Determination of Thermal Neutron Cross Section and Resonance Integral for 64Zn (n, γ) 65Zn Reaction by Activation Method
Keywords:
Thermal neutron cross section, Resonance integrals, monitor and Nigerian Research Reactor-1 (NIRR-1)Abstract
Abstract: Despite the growing availability of resonance integral data for stable nuclides, several isotopes produced via (n,γ) reactions still lack precise or consistent experimental data. Accurate nuclear data are essential for reactor physics, neutron flux characterization, and analytical applications. This study reports the thermal neutron cross section and resonance integral of the ⁶⁴Zn(n,γ)⁶⁵Zn reaction, measured using the activation method at the Nigerian Research Reactor-1 (NIRR-1), Ahmadu Bello University, Zaria. High-purity powdered ZnO samples were irradiated under both bare and 1-mm cadmium-covered conditions to separate thermal and epithermal neutron contributions. A monitor with a well-known neutron cross section was used as a single comparator to minimize neutron self-shielding and to quantify zinc concentration. Irradiated samples were measured using a calibrated p-type high-purity germanium (HPGe) detector at a source-to-detector distance of 2.2 cm. The thermal neutron cross section of the ⁶⁴Zn(n,γ)⁶⁵Zn reaction was determined to be 0.726 ± 0.02 barn, while the resonance integral was found to be 1.47 ± 0.05 barn at a cadmium cut-off energy of 0.55 eV. The cadmium ratio (R_Cd) was measured as 7.01 ± 0.99, consistent with previous work in other NIRR-1 channels. These results agree well with evaluated nuclear data, such as 0.726 ± 0.02 barn (De Corte and Simonits, 2003), 0.76 ± 0.02 barn (Mughabghab, 2003), and 1.45–1.428 barn for the resonance integral from various libraries, while earlier experimental cross sections ranged from 0.72 ± 0.04 to 1.23 ± 0.12 barn and resonance integrals from 0.76 ± 0.08 to 3.10 ± 0.02 barn.The agreement of measured activities, cadmium ratio, and derived cross sections demonstrates the stability of the thermal neutron flux and the high analytical capability of the NIRR-1 LEU core. The results provide reliable nuclear data for ⁶⁴Zn and validate the use of powdered ZnO as a monitor in thermal neutron activation studies.
Downloads
Published
Issue
Section
Similar Articles
- Christopher Ejeomo, Ufuomaefe Oghoje, Composition and Distribution of Polynuclear Aromatic Hydrocarbons Contamination in Surficial Coastal Sediments from Odidi Area of Delta State, Nigeria , Communication In Physical Sciences: Vol. 11 No. 4 (2024): VOLUME 11 ISSUE 4
- Osaghae Edgar O, Obi Jonathan Chukwuyeni, Solving towers of Hanoi problem using 2-Consecutive moves Algorithm , Communication In Physical Sciences: Vol. 10 No. 3: VOLUME 10 ISSUE 3 (2023-2024)
- Humphrey Sam Samuel, Ugo Nweke-Maraizu, Gani Johnson, Emmaneul Etim Etim, A Review of Theoretical Techniques in Corrosion Inhibition Studies , Communication In Physical Sciences: Vol. 9 No. 4 (2023): VOLUME 9 ISSUE 4
- Taiwo Toyosola Ositimehin, AI-Driven Human Resource Management and Its Role in Sustainable Human Capital Development , Communication In Physical Sciences: Vol. 11 No. 4 (2024): VOLUME 11 ISSUE 4
- Helen O. Chukwuemeka-okorie, Ifeanyi Otukere, Kovo Akpomie, Isotherm, Kinetic and thermodynamic investigation on the biosorptive removal of Pb (II) ion from solution onto biochar prepared from breadfruit seed hull , Communication In Physical Sciences: Vol. 12 No. 3 (2025): VOLUME 12 ISSUE 3
- Ajogwu Cordelia Odinaka, Aaron Auduson, Tope Alege, Yusuf Odunsanwo, Formation Evaluation Using Integrated Petrophysical Data Analysis of Maboro Field Niger Delta Sedimentary Basin, Nigeria , Communication In Physical Sciences: Vol. 11 No. 3 (2024): VOLUME 11 ISSUE 3
- Olaleye Ibiyeye, Joy Nnenna Okolo, Samuel Adetayo Adeniji, A Comprehensive Evaluation of AI-Driven Data Science Models in Cybersecurity: Covering Intrusion Detection, Threat Analysis, Intelligent Automation, and Adaptive Decision-Making Systems , Communication In Physical Sciences: Vol. 8 No. 4 (2022): VOLUME 8 ISSUE 4
- Samuel A. Egu, Akachukwu Ibezim, Efeturi A. Onoabedje, Uchechukwu C. Okoro, N-Myristoyl Transferase Inhibitors with Antifungal Activity in Quinolinequinone Series: Synthesis, In-silico Evaluation and Biological Assay , Communication In Physical Sciences: Vol. 5 No. 4 (2020): VOLUME 5 ISSUE 4
- Irene Edem Johncross, Fanifosi Seyi Josiah, Abidemi Obatoyinbo Ajayi, Resource recovery from Sugar Cane Biomass for the Synthesis of Silicon Nanoparticles , Communication In Physical Sciences: Vol. 12 No. 1 (2024): VOLUME 12 ISSUE 1
- Joy Nnenna Okolo, A Review of Machine and Deep Learning Approaches for Enhancing Cybersecurity and Privacy in the Internet of Devices , Communication In Physical Sciences: Vol. 9 No. 4 (2023): VOLUME 9 ISSUE 4
You may also start an advanced similarity search for this article.



