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DOE OSTI2026

Securing The Future: 2026 Manufacturing & Critical Infrastructure Threat Landscape

This report outlines the current state of manufacturing weaknesses introduced by the complexities of modern environments, including cloud services and Internet of Things (IoT) devices, with particular attention paid to the unique vulnerabilities encountered by SMMs. It also highlights CyManII’s strategic initiatives and collaborative solutions to mitigate these risks and strengthen the cybersecurity posture of the manufacturing ecosystem. Utilizing data from 2025 to inform forward-looking mitigation strategies, this report provides manufacturers with a clear understanding of both current and emerging cybersecurity threats, as well as practical opportunities to strengthen their cyber ecosystems. The following sections detail key vulnerabilities and threat vectors, along with actionable mitigation strategies, many of which have been developed or piloted through CyManII-led efforts. A thorough understanding of these risks and mitigation strategies is essential for manufacturers seeking to strengthen the security and resilience of their manufacturing operations.

3D Printing↗
NASA NTRSDate not supplied

Evaluation of Markerless Motion Capture for Monitoring Sensorimotor Performance

BACKGROUND Astronauts returning from long-duration exposure to microgravity frequently exhibit alterations in sensorimotor function leading to postural imbalance, impaired locomotion, and operational challenges to manual control. Mission duration and individual responses often influence both the severity of performance decrements and the variability in adaptation timelines. Postflight disruptions during functional tasks are often detected through body-worn inertial measurement unit (IMU) devices. While IMU sensors are relatively compact, the long-term wear may lead to discomfort, displacement of the sensors on the body, and restrictions in movement or crew behavior. Although IMU data offers valuable insights from a research standpoint, interpreting changes in pre- and post-flight measures can be difficult for crew support personnel beyond the research domain, which can hinder the application for medical assessments and rehabilitation. Finally, the availability of inertial sensors in-flight is limited. There is a need for unobtrusive monitoring tools to improve our ability to monitor adaptation following gravitational transitions in various postflight evaluations and rehabilitation settings. Markerless motion capture (MMC) is an evolving unobtrusive technology that builds upon decades of research with marker-based motion capture systems to provide 3D human pose estimation from multiple synchronized 2D camera views using deep learning algorithms. Markerless technology can revolutionize how data is captured pre- and post-flight and potentially in-flight during intravehicular activity by enabling pose estimation of multiple crew members from onboard camera hardware. METHODS The following presents the initial evaluation of a state-of-the-art commercial-off-the-shelf MMC system, Theia Markerless, compared to IMU devices during various ground-based functional tasks and environmental conditions. The featured functional tasks include assessments from Human Research Program (HRP) funded studies such as Sensorimotor Standard Measures and Sensorimotor Assessments. Synchronous data collected using both motion capture and IMUs are analyzed for six male and female subjects of varying anthropometry. The analysis includes limited assessments of clothing, capture volume configurations, and the tool's sensitivity to detecting performance changes after a spaceflight analog centrifuge exposure. The development of visualization tools to enhance the application of the pose estimation output is also presented. RESULTS Initial results demonstrate comparable root mean square error (RMSE) to existing literature evaluating markerless and marker-based motion capture systems. Considering the relative functional range of motion of the cervical spine, normalized error values for the markerless system’s accuracy of the head was 0.032 in pitch, 0.025 in roll, and 0.018 in yaw plane of motion across a subset of functional tasks. The raw RMSE values were 3.49, 2.25, and 2.81 degrees respectively. For the torso, results suggest normalized errors of 0.469 in pitch, 0.191 in roll, and 0.307 in yaw planes of motion and raw RMSE values of 3.52, 1.53, and 3.07 degrees respectively. The data suggests the functional demands of a particular task influences the estimation accuracy of the MMC system where more dynamic motion and cases where subjects are not upright may introduce diminished tracking accuracy. DISCUSSION The following work lays the foundation for future implementations leveraging markerless motion capture to assess the time course of recovery and provide insight for rehabilitation protocols to enhance crew readiness for the resumption of daily activities. These tools offer effective methods for anonymizing sensitive crew data, facilitating numerous applications across research, medical, and rehabilitation groups. Collaborations with the Anthropometry and Biomechanics Facility will provide further comparisons of the Markerless system to a marker-based system. ACKNOWLEDGEMENT</ This work is supported by NASA’s Exploration Systems Development Mission Directorate Mars Campaign Office Crew Health Countermeasures.

