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NASA NTRS2017

Experimental and Numerical Investigation of Air Radiation in Superorbital Expanding Flow

To investigate air radiation in expanding flows and provide experimental data for validating associated computational models, experiments were conducted in the X2 expansion tunnel facility at the Centre for Hypersonics of the University of Queensland. A 54 turning angle wedge model was employed to generate steady expanding flows with in flow total enthalpies of 50.7, 63.4 and 75.4 MJkg. VUV spectra from 118 to 180 nm were acquired across the wedge at three equispaced distances away from the top of the model, as well as through its top surface. High speed filtered images were also obtained by coupling a Shimadzu 1 MHz high speed camera to a bandpass filter to obtain calibrated images of the 777 nm oxygen triplet. Both the across-wedge VUV spectra and filtered images of the 777 nm atomic oxygen were compared with NEQAIR simulations, which were performed using flow field data from two-dimensional CFD simulations with two-temperature 11-species air chemistry utilizing the in-house Navier-Stokes flow solver Eilmer3. Data extracted from consecutive frames of the filtered high speed images confirmed up to 8 s of available test time for the flow conditions tested. For the strongly radiating 149 and 174 nm atomic nitrogen lines, large disagreement between experimental data and NEQAIR predictions can be observed from the start of the expansion fan where the electron-ion recombination process commences. The spatial extent, or spans of the radiance profiles of the 149 and 174 nm N lines are significantly under predicted by NEQAIR, and are very close to those of N, N+ and electron number density profiles, which follow that of flow density. The electron-ion recombination process is proposed as the main reason for these discrepancies. The comparisons between NEQAIR simulations and filtered images of the 777 nm oxygen triplet show good agreement in the post-shock compression region and the start of the expansion fan for the 63.4 MJkg condition, but with up to a factor of three over prediction by NEQAIR further downstream, which is attributed to electron-impact excitation. Similar trends are found with the 75.4 MJkg condition, with reduced level of agreement in the compression region, which can be due to uncertainties in inflow condition.

Earth entry↗

NASA NTRS2017

Experimental and Numerical Investigation of Air Radiation in Superorbital Expanding Flow

To investigate air radiation in expanding flows and provide experimental data for validating associated computational models, experiments were conducted in the X2 expansion tunnel facility at the Centre for Hypersonics of the University of Queensland. A 54deg turning angle wedge model was employed to generate steady expanding flows with in flow total enthalpies of 50.7, 63.4 and 75.4 MJ/kg. VUV spectra from 118 to 180 nm were acquired across the wedge at three equispaced distances away from the top of the model, as well as through its top surface. High speed filtered images were also obtained by coupling a Shimadzu 1 MHz high speed camera to a bandpass filter to obtain calibrated images of the 777 nm oxygen triplet. Both the across-wedge VUV spectra and filtered images of the 777 nm atomic oxygen were compared with NEQAIR simulations, which were performed using flow field data from two-dimensional CFD simulations with two-temperature 11-species air chemistry utilising the in-house Navier-Stokes flow solver Eilmer3. Data extracted from consecutive frames of the filtered high speed images confirmed up to 8 s of available test time for the flow conditions tested. For the strongly radiating 149 and 174 nm atomic nitrogen lines, large disagreement between experimental data and NEQAIR predictions can be observed from the start of the expansion fan where the electron-ion recombination process commences. The spatial extent, or spans of the radiance profiles of the 149 and 174 nm N lines are significantly underpredicted by NEQAIR, and are very close to those of N, N+ and electron number density profiles, which follow that of flow density. The electron-ion recombination process is proposed as the main reason for these discrepancies. The comparisons between NEQAIR simulations and filtered images of the 777 nm oxygen triplet show good agreement in the post-shock compression region and the start of the expansion fan for the 63.4 MJ/kg condition, but with up to a factor of three overprediction by NEQAIR further downstream, which is attributed to electron-impact excitation. Similar trends are found with the 75.4 MJ/kg condition, with reduced level of agreement in the compression region, which can be due to uncertainties in inflow condition.

