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At least 55 records · Page 3

Achieving performance portability in Gaussian basis set density functional theory on accelerator based architectures in NWChemEx

The numerical integration of the exchange–correlation (XC) potential is one of the primary computational bottlenecks in Gaussian basis set Kohn–Sham density functional theory (KS-DFT). To achieve optimal performance and accuracy, care must be taken in this numerical integration to preserve local sparsity as to allow for near linear weak scaling with system size. This leads to an integration scheme with several performance critical kernels which must be hand optimized for each architecture of interest. As the set of available accelerator hardware goes more diverse, a key challenge for developers of KS-DFT software is to maintain performance portability across a wide range of computational architectures. In this article, we examine a modular software design pattern which decouples the implementation details of performance critical kernels from the expression of high-level algorithmic workflows in a device-agnostic language such as C++; thus allowing for developers to target existing and emerging accelerator hardware within a single code base. We consider the efficacy of such a design pattern in the numerical integration of the XC potential by demonstrating its ability to achieve performance portability across a set of accelerator architectures which are representative of those on current and future U.S. Department of Energy Leadership Computing Facilities.

97 MATHEMATICS AND COMPUTING↗

Fabrication of surrogate oxide spent fuel with various cracking patterns and design of an axial gas transport apparatus

In this article, understanding gas transport behavior in nuclear fuel rods is important for the design, performance, and safety of nuclear fuels. Surrogate materials help enable efficient research by reducing both the costs and the amount of time required. A parametric study using Darcy’s law is completed that demonstrates the feasibility of observing pressure decay over short 13-to-15-cm specimens to enable full characterization of the fabricated specimens using x-ray computed tomography. This paper demonstrates that thermally shocked and mechanically compressed alumina pellets produce surrogate samples whose various cracking patterns are representative of the severity of cracking observed as a function of burnup in irradiated nuclear fuels. Furthermore, image analyses of the cracking patterns—in conjunction with gas transport testing using surrogate samples—affords a valuable accelerated basis for developing gas transport simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Elastic forces drive nonequilibrium pattern formation in a model of nanocrystal ion exchange

The widely used process of nanocrystal ion exchange operates out of thermodynamic equilibrium and can require mixing components of varying sizes. Here we use theory and computer simulation to study a simple model which captures these two basic features of ion exchange reactions. We show that a strong driving force for exchange among different-sized species creates nonequilibrium patterns within model nanocrystals. We further demonstrate that such patterns can be thermodynamically stable within core/shell nanocrystals. These results help us understand the heterostructures formed in ion-exchanged nanocrystals and suggest strategies for leveraging elasticity to design patterns in nanoscale materials. Chemical transformations, such as ion exchange, are commonly employed to modify nanocrystal compositions. Yet the mechanisms of these transformations, which often operate far from equilibrium and entail mixing diverse chemical species, remain poorly understood. Here we explore an idealized model for ion exchange in which a chemical potential drives compositional defects to accumulate at a crystal’s surface. These impurities subsequently diffuse inward. We find that the nature of interactions between sites in a compositionally impure crystal strongly impacts exchange trajectories. In particular, elastic deformations which accompany lattice-mismatched species promote spatially modulated patterns in the composition. These same patterns can be produced at equilibrium in core/shell nanocrystals, whose structure mimics transient motifs observed in nonequilibrium trajectories. Moreover, the core of such nanocrystals undergoes a phase transition—from modulated to unstructured—as the thickness or stiffness of the shell is decreased. Our results help explain the varied patterns observed in heterostructured nanocrystals produced by ion exchange and suggest principles for the rational design of compositionally patterned nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

PLEXUS: A Pattern-Oriented Runtime System Architecture for Resilient Extreme-Scale High-Performance Computing Systems

For high-performance computing (HPC) system designers and users, meeting the myriad challenges of next-generation exascale supercomputing systems requires rethinking their approach to application and system software design. Among these challenges, providing resiliency and stability to the scientific applications in the presence of high fault rates requires new approaches to software architecture and design. As HPC systems become increasingly complex, they require intricate solutions for detection and mitigation for various modes of faults and errors that occur in these large-scale systems, as well as solutions for failure recovery. These resiliency solutions often interact with and affect other system properties, including application scalability, power and energy efficiency. Therefore, resilience solutions for HPC systems must be thoughtfully engineered and deployed.In previous work, we developed the concept of resilience design patterns, which consist of templated solutions based on well-established techniques for detection, mitigation and recovery. In this paper, we use these patterns as the foundation to propose new approaches to designing runtime systems for HPC systems. The instantiation of these patterns within a runtime system enables flexible and adaptable end-to-end resiliency solutions for HPC environments. The paper describes the architecture of the runtime system, named Plexus, and the strategies for dynamically composing and adapting pattern instances under runtime control. This runtime-based approach enables actively balancing the cost-benefit trade-off between performance overhead and protection coverage of the resilience solutions. Based on a prototype implementation of PLEXUS, we demonstrate the resiliency and performance gains achieved by the pattern-based runtime system for a parallel linear solver application.