Hannah M. Weiss↗
DOE OSTI2019

Deep Isolation - Innovation for the Storage and Disposal of High-level Waste and Spent Nuclear Fuel - 19367

Deep Isolation, Inc. is a private, Berkeley based company that has brought innovation to nuclear waste disposal. Deep Isolation has developed a disposal technique that adapts mature drilling technology and customizes it for the purpose of providing a safe and secure solution. Though the stalled nuclear waste program in the US has created unwanted burdens and costs, it has also provided object lessons which Deep Isolation has learned from and designed a novel approach. The solution proposed by Deep Isolation combines the best of the geosciences and social sciences to present the US and other countries with an optimized and tailored approach to disposing of a variety of nuclear waste. This system can complement existing potential storage and disposal sites, or in the case of countries with smaller amounts of waste--the national solution. Deep Isolation innovates where others have stalled and offers a means of deep geological disposal that costs less, takes less time to implement, and cuts down and in some cases eliminates the need for transportation of the waste. The technical solution optimized by Deep Isolation uses established directional drilling technology from the oil and gas industry to drill a vertical drill hole thousands of meters deep and then transition to a horizontal drill hole that is thousands of meters in length. The target media is in or below shale formations, which are present at various depths throughout much of the United States and throughout the world. The availability of suitable geology allows for permanent disposal at multiple locations - including existing nuclear sites, without a need to transport the waste to a central repository. This innovative solution not only offers options for commercial used nuclear fuel and defense spent nuclear fuel and high-level waste, but also other nuclear wastes such as those considered by DoE's past deep bore-hole program, i.e. cesium and strontium capsules. Greater-Than-Class-C (GTCC) waste is also an opportunity for Deep Isolation. DoE's preferred alternative for GTCC includes 'land disposal at generic commercial facilities.' Deep Isolation could provide safe, secure, and permanent disposal at a commercial facility. Deep Isolation complements the technical innovation with best practices from the social sciences. In acknowledgement that the past challenges to implement nuclear waste disposal facilities have been primarily due to socio-political failings, we have designed a means to deeply engage with public and stakeholders. Our approach is committed to partnering with communities, local jurisdictions, states, and Tribes to determine a path forward that benefits all involved, that is fully transparent, collaborative and accountable. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2017