expansion tube↗

DOE OSTI2025

Time Distribution Analysis for Task Primitives to Support Dynamic Human Reliability Analysis

To support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method and Human Reliability data EXtraction (HuREX). GOMS-HRA was developed to provide cognition-based time and human error probability (HEP) information for dynamic HRA calculations within the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework, while HuREX is a comprehensive HRA data collection method developed by the Korea Atomic Energy Research Institute (KAERI). In this paper, we examine time distributions by using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which proposes an HRA data collection framework to complement full-scope simulator research and gather input data for dynamic HRA by using simplified simulators such as the Rancor Microworld simulator. This paper investigates whether the time required for GOMS-HRA and HuREX task primitives fits 13 statistical distributions. Additionally, we compare and discuss the time distributions obtained from both student operators and professional operators. The result was that this study identified several time distributions for five GOMS-HRA and four HuREX task primitives. In the future, the results of this study are expected to provide objective reference data on the elapsed time for task primitives and aid in realistically simulating scenarios within dynamic HRA.

Dynamic Human Reliability Analysis↗

NASA NTRS2024

SMAnalytics Automated Shape Memory Test Analysis Software User's Manual: UCFTC, UPER, and DSC Test Methods, Version 1.0.2

Over the course of 60 years of shape memory alloy research and development, the properties of these alloys have been measured using various testing methods, which are often customized by the organization performing the test. However, commercial adoption of shape memory alloys in aeronautic actuator applications requires reducing property uncertainty through standardizing test methods. Historically, differential scanning calorimetry (DSC) has been used to measure transformation temperatures under stress-free conditions. This testing method is well established, and tests are run under the applicable standard, ASTM F2004-17: Standard Test Method for Transformation Temperature of Nickel-Titanium Alloys by Thermal Analysis. Two other test methods for measuring strains and transformation temperatures under constant load or free recovery after prestraining have only recently been standardized—ASTM E3097: Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of SMAs (UCFTC) and ASTM E3098: Standard Test Method for Mechanical Uniaxial Pre-Strain and Thermal Free Recovery of SMAs (UPFR). These standards represent a critical step forward in producing reliable material property data for the use of these alloys in aeronautics and other commercial areas. However, no standard programs or software packages were previously available for postprocessing UCFTC- and UPFR-type test data to extract property data. Each organization that performed the testing analyzed data using its own custom manual methods, such as using a plot and a straight edge, spreadsheet plotting methods, or custom code routines, to extract the required values for strains, stresses, and transformation temperatures. SMAnalytics represents the first publicly available uniform software package for processing data generated using the DSC, UCFTC, and UPFR test methods, as well as many modifications of these methods, including loading in martensite versus austenite and performing multiple thermal cycles at stress. In doing so, it provides a tool for reducing potential error or variability in the measured values due to the precision of the technique used and person-to-person variability. It is also expected that this automated data-parsing tool can accelerate the data analysis phase of the test campaign, especially for large data files. This User’s Manual describes how the SMAnalytics software works and the method for its use.

Shape Memory Alloy↗

DOE OSTI2024

Multicriteria Measures to Assess the Sustainability of Diets: A Systematic Review

Abstract Context Assessing the overall sustainability of a diet is a challenging undertaking requiring a holistic approach capable of addressing the multicriteria nature of this concept. Objective The aim was to identify and summarize the multicriteria measures used to assess the sustainability characteristics of diets reported at the individual level by healthy adults. Data Sources Articles were identified via PubMed, Scopus, and Web of Science. The search strategy consisted of key words and MeSH terms, and was concluded in September 2022, covering references in English, Spanish, and Portuguese. Data Extraction This systematic review followed the PRISMA guidelines. The search identified 5663 references, from which 1794 were duplicates. Two reviewers independently screened the titles and abstracts of each of the 3869 records and the full-text of the 144 references selected. Of these, 7 studies met the inclusion criteria. Data Analysis A total of 6 multicriteria measures were identified: 3 different Sustainable Diet Indices, the Quality Environmental Costs of Diet, the Quality Financial Costs of Diet, and the Environmental Impact of Diet. All of these incorporated a health/nutrition dimension, while the environmental and economic dimensions were the second and the third most integrated, respectively. A sociocultural sustainability dimension was included in only 1 of the measures. Conclusion Despite some methodological concerns in the development and validation process of the identified measures, their inclusion is considered indispensable in assessing the transition towards sustainable diets in future studies. Systematic Review Registration PROSPERO registration no. CRD42022358824.