Hukerikar, Saurabh↗

Heat-activated Plasmonic Chemical Sensors for Harsh Environments

A passive plasmonics based chemical sensing system to be used in harsh operating environments was investigated and developed within this program. The initial proposed technology was based on combining technologies developed at the SUNY Polytechnic Institute Colleges of Nanoscale Science and Engineering (CNSE) and at the University of Minnesota (UM). Specifically, a passive wireless technique developed at UM was to utilize a heat-activated plasmonic design to passively harvest the thermal energy from within a combustion emission stream and convert this into a narrowly focused light source. This plasmonic device was based on a bullseye design patterned into a gold film using focused ion beam methods (FIB). Critical to the design was the use of thermal stabilizing under and overlayers surrounding the gold film. These stabilizing layers were based on both atomic layer deposited films as well as metal laminate layers developed by United Technologies Aerospace Systems (UTAS). While the bullseye design was never able to be thermally stabilized for operating temperatures of 500oC or higher, an alternative energy harvesting design was developed by CNSE within this program. With this new development, plasmonic sensing results are presented where thermal energy is harvested using lithographically patterned Au nanorods, replacing the need for an external incident light source. Gas sensing results using the harvested thermal energy are in good agreement with sensing experiments, which used an external incident light source. Principal Component Analysis (PCA) was used to reduce the wavelength parameter space from 665 variables down to 4 variables with similar levels of demonstrated selectivity. The method was further improved by patterning rods which harvested energy in the near infrared, which led to a factor of 10 decrease in data acquisition times as well as demonstrated selectivity with a reduced wavelength data set. The combination of a plasmonic-based energy harvesting sensing paradigm with PCA analysis and wavelength down selection offers a novel path towards simplification and integration of plasmonic-based sensing methods using selected wavelengths rather than a full spectral analysis. Integration efforts were designed and modeled for thermal and mass transport considerations by UTAS which led to the 3D printing of scaled models that would serve as the housing for the alternative energy harvesting plasmonic chemical sensor design developed by CNSE.

47 OTHER INSTRUMENTATION↗

Island scanning pattern optimization for residual deformation mitigation in laser powder bed fusion via sequential inherent strain method and sensitivity analysis

Laser powder bed fusion (L-PBF) has emerged as one of the mainstream additive manufacturing approaches for fabricating metal parts with complex geometries and intricate internal structures. However, large deformation associated with rapid heating and cooling can lead to build failure and requires post-processing which may increase manufacturing cost and prolong the production period. Here in this work, an island scanning pattern design method is proposed to optimize the scanning direction of each island in order to reduce part deformation after cutting off the build platform. The objective of this optimization is to minimize the upward bending of the part after sectioning, which allows the part deformation to satisfy the tolerance requirement or reduce the post heat treatment time. Inherent strain method is employed in the sequential finite element analysis consisting of layer-by-layer activations and sectioning for fast residual distortion prediction. Full sequential sensitivity analysis for the formulated optimization is provided to update the island scanning directions. To show the feasibility and effectiveness of the proposed method, the scanning patterns of a block structure and a connecting rod were designed and parts were fabricated using an open architecture L-PBF machine. The fabrication experiments demonstrated that the residual deformation of both parts fabricated by optimized scanning pattern can be reduced by over 50% compared to the initial scanning patterns, which demonstrate the effectiveness of the proposed method.

36 MATERIALS SCIENCE↗

Nucleation and growth of blue phase liquid crystals on chemically-patterned surfaces: a surface anchoring assisted blue phase correlation length

