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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Cyber-Informed Engineering (CIE) – Engineered Controls Database and Use

Cyber-Informed Engineering (CIE) addresses the reality that cyber-attacks on engineered systems can have consequences far beyond data loss or disruption of digital networks. When control systems are compromised, safety, reliability, and performance of the physical process itself may be threatened. This database is meant to establish clear examples and guidance for defining and applying engineered controls in CIE. It explains what engineered controls are, how they differ from information security measures, and how they are integrated into system design. The goal is to ensure that resilience is engineered into systems from the outset. Unlike cybersecurity protections that defend the digital layer, engineered controls act directly at the physical and algorithmic levels to guarantee that unacceptable consequences are prevented or limited. CIE keeps the consequences of a cyber attack from impacting the safety, reliability, and performance of engineered systems.

42 - ENGINEERING↗
DOE OSTI2022

A conservative implicit-PIC scheme for the hybrid kinetic-ion fluid-electron plasma model on curvilinear meshes

We report that the hybrid kinetic-ion fluid-electron plasma model is widely used to study challenging multi-scale problems in space and laboratory plasma physics. Here, a novel conservative scheme for this model employing implicit particle-in-cell techniques is extended to arbitrary coordinate systems via curvilinear maps from logical to physical space. The scheme features a fully non-linear electromagnetic formulation with a multi-rate time advance - including sub-cycling and orbit-averaging for the kinetic ions. By careful choice of compatible particle-based kinetic-ion and mesh-based fluid-electron discretizations in curvilinear coordinates, as well as particle-mesh interpolations and implicit midpoint time advance, the scheme is proven to conserve total energy for arbitrary curvilinear meshes. In the electrostatic limit, the method is also proven to conserve total momentum for arbitrary curvilinear meshes. Although momentum is not conserved for arbitrary curvilinear meshes in the electromagnetic case, it is for an important subset of Cartesian tensor-packed meshes. The scheme and its novel conservation properties are demonstrated for several challenging numerical problems using different curvilinear meshes, including a merging flux-rope simulation for a space weather application, and a helical m = 1 mode simulation for magnetic fusion energy application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

PDFDataExtractor: A Tool for Reading Scientific Text and Interpreting Metadata from the Typeset Literature in the Portable Document Format

The layout of portable document format (PDF) files is constant to any screen, and the metadata therein are latent, compared to mark-up languages such as HTML and XML. No semantic tags are usually provided, and a PDF file is not designed to be edited or its data interpreted by software. However, data held in PDF files need to be extracted in order to comply with opensource data requirements that are now government-regulated. In the chemical domain, related chemical and property data also need to be found, and their correlations need to be exploited to enable data science in areas such as data-driven materials discovery. Such relationships may be realized using text-mining software such as the “chemistry-aware” natural-language-processing tool, ChemDataExtractor; however, this tool has limited data-extraction capabilities from PDF files. This study presents the PDFDataExtractor tool, which can act as a plug-in to ChemDataExtractor. It outperforms other PDF-extraction tools for the chemical literature by coupling its functionalities to the chemical-named entityrecognition capabilities of ChemDataExtractor. The intrinsic PDF-reading abilities of ChemDataExtractor are much improved. The system features a template-based architecture. This enables semantic information to be extracted from the PDF files of scientific articles in order to reconstruct the logical structure of articles. While other existing PDF-extracting tools focus on quantity mining, this template-based system is more focused on quality mining on different layouts. PDFDataExtractor outputs information in JSON and plain text, including the metadata of a PDF file, such as paper title, authors, affiliation, email, abstract, keywords, journal, year, document object identifier (DOI), reference, and issue number. With a self-created evaluation article set, PDFDataExtractor achieved promising precision for all key assessed metadata areas of the document text.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