Rei, Mariana (ORCID:0000000189453708)↗

NASA NTRS1994

Advanced Video Analysis Needs for Human Performance Evaluation

Evaluators of human task performance in space missions make use of video as a primary source of data. Extraction of relevant human performance information from video is often a labor-intensive process requiring a large amount of time on the part of the evaluator. Based on the experiences of several human performance evaluators, needs were defined for advanced tools which could aid in the analysis of video data from space missions. Such tools should increase the efficiency with which useful information is retrieved from large quantities of raw video. They should also provide the evaluator with new analytical functions which are not present in currently used methods. Video analysis tools based on the needs defined by this study would also have uses in U.S. industry and education. Evaluation of human performance from video data can be a valuable technique in many industrial and institutional settings where humans are involved in operational systems and processes.

Campbell, Paul D.↗

NASA NTRS2004

Grid Technology as a Cyber Infrastructure for Earth Science Applications

This paper describes how grids and grid service technologies can be used to develop an infrastructure for the Earth Science community. This cyberinfrastructure would be populated with a hierarchy of services, including discipline specific services such those needed by the Earth Science community as well as a set of core services that are needed by most applications. This core would include data-oriented services used for accessing and moving data as well as computer-oriented services used to broker access to resources and control the execution of tasks on the grid. The availability of such an Earth Science cyberinfrastructure would ease the development of Earth Science applications. With such a cyberinfrastructure, application work flows could be created to extract data from one or more of the Earth Science archives and then process it by passing it through various persistent services that are part of the persistent cyberinfrastructure, such as services to perform subsetting, reformatting, data mining and map projections.

Hinke, Thomas H.↗

NASA NTRS1983

Approach to establishing the effect of aeroelasticity on aerodynamic characteristics of the space shuttle orbiter

The static aeroelastic effects on the longitudinal stability and elevon/aileron effectiveness of the space transportation system (STS) Space Shuttle orbiter were estimated by a simplified approach called the elevon torsional stiffness (ETS) method. This method employs rigid model wind tunnel test results to predict aeroelastic effects. Lateral/directional stability and rudder effectiveness were based on results of a wind tunnel test in which a flexible tail model was used. Comparisons with selective flight data are made in this paper. Results of correlations with flight data (although limited at the present time) verify the predicted aeroelastic effects for the orbiter. The orbiter's structural characteristics are such that the effects of aeroelasticity, whether estimated using analytical techniques or simplified methods, do not appear to affect the vehicle performance to any great extent. The large amount of scatter in the flight-extracted data made verification of the aeroelastic corrections very difficult. Generally, the simplified elevon torsional stiffness method provided better correlation with flight test results than he analytical method and reduced the verification effort and cost.

Schlosser, D. C.↗

NASA NTRS1991

Spectra, composition and interactions of nuclei above 10 TeV using magnet-interferometric chambers (SCIN/MAGIC)

Initial definition studies were performed for the SCIN/MAGIC experiment selected as an Astromag investigation on Space Station Freedom. The study focused on Science Objectives and Science Requirement, Accommodation on both the STS and the Astromag facility, Data extraction techniques and Background Studies. The detectors are emulsion chambers which will be exposed for approximately 90 days and then recovered from orbit for subsequent processing and analysis in the laboratory. Such a technique is the only means to obtain information on the ultrahigh energy cosmic rays and their nuclear interactions. The SCIN/MAGIC investigation can supply unique data in relatively unexplored energy region and address many of the fundamental questions in particle astrophysics.

