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NASA NTRSDate not supplied

Analysis of the Tropospheric Doppler Radar Wind Profiler Measurement Accuracy

Space launch vehicle trajectory design uses atmospheric winds to determine vehicle performance and structural margin assessments prior to flight. For launches at the United States Space Force’s Eastern Range (ER) at the Cape Canaveral Space Force Station (CCSFS), tropospheric wind measurements come from either in-situ or remote sensing instrumentation. The use of the National Aeronautics and Space Administration’s (NASA) Kennedy Space Center (KSC) 48-MHz Tropospheric Doppler Radar Wind Profiler (TDRWP) has become the primary wind measurement source for several launch vehicles. Extensive evaluations of TDRWP data have occurred to quantify the system performance. This includes quantifying the accuracy of wind estimates over the entire sampling altitude as well as at discrete altitudes. This paper will describe methodology and analyses used to quantify the measurement accuracy of TDRWP data when operating in an alternative mission support mode over a 2-year period from March 2020 to March 2022.

Meghan E Carrico↗
DOE OSTI2025

Instrumentation and methods for efficient time-resolved X-ray crystallography of biomolecular systems with sub-10 ms time resolution

Time-resolved X-ray crystallography has great promise to illuminate structure–function relations and key steps of enzymatic reactions with atomic resolution. The dominant methods for chemically-initiated reactions require complex instrumentation at the X-ray beamline, significant effort to operate and maintain this instrumentation, and enormous numbers (∼10 5 –10 9 ) of crystals per time point. We describe instrumentation and methods that enable high-throughput time-resolved study of biomolecular systems using standard crystallography sample supports and mail-in X-ray data collection at standard high-throughput cryocrystallography synchrotron beamlines. The instrumentation allows rapid reaction initiation by mixing of crystals and substrate/ligand solution, rapid capture of structural states via thermal quenching with no pre-cooling perturbations, and yields time resolutions in the single-millisecond range, comparable to the best achieved by any non-photo-initiated method in both crystallography and cryo-electron microscopy. Our approach to reaction initiation has the advantages of simplicity, robustness, low cost, adaptability to diverse ligand solutions and small minimum volume requirements, making it well suited to routine laboratory use and to high-throughput screening. We report the detailed characterization of instrument performance, present structures of binding of N -acetylglucosamine to lysozyme at time points from 8 ms to 2 s determined using only one crystal per time point, and discuss additional improvements that will push time resolution toward 1 ms.

Indergaard, John A. (ORCID:000000022367699X)↗
NASA NTRS2004

Novel Phenylethynyl Imide Silanes as Coupling Agents for Titanium Alloy

The durability of titanium (Ti) alloys bonded with high temperature adhesives such as polyimides has failed to attain the level of performance required for many applications. The problem to a large part is attributed to the instability of the surface treatment on the Ti substrate. Although Ti alloy adhesive specimens with surface treatments such as chromic acid anodization, Pasa-Jell, Turco, etc. have provided high initial mechanical properties, these properties have decreased as a function of aging at ambient temperature and faster, when aged at elevated temperatures or in a hot-wet environment. As part of the High Speed Civil Transport program where Ti honeycomb sandwich structure must perform for 60,000 hours at 177 C, work was directed to the development of environmentally safe, durable Ti alloy surface treatments.

Park, C.↗
NASA NTRS2003

Advances in Structural Integrity Analysis Methods for Aging Metallic Airframe Structures with Local Damage

Analysis methodologies for predicting fatigue-crack growth from rivet holes in panels subjected to cyclic loads and for predicting the residual strength of aluminum fuselage structures with cracks and subjected to combined internal pressure and mechanical loads are described. The fatigue-crack growth analysis methodology is based on small-crack theory and a plasticity induced crack-closure model, and the effect of a corrosive environment on crack-growth rate is included. The residual strength analysis methodology is based on the critical crack-tip-opening-angle fracture criterion that characterizes the fracture behavior of a material of interest, and a geometric and material nonlinear finite element shell analysis code that performs the structural analysis of the fuselage structure of interest. The methodologies have been verified experimentally for structures ranging from laboratory coupons to full-scale structural components. Analytical and experimental results based on these methodologies are described and compared for laboratory coupons and flat panels, small-scale pressurized shells, and full-scale curved stiffened panels. The residual strength analysis methodology is sufficiently general to include the effects of multiple-site damage on structural behavior.

