Neutrons and X-rays provide excellent complementary, nondestructive probes to understand internal structure of systems across engineering and material science. With its sensitivity to hydrogen, neutrons excel at separating fluids, such as water or oil, from solid and gas phases in three-phase systems whereas X-rays excel at identifying the solid phase. To fully leverage the complementarity of the two methods, the National Institute of Standards and Technology (NIST) has developed the Neutron and X-ray Tomography (NeXT) system which orients a microfocus X-ray generator orthogonally to a reactor sourced thermal neutron beam. This orientation allows for truly simultaneous acquisition of both modalities so that the multi-modal data sets of samples that are evolving with time or undergoing stochastic processes can be directly correlated. The NeXT system has been available for external researchers since 2015 through the NIST Center for Neutron Research user facility program. Significant efforts have resulted in distributable software packages to facilitate image denoising, tomography reconstruction, volume registration, and bivariate histogram segmentation. This paper will give an overview of the NeXT system, explain the process for bivariate histogram segmentation, and provide several examples of use cases for the system.
The NIST Neutron and X-ray Tomography (NeXT) system provides simultaneous, complementary, multimodal information for the characterization of materials. Neutrons and X-rays yield complementary, non-destructive views of a complex system due to the contrast differences that arise from the differences in interaction with matter for the two modes. The NeXT system orients a 90 keV microfocus X-ray tube orthogonally to the thermal neutron beam. This enables truly simultaneous capture of the two modalities, thus it is possible to perform multimodal tomography of dynamic or stochastic samples while penetrating through sample environment equipment such as pressure and flow vessels. NIST has developed and continues to update distributable software for reconstructing and analyzing the multimodal datasets. Tomographic reconstruction offers multiple CPU and GPU based algorithms for parallel and cone beam geometries. Additional analysis routines perform volume registration and region of interest segmentation of the bivariate histogram that leverages the contrast differences between the two modalities. This talk will give an overview of the NeXT system, the algorithm developments underway and provide multiple research applications using the system.
X-rays and neutrons provide complementary non-destructive probes for the analysis of structure and chemical
composition of materials. Contrast differences between the modes arise due to the differences in interaction with matter.
Due to the high sensitivity to hydrogen, neutrons excel at separating liquid water or hydrogenous phases from the
underlying structure while X-rays resolve the solid structure. Many samples of interest, such as fluid flow in porous
materials or curing concrete, are stochastic or slowly changing with time which makes analysis of sequential imaging
with X-rays and neutrons difficult as the sample may change between scans. To alleviate this issue, NIST has developed
a system for simultaneous X-ray and neutron tomography by orienting a 90 keVpeak micro-focus X-ray tube orthogonally
to a thermal neutron beam. This system allows for non-destructive, multimodal tomography of dynamic or stochastic
samples while penetrating through sample environment equipment such as pressure and flow vessels. Current efforts are
underway to develop methods for 2D histogram based segmentation of reconstructed volumes. By leveraging the
contrast differences between X-rays and neutrons, greater histogram peak separation can occur in 2D vs 1D enabling
improved material identification.
Publisher’s Note: This paper, originally published on 5/13/2015, was replaced with a corrected/revised version on 7/1/2015. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance.
Plants exhibit complex responses to changes in environmental conditions such as radiant heat flux, water quality, airborne pollutants, soil contents. We seek to utilize the natural chemical and electrophysiological response of plants to develop novel plant-based sensor networks. Our present work focuses on plant responses to high-energy radiation – with the goal of monitoring natural plant responses for use as benchmarks for detection and dosimetry. For our study, we selected a plants cactus, Arabidopsis, Dwarf mango (pine), Euymus and Azela. We demonstrated that the ratio of Chlorophyll a to Chlorophyll b of the leaves has changed due to the exposure gradually come back to the normal stage after the radiation die.
We used blue laser-induced blue fluorescence-emission spectra to characterize the pigment status of the trees. Upon blue laser excitation (400 nm) leaves show a fluorescence emission in the red spectral region between 650 and 800nm (chlorophyll fluorescence with maxima near 690nm and 735 nm). Sample tree subjects were placed at a distance of 1m from NIST-certified 241AmBe neutron source (30 mCi), capable of producing a neutron field of about 13 mrem/h. This corresponds to an actual absorbed dose of ~ 1 mrad/h.
Our results shows that all plants are sensitive to nuclear radiation and some take longer time to recover and take less. We can use their characteristics to do differential detection and extract nuclear activity information out of measurement results avoid false alarms produced environmental changes. Certainly the ultimate verification can be obtained from genetic information, which only need to be done when we have seen noticeable changes on plant optical spectra, mechanical strength and electrical characteristics.
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