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DOE OSTI2025

Flow Enhanced Electrochemical Sensor Performance in Complex Salt Systems

To advance MSR MC&A practices, Argonne National Laboratory developed and optimized robust flow enhanced electrochemical sensors (FEES) and multielectrode array voltammetry sensors (MAVS) which provide accurate near-real time measurements of actinides in molten salts. Flow-enhanced electrochemical sensors are installed directly into MSR flow conduits for inline salt chemistry measurement, while MAVS are deployed in quiescent salt conditions enabling online species concentration determination in stationary salt vessels. This report summarizes efforts to improve electrochemical sensor technological readiness through (1) sensor testing in complex, high concentration molten salt systems to demonstrate low uncertainty actinide measurements in MSR-representative solutions and (2) demonstrations of sensor performance in challenging real-world conditions in collaboration with partner MSR institutions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Deep reinforcement learning control for co-optimizing energy consumption, thermal comfort, and indoor air quality in an office building

With the recent demand for decarbonization and energy efficiency, advanced HVAC control using Deep Reinforcement Learning (DRL) becomes a promising solution. Due to its flexible structures, DRL has been successful in energy reduction for many HVAC systems. However, only a few researches applied DRL agents to manage the entire central HVAC system and control multiple components in both the water loop and the air loop, owing to its complex system structures. Moreover, those researches have not extended their applications by incorporating the indoor air quality, especially both CO2 and PM2.5concentrations, on top of energy saving and thermal comfort, as achieving those objectives simultaneously can cause multiple control conflicts. What's more, DRL agents are usually trained on the simulation environment before deployment, so another challenge is to develop an accurate but relatively simple simulator. Therefore, we propose a DRL algorithm for a central HVAC system to co-optimize energy consumption, thermal comfort, indoor CO2 level, and indoor PM2.5 level in an office building. To train the controller, we also developed a hybrid simulator that decoupled the complex system into multiple simulation models, which are calibrated separately using laboratory test data. The hybrid simulator combined the dynamics of the HVAC system, the building envelope, as well as moisture, CO2, and particulate matter transfer. Three control algorithms (rule-based, MPC, and DRL) are developed, and their performances are evaluated on the hybrid simulator environment with a realistic scenario (i.e., with stochastic noises). The test results showed that, the DRL controller can save 21.4 % of energy compared to a rule-based controller, and has improved thermal comfort, reduced indoor CO2 concentration. The MPC controller showed an 18.6 % energy saving compared to the DRL controller, mainly due to savings from comfort and indoor air quality boundary violations caused by unmeasured disturbances, and it also highlights computational challenges in real-time control due to non-linear optimization. Finally, we provide the practical considerations for designing and implementing the DRL and MPC controllers based on their respective pros and cons.

Guo, Fangzhou↗

DOE OSTI2024

Unconventional quantum oscillations and evidence of nonparabolic electronic states in quasi-two-dimensional electron system at complex oxide interfaces

The simultaneous occurrence of electric-field controlled superconductivity and spin-orbit interaction makes two-dimensional electron systems (2DES) constructed from perovskite transition metal oxides promising candidates for the next generation of spintronics and quantum computing. It is, however, essential to understand the electronic bands thoroughly and verify the predicted electronic states experimentally in these 2DES to advance technological applications. Here, we present insights into the electronic states of the 2DES at oxide interfaces through comprehensive investigations of Shubnikov–de Haas oscillations in three different systems: EuO/KTaO 3 , LaAlO 3 /SrTiO 3 , and amorphous-LaAlO 3 /KTaO 3 . To accurately resolve these oscillations, we conducted transport measurements in high magnetic fields up to 60 T and low temperatures down to 100 mK. For 2D confined electrons at these interfaces, we observed a progressive increase of oscillations frequency and cyclotron mass with the magnetic field. We interpret these universal and intriguing findings by considering the existence of nontrivial electronic bands, for which the 𝐸−𝑘 dispersion incorporates both linear and parabolic relations. In addition to providing experimental evidence for nonparabolic electronic states in KTaO 3 and SrTiO 3 2DES, the unconventional oscillations presented in this study establish a paradigm for quantum oscillations in 2DES based on perovskite transition metal oxides, where the oscillation frequencies in 1/𝐵 exhibit quadratic dependence on the magnetic field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Process for ultra-sensitive quantification of target analytes in complex biological systems

