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DOE OSTI2016

Comparison of Ion and Neutron Irradiations to 3 dpa at 500 deg. C in Ferritic-Martensitic Alloys

The growing global demand for energy will increasingly call upon advanced nuclear fission reactors to supply safe and reliable electricity. The structural and fuel cladding components of these reactors will be subject to extreme conditions of irradiation damage up to several hundred displacements per atom (dpa) at temperatures as high as 700 deg. C. Ferritic-martensitic (F-M) steels are leading candidates for these challenging conditions due to their strength and dimensional stability under irradiation. In order to accelerate the process for evaluating F-M alloys, charged particles are increasingly being used to emulate neutron irradiations. Charged particle irradiations allow the possibility of conducting irradiation experiments within a shorter time period (i.e. at a rate up to 4 orders of magnitude faster) and with minimal radioactivation of the material, enabling lower cost and faster turnaround of post irradiation examination and analysis. However, the irradiation dose rate, damage cascade morphologies, and irradiation damage depth profiles all differ widely between protons, heavier ions, and neutrons. Currently, there is limited understanding of the significance of these physical differences and how they manifest in the irradiated microstructure and mechanical properties of F-M steels. The objective of this study is to evaluate charged particles as a surrogate for neutron irradiations in F-M alloys by assessing common irradiation conditions using Fe{sup ++} ions, protons, and neutrons. Keeping the temperature and dose consistent enables isolation of the effects of each irradiating particle and their respective dose rates and cascade morphologies. Specimens of HCM12A and HT9 were irradiated separately with protons, self-ions, and neutrons to a common dose of 3 dpa at 500 deg. C. The microstructure of each specimen was characterized with TEM and LEAP and compared to evaluate proton and self-ion irradiation as a surrogate for neutron irradiation at these conditions. - Proton, self-ion, and neutron irradiations produced consistent sizes and number densities of grains, carbides, dislocation lines, and dislocation loops. Voids were absent in all conditions. The charged particle irradiations have successfully reproduced the neutron irradiation results for these microstructural features without a temperature shift. - Nano-cluster evolution of Si-Mn-Ni-P and Cu-rich clusters was markedly different for each irradiating particle type. Some cluster morphology trends could be explained by differences in cascade volume for differing irradiating species. But dose rate likely also influences cluster evolution. - Cr-rich nanoclusters nucleated only in the neutron-irradiated HCM12A and HT9. This is likely due to thermal aging at 500 deg. C over a longer experimental time, as compared to the proton and self-ion irradiations. (authors)

36 MATERIALS SCIENCE↗

DOE OSTI2017

Resistive field structures for semiconductor devices and uses therof

The present disclosure relates to resistive field structures that provide improved electric field profiles when used with a semiconductor device. In particular, the resistive field structures provide a uniform electric field profile, thereby enhancing breakdown voltage and improving reliability. In example, the structure is a field cage that is configured to be resistive, in which the potential changes significantly over the distance of the cage. In another example, the structure is a resistive field plate. Using these resistive field structures, the characteristics of the electric field profile can be independently modulated from the physical parameters of the semiconductor device. Additional methods and architectures are described herein.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Molecular engineering of fluorescein dyes as complementary absorbers in dye co-sensitized solar cells

Fluorescein dye derivatives exhibit extended optical absorption up to 500 nm, rendering these compounds suitable as co-absorbers in dye-sensitized solar cells (DSCs). A molecular engineering approach is presented, which embraces this intrinsic optical attribute of fluoresceins, while modifying the dye chemistry to enhance their light harvesting efficiency, in order to effectively tailor them for DSC applications. This approach first realizes relationships between the molecular structure and the optoelectronic properties for a series of five a priori known (parent) fluorescein dyes: 5-carboxyfluorescein (1), a mixture of m -carboxyfluorescein where m = 5 or 6 (2), 5-carboxyfluorescein diacetate (3), 6-carboxyfluorescein diacetate (4), a mixture of n -carboxy-2',7'-dichlorofluorescein diacetate where n = 5 or 6 (5). The first step in this approach combines, where available, experimental and computational methods so that electronic structure calculations can also be validated for representative fluorescein dyes. Such calculations can then be used reliably to predict the structure and properties of fluorescein dyes for cases where experimental data are lacking. Structure-function relationships established from this initial step inform the selection of parent dye 1 that is taken forward to the second step in molecular engineering: in silico chemical derivation to re-functionalize 1 for DSC applications. For this purpose, computational calculations are used to extend the charge conjugation in 1 between its donor and acceptor moieties. These structural modifications result in a bathochromic shift of the lowest excitation by ~1.3-1.9 eV (100-170 nm), making the dye optically absorb in the visible region. Further calculations on dye molecules adsorbed onto the surface of a TiO 2 cluster are used to investigate the dye sensitization behavior via dye adsorption energies and anchoring modes. The results of this theoretical investigation lead to two molecularly engineered fluoresceins being proposed to act as co-sensitizers together with a rhodamine dye. This combination of three dyes ensures chemical compatibility, panchromatic absorption, and restores optical absorption dipping otherwise observed in a DSC device at ~350-400 nm owing to the I-/I- 3 electrolyte. Altogether, the results of this study demonstrate that molecular engineering can be used to identify suitable chemical modifications for organic dyes with improved light harvesting properties for photovoltaic applications.

