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DOE OSTI2020

Striped Data Analysis Framework

A columnar data representation is known to be an efficient way for data storage, specifically in cases when the analysis is often done based only on a small fragment of the available data structures. A data representation like Apache Parquet is a step forward from a columnar representation, which splits data horizontally to allow for easy parallelization of data analysis. Based on the general idea of columnar data storage, working on the [LDRD Project], we have developed a striped data representation, which, we believe, is better suited to the needs of High Energy Physics data analysis. A traditional columnar approach allows for efficient data analysis of complex structures. While keeping all the benefits of columnar data representations, the striped mechanism goes further by enabling easy parallelization of computations without requiring special hardware. We will present an implementation and some performance characteristics of such a data representation mechanism using a distributed no-SQL database or a local file system, unified under the same API and data representation model. The representation is efficient and at the same time simple so that it allows for a common data model and APIs for wide range of underlying storage mechanisms such as distributed no-SQL databases and local file systems. Striped storage adopts Numpy arrays as its basic data representation format, which makes it easy and efficient to use in Python applications. The Striped Data Server is a web service, which allows to hide the server implementation details from the end user, easily exposes data to WAN users, and allows to utilize well known and developed data caching solutions to further increase data access efficiency. We are considering the Striped Data Server as the core of an enterprise scale data analysis platform for High Energy Physics and similar areas of data processing. We have been testing this architecture with a 2TB dataset from a CMS dark matter search and plan to expand it to multiple 100 TB or even PB scale. We will present the striped format, Striped Data Server architecture and performance test results.

Gutsche, Oliver↗

DOE OSTI2018

Striped Data Server for Scalable Parallel Data Analysis

A columnar data representation is known to be an efficient way for data storage, specifically in cases when the analysis is often done based only on a small fragment of the available data structures. A data representation like Apache Parquet is a step forward from a columnar representation, which splits data horizontally to allow for easy parallelization of data analysis. Based on the general idea of columnar data storage, working on the [LDRD Project], we have developed a striped data representation, which, we believe, is better suited to the needs of High Energy Physics data analysis. A traditional columnar approach allows for efficient data analysis of complex structures. While keeping all the benefits of columnar data representations, the striped mechanism goes further by enabling easy parallelization of computations without requiring special hardware. We will present an implementation and some performance characteristics of such a data representation mechanism using a distributed no-SQL database or a local file system, unified under the same API and data representation model. The representation is efficient and at the same time simple so that it allows for a common data model and APIs for wide range of underlying storage mechanisms such as distributed no-SQL databases and local file systems. Striped storage adopts Numpy arrays as its basic data representation format, which makes it easy and efficient to use in Python applications. The Striped Data Server is a web service, which allows to hide the server implementation details from the end user, easily exposes data to WAN users, and allows to utilize well known and developed data caching solutions to further increase data access efficiency. We are considering the Striped Data Server as the core of an enterprise scale data analysis platform for High Energy Physics and similar areas of data processing. As a result, we have been testing this architecture with a 2TB dataset from a CMS dark matter search and plan to expand it to multiple 100 TB or even PB scale. We will present the striped format, Striped Data Server architecture and performance test results.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2026

Poisson-response Tensor-on-Tensor Regression and Applications

We introduce Poisson-response tensor-on-tensor regression (PToTR), a novel regression framework designed to handle tensor responses composed element-wise of random Poisson-distributed counts. Tensors, or multi-dimensional arrays, composed of counts are common data in fields such as inter national relations, social networks, epidemiology, and medical imaging, where events occur across multiple dimensions like time, location, and dyads. PToTR accommodates such tensor responses alongside tensor covariates, providing a versatile tool for multi dimensional data analysis. We propose algorithms for maximum likelihood estimation under a canonical polyadic (CP) structure on the regression coefficient tensor that satisfy the positivity of Poisson parameters and then provide an initial theoretical error analysis for PToTR estimators. We also demonstrate the utility of PToTR through three concrete applications: longitudinal data analysis of the Integrated Crisis Early Warning System database, positron emission tomography (PET) image reconstruction, and change-point detection of communication patterns in longitudinal dyadic data. These applications highlight the versatility of PToTR in addressing complex, structured count data across various domains.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Active Learning for Metamaterial Optimization on HPC and QC Integrated Systems

Active learning algorithms, integrating machine learning, quantum computing and optics simulation in an iterative loop, offer a promising approach to optimizing metamaterials. However, these algorithms can face difficulties in optimizing highly complex structures due to computational limitations. High-performance computing (HPC) and quantum computing (QC) integrated systems can address these issues by enabling parallel computing. In this study, we develop an active learning algorithm working on HPC-QC integrated systems. We evaluate the performance of optimization processes within active learning (i.e., training a machine learning model, problem-solving with quantum computing, and evaluating optical properties through wave-optics simulation) for highly complex metamaterial cases. Our results showcase that utilizing multiple cores on the integrated system can significantly reduce computational time, thereby enhancing the efficiency of optimization processes. Therefore, we expect that leveraging HPC-QC integrated systems helps effectively tackle large-scale optimization challenges in general.