CERES MODIS Cloud Product Retrievals for Edition 4--Part I: Algorithm Changes

The Edition 2 (Ed2) cloud property retrieval algorithm system was upgraded and applied to the MODerate-resolution Imaging Spectroradiometer (MODIS) data for the Clouds and the Earth's Radiant Energy System (CERES) Edition 4 (Ed4) products. New calibrations for solar channels and the use of the 1.24-μm channel for cloud optical depth (COD) over snow improve the daytime consistency between Terra and Aqua MODIS retrievals. Use of additional spectral channels and revised logic enhanced the cloud-top phase retrieval accuracy. A new ice crystal reflectance model and a CO₂-channel algorithm retrieved higher ice clouds, while a new regional lapse rate technique produced more accurate water cloud heights than in Ed2. Ice cloud base heights are more accurate due to a new cloud thickness parameterization. Overall, CODs increased, especially over the polar (PO) regions. The mean particle sizes increased slightly for water clouds, but more so for ice clouds in the PO areas. New experimental parameters introduced in Ed4 are limited in utility, but will be revised for the next CERES edition. As part of the Ed4 retrieval evaluation, the average properties are compared with those from other algorithms and the differences between individual reference data and matched Ed4 retrievals are explored. Part II of this article provides a comprehensive, objective evaluation of selected parameters. More accurate interpretation of the CERES radiation measurements has resulted from the use of the Ed4 cloud properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Signal Temporal Logic Control for Residential HVAC Systems to Accommodate High Solar PV Penetration

This paper proposes a new signal temporal logic (STL) control for ON/OFF residential buildings' Heating Ventilation and Air Conditioning (HVAC) systems. STL is used to control indoor temperatures while consuming most of the generated solar photovoltaic (PV) power locally to minimize its impact on the grid and reduce the need for large energy storage devices. In contrast to most, if not all, control mechanisms such as the traditional model predictive control (MPC), STL control allows for including temporal constraints in the control formulation to further relax indoor temperatures' constraints and allow them to exceed the comfort band limits for a prespecified (short) period of time. This relaxation allows to consume an additional PV power by the HVAC systems, which prevents such an unwanted intermittent power from affecting the grid. We formulate the MPC-based STL control mechanism to implement the objective. Simulation results show that the PV tracking performance has been improved while employing the proposed STL controller.

Wu, Tumin↗
DOE OSTI2025

Synchronous Machine Governor Upgrade

Conventional generation sources play a critical role in the stability and reliability of the electrical grid, particularly as we transition towards more renewable energy sources. To understand and accurately emulate their behavior for optimizing grid operations and ensuring seamless integration with renewable technologies, it is essential to better emulate the grid- and plant-level impacts of conventional generation sources, such as natural gas (NG) driven heat recovery steam generators (HRSGs) and combustion turbines (CTs). Therefore, a governor model is developed in a programmable logic controller (PLC) to investigate the performance of the conventional generator under various dynamic operating conditions and to identify the impact on grid stability in a controlled environment. The governor model aims to enable the hardware-in-the-loop (HIL) based emulation of these conventional generation sources using the existing 2 MVA synchronous machine/generator that is driven by a flexible 2.5 MW variable speed drive. This setup will allow us to replicate the dynamic characteristics and response behaviors of NG-driven HRSGs and CTs. The controls for the emulated conventional plants follow the industry standard and are adjustable, ensuring they accurately reflect the operational capabilities and limitations of real-world systems. These controls include load-following capabilities, ramp rates, startup and shutdown sequences, and emissions characteristics. By incorporating these adjustable controls, we aim to capture the nuanced impacts of conventional generation, such as their ability to provide ancillary services like frequency regulation, voltage support, and spinning reserve. In this report, we simulate two types of dynamic operations: grid-connected and islanding. For each dynamic operation, representative starting sequences are tested, including turbine purge, ignition, speed ramping up, generator excitation and synchronizing, and breaker close. The HIL based tests provides insights for field deployment, specifically the high-fidelity governor model provides results to predict the potential stability and reliability risk and suggest possible integration measures (e.g., generation and load balancing, tuning of governor control parameters). Ultimately, this enhanced emulation capability will be integrated into our Advanced Research on Integrated Energy Systems (ARIES), enabling us to conduct comprehensive studies on the interactions between conventional and renewable energy sources. By better understanding these interactions, we can develop strategies to optimize the overall performance and reliability of the grid. This will support the deployment of advanced grid management techniques, such as demand response, grid-forming inverters, and energy storage systems. The main contributions are summarized as follows: (1) This report introduces a PLC-based governor model for gas turbines. This model accurately simulates the dynamic behavior of conventional generation sources under various operational scenarios; (2) The model is integrated with an HIL testbed that includes a 2.5 MW variable speed drive and a 2 MVA synchronous machine. This setup enables realistic, real-time emulation of conventional power plants, particularly NG driven HRSGs and CTs; (3) The developed model is adaptable to various gas turbine configurations and allows for precise control over parameters such as MW ramp rates. This flexibility makes it a valuable tool for future research and industry collaboration; and (4) By incorporating the model into the National Renewable Energy Laboratory's Advanced Research on Integrated Energy Systems, the report lays the groundwork for future studies on interactions between conventional and renewable energy sources, enhancing the ability to develop advanced grid management strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Comprehensive characterization of the structure of Zr-based metallic glasses

