Neutron activation analysis challenges: Problems and applications in biomedical and other areas

Neutron Activation Analysis: An Excellent Nondestructive Analytical Technique for Trace Metal Analysis

For proper functioning of the human body, several metals are required in different concentrations but if their concentration slightly elevates, because of any metal-contaminated environment or of other food sources, which leads to high toxicity and different chronic health issues. Different analytical techniques like atomic absorption spectroscopy, X-ray fluorescence, inductively coupled plasma- mass spectroscopy (ICP-MS) and flame atomic absorption spectroscopy are used for metals analysis present in different samples in different fields but nowadays neutron activation analysis (NAA) is preferred over other analytical techniques because it is an efficient, multi-elemental, nondestructive analytical technique having an ultralow minimum detection limit, therefore it can detect heavy metals (HMs) even if at a very trace level parts per billion (ppb) with a quite simple sample preparation technique. This technique is known as "referee technique" because of its accuracy and trustworthiness. There is a widespread use of this technique in biomedical science like in Alzheimer's disease, cancer, arthritis, metabolism study, brain tumor and in many more conditions where metals are actively present. For its typical sample sizes and due to a multitude of additional benefits, it also helps in mapping of pathophysiology of the disease. Besides all, mainly in biomedical science the biological samples can easily be analyzed irrespective of any form. In recent years NAA is preferred over other analytical techniques in several research fields, so this article focuses on the analytical technique, its general principle and recent applications.

The comparison of four neutron sources for Prompt Gamma Neutron Activation Analysis (PGNAA) in vivo detections of boron

A Prompt Gamma Ray Neutron Activation Analysis (PGNAA) system, incorporating an isotopic neutron source has been simulated using the MCNPX Monte Carlo code. In order to improve the signal to noise ratio different collimators and a filter were placed between the neutron source and the object. The effect of the positioning of the neutron beam and the detector relative to the object has been studied. In this work the optimisation procedure is demonstrated for boron. Monte Carlo calculations were carried out to compare the performance of the proposed PGNAA system using four different neutron sources (241Am/Be, 252Cf, 241Am/B, and DT neutron generator). Among the different systems the 252Cf neutron based PGNAA system has the best performance.

Trace element intake and dietary status of nuts consumed in Pakistan: study using INAA

Five nuts, namely almond, cashew nuts, peanuts, pine nuts and pistachio, commonly consumed in Pakistan, were analyzed for their inorganic element contents. Instrumental neutron activation analysis (INAA) methodology, using different irradiation, cooling and counting protocols, was adopted to determine Al, Br, Ca, Cl, Co, Cs, Eu, Fe, Hg, K, La, Mg, Mn, Mo, Na, Rb, Sc, Se, Sr and Zn. The investigated nuts were found to contain substantial amounts of Ca, Cl, Fe, Mg, K, Na and Zn. Dietary intake of the essential inorganic elements present in these nuts, as compared to the recommended dietary allowance, has also been calculated. This has further substantiated the nutrient role of nuts in the prevention of cardiovascular disease, as in addition to their established efficacy in improving the lipid profile, they are a rich source of cardioprotective trace elements such as magnesium, zinc, iron and calcium. Toxic elements were present in very low concentrations in nuts.

Explosives detection using prompt-gamma neutron activation and neural networks

This work describes a study of the application of a neural network to determine the presence of explosives using the neutron capture prompt gamma-ray spectra of the substances as patterns which were simulated via Monte Carlo N-particle transport code, version 4B. After the training of the neural networks, it was possible to determine the presence of the C-4 explosive, even when they were occluded by several materials. The neural network was a powerful tool, able to recognize prompt gamma-ray explosive patterns in spite of the presence of occluding materials. Besides that, the network was able to generalize, identify the presence of explosive in cases in which it had not been trained. In that way, it was revealed as a potential tool for in situ inspection systems.