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DOE OSTI2024

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:↗

NASA NTRS2022

Design Optimization of Energized Composite Using Simulation and Experimental Methods

As electric vehicles (EVs) are evolving, innovative technologies like “energized composite” that can store energy in the car's body helps extend its range per charge. The composite's unique ability to function as both structural body panel and charge storage medium stems from its unique pattern design between “electrochemical areas (EcA)” and “epoxy area (EpA)”. Herein, a design optimization study is presented to obtain a balanced ratio between EcA versus EpA to maximize the charge storage ability of the composite while maintaining a decent tensile and bending strength. Simulations using ANSYS software and experimental confirmation using universal testing machines and electrochemical analyzers are used to derive optimum ratios between EcA and EpA. Uniaxial tension test and 3-point bend test have been performed to optimize the tensile and bend strengths, whereas cyclic voltammetry, galvanic charge–discharge, and electrochemical impedance spectroscopy are used to determine the electrochemical performance of various design configurations by modulating the ratios of EcA versus EpA. Overall, the highest achieved energy storage per lamina is 2531 mWh m−2 for a maximum of 81.6% EcA with a tensile strength of 417.73 MPa and bending strength of 263.13 MPa. This study is highly beneficial for EVs and aerospace applications.

energy storage↗

NASA NTRS1996

Antennas For Receiving Signals Broadcast Via Satellites

Four different antennas designed for use in receiving radio AM and FM signals broadcast via Earth-orbiting satellites at carrier frequency of 2.05 GHz in right-hand circular polarization. Antennas small, lightweight, inexpensive units with low-to-medium-gain, quasi-omnidirectional radiation patterns. Designed for outdoor and indoor uses.

Wu, Te-Kao↗

NASA NTRS2009

An Assessment of the Potential Predictability of Interannual and Decadal Variability Based on Climate Model Simulations with Specified SST

Schubert, Siegfried↗

NASA NTRS1977

Automated array assembly task, phase 1

An assessment of state-of-the-art technologies that are applicable to silicon solar cell and solar cell module fabrication is provided. The assessment consists of a technical feasibility evaluation and a cost projection for high-volume production of silicon solar cell modules. The cost projection was approached from two directions; a design-to-cost analysis assigned cost goals to each major process element in the fabrication scheme, and a cost analysis built up projected costs for alternate technologies for each process element. A technical evaluation was used in combination with the cost analysis to identify a baseline low cost process. A novel approach to metal pattern design based on minimum power loss was developed. These design equations were used as a tool in the evaluation of metallization technologies.

Carbajal, B. G.↗

NASA NTRS2016

Phase Retrieval Implementation for the WFIRST Coronagraph Development Testbed

The Wide-Field Infrared Survey Telescope (WFIRST) is a 2.4m diameter space telescope NASA program. The payload will include two instruments, including a coronagraph instrument (CGI). The CGI will be the first active, high-contrast stellar coronagraph in space intended for imaging, discovery, and spectral characterization of exoplanets and debris discs. The CGI designs under development use deformable mirrors (DM) to create a point spread function (PSF) with a dark region around the obscured star object. Each DM consists of an array of actuators, and each actuator causes a local displacement to a thin, mirror-coated, glass face sheet. The actuator displacements are designed to create the PSF. Typically, phase retrieval is used to set the DM actuator displacements to their designed pattern, and then the actuators are further modified by an iterative control loop to correct for system non-idealities. To observe an exoplanet near the star object, the contrast in the annular region must be better than 10^8 (10^9 after post processing) relative to the unobstructed image of the star [1,2]. The coronagraph testbed at Jet Propulsion Laboratory is used to test coronagraph design and control algorithms. The optical system (Fig. 1) is maintained in a vacuum tank so that the PSF is stable for long integration times. Phase retrieval is an important tool for the testbed and serves several purposes, in addition to setting initial DM actuator displacements. Other uses include evaluation of systematic wavefront error introduced by system components, and alignment of the DMs and pupil masks. For example, the location of specific DM actuators relative to the Lyot mask can be determined by displacing the actuator, then measuring the location of the phase disturbance in the pupil plane with phase retrieval. In the next section we further describe the optical train of the testbed and the collection of source and pupil images available as inputs for phase retrieval, as well as one phase retrieval algorithm employed. Section 3 shows example phase retrieval results.