Wefel, John P.↗

NASA NTRS1973

Engineering analysis of ERTS data for rice in the Philippines

The author has identified the following significant results. Rice is an important food worldwide. Worthwhile goals, particularly for developing nations, are the capability to recognize from satellite imagery: (1) areas where rice is grown, and (2) growth status (irrigation, vigor, yield). A two-step procedure to achieve this is being investigated. Ground truth, and ERTS-1 imagery (four passes) covering 80% of a rice growth cycle for some Philippine sites, have been analyzed. One-D and three-D signature extraction, and synthesis of an initial site recognition/status algorithm have been performed. Results are encouraging. but additional passes and sites must be analyzed. Good position information for extracted data is a must.

Mcnair, A. J.↗

NASA NTRS1995

Analysis of filter tuning techniques for sequential orbit determination

This paper examines filter tuning techniques for a sequential orbit determination (OD) covariance analysis. Recently, there has been a renewed interest in sequential OD, primarily due to the successful flight qualification of the Tracking and Data Relay Satellite System (TDRSS) Onboard Navigation System (TONS) using Doppler data extracted onboard the Extreme Ultraviolet Explorer (EUVE) spacecraft. TONS computes highly accurate orbit solutions onboard the spacecraft in realtime using a sequential filter. As the result of the successful TONS-EUVE flight qualification experiment, the Earth Observing System (EOS) AM-1 Project has selected TONS as the prime navigation system. In addition, sequential OD methods can be used successfully for ground OD. Whether data are processed onboard or on the ground, a sequential OD procedure is generally favored over a batch technique when a realtime automated OD system is desired. Recently, OD covariance analyses were performed for the TONS-EUVE and TONS-EOS missions using the sequential processing options of the Orbit Determination Error Analysis System (ODEAS). ODEAS is the primary covariance analysis system used by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD). The results of these analyses revealed a high sensitivity of the OD solutions to the state process noise filter tuning parameters. The covariance analysis results show that the state estimate error contributions from measurement-related error sources, especially those due to the random noise and satellite-to-satellite ionospheric refraction correction errors, increase rapidly as the state process noise increases. These results prompted an in-depth investigation of the role of the filter tuning parameters in sequential OD covariance analysis. This paper analyzes how the spacecraft state estimate errors due to dynamic and measurement-related error sources are affected by the process noise level used. This information is then used to establish guidelines for determining optimal filter tuning parameters in a given sequential OD scenario for both covariance analysis and actual OD. Comparisons are also made with corresponding definitive OD results available from the TONS-EUVE analysis.

Lee, T.↗

NASA NTRSDate not supplied

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The Predictive Simulation Capability (PSC) Element is focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the predictive simulation capability, the GCD Program also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper will present the status of implementing and maturing particle-particle interaction constituent physics models essential in simulating the landing surface granular material flow under PSI effects. This gas-particle multi-phase interaction modeling of plume impingement flow on the extra-terrestrial soil material is performed with the Gas-Granular Flow Solver (GGFS) addressed in a companion paper. The response of regolith particle flow induced by lander PSI requires accurate representation of the regolith granular material fluidic behavior and gas-granular interactions. The lunar regolith, as the extreme example, is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking particle shapes for the very jagged particles. The combination of particle shape and size distribution has been identified as major drivers in the complex particle flow response and resulting crater shape characteristics of extraterrestrial granular material. Constituent models for spherical particles can be formulated directly from particle kinetics theory. Complex particle shapes can be modeled by gluing together elemental spherical shapes into composite particles, requiring a Discrete Element Model (DEM) particle kinetics modeling approach to extract data and formulate constituent models. Mixture constituent models for poly-disperse mixtures (i.e, containing distribution of particle sizes) have recently been developed. The required non-spherical particle mixture granular material response closure models are then obtained through small-scale unit physics DEM simulations for the range of particle shapes, mixtures and packing densities. The granular material response closure models are then implemented in the Eulerian granular flow formulation. This DEM-based constituent model extraction process and formulation of poly-disperse particle mixtures has been successfully developed by small business and academic partners in the development of the Gas-Granular Flow Solver (GGFS) simulation program simulation framework. The currently implemented capabilities have reached the capability level of modeling bi-disperse, non-spherical particle mixtures is being continuously extended towards computational modeling of full range irregular particle mixtures. Under the GCD project, this technology is being further developed, transferred to NASA analysts, and matured towards application readiness. The predictive simulation capability team under the GCD project has acquired the modeling tools and processes of the DEM based constituent model formulation from the GGFS development team and is developing the capability to replicate the existing process. This is the first important step towards the ability of the NASA team to independently perform such model development in a production setting. Further efforts are underway to migrate the DEM based model simulation process performed with the academic based tools to more capable Open Source, highly parallelized simulation tools for efficient operation on NASA HPC assets. Evaluation of the currently implemented (such as mono-disperse and bi-disperse spherical and irregular shape particle constituent model applications) and continuously evolving full-range particle physics models in the GGFS tool is performed by the NASA team to advance application readiness of the simulations. Application testing for complex PSI erosions and cratering scenarios such as the Apollo LM is performed for axi-symmetric and full 3D simulations to aid the tool developers in achieving practical application readiness for NASA projects. Important validation and application testing will further be performed against experimental data generated under the GCD PSI project experimental component.

