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At least 487 records · Page 27

The Synthetic Biology Open Language (SBOL) Version 3: Simplified Data Exchange for Bioengineering

The Synthetic Biology Open Language (SBOL) is a community-developed data standard that allows knowledge about biological designs to be captured using a machine-tractable, ontology-backed representation that is built using Semantic Web technologies. While early versions of SBOL focused only on the description of DNA-based components and their sub-components, SBOL can now be used to represent knowledge across multiple scales and throughout the entire synthetic biology workflow, from the specification of a single molecule or DNA fragment through to multicellular systems containing multiple interacting genetic circuits. The third major iteration of the SBOL standard, SBOL3, is an effort to streamline and simplify the underlying data model with a focus on real-world applications, based on experience from the deployment of SBOL in a variety of scientific and industrial settings. Here, we introduce the SBOL3 specification both in comparison to previous versions of SBOL and through practical examples of its use.

59 BASIC BIOLOGICAL SCIENCES↗

Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation

Viruses influence global patterns of microbial diversity and nutrient cycles. Though viral metagenomics (viromics), specifically targeting dsDNA viruses, has been critical for revealing viral roles across diverse ecosystems, its analyses differ in many ways from those used for microbes. To date, viromics benchmarking has covered read pre-processing, assembly, relative abundance, read mapping thresholds and diversity estimation, but other steps would benefit from benchmarking and standardization. Here we use in silico-generated datasets and an extensive literature survey to evaluate and highlight how dataset composition (i.e., viromes vs bulk metagenomes) and assembly fragmentation impact (i) viral contig identification tool, (ii) virus taxonomic classification, and (iii) identification and curation of auxiliary metabolic genes (AMGs). The in silico benchmarking of five commonly used virus identification tools show that gene-content-based tools consistently performed well for long (≥3 kbp) contigs, while k -mer- and blast-based tools were uniquely able to detect viruses from short (≤3 kbp) contigs. Notably, however, the performance increase of k -mer- and blast-based tools for short contigs was obtained at the cost of increased false positives (sometimes up to ~5% for virome and ~75% bulk samples), particularly when eukaryotic or mobile genetic element sequences were included in the test datasets. Furthermore, for viral classification, variously sized genome fragments were assessed using gene-sharing network analytics to quantify drop-offs in taxonomic assignments, which revealed correct assignations ranging from ~95% (whole genomes) down to ~80% (3 kbp sized genome fragments). A similar trend was also observed for other viral classification tools such as VPF-class, ViPTree and VIRIDIC, suggesting that caution is warranted when classifying short genome fragments and not full genomes. Finally, we highlight how fragmented assemblies can lead to erroneous identification of AMGs and outline a best-practices workflow to curate candidate AMGs in viral genomes assembled from metagenomes. Together, these benchmarking experiments and annotation guidelines should aid researchers seeking to best detect, classify, and characterize the myriad viruses ‘hidden’ in diverse sequence datasets.

59 BASIC BIOLOGICAL SCIENCES↗

HTGR Validation: NEUP Survey and Database - Data Reporting Standard for HTGR Thermal-Fluid Experiments

Since 2009, the U.S. Department of Energy (DOE) Office of Nuclear Energy's Nuclear Energy University Program (NEUP) has been at the forefront of nuclear research, specifically concentrating on advancing high-temperature gas-cooled reactor (HTGR) technologies. By Fiscal Year 2024, NEUP has authorized 36 projects dedicated to HTGR research, each contributing significantly to the enhancement of our understanding of this technology. The outcomes of these diverse projects have been disseminated through final NEUP reports, peer-reviewed journal articles, and presentations at academic conferences, forming a comprehensive tapestry of knowledge. Despite the substantial value of these findings, their dissemination has been fragmented, posing challenges for accessibility to researchers and policymakers and leading to underutilization of DOE investments. Recognizing this critical gap and its potential consequences for the future of nuclear research, the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program conducted an extensive survey of completed and ongoing HTGR NEUP projects. This survey enabled the compilation of crucial data, resulting in the development of a specialized public-access database tailored for computational fluid dynamics and system code validation, specifically designed for HTGR applications. However, the data collection process revealed a significant challenge in central data organization due to individual researchers from different institutes employing varying logics and preferences for recording and documenting experimental data. Consequently, an urgent need has been identified to establish a standardized reporting format for HTGR experimental projects. Addressing this issue is essential for enhancing collaboration, maximizing the impact of DOE investments, and ensuring the seamless advancement of HTGR technologies in nuclear research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Whole core analysis of OECD/NEA TVA-WB1 benchmark exercise 1 using continuous-energy Monte Carlo code MVP with JENDL-4.0u and ENDF/B-VII.0

