Development and Validation of an Excel-Based Computational Tool for k₀-Instrumental Neutron Activation Analysis at the Nigerian Research Reactor-1

Abstract

The k₀-standardization method in instrumental neutron activation analysis (k₀-INAA) 
provides a robust framework for simultaneous multi-element determination using a 
single comparator, thereby eliminating the need for element-specific standards. 
However, its practical implementation requires intricate calculations involving reactor
dependent neutron spectrum parameters, nuclear constants, irradiation conditions, and 
detector efficiency functions, which can limit routine application in laboratories lacking 
specialized software. This study presents the development of a user-friendly Microsoft 
Excel–based computational tool specifically configured for the post-low-enriched 
uranium (LEU) Nigerian Research Reactor-1 (NIRR-1). The tool incorporates reactor
specific thermal-to-epithermal neutron flux ratios (f) and epithermal neutron spectrum 
shape factors (α), an embedded k₀ nuclear data library, detector efficiency calibration 
models, and automated concentration calculations with full uncertainty propagation. The 
application is structured into modular worksheets covering sample and irradiation input 
parameters, nuclear data management, efficiency calibration, core k₀ computations, and 
formatted output reporting. Automation is achieved through advanced Excel functions 
and Visual Basic for Applications (VBA) macros, enabling streamlined data processing 
while maintaining computational transparency. Performance validation using certified 
reference materials (NIST SRM 1633b Coal Fly Ash, NIST SRM 1573a Tomato Leaves, 
and IAEA Soil-7) demonstrated strong analytical accuracy, with mean relative errors 
between 3.8% and 5.1%, z-scores below 0.62, and more than 88% of determined 
elements satisfying |z| ≤ 2. Analytical precision, expressed as relative standard 
deviation (RSD), ranged from 3.8% to 8.2%. Comparative evaluation against the k₀-IAEA 
software package and conventional relative INAA methods using identical datasets 
showed agreement within 5%. The developed tool therefore constitutes a cost
effective, transparent, and locally adaptable alternative to proprietary platforms, 
significantly enhancing routine k₀-INAA capability at NIRR-1 for environmental 
monitoring, agricultural studies, and geological investigations in resource-constrained 
settings.