Peter A Liever↗

DOE OSTI2025

A new database website for nuclear level densities

We introduce a new open-access, web-based database (http://nld.ascsn.net), Current Archive of Nuclear Density of Levels (CANDL), that hosts experimental nuclear level density (NLD) datasets from a variety of techniques and energy ranges. Built using the Dash framework in Python, the database is designed to be interactive and user-friendly, allowing researchers to search, visualize, fit, and export NLD data with minimal effort. This resource includes data extracted from evaporation spectra, Oslo method variants, and other experimental techniques that cover excitation energies beyond the neutron resonance region. The database supports on-the-fly fitting with two widely-used phenomenological models—the Constant Temperature (CT) model and the Back-Shifted Fermi Gas (BSFG) model—selected for their simplicity and computational efficiency. Future versions aim to include additional datasets and model types, as well as easy-to-use interfaces to data science techniques. Here, this platform offers a vital tool for the nuclear physics, astrophysics, medicine, and reactor design communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Adjusting the Energy Profile for CH–O Interactions Leads to Improved Stability of RNA Stem-Loop Structures in MD Simulations

The role of ribonucleic acid (RNA) in biology continues to grow, but insight into important aspects of RNA behavior is lacking, such as dynamic structural ensembles in different environments, how flexibility is coupled to function, and how function might be modulated by small molecule binding. In the case of proteins, much progress in these areas has been made by complementing experiments with atomistic simulations, but RNA simulation methods and force fields are less mature. It remains challenging to generate stable RNA simulations, even for small systems where well-defined, thermostable structures have been established by experiments. Further many different aspects of RNA energetics have been adjusted in force fields, seeking improvements that are transferable across a variety of RNA structural motifs. In this work, the role of weak CH···O interactions is explored, which are ubiquitous in RNA structure but have received less attention in RNA force field development. By comparing data extracted from high-resolution RNA crystal structures to energy profiles from quantum mechanics and force field calculations, it is shown that CH···O interactions are overly repulsive in the widely used Amber RNA force fields. A simple, targeted adjustment of CH···O repulsion that leaves the remainder of the force field unchanged was developed. Then, the standard and modified force fields were tested using molecular dynamics (MD) simulations with explicit water and salt, amassing over 300 μs of data for multiple RNA systems containing important features such as the presence of loops, base stacking interactions as well as canonical and noncanonical base pairing. In this work and others, standard force fields lead to reproducible unfolding of the NMR-based structures. Including a targeted CH···O adjustment in an otherwise identical protocol dramatically improves the outcome, leading to stable simulations for all RNA systems tested.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2009

