Educating future professionals in XRD technique
Applications | 2025 | Thermo Fisher ScientificInstrumentation
X-ray powder diffraction (XRD) is a cornerstone technique for nondestructive characterization of crystalline materials across geology, materials science, pharmaceuticals and forensic investigations. Its ability to identify phases, quantify composition and assess structural imperfections makes it indispensable for both research and quality control.
This application note outlines an educational protocol using the Thermo Scientific™ ARL X’TRA Companion benchtop diffractometer. It aims to equip students and new users with practical skills in XRD data acquisition, interpretation and quantitative analysis through hands-on laboratory exercises.
The instructional workflow includes:
The ARL X’TRA Companion features:
Laboratory exercises on alumina (NIST 1976) and limestone samples demonstrated:
The benchtop system’s intuitive interface and rapid data acquisition support:
Anticipated developments include:
The ARL X’TRA Companion benchtop XRD system offers an accessible, robust platform for training future XRD practitioners. Its combination of user-friendly hardware, open-access software and reliable performance ensures high-quality educational experiences.
X-ray
IndustriesPharma & Biopharma
ManufacturerThermo Fisher Scientific
Summary
Importance of the Topic
X-ray powder diffraction (XRD) is a cornerstone technique for nondestructive characterization of crystalline materials across geology, materials science, pharmaceuticals and forensic investigations. Its ability to identify phases, quantify composition and assess structural imperfections makes it indispensable for both research and quality control.
Objectives and Overview
This application note outlines an educational protocol using the Thermo Scientific™ ARL X’TRA Companion benchtop diffractometer. It aims to equip students and new users with practical skills in XRD data acquisition, interpretation and quantitative analysis through hands-on laboratory exercises.
Methodology
The instructional workflow includes:
- Introduction to XRD principles, Bragg’s law and safety procedures
- Sample preparation, mounting and alignment on the diffractometer
- Selection of experimental parameters and real-time data collection
- Data processing with Profex software, including peak identification and background correction
- Quantitative phase analysis via search–match and basic Rietveld refinement concepts
Instrumentation Used
The ARL X’TRA Companion features:
- θ/θ Bragg–Brentano goniometer with 160 mm radius
- 600 W X-ray source available in Cu or Co
- High-resolution semiconductor pixel detector (55 × 55 µm pixels)
- Optional integrated water cooling for continuous operation
- Open-source Profex analysis software and access to the Crystallographic Open Database (COD)
Main Results and Discussion
Laboratory exercises on alumina (NIST 1976) and limestone samples demonstrated:
- Clear diffraction peaks matching reference patterns
- Phase quantification and crystallite size estimation from peak intensities and widths
- Detection of amorphous content via background hump analysis
- Effective search–match identification and preliminary Rietveld refinement insights
Benefits and Practical Applications
The benchtop system’s intuitive interface and rapid data acquisition support:
- Hands-on training in undergraduate and graduate XRD courses
- Flexible analysis of diverse sample types in teaching laboratories
- Immediate data interpretation to reinforce theoretical learning
Future Trends and Applications
Anticipated developments include:
- Integration of in situ and operando XRD for real-time reaction monitoring
- Automation and remote access to facilitate distance learning
- AI-enhanced pattern recognition and quantitative workflows
- Advanced detector technologies for faster, higher-resolution measurements
Conclusion
The ARL X’TRA Companion benchtop XRD system offers an accessible, robust platform for training future XRD practitioners. Its combination of user-friendly hardware, open-access software and reliable performance ensures high-quality educational experiences.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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