In condensed matter, the correlation length is an essential parameter which describes the distance over which a material maintains its structural properties. In liquid crystals, for the orientational order parameter this characteristic length is of the order of nanometers, while in solid crystals it can extend to macroscopic length scales. Here, we report the measurement of the correlation length, or persistence length, of the crystallographic orientation of blue phases (BPs)—chiral liquid crystals with long-range 3D-crystalline structures and submicron-sized lattice-parameters. These materials exhibit phase transformations that have been identified as the liquid analog of crystal-crystal martensitic transformations. In this work, we use liquid epitaxial growth to achieve spontaneous BP-crystal nucleation and subsequent growth. Specifically, we design patterned substrates made of a binary array of regions with different liquid crystal anchoring, which facilitate a uniform nucleation and growth of BP-crystals with (100)-lattice orientation and a simple cubic symmetry. Furthermore, our results indicate that this simple cubic BP, the so-called blue phase II (BPII), forms first on the patterned surface, thereby propagating the growth of domains in directions parallel or perpendicular to the patterned regions. These results are used to understand the emergence of a surface anchoring assisted BPII-correlation length, taken as the distance over which the BP preserves its lattice orientation, as a function of time and pattern characteristics. We found that BPII single crystals can be achieved on patterned regions whose lateral dimensions are equal to or larger than 10 μm, consistent with our measurements of the BPII-correlation length. This newly acquired understanding of the role of surfaces on the formation of BPs is then used to design processes that permit formation of macroscopically large mono-domain, single-crystal BPs by relying on significantly reduced patterned areas (only part of the area is patterned), a feature that could benefit the applications of this intriguing class of materials.

correlation length↗

GraphAide: Advanced Graph-Assisted Query and Reasoning System

Curating knowledge from multiple siloed sources that contain both structured and unstructured data is a major challenge in many real-world applications. Pattern matching and querying represent fundamental tasks in modern data analytics that leverage this curated knowledge. The development of such applications necessitates overcoming several research challenges, including data extraction, named entity recognition, data modeling, and designing query interfaces. Moreover, the explainability of these functionalities is critical for their broader adoption. The emergence of Large Language Models (LLMs) has accelerated the development lifecycle of new capabilities. Nonetheless, there is an ongoing need for domain-specific tools tailored to user activities. The creation of digital assistants has gained considerable traction in recent years, with LLMs offering a promising avenue to develop such assistants utilizing domain-specific knowledge and assumptions. In this context, we introduce an advanced query and reasoning system, GraphAide, which constructs a knowledge graph (KG) from diverse sources and allows to query and reason over the resulting KG. GraphAide harnesses both the KG and LLMs to rapidly develop domain-specific digital assistants. It integrates design patterns from retrieval augmented generation (RAG) and the semantic web to create an agentic LLM application. GraphAide underscores the potential for streamlined and efficient development of specialized digital assistants, thereby enhancing their applicability across various domains.

Purohit, Sumit [BATTELLE (PACIFIC NW LAB)] (ORCID:↗

TermGenie – a web-application for pattern-based ontology class generation

Biological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes. TermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 new classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes. Lastly, TermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.

97 MATHEMATICS AND COMPUTING↗

Reactivity Coefficient Calculation for a Low-Power LEU Research Reactor

Core design studies on a 20-MW thermal power low enriched uranium (LEU) fueled research reactor are underway at the NIST Center for Neutron Research (NCNR) with the primary purpose of providing quality neutron beams for scientific research. The 'tank-in-pool' design pattern is adopted for the new reactor: A compact core composed of two horizontally split halves are surrounded by a cylindrical D{sub 2}O reflector tank, and the tank is itself surrounded by a large H{sub 2}O pool, which functions as thermal and biological shielding. The split core consists of 18 MTR-type fuel elements which are evenly distributed into two regions. The LEU fuel used in the study is the U{sub 3}Si{sub 2}-Al dispersion fuel with U-235 enrichment of 19.75%, the only NRC certified LEU fuel in the U.S. The core is cooled and moderated by H{sub 2}O, and separated from D{sub 2}O by zircaloy core boxes. Hafnium control blades are utilized as both criticality and safety control elements for the reactor. They are controlled by a mechanical driver located at the bottom of the core but with the fully withdrawn positions at the top of the core. In a standard reactor calculation, it is necessary to evaluate the reactivity coefficient with respect to some physical parameters such as fuel or moderator temperature. For nearly all reactor designs, negative reactivity coefficients are required for safety. As a light-water cooled thermal reactor, the new reactor is designed to work in an under-moderated mode with the most achievable reactivity. The core is required to have negative reactivity coefficients under any normal or abnormal circumstances such as over power transient, loss of coolant or reflector, etc. Therefore the reactivity coefficient addresses reactor safety concerns as well as provides valuable quantitative parameters for reactor safety analyses. In this summary, three typical reactivity coefficients for the low-power LEU core are calculated using the Monte-Carlo code MCNP-6: the moderator temperature coefficient (MTC), the fuel temperature coefficient (FTC), and the void coefficient (VC). A direct perturbation methodology is applied to calculate all these coefficients. The perturbed case is produced by manually perturbing a single physical property with respect to the reference case (the one with normal operational conditions), as the multiplication factor (i.e. k{sub eff}) of the perturbed case is calculated by MCNP. The corresponding reactivity coefficient is thereby determined by dividing the reactivity change over the associated parameter changes. Core design studies are underway at NIST to develop a low-power LEU fueled beam reactor to advance the neutron source capability at NCNR for the next century. The reactivity effect caused by moderator temperature, fuel temperature and void is investigated though a direct perturbation approach using the MCNP code. The MTC, FTC, and VC for a representative startup core is obtained and the negative effect characteristics of these coefficients are observed. The reactivity effects under several postulated abnormal scenarios are also investigated. The overall negative feedback to the reactivity at each situation is confirmed. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

