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NASA NTRS2010

Progress in Measurement of Carbon Dioxide Using a Broadband LIDAR

Innovative active system using advanced source technology development will enable precise daytime or nighttime measurements of column CO2. Directly responds to NRC DS ASCENDS mission. Number of lasers is reduced compared to competing technologies which reduces the complexity of sensor and thus the cost and risk of failure. Knowledge gained from previously developed passive sensor decreases the risk and cost of the present lidar system development. The instrument can play a significant role as an intercomparison instrument for OCO (Orbiting Carbon Observatory) if it is rebuilt and launched as well as other laser based instruments under development for participation in ASCENDS. It can play a role as an airborne instrument in its own right in addressing the problems of scale arising from differences between point observations by the existing ground based CO2 network and wider area measurements obtained by satellites. Developed 2.0 micron broadband system as well and will compare performance of both systems to choose optimal approach for ASCENDS. Have begun development of approach that uses array detectors instead of APD. This approach will have lower noise than APD and may simplify design of the detector optical train.

Heaps, William S.↗

NASA NTRS2014

Feedback-Driven Dynamic Invariant Discovery

Program invariants can help software developers identify program properties that must be preserved as the software evolves, however, formulating correct invariants can be challenging. In this work, we introduce iDiscovery, a technique which leverages symbolic execution to improve the quality of dynamically discovered invariants computed by Daikon. Candidate invariants generated by Daikon are synthesized into assertions and instrumented onto the program. The instrumented code is executed symbolically to generate new test cases that are fed back to Daikon to help further re ne the set of candidate invariants. This feedback loop is executed until a x-point is reached. To mitigate the cost of symbolic execution, we present optimizations to prune the symbolic state space and to reduce the complexity of the generated path conditions. We also leverage recent advances in constraint solution reuse techniques to avoid computing results for the same constraints across iterations. Experimental results show that iDiscovery converges to a set of higher quality invariants compared to the initial set of candidate invariants in a small number of iterations.

Daikon↗

NASA NTRS2019

Empirical Absolute Calibration Model for Multiple Pseudo-Invariant Calibration Sites

This work extends an empirical absolute calibration model initially developed for the Libya 4 Pseudo-Invariant Calibration Site (PICS) to five additional Saharan Desert PICS (Egypt 1, Libya 1, Niger 1, Niger 2, and Sudan 1), and demonstrates the efficacy of the resulting models at predicting sensor top-of-atmosphere (TOA) reflectance. It attempts to generate absolute calibration models for these PICS that have an accuracy and precision comparable to or better than the current Libya 4 model, with the intent of providing additional opportunities for sensor calibration. In addition, this work attempts to validate the general applicability of the model to other sites. The method uses Terra Moderate Resolution Imaging Spectroradiometer (MODIS) as the reference radiometer and Earth Observing-1 (EO-1) Hyperion image data to provide a representative hyperspectral reflectance profile of the PICS. Data from a region of interest (ROI) in an “optimal region” of 3% temporal, spatial, and spectral stability within the PICS are used for developing the model. The developed models were used to simulate observations of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+), Landsat 8 (L8) Operational Land Imager (OLI), Sentinel 2A (S2A) MultiSpectral Instrument (MSI) and Sentinel 2B (S2B) MultiSpectral Instrument (MSI) from their respective launch date through 2018. The models developed for the Egypt 1, Libya 1 and Sudan 1 PICS have an estimated accuracy of approximately 3% and precision of approximately 2% for the sensors used in the study, comparable to the current Libya 4 model. The models developed for the Niger 1 and Niger 2 sites are significantly less accurate with similar precision.