Marx, David↗

NASA NTRS2016

An Introduction to Transient Engine Applications Using the Numerical Propulsion System Simulation (NPSS) and MATLAB

This document outlines methodologies designed to improve the interface between the Numerical Propulsion System Simulation framework and various control and dynamic analyses developed in the Matlab and Simulink environment. Although NPSS is most commonly used for steady-state modeling, this paper is intended to supplement the relatively sparse documentation on it's transient analysis functionality. Matlab has become an extremely popular engineering environment, and better methodologies are necessary to develop tools that leverage the benefits of these disparate frameworks. Transient analysis is not a new feature of the Numerical Propulsion System Simulation (NPSS), but transient considerations are becoming more pertinent as multidisciplinary trade-offs begin to play a larger role in advanced engine designs. This paper serves to supplement the relatively sparse documentation on transient modeling and cover the budding convergence between NPSS and Matlab based modeling toolsets. The following sections explore various design patterns to rapidly develop transient models. Each approach starts with a base model built with NPSS, and assumes the reader already has a basic understanding of how to construct a steady-state model. The second half of the paper focuses on further enhancements required to subsequently interface NPSS with Matlab codes. The first method being the simplest and most straightforward but performance constrained, and the last being the most abstract. These methods aren't mutually exclusive and the specific implementation details could vary greatly based on the designer's discretion. Basic recommendations are provided to organize model logic in a format most easily amenable to integration with existing Matlab control toolsets.

Matlab↗

NASA NTRS2008

The US CLIVAR Working Group on Drought: A Multi-Model Assessment of the Impact of SST Anomalies on Regional Drought

The US CLIVAR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. Specific questions that the runs are designed to address include: What are mechanisms that maintain drought across the seasonal cycle and from one year to the next. What is the role of the land? What is the role of the different ocean basins, including the impact of EL Nino/Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), the Atlantic Multi-decadal Oscillation (AMO), and warming trends in the global oceans? The runs were done with several global atmospheric models including NASA/NSIPP-1, NCEP/GFS, GFDL/AM2, and NCAR CCM3 and CAM3. In addition, runs were done with the NCEP CFS (coupled atmosphere-ocean) model by employing a novel adjustment technique to nudge the coupled model towards the imposed SST forcing patterns. This talk provides an overview of the experiments and some initial results.

Schubert, Siegfried↗

NASA NTRS2011

Category Learning Research in the Interactive Online Environment Second Life

The interactive online environment Second Life allows users to create novel three-dimensional stimuli that can be manipulated in a meaningful yet controlled environment. These features suggest Second Life's utility as a powerful tool for investigating how people learn concepts for unfamiliar objects. The first of two studies was designed to establish that cognitive processes elicited in this virtual world are comparable to those tapped in conventional settings by attempting to replicate the established finding that category learning systematically influences perceived similarity . From the perspective of an avatar, participants navigated a course of unfamiliar three-dimensional stimuli and were trained to classify them into two labeled categories based on two visual features. Participants then gave similarity ratings for pairs of stimuli and their responses were compared to those of control participants who did not learn the categories. Results indicated significant compression, whereby objects classified together were judged to be more similar by learning than control participants, thus supporting the validity of using Second Life as a laboratory for studying human cognition. A second study used Second Life to test the novel hypothesis that effects of learning on perceived similarity do not depend on the presence of verbal labels for categories. We presented the same stimuli but participants classified them by selecting between two complex visual patterns designed to be extremely difficult to label. While learning was more challenging in this condition , those who did learn without labels showed a compression effect identical to that found in the first study using verbal labels. Together these studies establish that at least some forms of human learning in Second Life parallel learning in the actual world and thus open the door to future studies that will make greater use of the enriched variety of objects and interactions possible in simulated environments compared to traditional experimental situations.

Andrews, Jan↗

DOE OSTI2019

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↗

DOE OSTI2025

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↗

DOE OSTI2023

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↗

DOE OSTI2021

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↗

DOE OSTI2025

The Unified Phenotype Ontology : a framework for cross-species integrative phenomics

Phenotypic data are critical for understanding biological mechanisms and consequences of genomic variation, and are pivotal for clinical use cases such as disease diagnostics and treatment development. For over a century, vast quantities of phenotype data have been collected in many different contexts covering a variety of organisms. The emerging field of phenomics focuses on integrating and interpreting these data to inform biological hypotheses. A major impediment in phenomics is the wide range of distinct and disconnected approaches to recording the observable characteristics of an organism. Phenotype data are collected and curated using free text, single terms or combinations of terms, using multiple vocabularies, terminologies, or ontologies. Integrating these heterogeneous and often siloed data enables the application of biological knowledge both within and across species. Existing integration efforts are typically limited to mappings between pairs of terminologies; a generic knowledge representation that captures the full range of cross-species phenomics data is much needed. We have developed the Unified Phenotype Ontology (uPheno) framework, a community effort to provide an integration layer over domain-specific phenotype ontologies, as a single, unified, logical representation. uPheno comprises (1) a system for consistent computational definition of phenotype terms using ontology design patterns, maintained as a community library; (2) a hierarchical vocabulary of species-neutral phenotype terms under which their species-specific counterparts are grouped; and (3) mapping tables between species-specific ontologies. This harmonized representation supports use cases such as cross-species integration of genotype-phenotype associations from different organisms and cross-species informed variant prioritization.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Gate-tunable enhancement of supercurrent in hybrid planar Josephson junctions