Antibody-free processes are disclosed that provide accurate quantification of a wide variety of low-abundance target analytes in complex samples. The processes can employ high-pressure, high-resolution chromatographic separations for analyte enrichment. Intelligent selection of target fractions may be performed via on-line Selected Reaction Monitoring (SRM) or off-line rapid screening of internal standards. Quantification may be performed on individual or multiplexed fractions. Applications include analyses of, e.g., very low abundance proteins or candidate biomarkers in plasma, cell, or tissue samples without the need for affinity-specific reagents.

Shi, Tujin↗

DOE OSTI2025

2025 ASMS Investigation of the Collision-Induced Dissociation Mechanism of Protonated TODGA with IRIS

Title (20 words): Investigation of the Collision-Induced Dissociation Mechanism of Protonated TODGA with IRIS Introduction (120 words): One of the challenges facing wide-spread adoption of nuclear power is the development of efficient separation processes for used nuclear fuel. The molecules in separation processes are subjected to an extreme environment due to the high radiation fields from the used fuel and highly acidic media used for fuel dissolution, which results in significant molecular degradation, leading to reduced process efficiency. These degradation products must be identified and studied so mitigation strategies can be developed to maintain process efficiency. However, complex systems can have many degradation products, complicating identification. Untargeted analysis tools could be used to understand radiation chemistry in complex systems. However, this would necessitate improved understanding of the gas-phase fragmentation mechanisms of fuel cycle molecules like tetraoctyldiglycolamide (TODGA). Methods (120 words): The gas-phase fragmentation of protonated TODGA was investigated using collision-induced dissociation (CID), resonance ejection, and infrared ion spectroscopy (IRIS). CID and resonance ejection experiments were conducted using a Bruker Daltonics (Bremen, Gemany) SolariX XR fourier transform ion cyclotron resonance (FT-ICR) mass spectrometer. IRIS spectra of protonated TODGA and its two CID fragmentation products were measured using a modified Bruker amaZon Speed ETD 3D quadrupole ion trap mass spectrometer coupled to the Free Electron Lasers for Infrared eXperiments (FELIX) free electron laser. Measured spectra were compared with density functional theory (DFT) calculations using the Gaussian 16, Revision C.02 software package with the ?B97X-D functional and def2-TZVPP basis sets. Candidate structures were generated using the CREST 3.0 conformational sampling software tool. Preliminary Data (300 words): Collision-induced dissociation of protonated TODGA ([C36H73N2O3]+, m/z=581.562) results two fragment ions, one at m/z=340.285 assigned as [C20H38NO3]+ and the other at m/z=312.290, assigned as [C19H38NO2]+. Based on the assigned formula and the structure of protonated TODGA, the fragment at m/z=340.285 is likely formed from elimination of neutral dioctylamine. Comparison of the IRIS spectrum of m/z=340.285 with DFT predictions suggests it contains a ring structure, and is assigned as N-octyl-N-(6-oxo-1,4-dioxan-2-ylidene)octan-1-aminium. Based on this structure and the structure of protonated TODGA, we hypothesize this fragment formed from elimination of neutral dioctylamine followed by a ring closure mechanism. Comparison of the IRIS spectrum of the fragment at m/z=312.290 with DFT predictions also indicated the presence of a ring structure, assigned as N-(1,3-dioxolan-4-ylidene)-N-octyloctan-1-aminium. This product could be formed from elimination of carbon monoxide from the ring of m/z=340.285 as a sequential fragmentation or formed directly from protonated TODGA via elimination of neutral N,N-dioctylformamide followed by a ring closure. Resonance ejection experiments where m/z=340 was continuously ejected from the IRC cell showed no decrease in intensity of m/z=312.290 across several collision energies, suggesting that the later, direct formation mechanism, dominates. The location of the ionizing proton in protonated TODGA is important for modeling the fragmentation mechanisms. DFT calculations suggested that the position of bands involving the coupled vibrations of the amide C—N and C=O bonds in TODGA are the most sensitive to proton location. Evaluation of the IRIS spectrum of protonated TODGA suggests that the ionizing proton is located between the two amid oxygens. This protonation location was calculated to lie approximately 30 kJ/mol lower in energy than the next lowest energy location, with the proton located solely on one of the amide oxygens. Novel aspect (20 words): Infrared ion spectroscopy combined with resonance ejection experiments and density functional theory to probe the collision-induced dissociation mechanism of tetraoctyldiglycolamide.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