Raut, Bipin↗

NASA NTRS2020

Encealdus Orbilander: A Flagship Mission Concept for Astrobiology

"Whether life exists beyond Earth remains a fundamental question driving our exploration of the Solar System. At Saturn’s moon Enceladus, plumes of oceanic material vented into space allow the investigation of the astrobiological potential of an ocean world, hinted at by Cassini, without the necessity of drilling through kilometers of ice crust. The Enceladus Orbilander is a flagship ($2.56B in fiscal year 2025 dollars) mission concept created for the 2023–2033 Planetary Science Decadal Survey. Orbilander takes full advantage of the opportunity provided by Enceladus’ plumes to search for signs of life. A single spacecraft both orbits and lands, capturing samples from four distinct reservoirs offered by the plumes. These samples, both particulate and vapor, are then analyzed by the Life Detection Suite (LDS), a set of five instruments conducting complementary and orthogonal biosignature-seeking measurements. To provide the context that specifically enhances interpretation of LDS measurements, geochemical and geophysical investigations are conducted both in orbit and on the surface. These reveal the physio-chemical state of the ocean and core as well as the processes involved in ejection of plume material and how these affect the ocean material analyzed by the LDS. The Orbilander can be delivered to the Saturn system via several launch vehicle and trajectory options, including a direct trajectory (7-year cruise), a ∆V-EGA trajectory (9-year cruise) and several options using an inner cruise with Venus and Earth flybys (10-year cruise). Upon Saturn Orbit Insertion, a 4-year moon tour pumps down the Orbilander’s orbit to intercept Enceladus. The most optimal arrival times balance the Jupiter flyby opportunities of the late 2030s and solar illumination at the Enceladus high southern latitudes where plume material is most abundant. This mission concept therefore targets project start in 2030. Upon Enceladus Orbit Insertion, the Orbilander begins a 1.5-year-long campaign of landing site reconnaissance, remote sensing science, and collecting sufficient plume sample to run all but one of the LDS measurements. After successful landing, the Orbilander spends 2 years on the surface conducting multiple LDS measurements with all five instruments on actively and passively collected plume material, as well as seismic investigations. The schedule laid out here is well-defined, but the mission also has operational and resource flexibility should additional reconnaissance be needed. As part of the design study, mission and development risks were identified and mitigation strategies proposed. Technologies key to achieving the life detection science objectives include instrumentation matured under programs like COLDTech and ICEE-2, such as aspects of the sampling system and microfluidic devices, as well as well-known techniques like high-resolution and separation-capable mass spectrometers. Autonomous onboard navigation is planned to maintain a halo orbit around Enceladus to enable passive sampling from orbit as well as reconnaissance measurements for use in site selection and landing. Terrain relative navigation is included to ensure safe landing, given that targeted areas may contain landing hazards. Continued development of radioisotope thermoelectric generator (RTG) technology and long-life batteries is essential for this long duration mission. The Enceladus Orbilander represents an optimal point in the trade space of science value versus cost, taking advantage of the extensive knowledge of Enceladus provided by Cassini, how well Enceladus lends itself to a search for life in material from its ocean, and the flexibility afforded by the innovative design developed by the APL team. By taking full advantage of Enceladus’ plumes both in orbit and on the surface, Orbilander represents a robust search for life with complementary and orthogonal biosignatures as well as contextual geophysical and geochemical measurements, determining not only whether Enceladus is inhabited (at levels up to 500,000× scarcer than in Earth’s oceans) but also why. "

Exobiology↗

NASA NTRS2023

UAM Instrument Flight Procedure Design and Evaluation in the Joby Flight Simulator

NASA’s Advanced Air Mobility (AAM) National Campaign (NC) partnered with Joby Aviation to test and evaluate different developmental candidate Urban Air Mobility (UAM) Instrument Flight Procedure (IFP) designs including new departure, enroute, approach and missed approach architectures using Joby’s high-fidelity engineering aircraft simulator. In conjunction with the simulator testing, this effort also evaluated related aspects such as charting, coding, and adherence to flight planning criteria. The test objectives were to assess the safety, efficiency, passenger comfort and noise of the different variations of the developmental IFPs. Safety-related measures include clearance from terrain and vertical obstructions, procedure flyability, and flight path conformance. Efficiency-related measures included time required, airspace volume required, and battery energy required. Passenger comfort and ride quality measures include roll/pitch angles, roll/pitch attitude change rates, and airspeeds prior to aggressive maneuvers, subjective pilot/passenger responses and acceleration forces. The noise impacts of the different IFPs will be interpolated/extrapolated using data from the simulator fed into a separate Joby acoustic software-based tool. Overall, several tradeoffs were identified and characterized between the different variations of the developmental IFP profiles. No single version of the developmental IFP structure scored highest across all measures listed above; rather, different IFP variations proved optimal for different measures, confirming that the best IFP depends on which specific measures are prioritized for a given aircraft, location and operation.