Structure of metallic glasses fascinates as the generic amorphous structural template for ubiquitous systems. Its specification necessitates determination of the complete hierarchical structure, starting from short-range-order (SRO) → medium-range-order (MRO) → bulk structure and free volume (FV) distribution. This link has largely remained elusive since previous investigations adopted one-technique-at-a-time approach, focusing on limited aspects of any one domain. Reconstruction of structure from experimental data inversion is non-unique for many of these techniques. As a result, complete and precise structural understanding of glass has not emerged yet. In this work, we demonstrate the first experimental pathway for reconstruction of the integrated structure, for and glasses. Our strategy engages diverse (×7) multi-scale techniques [XAFS, 3D-APT, ABED/NBED, FEM, XRD, PAS, FHREM] on the same glass. This strategy complemented mutual limitations of techniques and corroborated common parameters to generate complete, self-consistent and precise parameters. Further, MRO domain size and inter-void separation were correlated to identify the presence of FV at MRO boundaries. This enabled the first experimental reconstruction of hierarchical subset: SRO → MRO → FV → bulk structure. The first ever image of intermediate region between MRO domains emerged from this link. We clarify that determination of all subsets is not our objective; the essence and novelty of this work lies in directing the pathway towards finite solution, in the most logical and unambiguous way.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Domain wall enabled steep slope switching in MoS2 transistors towards hysteresis-free operation

Abstract The device concept of ferroelectric-based negative capacitance (NC) transistors offers a promising route for achieving energy-efficient logic applications that can outperform the conventional semiconductor technology, while viable operation mechanisms remain a central topic of debate. In this work, we report steep slope switching in MoS 2 transistors back-gated by single-layer polycrystalline PbZr 0.35 Ti 0.65 O 3 . The devices exhibit current switching ratios up to 8 × 10 6 within an ultra-low gate voltage window of $$V_{{{\mathrm{g}}}} = \pm \! 0.5$$ V g = ± 0.5 V and subthreshold swing (SS) as low as 9.7 mV decade −1 at room temperature, transcending the 60 mV decade −1 Boltzmann limit without involving additional dielectric layers. Theoretical modeling reveals the dominant role of the metastable polar states within domain walls in enabling the NC mode, which is corroborated by the relation between SS and domain wall density. Our findings shed light on a hysteresis-free mechanism for NC operation, providing a simple yet effective material strategy for developing low-power 2D nanoelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Concatenated dual displacement code for continuous-variable quantum error correction

The continuous-variable (CV) Gaussian no-go theorem fundamentally limits the suppression of Gaussian displacement errors using only Gaussian gates and states. Prior studies have employed Gottesman-Kitaev-Preskill (GKP) states as ancillary qumodes to suppress small Gaussian displacement errors. However, when the displacement magnitude becomes large, inevitable lattice-crossing errors arise beyond the correctable range of the GKP state. To address this issue, we concatenate the Gaussian-noise-suppression circuit with an outer analog Steane code that corrects such occasional lattice-crossing events as well as other abrupt displacement errors. Contrary to conventional concatenation, which primarily aims to reduce logical error rates, the Steane-GKP duality in encoding provides complementary protection against displacement errors at different scales: The inner GKP layer employs non-Gaussian resources to suppress continuous Gaussian noise and reduce residual variance, while the outer analog Steane code corrects discrete lattice-crossing events that exceed the GKP correctable range. It is precisely this separation of error-mitigation roles that enables CV error correction. In contrast to prior work on concatenating GKP and repetition codes to establish error correction for discrete qubit/qudit encoding, we provide correction in the continuous encoding space. Analytical studies show that, under infinite squeezing, the concatenated code suppresses the variance of Gaussian displacement errors acting on all qumodes by up to 50%, while enabling unbiased correction of lattice-crossing errors with a success probability determined by the ratio between the residual Gaussian error standard deviation and the lattice-crossing magnitude. Even with finite squeezing, the proposed architecture still provides Gaussian-error suppression and lattice-crossing correction. Moreover, the presence of the outer analog Steane code relaxes the squeezing requirement of the inner GKP states, indicating near-term experimental feasibility. This work establishes a viable route toward fault-tolerant continuous-variable quantum computation and provides insight into the design of concatenated CV error-correcting architectures.

quantum error correction↗
DOE OSTI2026

Rational design of heterogeneous single-site catalysts via surface organometallic chemistry