DOE OSTI2021

Guest-Host Interactions in Clathrate Hydrates: Benchmark MP2 and CCSD(T)/CBS Binding Energies of CH4, CO2 and H2S in (H2O)20 Cages

We present benchmark binding energies of naturally occurring gas molecules CH4, CO2, and H2S in the small cage, namely the pentagonal dodecahedron (512) (H2O)20, which is one of the constituent cages of the 3 major lattices (structures I, II and H) of clathrate hydrates. These weak interactions require higher levels of electron correlation and converge slowly with increasing basis set to the Complete Basis Set (CBS) limit, necessitating the use of large basis sets up to the augcc- pV5Z and subsequent correction for Basis Set Superposition Error (BSSE). For the host hollow (H2O)20 cages we have identified a most stable isomer with binding energy of -200.8 ± 2.1 kcal/mol at the CCSD(T)/CBS limit (-199.2 ± 0.5 kcal/mol at the MP2/CBS limit). Additionally, we report converged second order Moller-Plesset (MP2) CBS binding energies for the encapsulation of guests in the (H2O)20 cage of -4.3 ± 0.1 for CH4@(H2O)20, -6.6 ± 0.1 for CO2@(H2O)20 and -8.5 ± 0.1 kcal/mol for H2S@(H2O)20, respectively. For CH4@(H2O)20, exhibiting the weakest encapsulation affinity among the three, we report CCSD(T)/aug-cc-pVTZ binding energies and, based on them, a CCSD(T)/CBS estimate of -4.75 ± 0.1 kcal/mol. To the best of our knowledge, the CCSD(T)/aug-cc-pVTZ calculation for CH4@(H2O)20 is the largest one reported to date (168 valence electrons, 1978 basis functions and the correlation of 84 doubly occupied and 1873 virtual orbitals) and required a scalable implementation of the (T) module on 6144 nodes (350208 cores) of the “Cori” supercomputer at the National Energy Research Supercomputing Center (NERSC) for a total execution time of 195 minutes (for the (T) part). These efficient scalable implementations of highly correlated methods offer the capability to obtain long-lasting benchmarks of intermolecular interactions in complex systems. They also provide a path towards parametrizing classical potentials needed to study the dynamical and transport properties in these complex systems as well as assess the accuracy of lower scaling electronic structure methods such as Density Functional Theory (DFT) and MP2 including its spin-biased variants.

Heindel, Joseph↗

DOE OSTI2024

Visualizing an Exascale Data Center Digital Twin: Considerations, Challenges and Opportunities

Digital twins are an excellent tool to model, visualize, and simulate complex systems, to understand and optimize their operation. In this work, we present the technical challenges of real-time visualization of a digital twin of the Frontier supercomputer.We show the initial prototype and current state of the twin and highlight technical design challenges of visualizing such a large High Performance Computing (HPC) system. The goal is to understand the use of augmented reality as a primary way to extract information and collaborate on digital twins of complex systems. This leverages the spatio-temporal aspect of a 3D representation of a digital twin, with the ability to view historical and real-time telemetry, triggering simulations of a system state and viewing the results, which can be augmented via dashboards for details. Finally, we discuss considerations and opportunities for augmented reality of digital twins of large-scale, parallel computers.