ATDM LANL FleCSI: Topology and Execution Framework

FleCSI is a compile-time configurable C++ framework designed to support multi-physics application development. As such, FleCSI attempts to provide a very general set of infrastructure design patterns that can be specialized and extended to suit the needs of a broad variety of solver and data requirements. This means that FleCSI is potentially useful to many different ECP projects. Current support includes multidimensional mesh topology, mesh geometry, and mesh adjacency information, n-dimensional hashed-tree data structures, graph partitioning interfaces, and dependency closures (to identify data dependencies between distributed-memory address spaces). FleCSI introduces a functional programming model with control, execution, and data abstractions that are consistent with state-of-the-art task-based runtimes such as Legion and Charm++. The model also provides support for fine-grained, data-parallel execution with backend support for runtimes such as OpenMP and C++17. The FleCSI abstraction layer provides the developer with insulation from the underlying runtimes, while allowing support for multiple runtime systems, including conventional models like asynchronous MPI. The intent is to give developers a concrete set of user-friendly programming tools that can be used now, while allowing flexibility in choosing runtime implementations and optimizations that can be applied to architectures and runtimes that arise in the future. This project is essential to the ECP Ristra Next-Generation Code project, part of ASC ATDM, because it provides a hierarchically parallel programming model that is consistent with the design of modern system architectures, but which allows for the straightforward expression of algorithmic parallelism in a portably performant manner.

97 MATHEMATICS AND COMPUTING↗

Association of Maternal Social Relationships With Cognitive Development in Early Childhood

This study examines how different types of social network structures are associated with early cognitive development in children. Objectives To assess how social relationships and structures are associated with early cognitive development and to elucidate whether variations in the mother’s social networks alter a child’s early cognitive development patterns. Design, Setting, and Participants This cohort study used data from 1082 mother-child pairs in the University of Tennessee Health Science Center–Conditions Affecting Neurocognitive Development and Learning and Early Childhood project to examine the association between networks of different levels of complexity (triad, family, and neighborhood) and child cognitive performance after adjustment for the mother’s IQ, birth weight, and age, and the father’s educational level. The final model was adjusted for the household poverty level. Data were collected from December 2006 through January 2014 and analyzed from October through November 2018. Exposures The child-mother relationship, child-mother-father triad, family setting, child’s dwelling network, mother’s social support network, and neighborhood networks. Main Outcomes and Measures Measure of cognitive development of the child using Bayley Scales of Infant Development (BSID) at 2 years of age. Results Of 1082 participants, 544 (50.3%) were males and 703 (65.1%) were African American; the mean (SD) age was 2.08 (0.12) years. Large family size had a negative association with early cognitive development, with a mean 2.21-point decrease in BSID coefficient score (95% CI, 0.40 to 4.02; P = .01). Mother’s social support network size was positively associated early cognitive development, with a mean 0.40-point increase in BSID coefficient score (95% CI, 0.001 to 0.80; P = .05). Knowing many neighbors was not statistically significantly associated with early cognitive development, with a mean 1.39-point increase in BSID coefficient score (95% CI, -0.04 to 2.83; P = .06). Conclusions and Relevance The findings suggest that maternal social relationships are associated with cognitive development in children and that social relationships beyond the mother-child-father triad are significantly associated with children’s cognitive development. This study investigates the environmental influences on child health outcomes and, specifically, how early cognitive development is associated with social networks for the primary caregiver.