National Campaign↗

NASA NTRS2015

A Framework for Orbital Performance Evaluation in Distributed Space Missions for Earth Observation

Distributed Space Missions (DSMs) are gaining momentum in their application to earth science missions owing to their unique ability to increase observation sampling in spatial, spectral and temporal dimensions simultaneously. DSM architectures have a large number of design variables and since they are expected to increase mission flexibility, scalability, evolvability and robustness, their design is a complex problem with many variables and objectives affecting performance. There are very few open-access tools available to explore the tradespace of variables which allow performance assessment and are easy to plug into science goals, and therefore select the most optimal design. This paper presents a software tool developed on the MATLAB engine interfacing with STK, for DSM orbit design and selection. It is capable of generating thousands of homogeneous constellation or formation flight architectures based on pre-defined design variable ranges and sizing those architectures in terms of predefined performance metrics. The metrics can be input into observing system simulation experiments, as available from the science teams, allowing dynamic coupling of science and engineering designs. Design variables include but are not restricted to constellation type, formation flight type, FOV of instrument, altitude and inclination of chief orbits, differential orbital elements, leader satellites, latitudes or regions of interest, planes and satellite numbers. Intermediate performance metrics include angular coverage, number of accesses, revisit coverage, access deterioration over time at every point of the Earth's grid. The orbit design process can be streamlined and variables more bounded along the way, owing to the availability of low fidelity and low complexity models such as corrected HCW equations up to high precision STK models with J2 and drag. The tool can thus help any scientist or program manager select pre-Phase A, Pareto optimal DSM designs for a variety of science goals without having to delve into the details of the engineering design process.

Earth Science↗

DOE OSTI2024

The Electron Spectro-Microscopy (ESM) Beamline at NSLS-II

Photoelectron spectroscopy is a primary tool for the study of the electronic structure of materials and the chemical composition of surfaces. High-resolution angle-resolved photoemission spectroscopy (ARPES) has the unique ability to map the energy bands in momentum space. Furthermore, going beyond the single particle picture, the self-energy corrections caused by correlations in solids can be extracted from the analysis of the emission line shape. The current level of refinement, in terms of energy and angular resolution (ΔE < 1 meV, Δθ < 0.1°), makes the technique sensitive to the lowest energy excitations and the dynamics of electrons, which in turn virtually determine all the macroscopic properties of any system and govern the chemical, electrical, magnetic, and physical processes. Similarly important, X-ray photoelectron microscopy (XPEEM), combined with the low-energy electron microscopy (LEEM), is indispensable in probing the complexity of chemical, structural, electronic and magnetic properties of surfaces and shallow interfaces, with the spatial resolution of few tens of nanometer (nm). The Electron-Spectro-Microscopy beamline (ESM) has been recently commissioned at NSLS-II and is now in operation. The primary spectroscopic technique is photoemission, performed over a wide energy range with control of light polarization and in a variety of flux/resolution conditions. The beamline has two experimental end stations that allow to perform ARPES and XPEEM/LEEM, separately. The ARPES end station focuses on high energy-resolution work, with spot-size of a few microns. The XPEEM/LEEM end station is a full-field microscope (XPEEM) operating either with the synchrotron generated X-rays (XPEEM), or with an internal electron gun (LEEM). Spatial resolution is crucial in studies of newly synthesized complex materials since they are often initially available only as small specimens (typically micron size). Furthermore, chemical inhomogeneities on surfaces are often an integral part of surface chemical processes. Finally, the ESM beamline with X-ray spots of few microns is optimized to study the electronic structure of novel materials with microscopy capabilities.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Verification and validation of developed short-term forecasting models