fatigue-crack growth↗
DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials Using MALAMUTE

Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy, aims to develop and qualify additively-manufactured materials for nuclear applications. The key challenges to these efforts are the microstructural variabilities observed on the AM products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-through-put experimental and modeling techniques to accelerate the qualification efforts. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the AM process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture the microstructural variabilities is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning modeling capabilities to develop a digital twin for AM that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation for AM materials. The melting and subsequent solidification that occurs during the AM process is a complex phenomenon that requires multiscale multiphysics analysis. Idaho National Laboratory’s (INL) Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for AM materials in an efficient, reliable, and cost-effective way. This work package focuses on understanding the role of process variabilities on the various microstructural characteristics of the AM materials. Microstructures unique to AM materials, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. In fiscal year (FY) 24, we significantly advanced upon our work in the last fiscal year, both on physics-based and ML models. The alloy solidification model available in MOOSE has been extended to incorporate the thermodynamic properties and free energy relevant to 316SS. The model demonstrates the Cr segregation that occurs during solidifcation. It is demonstrated that rate of solidification and solute segregation is primarily influence by the cooling rate dictating the level of freezing. This work captures the microstructural variabilities at the subgrain level that are often missing in the part-scale models. With an aim to connect the microstructural evolution model to realistic process conditions, a reduced order model is developed for predicting the thermal conditions around meltpool from high-fidelity process simulations. Furthermore, machine learning approach is used to accelerate the temperature prediction during the AM process. In the following years, MALAMUTE will be used to connect different aspects of the models and quantitatively predict the microstructural evolution. The developed ML-based surrogate model will consider the process conditions as the input to predict the microstructural features in a cost-effective way. The generated microstructures can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work help identify the key microstructural features at the subgrain level that are significant in property/performance prediction of the AM products. This work will provide inputs to the large-scale process variability models to reevaluate and validate assumptions/simplifications made in the part-scale models. Furthermore, through active learning this work will help identify the data need from both modeling and experimental sides for development of a robust digital twin for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Steam-Assisted Selective CO 2 Hydrogenation to Ethanol over Ru–In Catalysts

Multicomponent catalysts can be designed to synergistically combine reaction intermediates at interfacial active sites, but restructuring makes systematic control and understanding of such dynamics challenging. In this work, we unveil how reducibility and mobility of indium oxide species in Ru-based catalysts crucially control the direct, selective conversion of CO 2 to ethanol. When uncontrolled, reduced indium oxide species occupy the Ru surface, leading to deactivation. With the addition of steam as a mild oxidant and using porous polymer layers to control In mobility, Ru–In 2 O 3 interface sites are stabilized, and ethanol can be produced with superior overall selectivity (70 %, rest CO). Our work highlights how engineering of bifunctional active ensembles enables cooperativity and synergy at tailored interfaces, which unlocks unprecedented performance in heterogeneous catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Crack Growth Rate and Fracture Toughness Tests on Irradiated Ex-Plant Materials

The performance of structural materials is critical for the safe and economic operation of light water reactors. Exposed to neutron irradiation during service, the reactor core internal materials can undergo significant microstructural and microchemical changes, leading to irradiation hardening and embrittlement. To ensure the structural integrity and functionality of nuclear reactor components during long-term operation, material degradation and damage mechanisms must be understood and managed adequately. In this work, irradiated materials harvested from the decommissioned Zorita reactor were studied for their cracking susceptibility and fracture resistance as a function of irradiation dose up to 47 displacement per atom (dpa). The material is a Type 304 stainless steel sectioned from the baffle plates of this pressurized water reactor with 38 years of service. Crack growth rate and fracture toughness J-resistance (J-R) curve tests were performed in low-corrosion-potential environments at ~315°C. All samples behaved similarly under cyclic loading, and no deteriorated corrosion-fatigue behavior was observed in the test environments. Under constant stress intensity factors, most samples did not show elevated crack growth rates, suggesting an adequate stress corrosion cracking resistance in the test environments. However, an unstable cracking behavior was observed in a 47-dpa sample, resulting in significantly higher crack growth rates than expected at high stress intensity factors. Crack instability was also observed in a 0.06-dpa sample but did not lead to a sustained high crack growth rate. The impact of neutron irradiation was more evident in the fracture toughness J-R curve tests. As the dose increased, the J-R curve declined considerably and became very shallow at high doses. A fully intergranular fracture morphology was also observed among the high-dose samples ruptured in an air atmosphere at room temperature. This brittle fracture mode in the absence of high temperature water environment confirmed a high degree of embrittlement of this material resulting from its service exposure to neutron irradiation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1991