The TVA WB1 benchmark problem was precisely modeled in accordance with the geometry and material specifications, and benchmark exercise 1 was solved with the MVP code and the nuclear data libraries based on JENDL-4.0u (JENDL-4.0 updated file) and ENDF/B-VII.0. The criticality, the control rod bank worth, the isothermal temperature coefficient (ITC), the integral rod worth of bank D, and differential soluble boron worth (DBW) were obtained. The criticality and the control rod bank worth were compared with the measured data and published calculation results with other codes, Serpent and KENO. The criticality and the control rod bank worth calculated by MVP and the libraries agree with the measured and the published calculation results within the criteria specified in the ANSI/ANS standard. From these results, the calculation model for the MVP and the libraries was verified. The other parameters such as ITC, the integral rod worth, and DBW were also compared between JENDL-4.0u and ENDF/B-VII.0. The comparison of the results shows JENDL-4.0u and ENDF/B-VII.0 give comparable results within the standard deviation, the difference between libraries is small. (author)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

INTERSECT Architecture Specification: Microservice Architecture (V.0.5)

Oak Ridge National Laboratory (ORNL)’s Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) architecture project, titled “An Open Federated Architecture for the Laboratory of the Future”, creates an open federated hardware/software architecture for the laboratory of the future using a novel system of systems (SoS) and microservice architecture approach, connecting scientific instruments, robot-controlled laboratories and edge/center computing/data resources to enable autonomous experiments, “self-driving” laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The project describes science use cases as design patterns that identify and abstract the involved hardware/software components and their interactions in terms of control, work and data flow. It creates a SoS architecture of the federated hardware/software ecosystem that clarifies terms, architectural elements, the interactions between them and compliance. It further designs a federated microservice architecture, mapping science use case design patterns to the SoS architecture with loosely coupled microservices, standardized interfaces and multi programming language support. The primary deliverable of this project is an INTERSECT Open Architecture Specification, containing the science use case design pattern catalog, the federated SoS architecture specification and the microservice architecture specification. This document represents the microservice architecture specification of the INTERSECT Open Architecture Specification.

97 MATHEMATICS AND COMPUTING↗

INTERSECT Architecture Specification: Microservice Architecture (V.0.9)

Oak Ridge National Laboratory (ORNL)’s Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) architecture project, titled “An Open Federated Architecture for the Laboratory of the Future”, creates an open federated hardware/software architecture for the laboratory of the future using a novel system of systems (SoS) and microservice architecture approach, connecting scientific instruments, robot-controlled laboratories and edge/center computing/data resources to enable autonomous experiments, “self-driving” laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The project describes science use cases as design patterns that identify and abstract the involved hardware/software components and their interactions in terms of control, work and data flow. It creates a SoS architecture of the federated hardware/software ecosystem that clarifies terms, architectural elements, the interactions between them and compliance. It further designs a federated microservice architecture, mapping science use case design patterns to the SoS architecture with loosely coupled microservices, standardized interfaces and multi programming language support. The primary deliverable of this project is an INTERSECT Open Architecture Specification, containing the science use case design pattern catalog, the federated SoS architecture specification and the microservice architecture specification. This document represents the microservice architecture specification of the INTERSECT Open Architecture Specification.