An Analysis of Rocket Propulsion Testing Costs

The primary mission at NASA Stennis Space Center (SSC) is rocket propulsion testing. Such testing is generally performed within two arenas: (1) Production testing for certification and acceptance, and (2) Developmental testing for prototype or experimental purposes. The customer base consists of NASA programs, DOD programs, and commercial programs. Resources in place to perform on-site testing include both civil servants and contractor personnel, hardware and software including data acquisition and control, and 6 test stands with a total of 14 test positions/cells. For several business reasons there is the need to augment understanding of the test costs for all the various types of test campaigns. Historical propulsion test data was evaluated and analyzed in many different ways with the intent to find any correlation or statistics that could help produce more reliable and accurate cost estimates and projections. The analytical efforts included timeline trends, statistical curve fitting, average cost per test, cost per test second, test cost timeline, and test cost envelopes. Further, the analytical effort includes examining the test cost from the perspective of thrust level and test article characteristics. Some of the analytical approaches did not produce evidence strong enough for further analysis. Some other analytical approaches yield promising results and are candidates for further development and focused study. Information was organized for into its elements: a Project Profile, Test Cost Timeline, and Cost Envelope. The Project Profile is a snap shot of the project life cycle on a timeline fashion, which includes various statistical analyses. The Test Cost Timeline shows the cumulative average test cost, for each project, at each month where there was test activity. The Test Cost Envelope shows a range of cost for a given number of test(s). The supporting information upon which this study was performed came from diverse sources and thus it was necessary to build several intermediate databases in order to understand, validate, and manipulate data. These intermediate databases (validated historical account of schedule, test activity, and cost) by themselves are of great value and utility. For example, for the Project Profile, we were able to merged schedule, cost, and test activity. This kind of historical account conveys important information about sequence of events, lead time, and opportunities for improvement in future propulsion test projects. The Product Requirement Document (PRD) file is a collection of data extracted from each project PRD (technical characteristics, test requirements, and projection of cost, schedule, and test activity). This information could help expedite the development of future PRD (or equivalent document) on similar projects, and could also, when compared to the actual results, help improve projections around cost and schedule. Also, this file can be sorted by the parameter of interest to perform a visual review of potential common themes or trends. The process of searching, collecting, and validating propulsion test data encountered a lot of difficulties which then led to a set of recommendations for improvement in order to facilitate future data gathering and analysis.

Ramirez-Pagan, Carmen P.↗

NASA NTRS2018

Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) Version 4.0: User Manual

The IHEAT v4.0 software is a data reduction code for global thermography data acquired in the NASA Langley Aerothermodynamics Laboratory (LAL) hypersonic wind tunnels. IHEAT uses red and green color-intensity data from two-dimensional images of wind tunnel models to compute temperatures and heat-transfer rates using a semi-infinite, one-dimensional heat transfer approximation at each image pixel. Multiple automated tools in IHEAT v4.0 decrease the time required to reduce the data from a phosphor thermography wind tunnel run. Data at one or all of the image pixel locations can be exported to computer files for further analysis. The prior version of IHEAT, v3.2, was written in PV-WAVE® (now owned by Rogue Wave® Software) in 1994 and was limited in functionality to fit within the memory constraints of the available computers at the time. IHEAT v4.0 is written in MATLAB® by MathWorks® and contains several new features that leverage the increase in available memory of the current computers. A Piecewise tool permits the user to extract data along a segmented line cut that can follow interesting features in the image better than the single, straight line cuts that were possible with the legacy Length and Profile tools. The new Load Run and Batch tools facilitate batch processing by loading in all of the input files and images for a run at the same time. Load Run permits the user to process the available run images manually, while Batch automatically saves heat transfer data from all of the images based on the analysis previously performed on a single frame. IHEAT v4.0 also can automatically calculate the temporal collapse of reference line cuts from the time history heating data for a run to indicate the appropriate frame to reduce for each run. The IHEAT v4.0 source code was compiled into a standalone executable file that can be accessed remotely from several computers with different operating systems, simultaneously. The software is run through the MATLAB® Compiler Runtime engine, and therefore, IHEAT does not require a software license to run. Any software commands executed in the IHEAT v4.0 code will not affect other similar applications running on the same machine. Similarly, changes to the parent software do not affect a compiled code. These features of IHEAT v4.0 are improvements over the legacy v3.2 code, which required regular maintenance to avoid losing functionality as the PVWAVE ® programming language was upgraded.