14 SOLAR ENERGY↗

DOE OSTI2013

X-ray diffraction study of fluorene, 9-fluorenone, and 9-dicyanomethylenefluorene derivatives

The results of a single-crystal X-ray diffraction analysis of fluorene, 9-fluorenone, and 9-dicyanomethylenefluorene derivatives as individual compounds, as well as their crystal solvates, molecular complexes, and charge-transfer complexes, are generalized. The most interesting features of the molecular geometry and conformation and the molecular packing in the crystals are discussed. The structural formula of 95 compounds and the R factors for X-ray diffraction analysis, which characterize the reliability of determining the structure, are summarized in three tables.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Revisit the VEC criterion in high entropy alloys (HEAs) with high-throughput ab initio calculations: A case study with Al-Co-Cr-Fe-Ni system

Valence electron concentration (VEC) was treated as a useful parameter to predict the stability of solid solution phases. However, the available experimental data to support this criterion is far from enough. In the current study, the high-throughput ab initio modeling is applied to investigate the relative stability of FCC and BCC single crystals of the Al-Co-Cr-Fe-Ni high entropy alloys (HEAs) by using the special quasi-random structure (SQS) approach. Furthermore, the predictions start with pure elements of the Al-Co-Cr-Fe-Ni system and are continued with binaries, ternaries, and quaternary compositions, which come up with 180 compositions (360 structures). After that, the reliability of the VEC criterion is testified. The results show that the VEC criterion not only works for the stable structure but also works effectively for metastable structure when both FCC and BCC are not thermodynamic stable. However, it is found that the old VEC criterion proposed by Guo et al. fails to work effectively for compositions containing high concentrations of light-weight metals such as Al at VEC<5. To solve this problem, the present work proposes a new VEC rule to define the stability of FCC and BCC structures at the ground state. With the implementation of the new VEC rule, the effectiveness of the VEC rule (EVEC) of both FCC and BCC structures is enhanced, especially for pure elements and binary compositions, indicating that this rule does not only work effectively for multicomponent systems but also works for low-order systems.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Detailed analysis of hollow ions spectra from dense matter pumped by X-ray emission of relativistic laser plasma

X-ray emission from hollow ions offers new diagnostic opportunities for dense, strongly coupled plasma. We present extended modeling of the x-ray emission spectrum reported by Colgan et al. [Phys. Rev. Lett. 110, 125001 (2013)] based on two collisional-radiative codes: the hybrid-structure Spectroscopic Collisional-Radiative Atomic Model (SCRAM) and the mixed-unresolved transition arrays (MUTA) ATOMIC model. We show that both accuracy and completeness in the modeled energy level structure are critical for reliable diagnostics, investigate how emission changes with different treatments of ionization potential depression, and discuss two approaches to handling the extensive structure required for hollow-ion models with many multiply excited configurations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

NWGraph: A Library of Generic Graph Algorithms and Data Structures in C++20

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

NWGraph: A Library of Generic Graph Algorithms and Data Structures in C++20

The C++ Standard Library is a valuable collection of generic algorithms and data structures that improves the usability and reliability of C++ software. Graph algorithms and data structures are notably absent from the standard library, and previous attempts to fill this gap have not gained widespread adoption. In this paper we show that the richness of graph algorithms and data structures can in fact be captured by straightforward composition of existing C++ mechanisms. Generic programming is algorithm-oriented. Accordingly, we apply a systematic approach to analyzing a broad set of graph algorithms, “lift” unnecessary constraints from them, and organize the resulting set of minimal common type requirements, i.e., concepts, for defining their interfaces. By using the newly available ranges and concepts in C++20, the type requirements for generic graph algorithms can be succinctly expressed. The generic algorithms and data structures resulting from our analysis are realized in NWGraph, in a modern, composable, and extensible C++ library.