97 MATHEMATICS AND COMPUTING↗

INTERSECT Architecture Specification: Use Case Design Patterns (V.0.5)

Oak Ridge National Laboratory (ORNL)’s Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) architecture project, titled “An Open Federated Architecture for the Laboratory of the Future”, creates an open federated hardware/software architecture for the laboratory of the future using a novel system of systems (SoS) and microservice architecture approach, connecting scientific instruments, robot-controlled laboratories and edge/center computing/data resources to enable autonomous experiments, “self-driving” laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The project describes science use cases as design patterns that identify and abstract the involved hardware/software components and their interactions in terms of control, work and data flow. It creates a SoS architecture of the federated hardware/software ecosystem that clarifies terms, architectural elements, the interactions between them and compliance. It further designs a federated microservice architecture, mapping science use case design patterns to the SoS architecture with loosely coupled microservices, standardized interfaces and multi programming language support. The primary deliverable of this project is an INTERSECT Open Architecture Specification, containing the science use case design pattern catalog, the federated SoS architecture specification and the federated microservice architecture specification. This document represents the science use case design pattern catalog of the INTERSECT Open Architecture Specification.

42 ENGINEERING↗

Development and cross‐validation of a circumference‐based predictive equation to estimate body fat in an active population

Abstract Objective The U.S. Army uses sex‐specific circumference‐based prediction equations to estimate percent body fat (%BF) to evaluate adherence to body composition standards. The equations are periodically evaluated to ensure that they continue to accurately assess %BF in a diverse population. The objective of this study was to develop and validate alternative field expedient equations that may improve upon the current Army Regulation (AR) body fat (%BF) equations. Methods Body size and composition were evaluated in a representatively sampled cohort of 1904 active‐duty Soldiers (1261 Males, 643 Females), using dual‐energy X‐ray absorptiometry (%BF DXA ), and circumferences obtained with 3D imaging and manual measurements. Sex stratified linear prediction equations for %BF were constructed using internal cross validation with %BF DXA as the criterion measure. Prediction equations were evaluated for accuracy and precision using root mean squared error, bias, and intraclass correlations. Equations were externally validated in a convenient sample of 1073 Soldiers. Results Three new equations were developed using one to three circumference sites. The predictive values of waist, abdomen, hip circumference, weight and height were evaluated. Changing from a 3‐site model to a 1‐site model had minimal impact on measurements of model accuracy and performance. Male‐specific equations demonstrated larger gains in accuracy, whereas female‐specific equations resulted in minor improvements in accuracy compared to existing AR equations. Equations performed similarly in the second external validation cohort. Conclusions The equations developed improved upon the current AR equation while demonstrating robust and consistent results within an external population. The 1‐site waist circumference‐based equation utilized the abdominal measurement, which aligns with associated obesity related health outcomes. This could be used to identify individuals at risk for negative health outcomes for earlier intervention.

Taylor, Kathryn M.↗

Natural Abundance Isotope Ratio Measurements of Organic Molecules Using 21 T FTICR MS

Subtle variations in stable isotope ratios at natural abundance are challenging to measure but can yield critical insights into biological, physical, and geochemical processes. Well established methods, particularly multi-collector, gas-source or plasma isotope ratio mass spectrometry (IRMS) are the gold standard for stable isotope measurement but inherent limitations in these approaches make them ill-suited to determining site-specific and multiply substituted isotopic abundances of all but a few compounds, or to characterizing mixtures or larger intact molecules. Additionally, Fourier transform mass spectrometry (FTMS), namely Orbitrap mass spectrometry, has recently demonstrated the ability to measure natural abundance isotope ratios with chemically informative accuracy and precision. Here, we report the first use of Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) for the accurate (<1‰) and precise (<1‰ standard error) simultaneous determination of $δ$ 13 C and $δ$ 15 N in caffeine isotopologues and provide a discussion of the critical instrumental parameters necessary to make such measurements. Finally, we report the ability to make these measurements with online liquid chromatography, expanding the ability of this technique to explore mixtures in the future.