Hardware Assessment in Support of the Dynamic Power Convertor Development Effort

Stirling Radioisotope Power Systems (RPS) are being developed by NASA's RPS Program in collaboration with the U.S. Department of Energy (DOE). Efforts ranging from 2001 to 2015 enabled development of the Technology Demonstration Convertor (TDC) for use in the 110-watt Stirling Radioisotope Generator (SRG-110) and the Advanced Stirling Convertor (ASC) for use in the Advanced Stirling Radioisotope Generator (ASRG). The DOE selected Lockheed Martin Space Systems Company (LMSSC) as the system integration contractor for both flight development efforts. The SRG-110 housed two TDCs fabricated by Infinia and resulted in the production of 16x demonstration units and 2x engineering units. The project was redirected in 2006 to make use of a more efficient and lower mass ASCs under development by Sunpower Inc. The DOE managed the flight contract with LMSSC and subcontractor Sunpower Inc. from 2007 to 2013 to build the ASRG, with support from NASA Glenn Research Center (GRC). Sunpower Inc. held two parallel contracts to produce ASCs, one with Lockheed Martin to produce ASC-F flight units and one with GRC for the production of ASC-E3 engineering unit pathfinders that were used to refine the flight design and production processes. The DOE initiated termination of the ASRG contract in late 2013. After ASRG had ended, GRC completed characterization testing of the ASRG Engineering Unit #2 (EU2) and the GRC contract with Sunpower was also completed. The NASA RPS Program Office has recently initiated a new Dynamic Power Conversion development effort which includes the potential maturation of Stirling, Brayton, and Rankine power convertors for the next generation of RPS. The effort started with the request for proposal and review of submits. Contracts are anticipated for release in 2017 and will initially focus on a design phase prior to fabrication and testing. This new effort will focus on robustness in addition to high efficiency, specific power, and reliability. Also, some requirements introduced during the ASRG contract have also been included in the new effort, such as constant lateral loading. Due to the focus on robustness and new requirements relative to the older TDC design, the Stirling Cycle Development Project has initiated an assessment of government owned hardware to help inform requirements evolution and evaluation of future designs. While lessons learned from the ASRG flight development project have been taken into consideration, the evaluation of the TDC design had not been completed for some existing environments or relatively new requirements. To further assess the TDC design, a series of tasks were initiated to evaluate degradation for units that have operated unattended for over 105,000 hours, demonstrate robustness to a random vibration environment, characterize and evaluate performance for varying lateral load profiles. The status for each task are described.

Wilson, Scott D.↗
NASA NTRS2018

Hardware Assessment in Support of the Dynamic Power Convertor Development Effort

Stirling Radioisotope Power Systems (RPS) are being developed by NASAs RPS Program in collaboration with the U.S. Department of Energy (DOE). Efforts ranging from 2001 to 2015 enabled development of the Technology Demonstration Convertor (TDC) for use in the 110-watt Stirling Radioisotope Generator (SRG-110) and the Advanced Stirling Convertor (ASC) for use in the Advanced Stirling Radioisotope Generator (ASRG). The DOE selected Lockheed Martin Space Systems Company (LMSSC) as the system integration contractor for both flight development efforts. The SRG-110 housed two TDCs fabricated by Infinia and resulted in the production of 16x demonstration units and 2x engineering units. The project was redirected in 2006 to make use of a more efficient and lower mass ASCs under development by Sunpower Inc. The DOE managed the flight contract with LMSSC and subcontractor Sunpower Inc. from 2007 to 2013 to build the ASRG, with support from NASA Glenn Research Center (GRC). Sunpower Inc. held two parallel contracts to produce ASCs, one with Lockheed Martin to produce ASC-F flight units and one with GRC for the production of ASC-E3 engineering unit pathfinders that were used to refine the flight design and production processes. The DOE initiated termination of the ASRG contract in late 2013. After ASRG had ended, GRC completed characterization testing of the ASRG Engineering Unit 2 (EU2) and the GRC contract with Sunpower was also completed. The NASA RPS Program Office has recently initiated a new Dynamic Power Conversion development effort which includes the potential maturation of Stirling, Brayton, and Rankine power convertors for the next generation of RPS. The effort started with the request for proposal and review of submits. Contracts are anticipated for release in 2017 and will initially focus on a design phase prior to fabrication and testing. This new effort will focus on robustness in addition to high efficiency, specific power, and reliability. Also, some requirements introduced during the ASRG contract have also been included in the new effort, such as constant lateral loading. Due to the focus on robustness and new requirements relative to the older TDC design, the Stirling Cycle Development Project has initiated an assessment of government owned hardware to help inform requirements evolution and evaluation of future designs. While lessons learned from the ASRG flight development project have been taken into consideration, the evaluation of the TDC design had not been completed for some existing environments or relatively new requirements. To further assess the TDC design, a series of tasks were initiated to evaluate degradation for units that have operated unattended for over 105,000 hours, demonstrate robustness to a random vibration environment, characterize and evaluate performance for varying lateral load profiles. The status for each task are described.