Planar Josephson junctions (JJs) have emerged as a promising platform for the realization of topological superconductivity and Majorana zero modes. To obtain robust quasi one-dimensional (1D) topological superconducting states using planar JJs, limiting the number of 1D Andreev bound states’ subbands that can be present, and increasing the size of the topological superconducting gap are two fundamental challenges. It has been suggested that both problems can be addressed by properly designing the interfaces between the JJ’s normal region and the superconducting leads. We fabricated Josephson junctions with periodic hole structures on the superconducting contact leads on InAs heterostructures with epitaxial superconducting Al. By depleting the chemical potential inside the holes region with a top gate, we observed an enhancement of the supercurrent across the junction. The theoretical analysis shows that the enhancement of the JJ’s critical current is achieved when the depletion of the holes is such to optimize the matching of quasiparticles’ wave function at the normal/superconductor interface. Furthermore, these results show how the combination of carefully designed patterns for the Al coverage, and external gates, can be successfully used to tune the density and wave functions’ profiles in the normal region of the JJ, and therefore open an avenue to tune some of the critical properties, such as number of subbands and size of the topological gap, that must be optimized to obtain robust quasi-1D superconducting states supporting Majorana bound states.

Bogoliubov-de Gennes equations↗

DOE OSTI2021

Enabling discovery data science through cross-facility workflows

Experimental and observational instruments for scientific research (such as light sources, genome sequencers, accelerators, telescopes and electron microscopes) increasingly require High Performance Computing (HPC) scale capabilities for data analysis and workflow processing. Next-generation instruments are being deployed with higher resolutions and faster data capture rates, creating a big data crunch that cannot be handled by modest institutional computing resources. Often these big data analysis pipelines also require near real-time computing and have higher resilience requirements than the simulation and modeling workloads more traditionally seen at HPC centers. While some facilities have enabled workflows to run at a single HPC facility, there is a growing need to integrate capabilities across HPC facilities to enable cross-facility workflows, either to provide resilience to an experiment, increase analysis throughput capabilities, or to better match a workflow to a particular architecture. In this paper we describe the barriers to executing complex data analysis workflows across HPC facilities and propose an architectural design pattern for enabling scientific discovery using cross-facility workflows that includes orchestration services, application programming interfaces (APIs), data access and co-scheduling.

Antypas, Katerina B.↗

DOE OSTI2026

CAHS: Context-Aware Homology Search

Protein homology search is foundational to bioinformatics: it supports annotation transfer, structure/function inference, and evolutionary analysis over rapidly expanding sequence repositories (e.g., UniProtKB). Profile hidden Markov models (pHMMs), as implemented in HMMER, remain the most widely trusted approach because they provide statistically calibrated E-values; however, their gap behavior is fixed once a profile is trained, despite biological evidence that insertion/deletion tolerance varies across flexible loops and intrinsically disordered regions. We present CAHS (Context-Aware Homology Search), a lightweight query-time adapter for pHMM search that incorporates learned and biologically motivated signals without changing HMMER's downstream search pipeline or its calibrated E-value reporting. Given a query sequence, CAHS computes per-residue representations from a protein language model and a disorder predictor, maps these to profile coordinates, and modulates only match-state transition rows (gap-open and gap-extension probabilities) while preserving Plan7 constraints. We comprehensively evaluate CAHS across six structurally diverse protein families and multi-domain architectures against a 570k-sequence target corpus. CAHS expands detection capability, retrieving thousands of additional remote homologs at relaxed thresholds by maintaining alignment quality through flexible regions. For multi-domain proteins, context-aware modulation resolves 94% of fragmented alignments. Crucially, CAHS preserves hit-set invariance at stringent operating points (E<10-10), demonstrating increased statistical confidence without inflating false positives. Furthermore, sharper statistical distinction between homologs and background noise during early filter stages yields up to a 3.87× acceleration in end-to-end wall-clock time on high-performance computing clusters. Overall, CAHS illustrates a practical AI-for-science design pattern: augmenting a trusted probabilistic model with query-specific learned signals to improve interpretable, reproducible inference in data-rich biology.

Bhattaram, Swethasree [Georgia Institute of Techno↗

DOE OSTI2025

solposx: A Python package for determining solar position and atmospheric refraction

solposx is a Python package of reference algorithms for calculating the sun’s position and atmospheric refraction. The package includes 11 solar position algorithms and 6 refraction models from the past 50 years. All functions follow a standardized design pattern, making it easy to compare different algorithms. The provided algorithm implementations have been thoroughly vetted, making the package a valuable research tool and a reliable reference for implementing solar position algorithms in other programming languages or applications.

Jensen, Adam R. [Technical University of Denmark, ↗