Recent advancements in machine learning (ML) and artificial intelligence (AI) technologies provide an opportunity for leveraging data-driven algorithms to predict future nuclear power plant (NPP) operating conditions by using recorded plant process data. Successfully implementing these models can lead to cost-reducing, conditioned-based predictive maintenance through optimized maintenance schedules and a reduction of unnecessary maintenance activities. This report discusses the verification and validation of short-term forecasting processes (i.e., data cleaning, feature selection, model optimization, and forecasting) developed in previous reports. The verification and validation (V&V) process demonstrates the expected precision and accuracy when the ML model encounters new datasets from different systems. Shapley additive explanations were used as the primary means of feature selection across these different data set. Individual models were trained for each data set, then validated through a cross-validation procedure. In this report, two different ML models were tasked to predict variables from three different plant process data sets with varying prediction horizons. The results indicate that support vector regression (SVR) outperformed long short-term memory (LSTM) neural networks in regard to each data set and each prediction horizon in this study, but further tuning and optimization could improve long short-term memory results. However, each forecasting model showed reduced performance as the prediction horizon was extended from 1 hour to 1 day ahead. Research is ongoing to evaluate the optimal input variable space, which is based on a given set of process parameters, to further improve forecasting accuracy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Delivery of LiH Shell for DANCE

Material for a new LiH shell for neutron shielding has been obtained for the Detector for Advanced Neutron Capture Experiments. This is a critical component for optimizing sensitivity of neutron capture experiments performed in support of Office of Experimental Sciences mission, particularly in the case of small, rare samples.

42 ENGINEERING↗

NASA NTRS1985

Advanced Moisture and Temperature Sounder (AMTS) baseline 5 study report

An Advanced Moisture and Temperature Sounder (AMTS) passive infrared atmospheric sounding system is described. Instrument requirements are developed. Parametric and scaling equations for a grating spectrometer instrument approach are developed which define detector noise limited performance in terms of instrument, orbit, and spatial coverage parameters. Instrument design criteria are developed and a baseline instrument design is presented. Error sources are identified and corresponding system error component values are estimated. Within narrow limits, the highest level of performance achievable with a stand alone infrared sounder using current state of the art technology is established. Additional trade offs necessary to establish a reasonably optimal system design in terms of performance, cost, and risk are identified.

Evans, N. L., Jr.↗

NASA NTRS1993

The Feasibility of Tropospheric and Total Ozone Determination Using a Fabry-perot Interferometer as a Satellite-based Nadir-viewing Atmospheric Sensor

Monitoring of the global distribution of tropospheric ozone (O3) is desirable for enhanced scientific understanding as well as to potentially lessen the ill-health impacts associated with exposure to elevated concentrations in the lower atmosphere. Such a capability can be achieved using a satellite-based device making high spectral resolution measurements with high signal-to-noise ratios; this would enable observation in the pressure-broadened wings of strong O3 lines while minimizing the impact of undesirable signal contributions associated with, for example, the terrestrial surface, interfering species, and clouds. The Fabry-Perot Interferometer (FPI) provides high spectral resolution and high throughput capabilities that are essential for this measurement task. Through proper selection of channel spectral regions, the FPI optimized for tropospheric O3 measurements can simultaneously observe a stratospheric component and thus the total O3 column abundance. Decreasing stratospheric O3 concentrations may lead to an increase in biologically harmful solar ultraviolet radiation reaching the earth's surface, which is detrimental to health. In this research, a conceptual instrument design to achieve the desired measurement has been formulated. This involves a double-etalon fixed-gap series configuration FPI along with an ultra-narrow bandpass filter to achieve single-order operation with an overall spectral resolution of approximately .068 cm(exp -1). A spectral region of about 1 cm(exp -1) wide centered at 1054.73 cm(exp -1) within the strong 9.6 micron ozone infrared band is sampled with 24 spectral channels. Other design characteristics include operation from a nadir-viewing satellite configuration utilizing a 9 inch (diameter) telescope and achieving horizontal spatial resolution with a 50 km nadir footprint. A retrieval technique has been implemented and is demonstrated for a tropical atmosphere possessing enhanced tropospheric ozone amounts. An error analysis assessing the impact on retrieved O3 amounts of the most significant uncertainties associated with this particular measurement has been performed for several different types of atmospheres. Results show the proposed instrumentation to enable a good measurement of absolute ozone amounts and an even better determination of relative changes, with a range of accuracy to within 7.55 to 20.6 percent for integrated tropospheric amounts (and 1.99 to 4.02 percent for total O3 column abundance) and a corresponding range in precision to within 7.73 to 10.4 percent (and 3.30 to 3.95 percent for total O3 column abundance), for the atmospheric conditions considered.