Single-site heterogeneous catalysts offer an attractive route to unite the molecular precision of homogeneous catalysis with the durability and practical advantages of solids. Surface organometallic chemistry (SOMC) provides a particularly powerful strategy for this purpose by grafting molecular precursors onto tailored surfaces and converting support functionalities into ligand environments for isolated metal centers. As a result, SOMC brings the language and logic of coordination chemistry to heterogeneous catalysis, where the support becomes an integral part of the active site coordination sphere. This Review surveys recent progress in the rational design of SOMC-derived single-site catalysts, with emphasis on synthetic routes, post synthetic transformations, and the deliberate tuning of catalytic behavior through metal-support interactions. Discussions are made on how support identity, hydroxyl topology, acidity, and redox activity shape the geometry, electronic structure, and oxidation state of supported metal sites, as well as how these factors determine activity, selectivity, and stability. We also examine a central limitation of these systems: despite their molecularly informed design, supported single sites often exist as structurally distributed ensembles rather than uniform species, particularly on amorphous supports. This site heterogeneity, along with catalyst dynamics under operating conditions, remains a major barrier to definitive structure-activity relationships. Therefore, emerging approaches that combine advanced characterization, first-principles modeling, ensemble kinetics, and machine learning to resolve active-site structure and guide catalyst development are highlighted. Together, these advances position SOMC as a versatile coordination chemistry framework for the predictive design of heterogeneous catalysts with well-defined molecularly tailored active sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Parsimonious Inference Information-Theoretic Foundations for a Complete Theory of Machine Learning (CIS-LDRD Project 218313 Final Technical Report)

This work examines how we may cast machine learning within a complete Bayesian framework to quantify and suppress explanatory complexity from first principles. Our investigation into both the philosophy and mathematics of rational belief leads us to emphasize the critical role of Bayesian inference in learning well-justified predictions within a rigorous and complete extended logic. The Bayesian framework allows us to coherently account for evidence in the learned plausibility of potential explanations. As an extended logic, the Bayesian paradigm regards probability as a notion of degrees of truth. In order to satisfy critical properties of probability as a coherent measure, as well as maintain consistency with binary propositional logic, we arrive at Bayes' Theorem as the only justifiable mechanism to update our beliefs to account for empiracle evidence. Yet, in the machine learning paradigm, where explanations are unconstrained algorithmic abstractions, we arrive at a critical challenge: Bayesian inference requires prior belief. Conventional approaches fail to yield a consistent framework in which we could compare prior plausibility among the infinities of potential choices in learning architectures. The difficulty of articulating well-justified prior belief over abstract models is the provinence of memorization in traditional machine learning training practices. This becomes exceptionally problematic in the context of limited datasets, when we wish to learn justifiable predictions from only a small amount of data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Integrate Latimer Controls' Solution into RTAC (CRADA Final Report, CRD-23-24672)

Latimer Controls, Inc. was awarded two vouchers under the Department of Energy's American-Made Solar Prize Round 6 to conduct collaborative research at a national laboratory. The National Renewable Energy Laboratory (NREL) was selected as a partner to assist Latimer Controls in the performance evaluation of its photovoltaic (PV) control software. This collaboration focuses on developing a hardware-in-the-loop (HIL) testbed at NREL, which will be used to test and validate the Latimer PV control technology in a realistic yet de-risked environment. Both Latimer and NREL teams will work together to analyze the collected test data, derive insights, and disseminate the scientific findings. Recent studies underscore the potential of solar energy as a zero-marginal-cost and zero-emission flexibility resource within the bulk power system, particularly when integrated with advanced control systems. To enhance the performance of such systems, Latimer Controls has developed leading-edge technologies, including machine learning (ML) algorithms and hierarchical inverter set-point allocation methods. These innovations are designed to estimate the operational headroom of large PV plants for grid integration and control. However, comprehensive validation under real-world conditions remains necessary. To address this gap, the concurrent CRADA project proposes the real-world application and validation of the Latimer Control solution within a HIL environment. Initially, the Latimer algorithm was developed and tested within MATLAB Simulink, a platform suitable for research-level simulations and iterative development. However, transitioning this technology to a real solar site as an industry-ready solution necessitates implementation in a format compatible with widely used solar power plant controllers. In this additional CRADA work, the MATLAB Simulink-based logic will be translated into Structured Text, a programming language compliant with IEC 61131 standards, which is commonly used for custom logic implementations in industry-leading programmable logic controllers (PLCs), such as the Schweitzer SEL real-time automation controller (RTAC). This transition will facilitate the deployment of the Latimer Control solution in real-world solar power plants, thereby advancing the technology towards commercialization.