Kim, Seongmin↗

DOE OSTI2024

Learning Molecular Mixture Property Using Chemistry-Aware Graph Neural Network

Recent advances in machine learning (ML) are expediting materials discovery and design. One significant challenge facing ML for materials is the expansive combinatorial space of potential materials formed by diverse constituents and their flexible configurations. This complexity is particularly evident in molecular mixtures, a frequently explored space for materials, such as battery electrolytes. Owing to the complex structures of molecules and the sequence-independent nature of mixtures, conventional ML methods have difficulties in modeling such systems. Here, we present MolSets, a specialized ML model for molecular mixtures, to overcome the difficulties. Representing individual molecules as graphs and their mixture as a set, MolSets leverages a graph neural network and the deep sets architecture to extract information at the molecular level and aggregate it at the mixture level, thus addressing local complexity while retaining global flexibility. We demonstrate the efficacy of MolSets in predicting the conductivity of lithium battery electrolytes and highlight its benefits in the virtual screening of the combinatorial chemical space. Published by the American Physical Society 2024

Zhang, Hengrui (ORCID:0000000231831654)↗

DOE OSTI2020

A review of the application of 2D isotropic-anisotropic correlation NMR spectroscopy in structural studies of chalcogenide glasses

The application of solid-state high-resolution NMR spectroscopy in the structural investigation of chalcogenide glasses in Ge/As/P/Si-X (X = S, Se,Te) systems has remained challenging even for the spin-1/2 nuclides ( 29 Si, 31 P, 77 Se, 125 Te), owing to their low natural abundance (except for 31 P), slow spin-lattice relaxation rate and large CSA and chemical shift distribution induced line broadening effects. However, most of these deleterious effects can be successfully overcome in two-dimensional (2D) isotropic-anisotropic correlation NMR experiments, especially when performed at high magnetic field and in conjunction with the Car-Purcell-Meiboom-Gill (CPMG) echo train acquisition. Here, we present a short introduction to the basic principles of such experiments and review their applications over the last decade in deciphering various short- and intermediate- range structural characteristics of chalcogenide glasses in S-Se, Se-Te, Ge-Se, As-Se and Si-Se systems as well as in investigating the molecular dynamics in a P-Se supercooled liquid. We anticipate possible future applications of these 2D isotropic-anisotropic correlation NMR experiments, particularly in conjunction with density functional theory-based calculations of NMR chemical shift tensor parameters and additional signal enhancement schemes, in addressing complex structural correlations and distributions in chalcogenide glasses.

2D NMR↗

DOE OSTI2015

Luminescent hybrid lanthanide sulfates and lanthanide sulfonate-carboxylates with 1,10-phenanthroline involving in-situ oxidation of 2-mercaptonbenzoic acid

A series of lanthanide sulfates and lanthanide sulfonate-carboxylates, [Ln{sub 2}(phen){sub 2}(SO{sub 4}){sub 3}(H{sub 2}O){sub 2}]{sub n} (I:Ln=Nd(1a), Sm(1b), Eu(1c), phen=1,10-phenanthroline) and [Ln(phen)(2-SBA)(BZA)]{sub n} (II: Ln=Sm(2a), Eu(2b), Dy(2c), 2-SBA=2-sulfobenzoate, BZA=benzoate) have been hydrothermally synthesized from lanthanide oxide, 2-mercaptonbenzoic acid with phen as auxiliary ligand and characterized by single-crystal X-ray diffraction, elemental analyses, IR spectra, TG analyses and luminescence spectroscopy. Interestingly, SO{sub 4}{sup 2−} anions in I came from the in situ deep oxidation of thiol groups of 2-mercaptonbenzoic acid while 2-sulfobenzoate and benzoate ligands in II from the middle oxidation and desulfuration reactions of 2-mercaptonbenzoic acid. Compounds I are organic–inorganic hybrid lanthanide sulfates, which have rare one-dimensional column-like structures. Complexes II are binuclear lanthanide sulfonate-carboxylates with 2-sulfobenzoate and benzoate as bridges and 1,10-phenanthroline as terminal. Photoluminescence studies reveal that complexes I and II exhibit strong lanthanide characteristic emission bands in the solid state at room temperature. - Graphical abstract: Lanthanide sulfates and lanthanide sulfonate-carboxylates have been hydrothermally synthesized. Interestingly, sulfate anions, 2-sulfobenzoate and benzoate ligands came from the in situ oxidation and desulfuration reactions of 2-mercaptonbenzoic acid. - Highlights: • In situ oxidation and desulfuration reactions of 2-mercaptonbenzoic acid. • The organic–inorganic hybrid lanthanide sulfates with one-dimensional column-like structure. • The dinuclear lanthanide sulfonate-carboxylates. • The emission spectra exhibit the characteristic transition of {sup 5}D{sub 0}→{sup 7}F{sub J} (J=0–4) of the Eu(III)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Self‐Assembled Metal–Dielectric Hybrid Metamaterials in Vertically Aligned Nanocomposite Form with Tailorable Optical Properties and Coupled Multifunctionalities