Contraction ratio effects in a generic sidewall compression scramjet inlet - A computational and experimental investigation

Computed and experimental data on a generic three-dimensional sidewall compression scramjet inlet with a leading edge sweep of 45 degrees at Mach 20 are presented. A three-dimensional Navier-Stokes code was adapted to perform preliminary parametric studies leading to the present configuration. Following the design phase, the code was then employed as an analysis tool to provide a better understanding of the flow field and the experimental static and pitot pressure data. The model possessed 240 static pressure orifices distributed on the forebody plane, sidewalls, and cowl and was tested in the 31 Inch Mach 10 facility at the NASA Langley Research Center. Pitot rakes were employed to map the entrance and exit planes. The contraction ratio was observed to have a dominant effect on the inlet shock structure and performance; these effects are the emphasis of the present report. In addition to pressure measurements, oil flows were used for further visualization and comparison with computation.

Holland, Scott D.↗
DOE OSTI2022

Te/CdTe and Al/CdTe Interfacial Energy Band Alignment by Atomistic Modeling

A synergistic approach that incorporates first-principles atomistic modeling with numerical device simulations is used to systematically evaluate the role of heterointerfaces within metal-chalcogenide-based photovoltaic technologies. Two interfaces involving either a tellurium back contact or aluminum back electrode combined with a cadmium telluride absorber layer within cadmium-telluride-based thin-film solar cells are investigated on an atomic scale to determine the mechanisms contributing to variations in device performance. Electronic structures and predicted charge transport behavior with respect to cadmium and tellurium termination of the absorber layer are studied along the polar oriented CdTe{111} facets. The computational methodology reveals a noticeable contrast between the Schottky barrier forming Al/CdTe interface versus the Type I Te/CdTe heterojunction. Greater band bending features are exhibited by the cadmium termination as opposed to the tellurium termination for each interface case. Subsequent device modeling suggests that 3.6% higher photovoltaic conversion efficiency is achievable for the cadmium termination relative to the tellurium termination of the Te/CdTe interface. Based strictly on an idealistic representation, both interface models show the importance of atomic-scale interfacial properties for cadmium telluride solar cell device performance with their bulk properties being validated in comparison to published experimental data. Here, the synergistic approach offers a suitable method to analyze solar cell interfaces through a predictive computational framework for the engineering and optimization of metal-chalcogenide-based thin-film photovoltaic technologies.

Green’s function↗
DOE OSTI2021

Multicolor Photonic Pigments for Rotation-Asymmetric Mechanochromic Devices

Photonic crystals are extensively explored to replace inorganic pigments and organic dyes as coloring elements in printing, painting, sensing, and anti-counterfeiting due to their brilliant structural colors, chemical stability, and environmental friendliness. However, most existing photonic-crystal-based pigments can only display monochromatic colors once made, and generating multicolors has to start with designing different building blocks. In this work, a novel photonic pigment featuring highly tunable structural colors in the entire visible spectrum, made by the magnetic assembly of monodisperse nanorods into body-centered-tetragonal photonic crystals, is reported. Their prominent magnetic and crystal anisotropy makes it efficient to generate multicolors using one photonic pigment by magnetically controlling the crystal orientation. Further, the combination of angle-dependent diffraction and magnetic orientation control enables the design of rotation-asymmetric photonic films that display distinct patterns and encrypted information in response to rotation. The efficient multicolor generation through precise orientational control makes this novel photonic pigment promising in developing high-performance structural-colored materials and optical devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Facilitating Ionic and Electronic Conduction in Radical Polymers through Controlled Assembly

The major objectives, research performed, and significant results associated with this effort agree with the originally proposed work. That is, we have made significant advances in terms of both the experimental and computational thrusts of this effort, and these key results have allowed for us to have significant impact in the materials chemistry community. As is usual, this has led to even greater tangible product generation in the final year of the work relative to the first two years. Importantly, we have observed that the materials created under this effort have promising electronic and ionic conductivity properties along these lines, and we have developed the initial structure-property-performance relationships that offer future promise for these open-shell materials in advanced energy applications. One metric that represents this success is the number of publications that appear in notable journals regarding the work performed. Additionally, the team has been invited to present at many conferences of leading societies and at top academic institutions due to the work associated with this award. Finally, we anticipate that this will be of interest to multiple communities in the materials chemistry realm, and they will have broader impact into related technologies as well.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Structural origin of size effect on piezoelectric performance of Pb(Zr,Ti)O 3