Larar, Allen Maurice↗

NASA NTRS2006

Variable-Tension-Cord Suspension/Vibration-Isolation System

A system for mechanical suspension and vibration isolation of a machine or instrument is based on the use of Kevlar (or equivalent aromatic polyamide) cord held in variable tension between the machine or instrument and a surrounding frame. The basic concept of such a tensioned-cord suspension system (including one in which the cords are made of aromatic polyamide fibers) is not new by itself; what is new here is the additional provision for adjusting the tension during operation to optimize vibration- isolation properties. In the original application for which this system was conceived, the objective is to suspend a reciprocating cryocooler aboard a space shuttle and to prevent both (1) transmission of launch vibrations to the cryocooler and (2) transmission of vibrations from the cryocooler to samples in a chamber cooled by the cryocooler. The basic mechanical principle of this system can also be expected to be applicable to a variety of other systems in which there are requirements for cord suspension and vibration isolation. The reciprocating cryocooler of the original application is a generally axisymmetric object, and the surrounding frame is a generally axisymmetric object with windows (see figure). Two cords are threaded into a spoke-like pattern between attachment rings on the cryocooler, holes in the cage, and cord-tension- adjusting assemblies. Initially, the cord tensions are adjusted to at least the level necessary to suspend the cryocooler against gravitation. Accelerometers for measuring vibrations are mounted (1) on the cold tip of the cryocooler and (2) adjacent to the cage, on a structure that supports the cage. During operation, a technician observes the accelerometer outputs on an oscilloscope while manually adjusting the cord tensions in an effort to minimize the amount of vibration transmitted to and/or from the cryocooler. A contemplated future version of the system would include a microprocessor-based control subsystem that would include cord-tension actuators. This control subsystem would continually adjust the cord tension in response to accelerometer feedback to optimize vibration-isolation properties as required for various operating conditions. The control system could also adjust cord tensions (including setting the two cords to different tensions) to suppress resonances. Other future enhancements could include optimizing the cord material, thickness, and braid; optimizing the spoke patterns; and adding longitudinal cords for applications in which longitudinal stiffness and vibration suppression are required.

Villemarette, Mark L.↗

NASA NTRS2005

Satellite-Derived Management Zones

The term "satellite-derived management zones" (SAMZ) denotes agricultural management zones that are subdivisions of large fields and that are derived from images of the fields acquired by instruments aboard Earth-orbiting satellites during approximately the past 15 years. "SAMZ" also denotes the methodology and the software that implements the methodology for creating such zones. The SAMZ approach is one of several products of continuing efforts to realize a concept of precision agriculture, which involves optimal variations in seeding, in application of chemicals, and in irrigation, plus decisions to farm or not to farm certain portions of fields, all in an effort to maximize profitability in view of spatial and temporal variations in the growth and health of crops, and in the chemical and physical conditions of soils. As used here, "management zone" signifies, more precisely, a subdivision of a field within which the crop-production behavior is regarded as homogeneous. From the perspective of precision agriculture, management zones are the smallest subdivisions between which the seeding, application of chemicals, and other management parameters are to be varied. In the SAMZ approach, the main sources of data are the archives of satellite imagery that have been collected over the years for diverse purposes. One of the main advantages afforded by the SAMZ approach is that the data in these archives can be reused for purposes of precision agriculture at low cost. De facto, these archives contain information on all sources of variability within a field, including weather, crop types, crop management, soil types, and water drainage patterns. The SAMZ methodology involves the establishment of a Web-based interface based on an algorithm that generates management zones automatically and quickly from archival satellite image data in response to requests from farmers. A farmer can make a request by either uploading data describing a field boundary to the Web site or else drawing the boundary on a reference image. Hence, a farmer can start to engage in precision farming shortly after gaining access to the Web site, without the need for incurring the high costs of conventional precision-agriculture data-collection practices that include collecting soil samples, mapping electrical conductivity of soil, and compiling multiyear crop-yield data. Given the boundary of a field, a SAMZ server computes the zones within the field in a three-stage process. In the first stage, a vector-valued image of the field is constructed by assembling, from the archives, the equivalent of a stack of the available images of the field (see figure). In the second stage, the vector-valued image is analyzed by use of a wavelet transform that detects spatial variations considered significant for precision farming while suppressing small-scale heterogeneities that are regarded as insignificant. In the third stage, a segmentation algorithm assembles the zones from smaller regions that have been identified in the wavelet analysis.