Wilson, Scott D.↗
DOE OSTI2026

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Establishing a Platform for Interest and Education in Interventional Radiology Amongst Radiology Trainees

Purpose: Over recent times, procedural Radiologists have begun to establish themselves as the distinct subspecialty of Interventional Radiology (IR). The Interventional Radiology Society of Australasia (IRSA) was established in 1982 to share collaborative ideas, encourage research, and promote education. IRSA developed a weekend registrar workshop attended by Radiology Registrars from Australia and New Zealand. In the 2018 event, we surveyed the Registrars to identify their interest in IR training before and after the workshop. Materials and Methods: The event was held over a weekend and consisted of both lectures and hands-on workshops. A survey was handed to all 67 registrants of the workshop and there was a 55% response rate including 78% of females in attendance. Results: Before the workshop, trainees rated their interest in IR training at a mean of 3.7 out of 5. After the workshop, trainees rated their interest in IR training as an average of 4.4 out of 5 (p < 0.001). The difference in interest between males and females before the workshop (4.0 vs. 3.1) was significant (p = 0.003), however after the workshop (4.5 vs. 4.1) was not significant (p = 0.07). The change in interest from attending the workshop was significant between genders, p = 0.03 (male interest increased mean 0.5, female increased mean 1.0). Conclusion: We show that a program of lectures and workshops designed to generate interest in IR leads to a significant increase in training interest, particularly amongst females. Other subspecialty groups should consider this type of intervention and promote ongoing education and inspiration. Level of Evidence: Cross-sectional study, Level IV.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Search for an Excess of Events in the Super-Kamiokande Detector in the Directions of the Astrophysical Neutrinos Reported by the IceCube Collaboration

We introduce the results of a search in the Super-Kamiokande (SK) detector for excesses of neutrinos with energies above a few GeV that are in the direction of the track events reported in IceCube. Data from all SK phases (SK-I through SK-IV) were used, spanning a period from April 1996 to April 2016 and corresponding to an exposure of 225 kilotonne-years . We considered the 14 IceCube track events from a data set with 1347 livetime days taken from 2010 to 2014. We use Poisson counting to determine if there is an excess of neutrinos detected in SK in a 10 ° search cone (5 ° for the highest energy data set) around the reconstructed direction of the IceCube event. No abundant excess was found in any of the search directions we examined. We also looked for coincidences with a recently reported IceCube multiplet event. No events were detected within a ± 500 s time window around the first detected event, and no significant excess was seen from that direction over the lifetime of SK.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects

Researchers at New Mexico Tech, Los Alamos National Laboratory (LANL), Sandia National Laboratory (SNL), and other collaborators are developing a methodology to improve characterization of stress in the subsurface by means of a model-based inversion of reservoir engineering data, time lapse seismic measurements, and microseismicity. Historically, various geophysical techniques have been used in efforts to understand the state of stress in the subsurface through direct and indirect imaging of stress sensitive features (faults and fractures) and observations of transient stress related observations (time variant elastic moduli and microseismicity). Standard direct and indirect techniques for seismic fault and fracture imaging suffer from detectability limits due to reliance on high data quality and multiplicity. Variations in effective elastic properties from inversion of high quality seismic (Vertical Seismic Profile (VSP)) data may be used to infer stress near the wellbore through integration with independent experimental characterization of the stress-velocity relationship. Given a sufficiently robust observation network, microseismic emissions may be inverted to characterize focal mechanisms which, together with supporting assumptions and constraints, inform estimates of in-situ stress. While each of these techniques contributes in part to the characterization of stress within limited spatial and temporal domains, no one method provides an unambiguous stress measurement or a predictive capability over a site scale spatial extent. Challenges associated with solution non-uniqueness, measurement ambiguity, and irregular sampling may be greatly minimized through combination of one or more of independent measurements within a common framework in which realistic geological, hydrodynamic, geomechanical, and seismological constituent process models may act as constraints.