14 SOLAR ENERGY↗
DOE OSTI2022

Resilient cooling through geothermal district energy system

Decarbonization and resilience to heat waves have recently become high priorities for building and district energy systems. Geothermal coupled district heating and cooling systems that operate a water loop near ground temperature gain increasing adoption to support decarbonization. In these systems, vapor-compression machines, distributed in the energy transfer stations, lift the temperature up or down to the needs of the particular building. In principle, these systems can provide low-power, free cooling from the geothermal bore field during heat waves when electricity is often scarce. However, the performance of such a resilience operation mode and its implication on the energy system configuration and the sizing of the bore field and HVAC equipment is not yet understood. Consequently, we are assessing their resilience, power use and design implications under a scenario of a heat wave on five working days during which chillers are switched off to reduce electrical consumption. Our analysis is based on high-fidelity, coupled dynamic models of district energy, building-side HVAC and actual control logic, with whole building energy simulation used to assess thermal conditions in a 2004 vintage multi-zone office building in Chicago, IL. The results show that relying only on waterside economizer cooling, the indoor thermal conditions can be maintained in a tolerable range for the majority of the building zones with half the electrical energy compared to standard chiller operation. Thermal comfort in the hottest zones can be further improved by oversizing the cooling coil. However, the waterside economizer has significant implications on the system configuration and sizing: The geothermal bore field needs to be sized about 30% larger than the upper limit of the range observed for conventional geothermal systems. Nevertheless, if a central chiller plant is added, the bore field can be downsized to the typical design range. The latter configuration still allows compressor-less cooling during the heat wave with peak power reduced by 60% compared to the standard design and chiller operation.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Evaluation of Real-Time Mitigation Techniques forCyber Security in IEC 61850 / IEC 62351Substations

This paper presents the design logic and implementation aspects of three potential real-time mitigation techniques capable of countering GOOSE-based attacks: (i) IEC 62351-compliant message authentication code (MAC) scheme, (ii) a semantics-enforced rule- based intrusion detection system (IDS), and (iii) a hybrid approach integrating both MAC verification and Intrusion Detection System (IDS). A comparative evaluation of these real-time mitigation approaches is conducted using a cyber-physical system(CPS) security testbed. The results show that the hybrid integration significantly enhances mitigation capability. Furthermore, the processing delays of all three methods remain within the strict delivery requirements of GOOSE communication. The study also identifies limitations that none of the techniques can fully address, highlighting areas for future work.

Liu, Chen-Ching [Virginia Polytechnic Inst. and St↗
DOE OSTI2022

Quantum computing in power systems

Electric power systems provide the backbone of modern industrial societies. Enabling scalable grid analytics is the keystone to successfully operating large transmission and distribution systems. However, today's power systems are suffering from ever-increasing computational burdens in sustaining the expanding communities and deep integration of renewable energy resources, as well as managing huge volumes of data accordingly. These unprecedented challenges call for transformative analytics to support the resilient operations of power systems. Recently, the explosive growth of quantum computing techniques has ignited new hopes of revolutionizing power system computations. Quantum computing harnesses quantum mechanisms to solve traditionally intractable computational problems, which may lead to ultra-scalable and efficient power grid analytics. This paper reviews the newly emerging application of quantum computing techniques in power systems. We present a comprehensive overview of existing quantum-engineered power analytics from different operation perspectives, including static analysis, transient analysis, stochastic analysis, optimization, stability, and control. We thoroughly discuss the related quantum algorithms, their benefits and limitations, hardware implementations, and recommended practices. We also review the quantum networking techniques to ensure secure communication of power systems in the quantum era. Finally, we discuss challenges and future research directions. This paper will hopefully stimulate increasing attention to the development of quantum-engineered smart grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Autonomous Hydrogen Fueling Station