Metal–dielectric hybrid metamaterials have attracted increasing research interest in recent years because of their novel optical properties and promising applications in the fields of electronic and photonic devices. Dielectric permittivity is a key parameter that strongly influences the optical properties of materials. By self‐assembling the metallic and dielectric components in a pillar‐in‐matrix structure, a strong anisotropic structure forms and results in opposite signs of permittivity components (i.e., ε || > 0 and ε ⊥ < 0, or vice versa) and exotic optical responses including hyperbolic dispersion in the visible to near‐infrared region. Herein, the main approaches of tuning the permittivity in self‐assembled metal–dielectric vertically aligned nanocomposite (VAN) thin films are reviewed, including tuning the metal pillar density and geometry, film strain state and background pressure during growth, and seeking other metal‐free and complex structure designs. Future research directions are also proposed, including unique approaches to improve their thermal stability, integrate on flexible substrates toward wearable device fabrication, and explore real‐time tunable metamaterials.

Zhang, Di↗

DOE OSTI2020

Reconfigurable structure and tunable transport in synchronized active spinner materials

Ensembles of actuated colloids are excellent model systems to explore emergent out-of-equilibrium structures, complex collective dynamics, and design rules for the next generation materials. Here, we demonstrate that ferromagnetic microparticles suspended at an air-water interface and energized by an external rotating magnetic field spontaneously form dynamic ensembles of synchronized spinners in a certain range of the excitation field parameters. Each spinner generates strong hydrodynamic flows, and collective interactions of the multiple spinners promote a formation of dynamic lattices. On the basis of experiments and simulations, we reveal structural transitions from liquid to nearly crystalline states in this novel active spinner material and demonstrate that dynamic spinner lattices are reconfigurable, capable of self-healing behavior and that the transport of embedded inert cargo particles can be remotely tuned by the parameters of the external excitation field. Our findings provide insights into the behavior of active spinner materials with reconfigurable structural order and tunable functionalities.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Metastable silica high pressure polymorphs as structural proxies of deep Earth silicate melts

Modelling of processes involving deep Earth liquids requires information on their structures and compression mechanisms. However, knowledge of the local structures of silicates and silica (SiO 2 ) melts at deep mantle conditions and of their densification mechanisms is still limited. Here we report the synthesis and characterization of metastable high-pressure silica phases, coesite-IV and coesite-V, using in situ single-crystal X-ray diffraction and ab initio simulations. Their crystal structures are drastically different from any previously considered models, but explain well features of pair-distribution functions of highly densified silica glass and molten basalt at high pressure. Built of four, five-, and six-coordinated silicon, coesite-IV and coesite-V contain SiO 6 octahedra, which, at odds with 3 rd Pauling’s rule, are connected through common faces. Our results suggest that possible silicate liquids in Earth’s lower mantle may have complex structures making them more compressible than previously supposed.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Influence of the hyperfine structure of the atomic states on the collective effects in the Rb{sub 2} quasi-molecule

A consistent quantum approach is used to study the influence of intraatomic spin–orbit and hyperfine interactions on the character of a resonance dipole–dipole interatomic interaction and, hence, collective effects. For this purpose, the collective spontaneous decay of excited states and the spectral dependence of the total scattering cross section of a monochromatic light wave are analyzed in the system consisting of two rubidium-87 atoms. The modification of the radiation properties and the interaction of the atoms with external radiation are studied as functions of the interatomic distance. The presence of a complex structure of the sublevels of both the ground and excited states is shown to modify the collective effects substantially as compared to the case when this structure is absent.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Application of Laser Powder Bed Fusion for Transformational Challenge Reactor Core