02 PETROLEUM↗
DOE OSTI2019

A Roadmap for HEP Software and Computing R&D for the 2020s

Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of software to acquire, manage, process, and analyse the shear amounts of data to be recorded. In planning for the HL-LHC in particular, it is critical that all of the collaborating stakeholders agree on the software goals and priorities, and that the efforts complement each other. In this spirit, this white paper describes the R&D activities required to prepare for this software upgrade.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Low-energy astrophysics with KamLAND

We present two results of a search for MeV-scale neutrino and anti-neutrino events correlated with gravitational wave events/candidates and large solar flares with KamLAND. The KamLAND detector is a large-volume neutrino detector using liquid scintillator, which is located at 1 km underground under the top of Mt. Ikenoyama in Kamioka, Japan. KamLAND has multiple reaction channels to detect neutrinos. Electron antineutrino can be detected via inverse-beta decay with 1.8 MeV neutrino energy threshold. All flavors of neutrinos can be detected via neutrino-electron scattering without neutrino energy threshold. KamLAND has continued the neutrino observation since 2002 March. We use the data set of 60 gravitational waves provided by the LIGO/Virgo collaboration during their second and third observing runs and search for coincident electron antineutrino events in KamLAND. We find no significant coincident signals within a ±500 s timing window from each gravitational wave and present 90% C.L. upper limits on the electron antineutrino fluence between 10 8 –10 13 cm -2 for neutrino energies of 1.8–111 MeV. For a solar-flare neutrino search at KamLAND, we determine the timing window using the solar X-ray data set provided by the GOES satellite series from 2002 to 2019 and search for the excess of coincident event rate on the all-flavor neutrinos. We find no significant event rate excess in the flare time windows and get 90% C.L. upper limits on the fluence of neutrinos of all flavors (electron anti-neutrinos) between 10 10 –10 13 cm -2 (10 8 –10 13 cm -2 ) for neutrino energies in the energy range of 0.4–35 MeV.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The Dark Energy Survey: Cosmology Results with ∼1500 New High-redshift Type Ia Supernovae Using the Full 5 yr Data Set

Abstract We present cosmological constraints from the sample of Type Ia supernovae (SNe Ia) discovered and measured during the full 5 yr of the Dark Energy Survey (DES) SN program. In contrast to most previous cosmological samples, in which SNe are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being an SN Ia, we find 1635 DES SNe in the redshift range 0.10 < z < 1.13 that pass quality selection criteria sufficient to constrain cosmological parameters. This quintuples the number of high-quality z > 0.5 SNe compared to the previous leading compilation of Pantheon+ and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints, we combine the DES SN data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning 0.025 < z < 0.10. Using SN data alone and including systematic uncertainties, we find Ω M = 0.352 ± 0.017 in flat ΛCDM. SN data alone now require acceleration ( q 0 < 0 in ΛCDM) with over 5 σ confidence. We find ( Ω M , w ) = ( 0.264 − 0.096 + 0.074 , − 0.80 − 0.16 + 0.14 ) in flat w CDM. For flat w 0 w a CDM, we find ( Ω M , w 0 , w a ) = ( 0.495 − 0.043 + 0.033 , − 0.36 − 0.30 + 0.36 , − 8.8 − 4.5 + 3.7 ) , consistent with a constant equation of state to within ∼2 σ . Including Planck cosmic microwave background, Sloan Digital Sky Survey baryon acoustic oscillation, and DES 3 × 2pt data gives (Ω M , w ) = (0.321 ± 0.007, −0.941 ± 0.026). In all cases, dark energy is consistent with a cosmological constant to within ∼2 σ . Systematic errors on cosmological parameters are subdominant compared to statistical errors; these results thus pave the way for future photometrically classified SN analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Knowledge gaps for neuromorphic ionic computing