Lepoutre, Damien↗

NASA NTRS2011

Integrated Lens Antennas for Multi-Pixel Receivers

Future astrophysics and planetary experiments are expected to require large focal plane arrays with thousands of detectors. Feedhorns have excellent performance, but their mass, size, fabrication challenges, and expense become prohibitive for very large focal plane arrays. Most planar antenna designs produce broad beam patterns, and therefore require additional elements for efficient coupling to the telescope optics, such as substrate lenses or micromachined horns. An antenna array with integrated silicon microlenses that can be fabricated photolithographically effectively addresses these issues. This approach eliminates manual assembly of arrays of lenses and reduces assembly errors and tolerances. Moreover, an antenna array without metallic horns will reduce mass of any planetary instrument significantly. The design has a monolithic array of lens-coupled, leaky-wave antennas operating in the millimeter- and submillimeter-wave frequencies. Electromagnetic simulations show that the electromagnetic fields in such lens-coupled antennas are mostly confined in approximately 12 15 . This means that one needs to design a small-angle sector lens that is much easier to fabricate using standard lithographic techniques, instead of a full hyper-hemispherical lens. Moreover, this small-angle sector lens can be easily integrated with the antennas in an array for multi-pixel imager and receiver implementation. The leaky antenna is designed using double-slot irises and fed with TE10 waveguide mode. The lens implementation starts with a silicon substrate. Photoresist with appropriate thickness (optimized for the lens size) is spun on the substrate and then reflowed to get the desired lens structure. An antenna array integrated with individual lenses for higher directivity and excellent beam profile will go a long way in realizing multi-pixel arrays and imagers. This technology will enable a new generation of compact, low-mass, and highly efficient antenna arrays for use in multi-pixel receivers and imagers for future planetary and astronomical instruments. These antenna arrays can also be used in radars and imagers for contraband detection at stand-off distances. This will be enabling technology for future balloon-borne, smaller explorer class mission (SMEX), and other missions, and for a wide range of proposed planetary sounders and radars for planetary bodies.

Lee, Choonsup↗

NASA NTRS1984

Research pressure instrumentation for NASA Space Shuttle main engine, modification no. 5

The advantages of silicon piezoresistive strain sensing technology are being used to achieve the objectives of state of the art pressure sensors for SSME applications. The integration of multiple functions on a single chip is the key attribute being exploited. Progress is reported in transducer packaging and materials; silicon resistor characterization at cryogenic temperatures; chip mounting; and frequency response optimization.

Anderson, P. J.↗

DOE OSTI2022

Digitalization of an experimental electrochemical reactor via the smart manufacturing innovation platform

The exponential increase in data produced over the last two decades has revolutionized the way we collect, store, process, analyze, model, and interpret information to improve profitability. Manufacturing is no exception. How- ever, Smart Manufacturing, the digital practice, organization, workforce, and infrastructure transformation for collection and deployment of data and models at scale and at all levels of manufacturing, is a complex, costly, and labor-intensive journey that is still seeing slow adoption. The Clean Energy Smart Manufacturing Innovation Institute (CESMII), a national Manufacturing USA public-private partnership sponsored by the Department of Energy, is addressing this scaled use of data and modeling in manufacturing. CESMII has focused on how to col- lect and use operating data for numerous applications that improve productivity, precision, and performance of manufacturing operations from factory floor to supply chain using process simulation, predictive analytics, mon- itoring and control, and real-time optimization. Because contextualized data are key, CESMII has developed the Smart Manufacturing Innovation Platform (SMIP) to lower the barriers to the data that are needed to accelerate data-based model building, improve data visualization, and more quickly gain insights. Reusable, standards-based ways of doing data collection, ingestion, and contextualization are particularly important for scaling access and use of data. The SMIP uses a standards-based definition and construct for reusable information models called an SM Profile. When an SM Profile is used in conjunction with the SMIP, the SMIP ensures the availability of contextualized, operational data for model building. The present work demonstrates Smart Manufacturing and the application of the SMIP for building several data-centered models for the operation and control of an ex- perimental electrochemical reactor that reduces carbon dioxide (CO 2 ) gas to valuable liquid and gas chemicals, such as alcohols, olefins, and syngas. We describe how the SMIP plays a central role in more effective model building and we demonstrate how the electochemical reactor can be controlled and optimized for the desired products. Use of the SMIP involves the transmission of real-time sensor measurements to a cloud resource so that the operating data are available to all model building experts. The data collection and transmission process is fully automated to greatly reduce the need for manual manipulation of the data. Data-driven machine learning models are used for advanced real-time state estimation, real-time optimization, and model-based feedback control for the reactor. The application models are implemented as a system to monitor the data flow and control the electrochemical reactor with a single visualization interface. SM Profiles are used to demonstrate reusability of the information models for the reactor and the instrumentation. The application packages, algorithms, and user interfaces developed are cast as Docker images in a library to facilitate reusability of the application models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Deep Learning enabled spectral energy conversion for in situ exposure measurements