graphs and networks, programming language, C++20↗

DOE OSTI2014

Multilevel probabilistic approach to evaluate manufacturing defect in composite aircraft structures

In this work it is developed a reliable approach and its feasibility to the design and analysis of a composite structures. The metric is compared the robustness and reliability designs versus the traditional design, to demonstrate the gain that can be achieved with a probabilistic approach. The use of the stochastic approach of the uncertain parameteters in combination with the multi-scale levels analysis is the main objective of this paper. The work is dedicated to analyze the uncertainties in the design, tests, manufacturing process, and key gates such as materials characteristic.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Assessing Local Structure Motifs Using Order Parameters for Motif Recognition, Interstitial Identification, and Diffusion Path Characterization

Structure–property relationships form the basis of many design rules in materials science, including synthesizability and long-term stability of catalysts, control of electrical and optoelectronic behavior in semiconductors, as well as the capacity of and transport properties in cathode materials for rechargeable batteries. The immediate atomic environments (i.e., the first coordination shells) of a few atomic sites are often a key factor in achieving a desired property. Some of the most frequently encountered coordination patterns are tetrahedra, octahedra, body and face-centered cubic as well as hexagonal close packed-like environments. Here, we showcase the usefulness of local order parameters to identify these basic structural motifs in inorganic solid materials by developing classification criteria. We introduce a systematic testing framework, the Einstein crystal test rig, that probes the response of order parameters to distortions in perfect motifs to validate our approach. Subsequently, we highlight three important application cases. First, we map basic crystal structure information of a large materials database in an intuitive manner by screening the Materials Project (MP) database (61,422 compounds) for element-specific motif distributions. Second, we use the structure-motif recognition capabilities to automatically find interstitials in metals, semiconductor, and insulator materials. Our Interstitialcy Finding Tool (InFiT) facilitates high-throughput screenings of defect properties. Third, the order parameters are reliable and compact quantitative structure descriptors for characterizing diffusion hops of intercalants as our example of magnesium in MnO 2 -spinel indicates. Finally, the tools developed in our work are readily and freely available as software implementations in the pymatgen library, and we expect them to be further applied to machine-learning approaches for emerging applications in materials science.

36 MATERIALS SCIENCE↗

DOE OSTI2020

GPR Robotic Assisted Non-Destructive Evaluation of Concrete Structures - 20196

Reinforced concrete structures are always under exposure of internal or external deteriorations due to many factors such as environmental, nuclear radiation or even construction deficiencies. The use of nondestructive test is one of the reliable methods to inspect structural members. In this case, GPR has a good capability to detect inside deteriorations of concrete structures. However, in many cases it is hard to inspect structural members by hand due to safety issues or inaccessibility. Thus, an alternative way to reduce such risks is to employ robot to carry nondestructive equipment. In this research, twelve reinforced concrete RC beams (8 x 16 x 96, width, height and length) are cast in the lab. Three RC beams have no defect and nine others various defects such as corrosion, de-bonded bars, void, delamination and honeycombing. The one-point load is applied at the center of the RC beam. The loading level is carried out at three levels: 50%, 75% and 100% of maximum load and total load-displacement diagram are performed. The load is held at each level and the robotic GPR is used to scan the side of RC beams. Then, RADAN software is employed to find out any defects at different loading conditions and visualize the crack propagation. The RADAN results show that the pattern of crack propagation for corrosion and debonding are same. Also, the load-displacement results present that inside defect cause reduction of load-capacity of RC beam. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2014

Stochastic formation of magnetic vortex structures in asymmetric disks triggered by chaotic dynamics

The non-trivial spin configuration in a magnetic vortex is a prototype for fundamental studies of nanoscale spin behaviour with potential applications in magnetic information technologies. Arrays of magnetic vortices interfacing with perpendicular thin films have recently been proposed as enabler for skyrmionic structures at room temperature, which has opened exciting perspectives on practical applications of skyrmions. An important milestone for achieving not only such skyrmion materials but also general applications of magnetic vortices is a reliable control of vortex structures. However, controlling magnetic processes is hampered by stochastic behaviour, which is associated with thermal fluctuations in general. Here we show that the dynamics in the initial stages of vortex formation on an ultrafast timescale plays a dominating role for the stochastic behaviour observed at steady state. Our results show that the intrinsic stochastic nature of vortex creation can be controlled by adjusting the interdisk distance in asymmetric disk arrays.