Maiterth, Matthias↗

DOE OSTI2021

Development of an Innovative Inspection Tool for Superheater Tubes in Fossil Fuel Power Plants

Fossil fuel power plants are complex systems containing multiple components that require periodic health monitoring. Failures in these systems can lead to increased downtime for the plant, reduction of power, and significant cost for repairs. Inspections of the plant’s superheater tubes are typically manual, laborious, and extremely time-consuming. This is due to their small diameter size (between 1.3 and 7.6 cm) and the coiled structure of the tubing. In addition, the tubes are often stacked close to each other, limiting access for external inspection. This paper presents the development and testing of an electrically powered pipe crawler that can navigate inside 5 cm diameter tubes and provide an assessment of their health. The crawler utilizes peristaltic motion within the tubes via interconnected modules for gripping and extending. The modular nature of the system allows it to traverse through straight sections and multiple 90° and 180° bends. Additional modules in the system include an ultrasonic sensor for tube thickness measurements, as well as environmental sensors, a light detecting and ranging (LiDAR) sensor, and camera. Furthermore, these modules utilize a gear system that allows for 360° rotation and provides a means to inspect the entire internal circumference of the tubes.

36 MATERIALS SCIENCE↗

DOE OSTI2024

ezAlign: A Tool for Converting Coarse-Grained Molecular Dynamics Structures to Atomistic Resolution for Multiscale Modeling

Soft condensed matter is challenging to study due to the vast time and length scales that are necessary to accurately represent complex systems and capture their underlying physics. Multiscale simulations are necessary to study processes that have disparate time and/or length scales, which abound throughout biology and other complex systems. Herein we present ezAlign, an open-source software for converting coarse-grained molecular dynamics structures to atomistic representation, allowing multiscale modeling of biomolecular systems. The ezAlign v1.1 software package is publicly available for download at github.com/LLNL/ezAlign. Its underlying methodology is based on a simple alignment of an atomistic template molecule, followed by position-restraint energy minimization, which forces the atomistic molecule to adopt a conformation consistent with the coarse-grained molecule. The molecules are then combined, solvated, minimized, and equilibrated with position restraints. Validation of the process was conducted on a pure POPC membrane and compared with other popular methods to construct atomistic membranes. Additional examples, including surfactant self-assembly, membrane proteins, and more complex bacterial and human plasma membrane models, are also presented. By providing these examples, parameter files, code, and an easy-to-follow recipe to add new molecules, this work will aid future multiscale modeling efforts.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Focus on monitoring and control of complex supply systems

The ongoing rapid transformation of our energy supply challenges the operation and stability of electric power grids and other supply networks. This focus issue comprises new ideas and concepts in the monitoring and control of complex networks to address these challenges.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Advocating Feedback Control for Human-Earth System Applications

This paper proposes a feedback control perspective for Human-Earth Systems (HESs) which essentially are complex systems that capture the interactions between humans and nature. Recent attention in HES research has been directed towards devising strategies for climate change mitigation and adaptation, aimed at achieving environmental and societal objectives. However, existing approaches heavily rely on HES models, which inherently suffer from inaccuracies due to the complexity of the system. Moreover, overly detailed models often prove impractical for optimization tasks. We propose a framework inheriting from feedback control strategies the robustness against model errors, because inaccuracies are mitigated using measurements retrieved from the field. The framework comprises two nested control loops. The outer loop computes the optimal inputs to the HES, which are then implemented by actuators controlled in the inner loop. Potential fields of applications are also identified and a numerical example is provided.

biological system modeling↗

DOE OSTI2021

Hypernetwork Science: From Multidimensional Networks to Computational Topology

As data structures and mathematical objects used for complex systems modeling, hypergraphs sit nicely poised between on the one hand the world of network models, and on the other that of higher-order mathematical abstractions from algebra, lattice theory, and topology. They are able to represent complex systems interactions more faithfully than graphs and networks, while also being some of the simplest classes of systems representing topological structures as collections of multidimensional objects connected in a particular pattern. In this paper we discuss the role of (undirected) hypergraphs in the science of complex networks, and provide a mathematical overview of the core concepts needed for hypernetwork modeling, including duality and the relationship to bicolored graphs, quantitative adjacency and incidence, the nature of walks in hypergraphs, and available topological relationships and properties. We close with a brief discussion of two example applications: biomedical databases for disease analysis, and domain-name system (DNS) analysis of cyber data.