The following report focuses on the utility of Laser Powder Bed Fusion (LPBF) for the construction of components for the Transformational Challenge Reactor (TCR) core. Multiple additive manufacturing processes are under investigation to evaluate the advantages and viability of each process for direct manufacturing of complex structures needed for future nuclear reactors. Technologies under investigation include binder jet, direct energy deposition (DED), electron beam powder bed fusion (EBPBF), and laser powder bed fusion (LPBF). Each process has advantages and disadvantages. For the core design, two manufacturing approaches are under consideration—one involving the exclusive use of LPDF to fabricate the entire core and the other consisting of integration of LPBF and DED where LPBF is used for the core’s top and bottom manifolds (where complexity is high) and DED is used for the manufacture of the cladding where complexity is still high but geometric variability, size, and speed are better suited for DED. For both approaches, LPBF research has focused on processing parameter development, core design, and manufacturing tolerances for integration of fuel elements. The following report highlights reactor core design as it relates to LPBF and experimental validation of test components necessary for finalizing the core design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Structure–transport correlations in Na 11 Sn 2 SbSe 12 and its sulfide solid solutions

We report a new ion conductor—Na 11 Sn 2 SbSe 12 —as a possible candidate for a solid catholyte in composite cathodes for all-solid state Na-batteries, which exhibits a room temperature ionic conductivity of 0.15 ± 0.03 mS cm −1 and an activation energy of 0.39 ± 0.02 eV. The sulfide solid solutions of Na 11 Sn 2 SbSe 12 , namely, Na 11 Sn 2 SbS 12−x Se x (x = 1 and 6), were also investigated through a combination of Rietveld refinement against powder x-ray diffraction data and electrochemical impedance spectroscopy to reveal the complex structure–property relationships governing ion transport in this class of materials. Meanwhile, broadening of the Na-ion diffusion pathways in Na 11 Sn 2 SbSe 12 is expected to facilitate Na-ion transport compared to the sulfide-rich member of the solid solution, the opposite holds: increasing the Se fraction in Na 11 Sn 2 SbS 12−x Se x leads to a little change in the activation energy but a reduction in the ionic conductivity. We ascribe this to the lowering of the prefactor, σ 0 , in the Arrhenius relationship with increasing lattice “softening” as a function of higher Se content.

Ramos, Erika P.↗

DOE OSTI2017

Neutron residual stress measurement and numerical modeling in a curved thin-walled structure by laser powder bed fusion additive manufacturing

Severe residual stresses in metal parts made by laser powder bed fusion additive manufacturing processes (LPBFAM) can cause both distortion and cracking during the fabrication processes. Limited data is currently available for both iterating through process conditions and design, and in particular, for validating numerical models to accelerate process certification. In this work, residual stresses of a curved thin-walled structure, made of Ni-based superalloy Inconel 625™ and fabricated by LPBFAM, were resolved by neutron diffraction without measuring the stress-free lattices along both the build and the transverse directions. The stresses of the entire part during fabrication and after cooling down were predicted by a simplified layer-by-layer finite element based numerical model. The simulated and measured stresses were found in good quantitative agreement. The validated simplified simulation methodology will allow to assess residual stresses in more complex structures and to significantly reduce manufacturing cycle time.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Pathway toward Optical Cycling and Laser Cooling of Functionalized Arenes

Rapid and repeated photon cycling has enabled precision metrology and the development of quantum information systems using atoms and simple molecules. Extending optical cycling to structurally complex molecules would provide new capabilities in these areas, as well as in ultracold chemistry. Increased molecular complexity, however, makes realizing closed optical transitions more difficult. Building on already established strong optical cycling of diatomic, linear triatomic, and symmetric top molecules, recent work has pointed the way to cycling of larger molecules, including phenoxides. The paradigm for these systems is an optical cycling center bonded to a molecular ligand. Theory has suggested that cycling may be extended to even larger ligands, like naphthalene, pyrene, and coronene. For this paper, we study optical excitation and fluorescent vibrational branching of CaO-[illus. chemical structure], SrO-[illus. chemical structure], and CaO-[illus. chemical structure] and find only weak decay to excited vibrational states, indicating a promising path to full quantum control and laser cooling of large arene-based molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Low-Cost Aero Technology Demonstrations