36 MATERIALS SCIENCE↗

DOE OSTI2025

ACCELERATED DEPLOYMENT OF NOVEL MATERIALS BASED ON RELIABILITY INTEGRITY MANAGEMENT USING CUMULATIVE DAMAGE MODELING

There is currently no widely agreed, detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. This paper discusses a framework for solving this problem that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev. 0, endorses, with conditions, the subject portion of the 2019 ASME Code. The proposed framework is meant to support development of a licensing case by addressing certain remaining technical challenges. The framework discussed here is compatible with the Licensing Modernization Project, but applying it in a specific case will call for advances in the state of practice, if not the state of the art. The RIM approach calls for applicants to (a) allocate reliability targets to plant structures, systems, and components (SSCs), (b) show that they are able to relate the currently observed physical condition of each SSC in the program to its failure probability well enough to determine whether the target reliability allocations are being satisfied, allowing for uncertainty related to the novelty of the materials/designs/operating environments, and (c) be able to demonstrate that the proposed program of surveillances will reliably detect unacceptable degradation of an SSC before SSC failure occurs. A modeling approach potentially applicable to item (b), based on cumulative damage modeling rather than failure rates, is briefly illustrated.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2015

A revised partiality model and post-refinement algorithm for X-ray free-electron laser data

An updated partiality model and post-refinement algorithm for XFEL snapshot diffraction data is presented and confirmed by observing anomalous density for S atoms at an X-ray wavelength of 1.3 Å. Research towards using X-ray free-electron laser (XFEL) data to solve structures using experimental phasing methods such as sulfur single-wavelength anomalous dispersion (SAD) has been hampered by shortcomings in the diffraction models for X-ray diffraction from FELs. Owing to errors in the orientation matrix and overly simple partiality models, researchers have required large numbers of images to converge to reliable estimates for the structure-factor amplitudes, which may not be feasible for all biological systems. Here, data for cytoplasmic polyhedrosis virus type 17 (CPV17) collected at 1.3 Å wavelength at the Linac Coherent Light Source (LCLS) are revisited. A previously published definition of a partiality model for reflections illuminated by self-amplified spontaneous emission (SASE) pulses is built upon, which defines a fraction between 0 and 1 based on the intersection of a reflection with a spread of Ewald spheres modelled by a super-Gaussian wavelength distribution in the X-ray beam. A method of post-refinement to refine the parameters of this model is suggested. This has generated a merged data set with an overall discrepancy (by calculating the R{sub split} value) of 3.15% to 1.46 Å resolution from a 7225-image data set. The atomic numbers of C, N and O atoms in the structure are distinguishable in the electron-density map. There are 13 S atoms within the 237 residues of CPV17, excluding the initial disordered methionine. These only possess 0.42 anomalous scattering electrons each at 1.3 Å wavelength, but the 12 that have single predominant positions are easily detectable in the anomalous difference Fourier map. It is hoped that these improvements will lead towards XFEL experimental phase determination and structure determination by sulfur SAD and will generally increase the utility of the method for difficult cases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Graph neural networks for CO 2 solubility predictions in Deep Eutectic Solvents

Deep Eutectic Solvents (DESs) are a promising class of solvents for CO 2 capture. DESs are complex mixtures that can be designed to optimize CO solubility and overall capture process efficiency. However, the vast design landscape of DES mixtures makes experimental investigation prohibitive; as such, there is a need for computational models that can quickly and efficiently navigate the design space and inform data collection efforts. In this work, we propose Graph Neural Network (GNN) models for predicting CO 2 solubility for DESs; the GNN leverages a mixture graph representation that captures the molecular structure of the DES components as well as their intermolecular interactions. Here, we compare the GNN framework against alternative architectures (neural networks, graph convolution networks, and random forests) and data representations (molecular fingerprints, sigma profiles, and graphs). We show that the proposed approach offers superior predictive performance; specifically, we show that solubility can be predicted reliably directly from molecular structure (without the need of using sigma profiles as proposed in previous studies). This result is important, as obtaining sigma profiles requires expensive density functional theory computations. We also explored the ability of GNNs to predict solubility for new DES mixtures and operating conditions. We found that the model extrapolates across temperature reliably. However, we also found deficiencies in the ability of the model to predict solubility for DES mixtures, pressures, and molar ratio not included in the training sets; we show that this is due to an inherent lack of chemical diversity in datasets available in the literature. The proposed computational capabilities can thus help navigate the design space of DES and inform data collection efforts. Our models, data, and benchmarks are shared as Python code implemented in Jupyter notebooks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Galvanic corrosion of structural non-stoichiometric silicon nitride thin films and its implications on reliability of microelectromechanical devices