BACKGROUND Neuromorphic computing, inspired by the human brain’s ability to process information efficiently, represents a transformative approach to computation. In this Review, we explore the emerging field of neuromorphic ionic computing, which leverages ionic conduction and coupling to mimic neural processes, and identify critical knowledge gaps that must be addressed to realize its full potential. A central theme of the discussion is energy efficiency, a challenge that is both a limitation and an opportunity for this technology. Although complementary metal-oxide semiconductor (CMOS)–based neuromorphic technologies have made strides in scaling to billions of neurons and are increasingly applied in artificial intelligence and numerical computing, they remain orders of magnitude behind the human brain in terms of connectivity and energy efficiency. Neuromorphic ionic computing promises to overcome these limitations by leveraging the distinct architectural and operational principles of the brain. Our brains achieve this energy efficiency by combining several key features: using the same network elements to store and process information; using an incredibly complex and massively interconnected three-dimensional (3D) network of locally active elements that enables sparsity, robustness in the presence of noise, adaptation, and life-long learning; computing at comparatively low voltage and frequency; and last, taking advantage of a plethora of ions and small molecules as information carriers. Here, we propose that ionic computing systems can take advantage of similar features to achieve substantial gains in energy efficiency. ADVANCES Since the first reports of neuromorphic ionic behavior in nanofluidic channels, we have witnessed an explosion of reports that used ionic devices to produce synaptomimetic behaviors. However, achieving the goals of ionic computing requires not only implementation of much more sophisticated device functionality but also overcoming fundamental barriers in materials science, device architecture, and system integration. Current ionic devices, even those incorporating state-of-the-art materials, still suffer from limited functionality and stability, which restrict their performance and increase energy demands. Developing new materials with enhanced ionic properties is essential to overcome these limitations. Similarly, the design of neuromorphic devices must evolve to leverage the particular advantages of ionic processes. Existing architectures often follow a single-information-carrier logic of conventional electronics or are constructed of mesoscale fluidics, failing to capitalize on the energy-efficient mechanisms inherent to ionic systems or implement the multiple-information-carrier paradigm. Current neuromorphic chips focus on large-scale networks of analog memory elements based on mechanisms such as charge trap (flash), filamentary, phase change, or spin, which are built on top of a network of artificial CMOS neurons. Although such prototype networks have achieved impressive performance, it is difficult to envision how they can implement the key features such as massive connectivity, sophisticated plasticity, adaptability, sparsity, and “multichromatic” computing. Although small-scale devices have demonstrated promising results, integrating them, maintaining energy efficiency, and implementing temperature control as systems grow in complexity and size to computationally relevant scale remain major hurdles. Furthermore, interfacing neuromorphic ionic devices with existing computing technologies presents technical and conceptual challenges that will require innovative approaches that combine insights from neuroscience, materials science, and engineering. OUTLOOK Despite these challenges, the potential impact of neuromorphic ionic computing is profound with potential applications ranging from artificial intelligence to robotics and beyond. We also argue that neuromorphic ionic computing systems should not, at least in the beginning, compete with CMOS technologies but rather should focus on applications that require extreme energy efficiency with chemical and/or biological compatibility, such as biomedical applications (for example, brain-computer interfaces), environmental monitoring, and agricultural and food applications. Ultimately, this Review highlights the crucial role of interdisciplinary collaboration in advancing the field. Neuromorphic ionic computing is not merely a technological innovation; it represents a substantial step toward sustainable computation, aligning with the growing demand for energy-conscious solutions in a world that is increasingly reliant on data and computation.

Neuromorphic↗
DOE OSTI2019

Integrating Systems Thinking into Teaching Emerging Technologies.