Mason, Michelle L.↗

DOE OSTI2025

Expediting field-effect transistor chemical sensor design with neuromorphic spiking graph neural networks

Improving the sensitive and selective detection of analytes in a variety of applications requires accelerating the rational design of field-effect transistor (FET) chemical sensors. Achieving high-performance detection relies on identifying optimal probe materials that can effectively interact with target analytes, a process traditionally driven by chemical intuition and time-consuming trial-and-error methods. To address the difficulties in probe screening for FET sensor development, this work presents a methodology that combines neuromorphic machine learning (ML) architectures, specifically a hybrid spiking graph neural network (SGNN), with an enriched dataset of physicochemical properties through semi-automated data extraction using large language models. Achieving a classification accuracy of 0.89 in predicting sensor sensitivity categories, the SGNN model outperformed traditional ML techniques by leveraging its ability to capture both global physicochemical properties and sparse topological features through a hybrid modeling framework. Next-generation sensor design was informed by the actionable insights into the connections between material properties and sensing performance offered by the SGNN framework. Through virtual screening for the detection of per- and polyfluoroalkyl substances (PFAS) as a use case, the effectiveness of the SGNN model was further validated. Density functional theory simulations confirmed graphene as a promising active material for PFAS detection as suggested by the SGNN framework. By bridging gaps in predictive modeling and data availability, this integrated approach provides a strong foundation for accelerating advancements in FET sensor design and innovation.

Ferreira, Rodrigo Pires [Univ. of Chicago, IL (Uni↗

NASA NTRS1997

Colloids and Nucleation

The objectives of the work funded under this grant were to develop a microphotographic technique and use it to monitor the nucleation and growth of crystals of hard colloidal spheres. Special attention is given to the possible need for microgravity studies in future experiments. A number of persons have been involved in this work. A masters student, Keith Davis, began the project and developed a sheet illumination apparatus and an image processing system for detection and analysis. His work on a segmentation program for image processing was sufficient for his master's research and has been published. A post doctoral student Bernie Olivier and a graduate student Yueming He, who originally suggested the sheet illumination, were funded by another source but along with Keith made photographic series of several samples (that had been made by Keith Davis). Data extraction has been done by Keith, Bernie, Yueming and two undergraduates employed on the grant. Results are published in Langmuir. These results describe the sheet lighting technique as one which illuminates not only the Bragg scattering crystal, but all the crystals. Thus, accurate crystal counts can be made for nucleation rate measurements. The strange crystal length scale reduction, observed in small angle light scattering (SALS) studies, following the initial nucleation and growth period, has been observed directly. The Bragg scattering (and dark) crystal size decreases in the crossover region. This could be an effect due to gravitational forces or due to over- compression of the crystal during growth. Direct observations indicate a complex morphology for the resulting hard sphere crystals. The crystal edges are fairly sharp but the crystals have a large degree of internal structure. This structure is a result of (unstable) growth and not aggregation. As yet unpublished work compares growth exponents data with data obtained by SALS. The nucleation rate density is determined over a broad volume fraction range (0.505 to 0.575) and compared to classical nucleation rate calculations. The experimental nucleation rate density varies with volume fraction more slowly than expected theoretically. Gravity may influence nucleation because crystal nuclei are more dense than the surrounding fluid and may be gravitationally convected. The largest observed crystal size was near volume fraction 0.52. Near the freezing point, crystals should grow to large size because nuclei are sparse and there is plenty of room to grow without contacting other crystals. Near melting the opposite is true, with crystals growing into one another shortly after nucleation. The maximum crystal size seen near 0.52 volume fraction suggests that gravitational stresses are limiting crystal growth near freezing.

Ackerson, Bruce↗