Grain size effect plays a vital role in piezoelectric performance from both scientific and technological view. However, the underlying structural mechanism related to grain size is still unclear. In the present study, the structural mechanism of grain size effect on piezoelectric performance has been revealed in the prototype Pb(Zr, Ti)O 3 system by using in-situ synchrotron X-ray diffraction. The miniaturization of grain size tends to favor the appearance of higher symmetric tetragonal phase, while a single monoclinic phase is determined in the coarse-grained ceramics. The direct structural evidence reveals that both tetragonal and monoclinic phases in the fine-grained ceramics are less sensitive to the electric field, corresponding to the inferior piezoelectric performance, while the single monoclinic phase in the coarse-grained ceramics is more active to be driven by the electric field, generating good piezoelectric behavior. Both domain switching ability and lattice strain are suppressed with decreasing grain size, which directly leads to the deterioration in piezoelectric performance. In conclusion, the current results will benefit the structural understanding of the size effect of piezoelectric and other related systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Microstructural heterogeneity of the buffer layer of TRISO nuclear fuel particles

Tristructural isotropic (TRISO) nuclear fuel particles contain a layered spherical shell designed to retain fission products; however, failure occurs in rare cases—commonly initiated in the porous pyrocarbon buffer layer. Achieving a comprehensive understanding of the buffer-initiated failure mechanisms requires detailed characterization of the buffer porosity and its heterogeneous distribution across multiple length scales. Here we performed FIB-SEM tomography across the buffer layer thickness (~100 µm) to produce 3D reconstructions of the buffer microstructure with 50 nm spatial resolution. We found an average overall porosity of ~14%, which does not solely account for the low density of the buffer (50% of the theoretical density). Additionally, the local porosity and its fluctuation increase from the kernel interface towards the inner pyrocarbon (IPyC) layer, which we attribute to the chemical vapor deposition process conditions during the TRISO particle fabrication. Detailed characterization of the porous microstructure—including analysis of the pore size, distribution, shape, and orientation—provides insight into the process-structure-property-performance relations of TRISO nuclear fuel particles and will inform multiscale models designed to predict the failure of TRISO particles under irradiation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Regional-scale fault-to-structure earthquake simulations with the EQSIM framework: Workflow maturation and computational performance on GPU-accelerated exascale platforms

Continuous advancements in scientific and engineering understanding of earthquake phenomena, combined with the associated development of representative physics-based models, is providing a foundation for high-performance, fault-to-structure earthquake simulations. However, regional-scale applications of high-performance models have been challenged by the computational requirements at the resolutions required for engineering risk assessments. The EarthQuake SIMulation (EQSIM) framework, a software application development under the US Department of Energy (DOE) Exascale Computing Project, is focused on overcoming the existing computational barriers and enabling routine regional-scale simulations at resolutions relevant to a breadth of engineered systems. This multidisciplinary software development—drawing upon expertise in geophysics, engineering, applied math and computer science—is preparing the advanced computational workflow necessary to fully exploit the DOE’s exaflop computer platforms coming online in the 2023 to 2024 timeframe. Achievement of the computational performance required for high-resolution regional models containing upward of hundreds of billions to trillions of model grid points requires numerical efficiency in every phase of a regional simulation. This includes run time start-up and regional model generation, effective distribution of the computational workload across thousands of computer nodes, efficient coupling of regional geophysics and local engineering models, and application-tailored highly efficient transfer, storage, and interrogation of very large volumes of simulation data. This article summarizes the most recent advancements and refinements incorporated in the workflow design for the EQSIM integrated fault-to-structure framework, which are based on extensive numerical testing across multiple graphics processing unit (GPU)-accelerated platforms, and demonstrates the computational performance achieved on the world’s first exaflop computer platform through representative regional-scale earthquake simulations for the San Francisco Bay Area in California, USA.