Collaborations and partnerships across disciplines are becoming increasingly recognized as valuable endeavors toward solving emerging global challenges in our rapidly changing world. Thus, it is crucial to create STEM educational strategies that infuse diverse and interconnected perspectives among scientists, policymakers, and the general public. Systems thinking represents one such pedagogical approach, in which a holistic framework empowers both teachers and students to recognize how fundamental concepts taught in the classroom can be used as resourceful tools to better address complex, multicomponent modern challenges. For chemical educators, topics on technology (the "T" in STEM education) represent a particularly meaningful avenue to introduce and study the effectiveness of systems thinking, but there have been few examples reported to date. Here, we show that a molecular engineering course introduced at the University of Chicago 5 years ago ("Introduction to Emerging Technologies") provides a model course to this end, where explicitly designing in elements of systems thinking to the course could further strengthen students' understanding of the already well suited, holistic course topics. Integrating systems thinking would illuminate how tissue engineering, nanomedicine, batteries, quantum information, and meat alternatives are developed from multiple, interrelated fields as well as from basic science to a practical reality. For each technology, we outline the direct connections between the current course topics and future opportunities to incorporate systems thinking strategies, challenging students to identify the interdependence of components in a successful technology. Finally, to offer further insight for instructors interested in utilizing systems thinking, we broaden our discussion to reflect on the challenges of redesigning any STEM course to utilize systems thinking, and we present corresponding teaching strategies to overcome them.

Interdisciplinary/Multidisciplinary↗
DOE OSTI2024

Artificial Intelligence for the Electron Ion Collider (AI4EIC)

The Electron-Ion Collider (EIC), a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in 2028. This is an opportune time for artificial intelligence (AI) to be included from the start at this facility and in all phases that lead up to the experiments. The second annual workshop organized by the AI4EIC working group, which recently took place, centered on exploring all current and prospective application areas of AI for the EIC. This workshop is not only beneficial for the EIC, but also provides valuable insights for the newly established ePIC collaboration at EIC. This paper summarizes the different activities and R&D projects covered across the sessions of the workshop and provides an overview of the goals, approaches and strategies regarding AI/ML in the EIC community, as well as cutting-edge techniques currently studied in other experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2024

Digital Lunar Exploration Sites (DLES) Terrain Crafting

Humans will soon be returning to the surface of the Moon with NASA’s Artemis program. The Artemis program is an international collaboration that will consist of a complex series of space systems and missions to explore the lunar surface and pave the way for the future exploration of Mars. NASA and its partners rely heavily on simulation for lighting and navigation studies as well as training astronauts, flight controllers, and mission support staff. The NASA Exploration Systems Simulations (NExSyS) team in the Simulation and Graphics Branch (ER7) in the Engineering Directorate at NASA’s Johnson Space Center has built up many simulation products to support this effort, one of which is the Digital Lunar Exploration Sites (DLES). DLES is a collection of products used to simulate and render the lunar surface in a digital environment. We discussed and presented an overview of the DLES products at the 2022 IEEE Aerospace Conference in Big Sky, MT with a paper titled "Digital Lunar Exploration Sites". This “DLES Terrain Crafting” paper will expand on the information previously provided in “DLES” paper and dive deeper into the details of the terrain crafting process and the toolsets used to support this task. The best digital data currently available of the lunar surface is provided by the Lunar Reconnaissance Orbiter (LRO). Its Lunar Orbiter Laser Altimeter (LOLA) achieves an impressive resolution of 5m per pixel at the Lunar South Pole (LSP) and can generate datasets covering a large continuous region near the LSP. There are a few additional methods, such as Shape from Shading which can infer higher resolution data (up to 1m per pixel) from the LRO Narrow Angle Camera (NAC) images. However, surface-based simulations require higher-resolution data, and this paper will discuss the process of enhancing the terrain to meet that need. The process begins with capturing statistical data of craters in the regions of interest using images provided by the LRO NAC. This data is then used to scatter artificial features which are not captured in the truth data, resulting in an enhanced DEM with a much higher resolution of 20cm per pixel. Many tools were built up to assist in the creation of these artificial Digital Elevation Models (DEM), which this paper will discuss in detail. DEMs themselves are a very powerful representation of a planetary surface, and many operations and tools can utilize the data they contain. This paper includes a description of the rendering of the lunar surface in a graphics engine, generation of contact patches to simulate tire to ground interaction, and ray tracing utilities to model Line of Sight (LOS) interactions with the terrain. This paper will also explore some new tool sets currently under development which aim to utilize Machine Learning (ML) to assist in the identification of craters from LRO NAC imagery. While this is not a novel idea, the NExSyS team is developing a unique approach which may result in more robust identification of crater characteristics.

Artemis↗
DOE OSTI2021

Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) (Final Scientific/Technical Report)

This report summarizes the activities conducted under the DOE VTO funded project DE- EE0008451, where ABB Inc. (ABB), in collaboration with Idaho National Laboratory (INL), APS Global (APS), and XOS Trucks (XOS) pursued the development of a cyber-resilient extreme fast charging (XFC) management system. This project entitled Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) focuses on a resilient architecture for smart charging EV Supply Equipment (EVSE) device control and Coordinated Anomaly Detection System (CADS) features that can be added at the charging site depot level to increase cybersecurity. The project was split into two budget periods focused first on developing the threat model and resilient control concepts and second on testing, improving, and validating those developed resilient control algorithms and features with a focus on key vulnerabilities identified during the threat assessment portion of the project. During the first budget period of the CyberX project, the ABB led team focused on activities to identify, model, and quantitatively prioritize high-impact attack scenarios with potential cyber-physical effects while also modeling and developing concepts for a resilient control system that could securely address integration of DERs and other resources with EV charging. Development of the security focused XFC management system (XMS) was accomplished first by offline simulation using a developed XFC station or depot with 480V input level and simulating measurement inputs to monitoring and control systems in concept development. A representative distribution grid model was developed supporting an EV charging site model with BESS and 6 general EV charging models. These EV charging models allowed multiple configurations of charging level, multiple connected protection and measurement devices, and simulation function to show general compromise of EV, BESS, and protection features based on parallel threat analysis. During the second budget period, the EV site and supporting systems model was developed in more detail and converted from offline model to real-time to real-time with EV charging hardware in the loop (HIL). The resilient control architecture developed as concept in the first part of the project was further tested and validated for integration of local energy resources and XFC charging station site equipment while maintaining cybersecure operating principles. The proposed resilient architecture for smart charging and cybersecurity features consists of two main concepts developed and tested within the project. The first concept is an XFC management system (XMS) consisting of a hardware gateway, software platform, and Supervisory Control and Data Acquisition (SCADA) or Distribution Management System integration components. The second concept is a Coordinated Anomaly Detection System (CADS) which forms a primarily software-related subsystem of the total CyberX solution focused on monitoring system measurements, estimation of measurement states, and predicting current at the utility point of interaction based on machine learning for anomaly detection.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Mitigating imaging systematics for DESI 2024 emission Line Galaxies and beyond

Emission Line Galaxies (ELGs) are one of the main tracers that the Dark Energy Spectroscopic Instrument (DESI) uses to probe the universe. However, they are afflicted by strong spurious correlations between target density and observing conditions known as imaging systematics. In this paper, we present the imaging systematics mitigation applied to the DESI Data Release 1 (DR1) large-scale structure catalogs used in the DESI 2024 cosmological analyses. We also explore extensions of the fiducial treatment. This includes a combined approach, through forward image simulations (Obiwan) in conjunction with neural network-based regression, to obtain an angular selection function that mitigates the imaging systematics observed in the DESI DR1 ELGs target density. We further derive a line of sight selection function from the forward model that removes the strong redshift dependence between imaging systematics and low redshift ELGs. Combining both angular and redshift-dependent systematics, we construct a three-dimensional selection function and assess the impact of all selection functions on clustering statistics. We quantify differences between these extended treatments and the fiducial treatment in terms of the measured 2-point statistics. We find that the results are generally consistent with the fiducial treatment and conclude that the differences are far less than the imaging systematics uncertainty included in DESI 2024 full-shape measurements. We extend our investigation to the ELGs at 0.6 < z < 0.8, i.e., beyond the redshift range (0.8 < z < 1.6) adopted for the DESI clustering catalog, and demonstrate that determining the full three-dimensional selection function is necessary in this redshift range. Our tests showed that all changes are consistent with statistical noise for BAO analyses indicating they are robust to even severe imaging systematics. Specific tests for the full-shape analysis will be presented in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