07 ISOTOPE AND RADIATION SOURCES↗

Determination of Scale Bar for AGHCF Metallography Data

The DOE Nuclear Energy Advanced Reactor Technologies (ART) Fast Reactor Program (FRP) has supported the development of several databases containing information on the safety performance of fast reactors, components, and fuels. This growing collection of legacy experimental data, operating data, and analysis is available online to registered users. Metallography data represents one of the most critical types of post-irradiation examination (PIE) data being collected, organized, and archived in several ART Fast Reactor Databases (https://frdb.ne.anl.gov), including the Metallic Fuels Irradiation & Physics Database (FIPD), Out-of-Pile Transient Database (OPTD), and TREAT (the Transient Reactor Test Facility) Experimental Relational Database (TREXR). These databases contain three principal sets of metallography data. The first set comprises metallography data from Experimental Breeder Reactor-II (EBR-II) and Fast Flux Test Facility (FFTF) irradiated fuel pins examined in the Hot Fuel Examination Facility (HFEF). The second set consists of metallography data from EBR-II irradiated fuel pins examined in the Alpha-Gamma Hot Cell Facility (AGHCF). The third set includes metallography data from transient-tested fuel pins (including both out-of-pile furnace tests and TREAT tests) examined in AGHCF. Since both the second and third sets were generated in AGHCF, they are governed by identical specifications. The metallography data in the databases consist of digital images scanned from either positive or negative photographic films. To analyze the microstructure of a fuel pin, a series of preparatory steps are required, including sectioning, epoxy mounting, mechanical grinding and polishing, and etching. Following sample preparation, specimens are transferred for metallographic examination. The AGHCF and HFEF metallography data were generated using optical microscopes manufactured by Leitz and Bausch and Lomb (B&L). Images were recorded on Polaroid film at preset magnifications. Magnification verification for the Leitz and B&L metallographs was conducted every two months prior to 1989 and at least every six months from 1989 through the conclusion of the IFR program. Magnifications determined from imaging of microslide standards were compared to the instrument settings for magnifications ranging from 50× to 500×. If the magnifications determined from standards deviated from the instrument settings, adjustments were made to the bellows extension until agreement was achieved. The specifications for AGHCF and HFEF legacy metallography data have been established based on available hard-copy and digital records, most of which have been incorporated into the data repositories associated with FIPD, OPTD, and TREXR. Detailed specifications including hard-copy records, digitized records, cutting diagrams and sectioning schemes, high-magnification photographs, photomosaics (composites), information tags, scale bars, and magnification verification procedures can be found in a separate report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Comprehensive Assessment of On-And Off-Board Vehicle-To-Grid Technology Performance and Impacts on Battery and the Grid

This project defined, developed, and tested the open standards-based requirements, engineering design and system integration of on and off-vehicle Vehicle-to-Grid technologies both on the grid and on the PEV, to assess their effectiveness in implementing the use cases that create value for the grid, which in turn, can be passed on to the ratepayers and the PEV owners. The project comprised of three key categories of work and four key sub-areas of work. The three key categories were: On-Vehicle V2G, Off-Vehicle V2G, and impact of V2G operation on the battery capacity degradation. The four key sub-areas of work under each of these categories were: defining requirements, implementing the technology, performing system integration testing, and estimating the value of each of the grid services under specific assumptions, on a per-vehicle and on an aggregated basis. The technical implementation demonstrated the validity of standards-based approach to grid integration that led to interoperability, in addition to assessing the operational details with grid constraints imposed at the transformer level. The technology implementation also identified the subtle gaps in the standards definition to close the feedback loop on the accuracy of the standards as written, which are being implemented as revisions to the appropriate protocols. The battery impacts assessment developed a test cycle that the batteries from a real PHEV were subjected to for both the mobility-only and mobility with V2G specific energy cycling. While the battery impact results show a clear incremental degradation in response to additional throughput for V2G application purposes, the amount of additional kWh that can be made available without exceeding the end-of-life capacity definition of the battery at its 10-year warranty period was found to be significant. Given that the PEV battery being exercised during testing was a PHEV battery (smaller energy capacity), and 44% of its usable energy (i.e., SOC) was utilized daily for V2G applications, the EVs with much larger batteries will fare much better, either in terms of extracting more value in terms of incremental kWh for V2G, or in terms of relative incremental degradation of the capacity through the battery lifespan. Further, this battery was the second-generation Lithium-Ion chemistry circa 2015, which is at least two generations ago. Continual improvements in electrochemistry and manufacturing techniques as well as on-board capacity will enable the future batteries to provide even more energy for non-mobility-related services. Finally, the valuation of V2G energy services at the premise, distribution, and the ISO/market level was carried out for both the on-vehicle and off-vehicle cases, to understand both the GHG mitigation and operational efficiency improvements in quantitative terms. The analysis indicates that between $\$400$ and $\$1400$ per year of total value to the grid can be realized. When netted of costs to implement V2G either on or off-vehicle, the net value is available to be shared between the ratepayers and the EV owners. Over the life of the EV, therefore, this value becomes significant and can easily provide both ratepayer and EV owner benefits more than the cost of the equipment, either on or off-board, in addition to providing GHG mitigation benefits both on the grid and on the mobility sides. For these benefits to accrue, the key learnings from both the on- and off-vehicle V2G parts of the project indicate the need for at-scale demonstrations through involvement of real EV owners to validate both the technical feasibility, interoperability, as well as real grid benefits by performing extensive data collection and analysis. This will help inform the grid planners, the program designs, and tariff designers, as well as automotive and equipment manufacturers how best to create their products to maximize grid, ratepayer, and EV owner value.

