Time-Resolved Neutron Bragg-Edge Imaging: A Case Study by Observing Martensitic Phase Formation in Low Temperature Transformation (LTT) Steel during GTAW

Polychromatic and wavelength-selective neutron transmission radiography were applied during bead-on-plate welding on 5 mm thick sheets on the face side of martensitic low transformation temperature (LTT) steel plates using gas tungsten arc welding (GTAW). The in situ visualization of austenitization upon welding and subsequent α’-martensite formation during cooling could be achieved with a temporal resolution of 2 s for monochromatic imaging using a single neutron wavelength and of 0.5 s for polychromatic imaging using the full spectrum of the beam (white beam). The spatial resolution achieved in the experiments was approximately 200 µm. The transmitted monochromatic neutron beam intensity at a wavelength of λ = 0.395 nm was significantly reduced during cooling below the martensitic start temperature Ms since the emerging martensitic phase has a ~10% higher attenuation coefficient than the austenitic phase. Neutron imaging was significantly influenced by coherent neutron scattering caused by the thermal motion of the crystal lattice (Debye–Waller factor), resulting in a reduction in the neutron transmission by approx. 15% for monochromatic and by approx. 4% for polychromatic imaging.

3D Isotope Density Measurements by Energy-Resolved Neutron Imaging

Tools for three-dimensional elemental characterization are available on length scales ranging from individual atoms, using electrons as a probe, to micrometers with X-rays. However, for larger volumes up to millimeters or centimeters, quantitative measurements of elemental or isotope densities were hitherto only possible on the surface. Here, a novel quantitative elemental characterization method based on energy-resolved neutron imaging, utilizing the known neutron absorption cross sections with their ‘finger-print’ absorption resonance signatures, is demonstrated. Enabled by a pixilated time-of-flight neutron transmission detector installed at an intense short-pulsed spallation neutron source, for this demonstration 3.25 million state-of-the-art nuclear physics neutron transmission analyses were conducted to derive isotopic densities for five isotopes in 3D in a volume of 0.25 cm3. The tomographic reconstruction of the isotope densities provides elemental maps similar to X-ray microprobe maps for any cross-section in the probed volume. The bulk isotopic density of a U-20Pu-10Zr-3Np-2Am nuclear transmutation fuel sample was measured, agrees well with mass-spectrometry and is evidence of the accuracy of the method.

Glass Transition in Rice Pasta as Observed by Combined Neutron Scattering and Time-Domain NMR

Experimental protocols aiming at the characterisation of glass transition often suffer from ambiguity. The ambition of the present study is to describe the glass transition in a complex, micro heterogeneous system, the dry rice pasta, in a most unambiguous manner, minimising the influence of technique-specific bias. To this end, we apply an unprecedented combination of experimental techniques. Apart from the usually used NMR and DSC, we employ, in a concurrent manner, neutron transmission, diffraction, and Compton scattering. This enables us to investigate the glass transition over a range of spatio-temporal scales that stretches over seven orders of magnitude. The results obtained by neutron diffraction and DSC reveal that dry rice pasta is almost entirely amorphous. Moreover, the glass transition is evidenced by neutron transmission and diffraction data and manifested as a significant decrease of the average sample number density in the temperature range between 40 and 60 °C. At the microscopic level, our NMR, neutron transmission and Compton scattering results provide evidence of changes in the secondary structure of the starch within the dry rice pasta accompanying the glass transition, whereby the long-range order provided by the polymer structure within the starch present in the dry rice pasta is partially lost.

Application of Machine Learning Methods to Neutron Transmission Spectroscopic Imaging for Solid–Liquid Phase Fraction Analysis

In neutron transmission spectroscopic imaging, the transmission spectrum of each pixel on a two-dimensional detector is analyzed and the real-space distribution of microscopic information in an object is visualized with a wide field of view by mapping the obtained parameters. In the analysis of the transmission spectrum, since the spectrum can be classified with certain characteristics, it is possible for machine learning methods to be applied. In this study, we selected the subject of solid–liquid phase fraction imaging as the simplest application of the machine learning method. Firstly, liquid and solid transmission spectra have characteristic shapes, so spectrum classification according to their fraction can be carried out. Unsupervised and supervised machine learning analysis methods were tested and evaluated with simulated datasets of solid–liquid spectrum combinations. Then, the established methods were used to perform an analysis with actual measured spectrum datasets. As a result, the solid–liquid interface zone was specified from the solid–liquid phase fraction imaging using machine learning analysis.

A novel method to obtain integral parameters of the orientation distribution function of textured polycrystals from wavelength-resolved neutron transmission spectra

A novel method to estimate integral parameters of the orientation distribution function (ODF) in textured polycrystals from the wavelength-resolved neutron transmission is presented. It is based on the expression of the total coherent elastic cross section as a function of the Fourier coefficients of the ODF. This method is broken down in detail for obtaining Kearns factors in hexagonal crystals, and other material properties that depend on the average of second- and fourth-rank tensors. The robustness of the method against three situations was analyzed: effects of sample misalignment, of cutoff value l max of the series expansion and of experimental standard deviation. While sample misalignment is shown not to be critical for the determination of Kearns factors and second-order-rank properties, it can be critical for fourth-rank and higher-order tensor properties. The effect of the cutoff value on the method robustness is correlated to the standard deviation of the experimental data. In order to achieve a good estimation of the Fourier coefficients, it is recommended that the experimental standard deviation be around 3–5% of the total scattering cross section of the material for the method to be stable. The method was applied for the determination of Kearns factors from transmission measurements performed at the instrument ENGIN-X (ISIS) on a Zr–2.5 Nb pressure tube along two sample directions and was shown to be able to estimate Kearns factors with an error below 5%.