The main focus of this work was to demonstrate the use of polymeric additive manufacturing (AM) to create tooling for both preforming and consolidation. Polymeric tooling was utilized where both modest and higher pressures are used for part consolidation. The key focus for the AM tooling development was for fabrication of complex structures such as ducting, C-channel stiffened skins, and airfoils where conventional male tooling would typically be trapped in the cured part. The AM tooling was evaluated for use as a tool master used to fabricate and re-shape deformable/re-formable mandrels based on SpinTech’s shape memory composite technology known as Smart Tooling. The AM tooling was also evaluated for use as a mold for composite infusion and consolidation. Key performance parameters were tracked for project schedule completion with each step comprising of “art to part” cycle time, cost, and model fidelity for dimensions, performance, and cost. The primary focus of this demonstration was to determine if a 50% cost reduction was achievable, for each AM tooling-set, as compared to conventional processes. UDRI leveraged project partner SpinTech, who manufactures tools and parts in these categories and thus provided a baseline regarding current best practices and provided valuable feedback during the entirety of this demonstration. This demonstration primarily focused on the use of AM tooling for fabrication of three composite component structures which are typically utilized in aircraft and comprise salient geometric features of broad interest. These components are often tooling intensive and have features requiring extraction of male tools which are usually trapped by the geometry. The three structures selected by the team included: 1) A one-piece airfoil shell comprised of compound contours where male tooling would be trapped unless the part were manufactured in two halves as is typically the case. 2) A one-piece duct used for air handling, comprised of compound contours where male tooling would be trapped unless the part were manufactured in two halves, or a washout mandrel were to be used. 3) A co-cured C-channel stiffened skin where typically C-channels would be individually manufactured and then bonded to a cured skin. The demonstration was comprised of three main tasks: • Task 1: AM Tool Feasibility Study – ensure the AM tooling meets the performance requirements as specified by SpinTech to match baseline performance. • Task 2: Complex Tool Demonstration – Fabricate tooling, preforms, and parts representative of an airfoil and duct. • Task 3: Large Aerostructure Fabrication Demonstration – Fabricate tooling, preforms, and part representative of a C-channel stiffened skin. With the conclusion of this project, a decision tree was developed to determine the key considerations necessary to determine if use of AM tooling for the three selected structures was able to attain the same quality as historically achieved on metallic tooling, while providing a significant cost reduction.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A unified understanding of minimum lattice thermal conductivity

Here, we propose a first-principles model of minimum lattice thermal conductivity ($κ^{min}_L$) based on a unified theoretical treatment of thermal transport in crystals and glasses. We apply this model to thousands of inorganic compounds and find a universal behavior of $κ^{min}_L$ in crystals in the high-temperature limit: The isotropically averaged $κ^{min}_L$ is independent of structural complexity and bounded within a range from ~0.1 to ~2.6 W/(m K), in striking contrast to the conventional phonon gas model which predicts no lower bound. We unveil the underlying physics by showing that for a given parent compound, $κ^{min}_L$ is bounded from below by a value that is approximately insensitive to disorder, but the relative importance of different heat transport channels (phonon gas versus diffuson) depends strongly on the degree of disorder. Moreover, we propose that the diffuson-dominated $κ^{min}_L$ in complex and disordered compounds might be effectively approximated by the phonon gas model for an ordered compound by averaging out disorder and applying phonon unfolding. With these insights, we further bridge the knowledge gap between our model and the well-known Cahill–Watson–Pohl (CWP) model, rationalizing the successes and limitations of the CWP model in the absence of heat transfer mediated by diffusons. Finally, we construct graph network and random forest machine learning models to extend our predictions to all compounds within the Inorganic Crystal Structure Database (ICSD), which were validated against thermoelectric materials possessing experimentally measured ultralow κ L . Our work offers a unified understanding of $κ^{min}_L$, which can guide the rational engineering of materials to achieve .

42 ENGINEERING↗

DOE OSTI2020

Oxygen evolution reaction over catalytic single-site Co in a well-defined brookite TiO 2 nanorod surface

Efficient electrocatalysts for the oxygen evolution reaction (OER) are paramount to the development of electrochemical devices for clean energy and fuel conversion. However, the structural complexity of heterogeneous electrocatalysts makes it a great challenge to elucidate the surface catalytic sites and OER mechanisms. Here, we report that catalytic single-site Co in a well-defined brookite TiO 2 nanorod (210) surface (Co-TiO 2 ) presents turnover frequencies that are among the highest for Co-based heterogeneous catalysts reported to date, reaching 6.6 ± 1.2 and 181.4 ± 28 s -1 at 300 and 400 mV overpotentials, respectively. Based on grand canonical quantum mechanics calculations and the single-site Co atomic structure validated by in situ and ex situ spectroscopic probes, we have established a full description of the catalytic reaction kinetics for Co-TiO 2 as a function of applied potential, revealing an adsorbate evolution mechanism for the OER. The computationally predicted Tafel slope and turnover frequencies exhibit exceedingly good agreement with experiment.

25 ENERGY STORAGE↗