Joslyn, Cliff A.↗

DOE OSTI2022

Application of Margin-Based Methods to Assess System Health

Health management of complex systems such as nuclear power plants is an essential task to guarantee system reliability. This task can be greatly enhanced by constantly monitoring asset status and performances and process such data (through anomaly detection, diagnostic, and prognostic computational algorithms) to identify asset degradation trends and faulty states. While such information and data are typically available for many of the assets, they are not propagated from the asset to the system level in order to identify the most critical assets and prioritize maintenance and surveillance activities. The main reason is driven by the fact that current reliability modeling techniques are inadequate to process such information/data. This is due to the nature of these techniques which are based on the concept of failure rate/probability that do not serve an operational context where quantitative asset health information is available. Simply stated, current reliability techniques serve a run-to-failure operational setting and not a predictive maintenance one where the goal is to perform maintenance and surveillance activities only when they are needed based on asset health. The risk informed asset management (RIAM) project is focusing on the development of a different kind of reliability modeling techniques designed to adequately serve a predictive operational setting. Such reliability techniques move aways from a failure rate/probability to a margin-based mindset where margin is here used as a metric to quantify asset health based only on current and past operational experience of the asset under consideration. In addition, margin-based reliability techniques are able to propagate asset health information from the component to system level and provide importance measure to each asset. This report summarizes a recent activity performed in collaboration with plant modernization pathway designed to integrate monitoring data into margin-based reliability models. Such activity focuses on a specific system of an existing nuclear power plant where large amount of historic monitoring data is used to monitor asset and system health.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Using AI Simulations to Dynamically Model Multi-agent Multi-team Energy Systems

The complexity of energy systems is well known as they are complex and intricate systems. As a result, many extant studies have used many simplifications or generalizations that do not accurately reflect the nature of this complex system. In particular, most HVAC systems are modeled as a single unit, or several large units, rather than as a hierarchical composite (e.g., as a floor rather than as a collection of disparate rooms). The net result of this is that the simulations are too generic to perform meaningful analysis, machine learning, or integrated simulation. We propose using a multi-agent multi-team strategic simulations framework called SiMAMT to better define, model, simulate, and learn the HVAC environment. SiMAMT allows us to create distinct models for each type of room, hierarchically aggregate them into units (like floors, or sections), and then into larger sets (like buildings or a campus), and then perform a simulation that interacts with each sub-element individually, the teams of sub-elements collectively, and the entire set in aggregation. Further, and most importantly, we additionally model another ‘team’ within the simulation framework - the users of the systems. Again, each individual is modeled distinctly, aggregated into sub-sets, then collected into large sets. Each user, or agent, is performing on their own but with respect to the larger team goals. This provides a simulation that has a much higher model fidelity and more applicable results that match the real-world.

Franklin, D. Michael↗

DOE OSTI2021

Transforming a Simple Structure Model to Represent a Complex Dynamic System with Unknown Boundary Restraints

Imposing a boundary condition on a structure can significantly alter its dynamic properties. However, sometimes the specifics of the new boundary conditions are not known. When the effects of a boundary condition are uncertain or there is not enough information, engineers need to excite the complex structure to obtain these modified properties. In order to experimentally obtain the new properties, engineers need multiple experiments and many outputs for interpolation in order to sufficiently represent the entire structure. In this study, the researchers attached a stinger to a cantilever beam, acting as a new transverse restraint of unknown properties. This paper presents a conversion expression that predicts the dynamic behavior of any point in the system with the new boundary condition. This expression relies only on one impact hammer experiment with one output and the model of the stinger-free cantilever beam, referred to as the simple structure. Researchers estimated the Transfer Function (TRF) of the beam and compared it with an experimentally measured TRF to validate the method. The mean absolute error of the estimated TRF compared to the experimental TRF is 1.99 dB. This demonstrates the use of the proposed method for estimating unmeasured TRFs in a system with an uncertain boundary condition using a single input, single output (SISO) test and a model of the simple structure.