60 APPLIED LIFE SCIENCES↗

Extrusion‐Based Printing of Nanostructured Fatty Acid Gels Incorporated in Hydrogels

Soft materials with unique nanostructures such as lamellar, hexagonal, and cubic morphologies can replicate complex structures that have potential in various fields, including biomedical and industrial applications. However, a key challenge in advancing the broader applications of 3D printing for these nanostructured soft materials is insufficient mechanical properties that hinder their printability and compromise structural stability in the final product. In this study, the suitability of a fatty acid‐based lamellar gel is evaluated for direct extrusion‐based 3D printing. Here, the lamellar gel with varying water content is integrated with a photocurable hydrogel to preserve the shape and stability of the final prints. Complex 2D and 3D design patterns are used to assess extrusion behavior, structural stability, and print precision under varying pressures. Small‐angle X‐ray Scattering (SAXS) measurements reveal the formation of lamellar nanostructures and confirm their retention after photocuring in various gels. Rheological analysis confirms that these gels exhibit key properties suitable for extrusion‐based 3D printing, such as shear‐thinning behavior. Additionally, tensile testing is conducted to evaluate the mechanical properties across cured print samples. This study underscores the potential of nanostructured gels as a robust and versatile platform, facilitating the development of materials engineered for various applications.

36 MATERIALS SCIENCE↗

The INTERSECT Open Federated Architecture for the Laboratory of the Future

A federated instrument-to-edge-to-center architecture is needed to autonomously collect, transfer, store, process, curate, and archive scientific data and reduce human-in-the-loop needs with (a) common interfaces to leverage community and custom software, (b) pluggability to permit adaptable solutions, reuse, and digital twins, and (c) an open standard to enable adoption by science facilities world-wide. The Selfdriven Experiments for Science/Interconnected Science Ecosystem (INTERSECT) Open Architecture enables science breakthroughs using intelligent networked systems, instruments and facilities with autonomous experiments, “self-driving” laboratories, smart manufacturing and artificial intelligence (AI) driven design, discovery and evaluation. It creates an open federated architecture for the laboratory of the future using a novel approach, consisting of (1) science use case design patterns, (2) a system of systems architecture, and (3) a microservice architecture.

Engelmann, Christian↗

Hoobas: A highly object-oriented builder for molecular dynamics

Polydispersity and random sequences are ubiquitous features of polymers, and molecular dynamics simulations can help elucidate the impact of disorder in polymer systems. However, currently available packages for building polymer topologies do not enable the user to include randomness in a straightforward fashion. Here, we introduce Hoobas, a molecular builder package that easily handles polydispersity using a prototype-builder design pattern. This enables fast and easy building of systems comprised of thousands of distinct objects. It is written in the Python programming language, which ensures compatibility with a wide range of molecular dynamics packages and tools, as well as easy integration into most workflows.

97 MATHEMATICS AND COMPUTING↗

Elliptic Cylinder Airborne Sampling and Geostatistical Mass Balance Approach for Quantifying Local Greenhouse Gas Emissions

In this paper, we explore observational, experimental, methodological, and practical aspects of the flux quantification of greenhouse gases from local point sources by using in situ airborne observations, and suggest a series of conceptual changes to improve flux estimates. We address the major sources of uncertainty reported in previous studies by modifying (1) the shape of the typical flight path, (2) the modeling of covariance and anisotropy, and (3) the type of interpolation tools used. We show that a cylindrical flight profile offers considerable advantages compared to traditional profiles collected as curtains, although this new approach brings with it the need for a more comprehensive subsequent analysis. The proposed flight pattern design does not require prior knowledge of wind direction and allows for the derivation of an ad hoc empirical correction factor to partially alleviate errors resulting from interpolation and measurement inaccuracies. Finally, the modified approach is applied to a use-case for quantifying CH 4 emission from an oil field south of San Ardo, CA, and compared to a bottom-up CH 4 emission estimate.

54 ENVIRONMENTAL SCIENCES↗

Low-temperature characterization of Nb-Cu-Nb weak links with Ar ion-cleaned interfaces

We characterize niobium-based lateral Superconductor (S)–Normal metal (N)–Superconductor (SNS) weak links through low-temperature switching current measurements and tunnel spectroscopy. We fabricate the SNS devices in two separate lithography and deposition steps, combined with strong argon ion cleaning before the normal metal deposition in the last step. Our SNS weak link consists of high-quality sputtered Nb electrodes that have contacted with evaporated Cu. The two-step fabrication flow enables more flexibility in the choice of materials and pattern design. A comparison of the temperature-dependent equilibrium critical supercurrent with theoretical predictions indicates that the quality of the Nb-Cu interface is similar to that of evaporated Al-Cu weak links. We further demonstrate a hybrid magnetic flux sensor based on an Nb-Cu-Nb SNS junction, where the phase-dependent normal metal density of states is probed with an Al tunnel junction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