30 DIRECT ENERGY CONVERSION↗

Bounding Pressure and Flammability Evaluations for a Department of Energy Standard Canister Loaded with Aluminum-Clad Spent Fuel

This report presents bounding pressurization and flammability evaluations from the radiolytic gas generation expected during extended (>50 years) dry storage of aluminum-clad spent nuclear fuel (ASNF) elements in a sealed Department of Energy (DOE) Standard Canister. The primary questions involving extended ASNF dry storage center around the adequacy of dry storage conditioning processes (i.e., drying) and the behavior of residual hydrated aluminum oxides on the cladding—specifically, the radiolytic breakdown of chemically bound water in these corrosion products. The objectives of the presented work include providing a bounding assessment of the pressure with respect to the DOE Standard Canister’s structural integrity limits and identifying the potential for forming flammable or explosive gas mixtures (i.e., exceedance of the lower flammability limit of the molecular hydrogen [H2] and oxygen [O2] concentrations). The evaluation results confirm the findings of previous, more complex M&S work. That is, the structural integrity of the canister remains unchallenged by a wide margin. Nevertheless, it is important to recognize that the presented pressure calculations consider a full breakdown of the chemisorbed water, including a consequent release of all available H2. In reality, the breakdown of water in these systems will likely remain incomplete, due to competing chemical and radiolytic reactions, thereby attaining an equilibrium in the storage environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Data for Greenhouse Gas Accounting Procedures in Low Carbon Fuel Policies Overlook the Spatial Variability of Miscanthus-Derived Sustainable Aviation Fuel

Low carbon fuel policies such as the U.S. Renewable Fuel Standard (RFS), Canada Clean Fuel Regulations (CFR), and California Low Carbon Fuel Standard (LCFS) as well as the 45Z tax credit are intended to reduce greenhouse gas (GHG) emissions from transportation. Cellulosic feedstocks, optimized biorefineries, and favorable farming locations can significantly reduce biofuel carbon intensity (CI). Despite advances in field-to-fuel GHG monitoring and flexibility in resource allocation within biorefineries (e.g., governing net electricity production), rigid CI accounting procedures in current policies may limit CI responsiveness across candidate sites and processing facilities. This work examines a hypothetical biomass-to-sustainable aviation fuel (SAF) pathway using miscanthus and alcohol-to-jet (i) to demonstrate how GHG accounting requirements drive estimates of biofuel CIs and (ii) to explore potential CI and financial implications of scenario-specific life cycle assessment (LCA). Results demonstrate that GHG accounting using the CFR/LCFS can reasonably account for distinct levels of net electricity production by a biorefinery, but only the CFR yields similar CI sensitivity to spatially explicit factors (feedstock CI, grid electricity CI) as scenario-specific LCA: most GHG accounting frameworks do not capture CI variation across candidate sites in the United States. Ultimately, this work demonstrates the importance of LCA methodological specifications in low carbon fuel policies and tax credits.

Miscanthus↗

Classification of events from α -induced reactions in the MUSIC detector via statistical and ML methods

The Multi-Sampling Ionization Chamber (MUSIC) detector is typically used to measure nuclear reaction cross sections relevant for nuclear astrophysics, fusion studies, and other applications. From the MUSIC data produced in one experiment scientists carefully extract an order of 10 3 events of interest from about 10 9 total events, where each event can be represented by an 18-dimensional vector. However, the standard data classification process is based on expert driven, manually intensive data analysis techniques that require several months to identify patterns and classify the relevant events from the collected data. Here, to address this issue, we present a method for the classification of events originating from specific α-induced reactions by combining statistical and machine learning methods that require significantly less input from the domain scientist, relative to the standard technique. Here, we applied the new method to two experimental data sets and compared our results with those obtained using traditional methods. With few exceptions, the number of events classified by our method agrees within ±20% with the results obtained using traditional methods. With the present method, which is the first of its kind for the MUSIC data, we have established the foundation for the automated extraction of physical events of interest from experiments using the MUSIC detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A priori error analysis of high-order LL* (FOSLL*) finite element methods