42 ENGINEERING↗

DOE OSTI2025

Extracted Water Induces Concentration Fluctuations in Model Ternary Liquid–Liquid Extraction System

Organic phase aggregation and phase splitting are two important (and connected) phenomena in liquid–liquid extraction of metal ions. Previously, we demonstrated how structure in binary mixtures of extractant and diluent originates from concentration fluctuations associated with the so-called “third-phase formation” liquid–liquid phase instability. For more complex systems, we sought to understand how extracted aqueous components affect these concentration fluctuations. Here, in this study, we use small-angle X-ray scattering and molecular dynamics simulations to investigate organic phase structural changes upon contact with water in a model ternary system of water/alkane/extractant. Critical exponents were determined from scattering with temperature variation and were consistent with mean field values. Then, by controlling the water content in the organic phase through direct dissolution of fixed quantities at constant temperature, we relate the observed increase in the fluctuation length scale to changes to the spinodal temperature of the third-phase formation phase boundary. We find a roughly linear relationship between water concentration and the spinodal temperature and a similar slope in that relationship for different linear alkane diluents. This suggests that the mechanism by which water extraction impacts the organic phase structure is to enhance concentration fluctuations through the introduction of additional polar extractant-water complexes, which increases the spinodal temperature and thereby decreases the reduced temperature, i.e., the distance to the instability. This explanation for how solutes induce aggregation in liquid–liquid extraction organic phases may extend to more complex systems, explaining the large increases in correlation lengths reported under high acid and metal loading.

Bonnett, Brittany L. [Argonne National Laboratory ↗

DOE OSTI2023

Accelerating Scientific Simulations with Bi-Fidelity Weighted Transfer Learning

High-fidelity modeling is an essential design tool for many engineering applications. However, for complex systems, computational cost can be a limiting factor. Analyzing parameter sensitivity, uncertainty quantification, and design optimization require many model evaluations. Surrogate models are often used to develop the relationship between model parameters and quantities of interest. However, in the case of complex systems, surrogate models require several degrees of freedom and, thus, a large number of data points to determine the correct dependencies. For many applications, this may be prohibitively expensive. The reduction of computational requirements can be achieved by leveraging low-fidelity models. Low-fidelity models represent the system at a coarser resolution with the advantage of computational efficiency. Therefore, a bi-fidelity modeling paradigm, which augments the accuracy of a low-fidelity model in a computationally efficient manner by invoking limited runs of a high-fidelity model, can be leveraged to sufficiently balance the accuracy and computational requirements. In this work, a bi-fidelity weighted transfer learning method using neural networks was applied to a computational fluid dynamics heat transfer modeling problem. The transfer learning advantage was investigated as a function of hyperparameters. Our main finding is that the use of a bi-fidelity modeling paradigm achieves accuracy close to that of a high-fidelity Gaussian process model while significantly reducing computational cost. The bi-fidelity model achieves comparable performance with 90 high-fidelity samples-that is, 60% less than the samples needed to achieve similar accuracy without the use of bi-fidelity modeling,

Borowiec, Katarzyna↗

DOE OSTI2022

Modifying Ionogel Solid-Electrolytes for Complex Electrochemical Systems

The solution processability of ionogel solid electrolytes has recently garnered attention in the Li-ion battery community as a means to address the interface and fabrication issues commonly associated with most solid electrolytes. However, the trapped ionic liquid (ILE) component has hindered the electrochemical performance. In this report we present a process to tune the properties by replacing the ILE in a silica-based ionogel after fabrication with a liquid component befitting the desired application. Electrochemical cycling under various conditions showcases gels containing different liquid components incorporated into LiFePO4 (LFP)/gel/Li cells: high power (455 W kg –1 at a 1 C discharge) systems using carbonates, low temperatures (-40 °C) using ethers, or high temperatures (100 °C) using ionic liquids. Fabrication of additive-manufactured cells utilizing the exchanged carbonate-based system is demonstrated in a planar LFP/Li 4 Ti 5 O 12 (LTO) system, where a marked improvement over an ionogel is found in terms of rate capability, capacity, and cycle stability (118 vs 41 mA h g –1 at C/4). This process represents a promising route to create a separator-less cell, potentially in complex architectures, where the electrolyte properties can be facilely tuned to meet the required conditions for a wide range of battery chemistries while maintaining a uniform electrolyte access throughout cast electrodes.

25 ENERGY STORAGE↗