This paper describes a reliability assessment and failure analysis of a poly-Si/non-stoichiometric silicon nitride thin film composite structure. A set of poly-Si/SiN{sub x} thin film structures were exposed to a mixed flowing gas (MFG) environment, which simulates outdoor environments, for 90 days, and an elevated temperature and humidity (85 °C/95% R.H.) test for 140 days. The mechanical integrity of the thin films was observed to degrade during exposure to the chemically reactive atmospheres. The degree of degradation was analyzed with nanoindentation tests. Statistical analysis of the forces required to initiate a fracture in the thin films indicated degradation due to the exposure to the MFG environment in the SiN{sub x} part of the films. Scanning electron microscopy revealed a porous-like reaction layer on top of SiN{sub x}. The morphology of the reaction layer resembled that of galvanically corroded poly-Si. Transmission electron microscopy further clarified the microstructure of the reaction layer which had a complex multi-phase structure extending to depths of ∼100 nm. Furthermore, the layer was oxidized two times deeper in a 90 days MFG-tested sample compared to an untested reference. The formation of the layer is proposed to be caused by galvanic corrosion of elemental silicon in non-stoichiometric silicon nitride during hydrofluoric acid etching. The degradation is proposed to be due uncontrolled oxidation of the films during the stress tests.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Critical assessment of the recent report on the gigaparsec-scale correlation of the orientations of large quasar groups

ABSTRACT Recently, it was reported that large quasar groups (LQGs) identified from the Sloan Digital Sky Survey (SDSS) data release seven catalogue are not randomly oriented but preferentially aligned or orthogonal over scales 1–2 Gpc. To confirm this claim, I reproduced the same LQG sample and performed Sobolev tests of uniformity on the LQG orientation axes in the redshift space. Contrary to the original report based on the bimodal distribution of the LQG position angles in the sky, I found no departure from uniformity in the distribution of the LQG orientation axes. I also examined whether the LQGs are physical structures using a statistically more reliable data set constructed from the SDSS data release 16 (DR16) large-scale structure (LSS) quasar catalogue. Considering the Gaussian primordial density fluctuations and shot noise, I estimated the mass density contrasts of the LQGs from the number counts of the DR16 LSS quasars and found that most of the LQGs do not trace statistically significant high-density regions. I conclude that the LQG sample is a collection of unphysical chance associations and should not be used for any cosmological studies.

Fujii, Hirokazu (ORCID:0000000161473512)↗

DOE OSTI2024

RCSB Protein Data Bank: supporting research and education worldwide through explorations of experimentally determined and computationally predicted atomic level 3D biostructures

The Protein Data Bank (PDB) was established as the first open-access digital data resource in biology and medicine in 1971 with seven X-ray crystal structures of proteins. Today, the PDB houses >210 000 experimentally determined, atomic level, 3D structures of proteins and nucleic acids as well as their complexes with one another and small molecules ( e.g. approved drugs, enzyme cofactors). These data provide insights into fundamental biology, biomedicine, bioenergy and biotechnology. They proved particularly important for understanding the SARS-CoV-2 global pandemic. The US-funded Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) and other members of the Worldwide Protein Data Bank (wwPDB) partnership jointly manage the PDB archive and support >60 000 `data depositors' (structural biologists) around the world. wwPDB ensures the quality and integrity of the data in the ever-expanding PDB archive and supports global open access without limitations on data usage. The RCSB PDB research-focused web portal at https://www.rcsb.org/ (RCSB.org) supports millions of users worldwide, representing a broad range of expertise and interests. In addition to retrieving 3D structure data, PDB `data consumers' access comparative data and external annotations, such as information about disease-causing point mutations and genetic variations. RCSB.org also provides access to >1 000 000 computed structure models (CSMs) generated using artificial intelligence/machine-learning methods. To avoid doubt, the provenance and reliability of experimentally determined PDB structures and CSMs are identified. Related training materials are available to support users in their RCSB.org explorations.

59 BASIC BIOLOGICAL SCIENCES↗