A number of non-standard finite element methods have been proposed in recent years, each of which derives from a specific class of PDE-constrained norm minimization problems. The most notable examples are LL* methods. In this work, we argue that all high-order methods in this class should be expected to deliver substandard uniform h-refinement convergence rates. In fact, one may not even see rates proportional to the polynomial order p > 1 when the exact solution is a constant function. Here, we show that the convergence rate is limited by the regularity of an extraneous Lagrange multiplier variable which naturally appears via a saddle-point analysis. In turn, limited convergence rates appear because the regularity of this Lagrange multiplier is determined, in part, by the geometry of the domain. Numerical experiments support our conclusions.

97 MATHEMATICS AND COMPUTING↗

Electrocoagulation in Water Treatment: Targeted Contaminant Removal and Laboratory Best Practices

Electrocoagulation for water treatment offers many advantages over traditional treatment technologies, including improved energy efficiency and modularity. One challenge with electrocoagulation is the lack of standardization in the methodology and reporting. This review provides a novel contribution by examining the past literature using a uniform metric (charge loading) as a basis for comparison, highlighting the importance of uniform reporting practices in this field. Furthermore, this review provides practical guidance for experimentalists in standardizing the electrocoagulation design and operating procedures. First, we present a comprehensive overview of contaminant-specific electrocoagulation as an electrochemical treatment technology for processing industrial, municipal, and agricultural water, with a focus on aluminum and iron electrocoagulation. We detail the fundamental mechanisms that allow for constituent removal during pretreatment. Specifically, we highlight electrocoagulation’s potential for organics, metalloids, microbes, and hardness remediation, examining the optimal removal conditions in terms of charge loading and current density. We conclude this work with some experimental best practices for lab-scale electrocoagulation experiments.

aluminum↗

Solid, structured composite neutron detectors with high dynamic range capability

Neutron detectors are essential across disciplines such as fundamental science, nuclear security, safeguards, and civilian applications. While 3 He-filled gas proportional counters have long been revered for their efficacy in detecting thermal neutrons and praised for their efficiency, neutron/gamma discrimination, and stability, the scarcity of 3He has spurred a search for alternatives. Here, we explore a solid structured scintillating particle composite (SPC) consisting of 6 Li-containing scintillating glass particles within an acrylic matrix as a neutron detector for high dynamic range applications. We show for the first time that an SPC neutron detector can boast an intrinsic detection efficiency of 0.261% for pure 252 Cf fission neutrons and an overall neutron detection efficiency of (0.546 ± 0.003)% at the Neutron Free-in-Air facility while being able to function in an intense gamma-ray environment. We also show that the SPC neutron detector supports fast neutron capture times and enables a dual-readout scheme that extends the detector dynamic range to high incident neutron fluxes. A scalable fabrication process allows for tailoring the SPC detector properties to the requirements of specific applications. Good agreement is found between the experimental results taken with a National Institute of Standards and Technology traceable 252 Cf source and the coupled MCNP6 and optical-ray-tracing simulations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Element differentiation with a Hartmann- based X-ray phase imaging system

Significant efforts are currently ongoing in X-ray imaging to provide multimodal imaging systems, targeting better sensitivity and specificity for both biomedical or non-destructive testing applications. Knowing the elemental composition of specific structures, such as breast microcalcifications in mammography, would help to differentiate malign and benign tumours. Standard X-ray Phase Contrast Imaging techniques provide only qualitative information on elements with similar absorption properties. However, their chemical composition can be determined from the measurement of the phase as it is directly related to the optical index of elemental materials. We will show new experimental results obtained with an X-ray phase imaging system based on a Hartmann mask. Early data treatment succeeded in retrieving both the real and imaginary parts of the refractive index. The system demonstrates the capability to discriminate materials based on elemental composition.

36 MATERIALS SCIENCE↗