58 GEOSCIENCES↗
DOE OSTI2026

A Full-Induction Magnetohydrodynamics Solver for Liquid Metal Fusion Blankets in Vertex-CFD

Multiphysics modeling of liquid metal fusion blankets, which produce tritium and convert energy of neutrons created via fusion reactions into heat, is crucial for predicting performance, ensuring structural integrity, and optimizing energy production. While traditional blanket modeling of liquid metal flows during normal steady operating conditions commonly employs the inductionless approximation of the magnetohydrodynamics (MHD) equations, transient scenarios, when the plasma-confining magnetic field varies on millisecond time scales, require a full-induction MHD approach that dynamically evolves the magnetic field via the time-dependent induction equation. This paper presents the formulation, implementation, and initial verification of a full-induction MHD solver integrated within the open-source Vertex-CFD framework, which aims to achieve tight multiphysics coupling, a flexible software design enabling easy extension and addition of physics models, and performance portability across computing platforms. The solver utilizes finite element spatial discretization, implicit Runge–Kutta time integration, and an inexact Newton method to solve the resulting discrete nonlinear system, leveraging Trilinos packages for efficient computation. Verification against selected benchmark problems demonstrates accuracy and robustness of the solver. Furthermore, when the solver is applied to an idealized blanket model in 2.5D and full 3D, results obtained with Vertex-CFD are in good agreement with recently published quasi-2D simulations. These findings establish a computational foundation for future simulations of transient MHD phenomena in liquid metal blankets with Vertex-CFD, and open avenues for future extensions and performance optimizations.

Endeve, Eirik [ORNL] (ORCID:0000000312519507)↗
DOE OSTI2023

Active Sites of Cobalt Phthalocyanine in Electrocatalytic CO 2 Reduction to Methanol

Many metal coordination compounds catalyze CO 2 electroreduction to CO, but cobalt phthalocyanine hybridized with conductive carbon such as carbon nanotubes is currently the only one that can generate methanol. The underlying structure–reactivity correlation and reaction mechanism desperately demand elucidation. Here, in this study, we report the first in situ X-ray absorption spectroscopy characterization, combined with ex situ spectroscopic and electrocatalytic measurements, to study CoPc-catalyzed CO 2 reduction to methanol. Molecular dispersion of CoPc on CNT surfaces, as evidenced by the observed electronic interaction between the two, is crucial to fast electron transfer to the active sites and multi-electron CO 2 reduction. CO, the key intermediate in the CO 2 -to-methanol pathway, is found to be labile on the active site, which necessitates a high local concentration in the microenvironment to compete with CO 2 for active sites and promote methanol production. A comparison of the electrocatalytic performance of structurally related porphyrins indicates that the bridging aza-N atoms of the Pc macrocycle are critical components of the CoPc active site that produces methanol. In situ X-ray absorption spectroscopy identifies the active site as Co(I) and supports an increasingly non-centrosymmetric Co coordination environment at negative applied potential, likely due to the formation of a Co−CO adduct during the catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Thallium Bromide Semiconductor Radiation Materials and Detectors Characterization Studies

Two overarching requirements of crucial importance for the commercial and scientific establishment of semiconductor radiation detectors are: (1) exceptionally high-purity crystals with impurity concentrations less than 1 part-per-billion and (2) single crystals that are relatively free from subgrain boundaries, secondary phases, dislocations, and other electrically-active defects. We investigated the properties of thallium bromide (TlBr) material that affect its performance with the goal of increasing the material's commercial viability for radiation detection applications. For this purpose, we used beamlines at the National Synchrotron Light Source (NSLS) at Brookhaven National Laboratory (BNL), performing Micron-scale X-ray Detector Mapping, White Beam X-ray Diffraction Topography, and Micron-scale X-ray Fluorescence. These characterization methods improve the industry's understanding of TlBr and lead to the production of improved instrumentation. In this particular study we report electro-migration measurements of positive-ion Cu, Ag, and Au impurities in TlBr detectors under electric field strengths typically used for device operation. BNL improved TlBr detectors with an electrode design that corrects the response non-uniformities caused by crystal defects. This design can achieve improved energy resolution while using typical-grade, commercial crystals with relaxed quality requirements, thus reducing the overall cost of detectors. Additional characterization will be necessary to fully understand the structure and performance of TlBr with the ultimate goal to achieve the highest energy resolution. Our findings from past work will be presented along with our recommendations for additional investigation.

36 MATERIALS SCIENCE↗