the determination of copper beta-resorcylate in DB propellant and the results were statistically compared based on t- and F-tests with those obtained by the by ICP-AES. There was no significant difference between the mean values and the precisions of the two methods at the ۹۵% confidence level. The results showed that the proposed method offers an accuracy and reliable approach for the determination of copper β-resorcylate in DB propellant, and can be suggested as a routine method in military quality control laboratories.

Authors

Ali Reza Zarei

Faculty of Chemistry and Chemical Engineering, Malek Ashtar University of Technology, Tehran, ۱۵۸۷۵-۱۷۷۴, Iran

Kimia Mardi

Faculty of Chemistry and Chemical Engineering, Malek Ashtar University of Technology, Tehran, ۱۵۸۷۵-۱۷۷۴, Iran

مراجع و منابع این Paper:

لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :