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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Development and Operation of PIP-II Injector Test, SSR1 Cryomodule, 325 MHz Amplifiers

The PIP-II Injector Test (PIP2IT) has successfully accelerated ionized hydrogen up to 17MeV through a superconducting, single spoke resonator (SSR1) cryomodule at Fermi National Accelerator Laboratory (FNAL). Each of the SSR1 cavities is tuned to 325MHz and requires up to 6 kW of RF power to accelerate 2mA of ionized hydrogen at the design gradients. RF power amplifiers, specialized for SRF cavity beam operations, were designed by Bhabha Atomic Research Center (BARC) and constructed in a collaboration between the BARC in Mumbai, India and the Electronics Corporation of India Limited (ECIL) in Hyderabad, India. The RF amplifiers meet the specifications and requirements mutually approved between BARC and FNAL. They operate at 325 MHz with a linear power output of 7 kW in both CW and pulse mode. The amplifiers are compatible with the FNAL accelerator personnel safety system and the cavity protection interlocks. Access to controls and internal diagnostic instrumentation are compatible with EPICS control standards. This paper gives details about RF power amplifier development within the Department of Atomic Energy (DAE), India and the operational details with PIP2IT at FNAL.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Securing Distributed Energy Resource Integration

The penetration of distributed energy resources (DER) is growing at much higher rates than predicted 20 years ago. Far from being used only in residential settings, DER are now installed on distribution and transmission circuits. In this position, they do not have the same properties as traditional generators and are more flexible in many cases. The growing penetration and range of uses for DER motivate the need to reliably and safely integrate them into the grid. Operators must be able to rely on them not only for normal operation, but also during abnormal conditions like black starts or adverse cyber scenarios. To that end, we study the communications, device interfaces, and potential consequences of DER operation under abnormal and adversarial conditions. The weaknesses of communications networks are studied based on the industrial protocols used, and the benefits of security features are examined. The device interfaces are found to be vulnerable to attack based on the requirements in the IEEE-1547 standard for DER interconnection and interoperability, which is expected to be adopted in the next ten years. In addition to exploring the requirements of the standard, we show that these vulnerabilities and others do exist and can be used maliciously in a modern storage system DER. Consequences of these vulnerabilities range from exacerbated grid instability, to simultaneous loss of large portions of DER penetration, to physical damage to inverters or DER themselves and other sensitive equipment. We tie these outcomes to specific attacker actions in an effort to give operators a better threat intelligence view that allows them to prioritize mitigations. Finally, we discuss mitigations that could prevent many of the adversarial scenarios described. Some solutions can be added to existing infrastructure, while others may require longer term planning for grid modernization with consideration for security.

25 ENERGY STORAGE↗
DOE OSTI2022

Improved Throughput and Analysis of Scratch Test Results via Automation and Machine Learning

A data analysis automation interface that incorporates machine learning (ML) has been developed to improve productivity, efficiency, and consistency in identifying and defining critical load values (or other values associated with optically identifiable characteristics) of a coating when a scratch test is performed. In this specific program, the machine learning component of the program has been trained to identify the Critical Load 2 (L C2 ) value by analyzing images of the scratch tracks created in each test. An optical examination of the scratch by a human operator is currently used to determine where this value occurs. However, the vagueness of the standard has led to varying interpretations and nonuniform usage by different operators at different laboratories where the test is implemented, resulting in multiple definitions of the desired parameter. Using a standard set of training and validation images to create the dataset, the critical load can be identified consistently amongst different laboratories using the automation interface without requiring the training of human operators. When the model was used in conjunction with an instrument manufacturer's scratch test software, the model produced accurate and repeatable results and defined L C2 values in as little as half of the time compared to a human operator. When combined with a program that automates other aspects of the scratch testing process usually conducted by a human operator, scratch testing and analysis can occur with little to no intervention from a human beyond initial setup and frees them to complete other work in the lab.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Countering Weapons of Mass Destruction (CWMD) Zero Trust Framework: CWMD Zero Trust Principles Model

The research focuses on the critical need for enhanced cybersecurity within the Countering Weapons of Mass Destruction (CWMD) Office, specifically targeting Chemical, Biological, Radiological, and Nuclear devices. Traditional perimeter-based security models are insufficient against modern cyber threats, prompting a shift toward Zero Trust principles (ZTP) that emphasize continuous verification and stringent security for all devices. Federal directives mandate the adoption of Zero Trust (ZT) across agencies, supported by guidelines from National Institute of Standards and Technology (NIST), U.S. Department of Homeland Security (DHS) Cybersecurity and Infrastructure Security Agency (CISA), U.S. Department of Defense (DoD) and National Security Agency (NSA). The research involved mapping ZT guidance from these agencies to develop tailored CWMD ZTP. The study identified gaps and areas for improvement, including clear transitional guidance from traditional to ZT architectures and the focus on explicit cross cutting capabilities. Design improvements are recommended to ensure increased comprehensive protection and resilience against sophisticated cyber threats for Chemical, Biological, Radiological, and Nuclear (CBRN) devices. Collaborative efforts among federal agencies are essential for the successful deployment of an optimized ZT guidance.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Sizing and Selection of Pressure Relief Valves for High-Pressure Thermal–Hydraulic Systems

This study covers the critical concerns related to the sizing, selection, installation, maintenance, and testing of pressure safety valves (PSVs). The aim is to ensure the safety of pressurized systems, hydrostatic transmission systems, and hydraulic plants, including process plants, thermal power plants, and nuclear reactor systems. PSVs are devices that ensure the safety and reliability of pressurized vessels, lines, and systems during overpressure events. The task of selecting which PSV features are of greatest value for a specific purpose is complex—especially in the design of a high-pressure experimental thermal–hydraulic facility for hydrostatic and transient testing of the reactor system—when the systems are in the design and development phases and require qualification and demonstration to prove that they have reached a given level of technological readiness. The present study highlights the required steps for users to follow the associated rules, guidelines, and recommendations. As a part of this research, case studies are presented to help readers better understand the applicable strategy and standards. A discussion and a review of PSV performance degradation and failure are summarized to provide a better understanding of varied process applications and conditions, including fluid flow dynamics, boundary-layer formation and pressure drops, gas bubble formation and collapse, geometric configurations, inlet/outlet piping, abrupt pressure fluctuations, and acoustic resonance. Moreover, this study discusses the servicing and testing of PSVs in a multiphase pressurized system. Overall, it provides a basic overview of how PSVs ensure the safety of pressurized systems, supported by case studies and industrial practices.

02 PETROLEUM↗
DOE OSTI2025

Disorder-induced spin excitation continuum and spin-glass ground state in the inverse spinel CuGa 2 O 4

Spinel-structured compounds serve as prototypical examples of highly frustrated systems and are promising candidates for realizing the long-sought quantum spin liquid (QSL) state. However, structural disorder is inevitable in many real QSL candidates and its impact remains a topic of intense debate. In this work, we conduct comprehensive investigations on CuGa 2 ⁢ O 4 , a spinel compound with significant structural disorder, focusing on its thermodynamic properties and spectroscopic behaviors. No long-range magnetic order is observed down to ∼80 mK, as evidenced by magnetic susceptibility, specific-heat, and elastic neutron scattering measurements. More intriguingly, inelastic neutron scattering experiments reveal a broad gapless continuum of magnetic excitations around the Brillouin zone boundary, resembling the magnetic excitation spectra expected for a QSL. Nevertheless, a spin-freezing transition at 𝑇 f ≈ 0.88 K is identified from the cusp in the dc susceptibility curves, where a bifurcation between zero-field-cooling and field-cooling curves occurs. Furthermore, ac susceptibility measurements show a peak close to 𝑇 f at low frequency, which shifts to higher temperature with increasing frequency. These results show that CuGa 2 ⁢ O 4 has a spin-glass ground state, consistent with the establishment of short-range order inferred from the specific-heat measurements. Collectively, these results illustrate the crucial role of disorder in defining the excitation spectrum out of the disordered ground state. Furthermore, our findings shed light onto the broader class of 𝐴⁢𝐵 2 ⁢O 4 spinels and advance our understanding of the spin dynamics in magnetically disordered systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

An extensible vector toolkit and parts library for advanced engineering of plant genomes

Abstract Plant biotechnology is rife with new advances in transformation and genome engineering techniques. A common requirement for delivery and coordinated expression in plant cells, however, places the design and assembly of transformation constructs at a crucial juncture as desired reagent suites grow more complex. Modular cloning principles have simplified some aspects of vector design, yet many important components remain unavailable or poorly adapted for rapid implementation in biotechnology research. Here, we describe a universal Golden Gate cloning toolkit for vector construction. The toolkit chassis is compatible with the widely accepted Phytobrick standard for genetic parts, and supports assembly of arbitrarily complex T‐DNAs through improved capacity, positional flexibility, and extensibility in comparison to extant kits. We also provision a substantial library of newly adapted Phytobricks, including regulatory elements for monocot and dicot gene expression, and coding sequences for genes of interest such as reporters, developmental regulators, and site‐specific recombinases. Finally, we use a series of dual‐luciferase assays to measure contributions to expression from promoters, terminators, and from cross‐cassette interactions attributable to enhancer elements in certain promoters. Taken together, these publicly available cloning resources can greatly accelerate the testing and deployment of new tools for plant engineering.

42 ENGINEERING↗
DOE OSTI2026

A Data-Driven Method for Modeling Creep-Fatigue Stress- Strain Behavior Using Neural ODEs

In this paper, we introduce a data-driven machine learning approach for modeling one-dimensional stress–strain behavior under cyclic loading, utilizing experimental data from the nickel-based Alloy 617. The study employs uniaxial creep–fatigue test data acquired under various loading histories and compares two distinct neural network-based ODE models. The first model, known as the black-box model, comprehensively describes the strain–stress relationship using a Neural ODE equation. To interpret this black-box model, we apply the Sparse Identification of Nonlinear Dynamical Systems (SINDy) technique, transforming the black-box model into an equation-based model using symbolic regression. The second model, the Neural flow rule model, incorporates Hooke’s Law for the linear elastic component, with the nonlinear part characterized by a Neural ODE. Both models are trained with experimental data to accurately reflect the observed stress–strain behavior. We conduct a detailed comparison with the standard Chaboche model, which includes three back stresses. Our results demonstrate that the neural network-based ODE models precisely capture the experimental creep–fatigue mechanical behavior, exceeding the standard Chaboche model’s accuracy. Furthermore, an interpretable model derived from the black-box neural ODE model through symbolic regression achieves accuracy comparable to the Chaboche model, enhancing its interpretability. The results highlight the potential of neural network-based ODE models to depict complex creep–fatigue behavior, eliminating the necessity for experts to define a specific, material-focused model form.

creep-fatigue↗
DOE OSTI2025

Mapping tree height in complex terrain of northern China using ultra-high-resolution images

Tree height is a key parameter for estimating forest biomass and carbon sequestration. In recent years, notable progress has been made in mapping tree height using satellite imagery. However, existing tree height products show low accuracy in mountainous and complex terrains, and few studies typically addressed tree height estimations in mountain areas. This study examines the Mentougou district of Beijing, China, characterized by complex terrain and mountainous landscapes. We analyzed two methods for estimating tree height: one using only spectral features and another combining spectral features with topographic factors (elevation, slope, aspect). We used 3-m resolution PlanetScope 8-band multispectral imagery, with 710 field-measured individual tree heights averaged to obtain 471 pixel-level tree height values as ground-truth, to develop tree height prediction models using eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Gradient Boosting Machine (GBM) models. The results show that the XGBoost model consistently presented the highest accuracy for both methods evaluated. Specifically, the XGBoost model that combined spectral data with elevation and slope variables with an R² of 0.75 and an RMSE of 2.69 m. Using the XGBoost model, we generated the tree height map for the Mentougou area at 3 m resolution, showing tree heights ranging from 0.5 to 30.4 m, and the model’s prediction error standard deviations ranged from 2.50 to 4.71 m, indicating reliable performance across varied terrain. Additionally, we compared and evaluated the global tree height products, identifying limitations in the accuracy within complex terrains. This study demonstrates the potential for accurately predicting tree heights by combining high-resolution multispectral satellites with a terrain factor modeling approach.

Complex terrain↗
DOE OSTI2024

Entangling quantum logic gates in neutral atoms via the microwave-driven spin-flip blockade

The Rydberg dipole blockade has emerged as the standard mechanism to induce entanglement between neutral-atom qubits. In these protocols, laser fields that couple qubit states to Rydberg states are modulated to implement entangling gates. Here, in this study, we present an alternative protocol to implement entangling gates via Rydberg dressing and a microwave-field-driven spin-flip blockade. We consider the specific example of qubits encoded in the clock states of cesium. An auxiliary hyperfine state is optically dressed so that it acquires partial Rydberg character. It thus acts as a proxy Rydberg state, with a nonlinear light shift that plays the role of blockade strength. A microwave-frequency field coupling a qubit state to this dressed auxiliary state can be modulated to implement entangling gates. Logic gate protocols designed for the optical regime can be imported to this microwave regime, for which experimental control methods are more robust. We show that unlike the strong dipole-blockade regime usually employed in Rydberg experiments, going to a moderate-spin-flip-blockade regime results in faster gates and smaller Rydberg decay. We study various regimes of operations that can yield high-fidelity two-qubit entangling gates and characterize their analytical behavior. In addition to the inherent robustness of microwave control, we can design these gates to be more robust to laser amplitude and frequency noises at the cost of a small increase in Rydberg decay.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

In Vitro Thrombogenicity Testing of Biomaterials in a Dynamic Flow Loop: Effects of Length and Quantity of Test Samples

Abstract The results of in vitro dynamic thrombogenicity testing of biomaterials and medical devices can be significantly impacted by test conditions. To develop and standardize a robust dynamic in vitro thrombogenicity tool, the key test parameters need to be appropriately evaluated and optimized. We used a flow loop test system previously developed in our laboratory to investigate the effects of sample length and the number of samples per test loop on the thrombogenicity results. Porcine blood heparinized to a donor-specific target concentration was recirculated at room temperature through polyvinyl chloride (PVC) tubing loops containing test materials for 1 h at 200 mL/min. Four test materials (polytetrafluoroethylene (PTFE), latex, PVC, and silicone) with various thrombotic potentials in two sample lengths (12 and 18 cm) were examined. For the 12-cm long materials, two different test configurations (one and two samples per loop) were compared. Thrombogenicity was assessed through percent thrombus surface coverage, thrombus weight, and platelet count reduction in the blood. The test system was able to effectively differentiate the thrombogenicity profile of the materials (latex > silicone > PVC ≥ PTFE) at all test configurations. Increasing test sample length by 50% did not significantly impact the test results as both 12 and 18 cm sample lengths were shown to equally differentiate thrombotic potentials between the materials. The addition of a second test sample to each loop did not increase the test sensitivity and may produce confounding results, and thus a single test sample per loop is recommended.

Engineering↗
DOE OSTI2020

Search for a scalar partner of the top quark in the all-hadronic $t{\bar{t}}$ plus missing transverse momentum final state at $\sqrt{s}=13$ TeV with the ATLAS detector

A search for direct pair production of scalar partners of the top quark (top squarks or scalar third-generation up-type leptoquarks) in the all-hadronic $t{\bar{t}}$ plus missing transverse momentum final state is presented. The analysis of 139 $\hbox {fb}^{-1}$ of ${\sqrt{s}=13}$ TeV proton–proton collision data collected using the ATLAS detector at the LHC yields no significant excess over the Standard Model background expectation. To interpret the results, a supersymmetric model is used where the top squark decays via ${\tilde{t}} \rightarrow t^{(*)} {\tilde{\chi }}^0_1$ t ~ → t ( * ) χ ~ 1 0 , with $t^{(*)}$ t ( * ) denoting an on-shell (off-shell) top quark and ${\tilde{\chi }}^0_1$ χ ~ 1 0 the lightest neutralino. Three specific event selections are optimised for the following scenarios. In the scenario where $m_{{\tilde{t}}}> m_t+m_{{\tilde{\chi }}^0_1}$ m t ~ > m t + m χ ~ 1 0 , top squark masses are excluded in the range 400–1250 GeV for ${\tilde{\chi }}^0_1$ χ ~ 1 0 masses below 200 GeV at 95% confidence level. In the situation where $m_{{\tilde{t}}}\sim m_t+m_{{\tilde{\chi }}^0_1}$ m t ~ ~ m t + m χ ~ 1 0 , top squark masses in the range 300–630 GeV are excluded, while in the case where $m_{{\tilde{t}}}< m_W+m_b+m_{{\tilde{\chi }}^0_1}$ m t ~ < m W + m b + m χ ~ 1 0 (with $m_{{\tilde{t}}}-m_{{\tilde{\chi }}^0_1}\ge 5$ m t ~ - m χ ~ 1 0 ≥ 5 GeV), considered for the first time in an ATLAS all-hadronic search, top squark masses in the range 300–660 GeV are excluded. Limits are also set for scalar third-generation up-type leptoquarks, excluding leptoquarks with masses below 1240 GeV when considering only leptoquark decays into a top quark and a neutrino.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Degradation of Commercial Lithium-Ion Cells as a Function of Chemistry and Cycling Conditions

Energy storage systems with Li-ion batteries are increasingly deployed to maintain a robust and resilient grid and facilitate the integration of renewable energy resources. However, appropriate selection of cells for different applications is difficult due to limited public data comparing the most commonly used off-the-shelf Li-ion chemistries under the same operating conditions. This article details a multi-year cycling study of commercial LiFePO 4 (LFP), LiNi x Co y Al 1–x–y O 2 (NCA), and LiNi x Mn y Co 1–x–y O 2 (NMC) cells, varying the discharge rate, depth of discharge (DOD), and environment temperature. The capacity and discharge energy retention, as well as the round-trip efficiency, were compared. Even when operated within manufacturer specifications, the range of cycling conditions had a profound effect on cell degradation, with time to reach 80% capacity varying by thousands of hours and cycle counts among cells of each chemistry. The degradation of cells in this study was compared to that of similar cells in previous studies to identify universal trends and to provide a standard deviation for performance. All cycling files have been made publicly available at batteryarchive.org, a recently developed repository for visualization and comparison of battery data, to facilitate future experimental and modeling efforts.

25 ENERGY STORAGE↗
DOE OSTI2023

EyeON

EyeON: Eye on Operational technology Software Supply Chain attacks have risen drastically over the past few years, none more well-known and impactful than the SolarWinds compromise. Criminal organizations inserted an attack vector into a specific version of the source code, giving themselves an air of credibility. Once news broke on SolarWinds, identifying compromised sites was very difficult, even knowing the culprit update. Software Bills of Materials (SBOM) have been touted as the solution to reclaiming control of your software supply chain. Deployment of SBOMs has been slow, however, due to conflicting standards, opaque storage requirements, and vendor adoption. Additionally, the path from obtaining an SBOM and securing your supply chain is unclear; how can an SBOM library be leveraged to provide insight to your attack surface? The EyeON tool, sponsored by Department of Energy Cybersecurity, Energy Security, and Emergency Response (DoE CESER), aims to address these gaps by providing an encapsulated solution to tracking which updates have been installed in an enterprise, and alerting system administrators to vulnerabilities as they become known. Similar to a virus scanner, EyeON is a command line tool to parse either a single file, nested directory structure, or filesystem. It collects data such as signature (hashes), version information, VirusTotal tags, compiler, compilation date, and code signing information. Users will anonymously submit scan data periodically to DoE CESER, who will then compile a database of known software products employed by Critical Infrastructure and broadcast alerts based on discovered flaws as they arise.