A detector-specific deep learning (DL) approach is presented for spectra-to-exposure conversion using large-format sodium iodide (NaI(Tl)) detectors deployed for in situ environmental radiation measurements in emergency response scenarios. Accurate determination of exposure from NaI spectra is challenging due to poor energy resolution, partial energy absorption, and the strong sensitivity of traditionally deployed analytical conversion methods to calibrated source geometry and pre-deployment assumptions. Here, to address these limitations, a multi-layer perceptron model was trained on a hybrid in situ /Monte Carlo dataset constructed to span a broad range of photon energies, spatial extents, and realistic deployment variability, representative of general in situ emergency response conditions. The DL model was evaluated against commonly fielded analytical approaches under matched simulation conditions, including a single-factor method, a G-function method, and a modeled pressurized ion chamber (PIC) baseline. This study was intentionally computational in scope to enable controlled, like-for-like comparisons between conversion techniques while minimizing confounding real-world variability. Comparison to the modeled PIC provides contextual benchmarking and is not intended as a field inter-comparison with deployed instruments. Across the evaluated 20 keV to 3 MeV energy range, the DL approach consistently exhibited higher accuracy and reduced variance relative to the analytical methods against a deterministically calculated exposure. This may indicate improved robustness to spectral complexity without reliance on source-, geometric-, or spectral region-specific optimization. While results do not represent real-world validation, the presented work demonstrates that deep learning may effectively learn the nonlinear detector response-to-exposure relationship for asymmetric NaI(Tl) detectors and offers a promising pathway for improving in situ exposure estimation using spectroscopic systems already integrated into initial real-time emergency response operations.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2025

Defect modeling in semiconductors: the role of first principles simulations and machine learning

Abstract Point defects in semiconductors dictate their electronic and optical properties. Vacancies, interstitials, substitutional defects, and defect complexes can form in the semiconductor lattice and significantly impact its performance in applications such as solar absorption, light emission, electronics, and catalysis. Understanding the nature and energetics of point defects is essential for the design and optimization of next-generation semiconductor technologies. Here, we provide a comprehensive overview of the current state of research on point defects in semiconductors, focusing on the application of density functional theory (DFT) and machine learning (ML) in accelerating the prediction and understanding of defect properties. DFT has been instrumental in accurately calculating defect formation energies, charge transition levels, and other defect-related properties such as carrier recombination rates and lifetimes, and ion migration barriers. ML techniques, particularly neural networks, have emerged as powerful tools for enabling rapid prediction of defect properties at DFT-accuracy in order to overcome the expense of using large supercells and advanced functionals. We begin this article with a discussion of different types of point defects and complexes, their impact on semiconductor properties, and the experimental and DFT approaches typically used for their characterization. Through multiple case studies, we explore how DFT has been successfully applied to understand defect behavior across a variety of semiconductors, and how ML approaches integrated with DFT can efficiently predict defect properties and facilitate the discovery of new materials with tailored defect behavior. Overall, the advent of ‘DFT+ML’ promises to drive advancements in semiconductor technology, catalysis, and renewable energy applications, paving the way for the development of high-performance semiconductors which are defect-tolerant or have desirable dopability.

Rahman, Md Habibur (ORCID:000000027705984X)↗