This project “Autonomous Hydrogen Fueling Station” covered the autonomous refueling with both gaseous hydrogen and liquid hydrogen. The part on gaseous hydrogen focused on the development of an autonomous robotic fueling arm that would couple to a fuel cell engine for hydrogen refueling without guidance from the forklift operator and budget period. Research was also covered for the robotic fueling with a commercial vehicle. The second phase of the project created the baseline for an autonomous liquid hydrogen transfer system that would minimize boil off losses by operating at thermodynamically efficient state points. For the development of the robotic fueling arm, testing was conducted to establish a baseline measurement of the accuracy and repeatability of a human operator positioning a lift truck in front of a dispenser. The goal was to establish the range of motion required for an autonomous fueling mechanism to mate a hydrogen nozzle with a receptacle on a fuel cell system installed in a forklift. The final design comprised a selective compliance articulated robot arm (SCARA)-type mechanism with two arms for horizontal motion and a ball screw for vertical movement and color and LIDAR cameras were used for marker identification and proximity awareness to guide the robotic arm to its target receptacle. Initial tests resulted in 199 out of 200 successful attempts at autonomous coupling of the dispensing coupler and a fuel cell engine, without hydrogen. The dispenser prototype was modified to include tubing for both hydrogen fuel and air purge lines, but subsequent tests were confounded by the shoulder motor over current errors which limited the robot from getting to the fully inserted position to achieve a positive latch. Robotic hydrogen refueling was successfully demonstrated over 1.5 hours of testing, Plug completed 29 successful latches with an average number of 4 sequential latches before failure. However, a robot capable of placing the nozzle with more force is required for higher reliability. For budget period two, a small scale (10 kg / transfer) automated control system was designed that would operate valves to control pressure and flow of liquid nitrogen between a source and receiving tank with an aim to minimize boil off losses by operating at the most thermodynamically efficient state points. Control system logic flow and a P&ID were developed prior to system safety characterization via HAZOP. A control narrative and system state points were defined. Delays in approval for a change of project objective and procurement issues precluded the construction and test of the final prototype system.

08 HYDROGEN↗
DOE OSTI2022

Microfluidic In-Situ Spectrophotometric Approaches to Tackle Actinides Analysis in Multiple Oxidation States

The study and development of present and future processes for the treatment/recycling of spent nuclear fuels require many steps, from design in the laboratory to setting up on an industrial scale. In all of these steps, analysis and instrumentation are key points. For scientific reasons (small-scale studies, control of phenomena, etc.) but also with regard to minimizing costs, risks, and waste, such developments are increasingly carried out on milli- or microfluidic devices. The logic is the same for the chemical analyses associated with their follow-up and interpretation. Due to this, over the last few years, opto–microfluidic analysis devices adapted to the monitoring of different processes (dissolution, liquid–liquid extraction, precipitation, etc.) have been increasingly designed and developed. In this work, we prove that photonic lab-on-a-chip (PhLoC) technology is fully suitable for all actinides concentration monitoring along the plutonium uranium refining extraction (plutonium, uranium, reduction, extraction, or Purex) process. Several PhLoC microfluidic platforms were specifically designed and used in different nuclear research and development (R&D) laboratories, to tackle actinides analysis in multiple oxidation states even in mixtures. The detection limits reached (tens of µmol·L −1 ) are fully compliant with on-line process monitoring, whereas a range of analyzable concentrations of three orders of magnitude can be covered with less than 150 µL of analyte. Finally, this work confirms the possibility and the potential of coupling Raman and ultraviolet–visible (UV–Vis) spectroscopies at the microfluidic scale, opening the perspective of measuring very complex mixtures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Agentic traffic intelligence: Augmented human-in-the-loop scenario generation for microscopic traffic simulation

Traditional microscopic traffic simulation generation often relies on static datasets and manual design, limiting its ability to simulate complex conditions easily. This paper presents a novel framework, Agentic Traffic Intelligence, which combines human approval large language models (LLMs), the Real-Twin tool, and multi-agent systems to perform realistic microscopic traffic simulation scenario generation. The proposed framework incorporates human-in-the-loop (HIL) control, retrieval-augmented generation (RAG), and multi-agent control mechanisms. HIL mechanisms are used to guide multiple LLMs focused on attributes for microscopic simulation generation and to improve the interpretability and transparency of LLM execution for users. RAG enhances context extraction by dynamically integrating external knowledge sources for traffic scenario generation foundations. A multi-agent architecture with supervisory control coordinates the interaction of simulation components, including traffic simulators, control logic, and calibration tools. This enables the synthesis of simulation-ready scenarios that reflect dynamic demand profiles and behavior controls. Furthermore, the framework fuses multisource traffic data with unstructured context and supports iterative refinement through interactive user feedback. Validated through microscopic simulation using Simulation of Urban Mobility, the generated scenarios demonstrate high-fidelity network generation with inflow and turn movement and behavioral calibration, offering a robust and efficient tool for stress-testing and optimizing urban mobility systems.

Hierarchical multi-agent control↗