Tenzing, Wangmo↗
DOE OSTI2024

Chemical-specific Parameters Dataset

The chemical-specific parameters dataset is searchable for physicochemical information for multiple chemicals simultaneously. After selecting chemicals of interest and the desired parameters, the RAIS will generate a table containing the values, chosen according to an established hierarchy. Results can be downloaded in Excel format. Over 40 parameters are available, including melting point, boiling point, density, density, vapor pressure, water solubility, and Henry’s Law constants. Thirteen primary sources are used to populate the dataset of chemical-specific parameters. These values should be used in cancer risk and noncancer hazard assessments for the calculation of preliminary remediation goals (PRGs), hazard characterization, and transport modeling. Users can select up to 1000 chemicals per query. The dataset supports environmental risk assessments, regulatory decision-making, and environmental planning with tools for benchmarking against risk-based standards. This structured approach ensures a robust evaluation of environmental risks tailored to regulatory needs.

Dolislager, Fred [Oak Ridge National Laboratory (O↗
DOE OSTI2025

Misclassification in Workers’ Telecommuting Frequency Choices Using a Generalized Extreme Value Model

Telecommuting frequency is a response variable collected in travel surveys and is, therefore, prone to errors leading to mismeasurements or misclassification. Misclassification of explanatory variables is a common risk when using statistical modeling techniques. We define “misclassification” as a response reported or recorded in the wrong category; for example, a variable is recorded as a 1 when it should be 0. Here, in this context, this study aims to develop a statistical model to analyze telecommuting data which accounts for potential misclassification errors by building on existing literature in econometrics. The empirical analysis was undertaken using the 2017 National Household Travel Survey (NHTS) and the general extreme value (GEV) models available in the literature. Specifically, the frequency of telecommuting days was analyzed using the negative binomial (NB) model recast as the multinomial logit (MNL) model. By nature—and consistent with other studies—NHTS data are prone to errors that can be classified as intentional or unintentional misinformation provided by the person being interviewed. Ignoring these errors while modeling telecommuting frequencies using standard discrete count models can result in biased parameter estimates. The misclassification parameter was calculated for both over-reporting and under-reporting scenarios. The misclassification errors can be as high as 14% over-reported and 10% under-reported, particularly for the neighboring values. Statistical fit comparison between the models shows that models that ignore misclassification have worse data fit and biased parameter estimates with significant policy implications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Graph link prediction in computer networks using Poisson matrix factorisation

Graph link prediction is an important task in cybersecurity: relationships between entities within a computer network, such as users interacting with computers or system libraries and the corresponding processes that use them, can provide key insights into adversary behaviour. Poisson matrix factorisation (PMF) is a popular model for link prediction in large networks, particularly useful for its scalability. In this article PMF is extended to include scenarios that are commonly encountered in cybersecurity applications. Specifically, an extension is proposed to explicitly handle binary adjacency matrices and include known categorical covariates associated with the graph nodes. A seasonal PMF model is also presented to handle seasonal networks. To allow the methods to scale to large graphs, variational methods are discussed for performing fast inference. The results show an improved performance over the standard PMF model and other statistical network models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Step Toward Working with Untrusted Ground Stations

We are witnessing a shift toward outsourcing satellite and ground station services to third-party commercial entities. As with any enterprise, these third parties can be vulnerable to cyber compromise, including image tampering and deepfake injection. The multimedia community is beginning to establish standards and technology to enable authenticity verification of multimedia created and edited by others. While appealing to the remote sensing domain, the nature of raw satellite imagery is incompatible with the proposed change verification tools, resulting in the need for a means to validate updates made to image products. We present a simple method for verifying a specific class of algorithms. Our inverse processing approach eliminates the need to see the original image as the reversed data can be checked against an original digital signature. We demonstrate our approach on basic image restoration routines and conclude with a discussion on open challenges and next steps.

97 MATHEMATICS AND COMPUTING↗