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DOE OSTI2022

Impact of cyber attacks on distributed compressive sensing based state estimation in power distribution grids

Modern power distribution grids suffer from multiple vulnerabilities due to the tight integration between the physical system and the cyber infrastructure. Sophisticated and malicious cyber attacks continue to adversely impact the grid operation leading to performance degradation, service interruption, and grid failure. State estimation plays an essential role in grid monitoring and advancing cyber-attack situational awareness. In this regard, this paper first proposes a distributed compressive sensing (CS) state estimation approach for an unobservable distribution grid. Further, the proposed distributed CS approach divides the distribution grid into sub-areas to perform local state estimation. Then an alternating direction method of multipliers (ADMM) based iterative information exchange among neighboring areas is employed to complete the estimation process. In this estimation process, the impact of loss of measurement data, false data injection (FDI), replay, and neighborhood cyber-attacks is analyzed. Extensive simulations are performed on the IEEE 37-bus and IEEE 123-bus standard networks to demonstrate the algorithm’s robustness to the aforementioned cyber-attacks. A quantitative analysis of computational complexity and simulation time of the distributed CS based approach is also presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Atomic-scale tuned interface of nickel-rich cathode for enhanced electrochemical performance in lithium-ion batteries

The Ni-rich layered LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC6 22 ) is one promising cathode for lithium-ion batteries (LIBs), but suffers from poor cycling stability under high cutoff potentials. The performance degradation was reflected as capacity fading and voltage drop, having their roots in instable interface of NMC622. Aimed at improving interfacial stability, in this study, we deposited nanoscale ZrO 2 coatings conformally over NMC622 cathodes using atomic layer deposition (ALD). We found that, under a high cutoff voltage (4.5 V), the ALD ZrO 2 coatings evidently improved the performance of NMC622 cathode, showing better cyclability and higher sustainable capacity. In addition, the ALD coatings dramatically boosted the rate capability of NMC622. All these compelling performance results are ascribed to the atomic-scale tunable ZrO 2 coatings via ALD, which create stable interface and thereby inhibit unfavorable evolutions. In the study, we utilize a suite of characterization tools and various analyses to clarify the effects of ALD ZrO 2 coatings. This study will be helpful for improving the performance of nickel-rich cathodes via interfacial engineering using ALD.

25 ENERGY STORAGE↗

DOE OSTI2021

Towards Learning-Based Architectures for Sensor Impact Evaluation in Building Controls

Advanced control algorithms for building systems are known to have significant potential in reducing energy consumption while optimizing thermal comfort. The success of such algorithms is critically contingent on several different types of sensor systems, which are in turn, used for continuous monitoring, identification and estimation of several important building states, such as temperatures, humidity, air quality, power consumption and occupancy status. Nonidealities in any of these sensors can lead to significant performance degradation of the control functionalities, and may lead to unwanted sub-optimal building operation. In this paper, we provide a simulation example with a high-fidelity building model, for a particular use-case of advanced optimization-based control in buildings, i.e., occupancy-based controls. We show how imperfections in occupancy sensing can offset performance. Subsequently, we discuss a novel learning-based architecture to efficiently evaluate the impact of sensor nonidealities for building systems, in context of advanced control algorithms.

Bhattacharya, Saptarshi↗

DOE OSTI2026

Radiation damage in tungsten under high-energy He-ion irradiation

Tungsten (W) is a primary candidate for plasma-facing components (PFCs) in fusion reactors and hybrid fission-fusion reactors. However, W suffers from severe microstructural damage under Helium (He) ion irradiation in operation conditions. Key irradiation parameters, including incident ion energy, fluence, and irradiation temperature, are known to determine the formation of He bubbles and dislocation loops, which ultimately lead to the degradation of mechanical properties, such as radiation hardening and ductile-to-brittle transition temperature (DBTT) shifts. Various strategies, for instance, interface engineering and alloying, have been developed to enhance He irradiation tolerance in W to address these challenges. Studies in the recent two decades have enhanced the understanding of the underlying mechanisms that drive defect evolution and mechanical performance degradation, thereby offering more insights into the design of more resilient W-based materials for extreme environments.

Liu, Yinghang [Purdue University]↗

DOE OSTI2025

Sulfonated Diels–Alder Poly(Phenylene)s in Membrane Electrode Assemblies for Fuel Cells

The transition to environmentally sustainable materials in fuel cells requires alternatives to persistent polyfluoroalkyl substances (PFAS) like Nafion. This study investigates the performance-limiting factors of membrane electrode assemblies (MEAs) utilizing sulfonated Diels–Alder poly(phenylene)s (sDAPPs) as PFAS-free polymer electrolytes. Among the configurations evaluated, the greatest performance loss occurred when sDAPP is used as the cathode binder, primarily due to phenyl group adsorption on catalyst surfaces, which reduces oxygen reduction reaction activity and impedes oxygen transport. Additional performance degradation arises from membrane-electrode interfacial incompatibility and insufficient ionomer hydrophobicity. By addressing ionomer adsorption and improving interfacial contact, an sDAPP-based cathode achieved a current density of 1.57 A cm −2 at 0.6 V under fully humidified H 2 /air conditions at 80 °C and 150 kPa abs . These results offer key insights for advancing high-performance, PFAS-free fuel cell technologies.

08 HYDROGEN↗

DOE OSTI2024

Probing the evolution of fault properties during the seismic cycle with deep learning

We use seismic waves that pass through the hypocentral region of the 2016 M6.5 Norcia earthquake together with Deep Learning (DL) to distinguish between foreshocks, aftershocks and time-to-failure (TTF). Binary and N-class models defined by TTF correctly identify seismograms in test with > 90% accuracy. We use raw seismic records as input to a 7 layer CNN model to perform the classification. Here we show that DL models successfully distinguish seismic waves pre/post mainshock in accord with lab and theoretical expectations of progressive changes in crack density prior to abrupt change at failure and gradual postseismic recovery. Performance is lower for band-pass filtered seismograms (below 10 Hz) suggesting that DL models learn from the evolution of subtle changes in elastic wave attenuation. Tests to verify that our results indeed provide a proxy for fault properties included DL models trained with the wrong mainshock time and those using seismic waves far from the Norcia mainshock; both show degraded performance. Our results demonstrate that DL models have the potential to track the evolution of fault zone properties during the seismic cycle. If this result is generalizable it could improve earthquake early warning and seismic hazard analysis.

58 GEOSCIENCES↗

DOE OSTI2025

Approaching hydro-equivalent ignition in laser direct-drive via target design optimization using novel statistical modeling

Laser direct-drive offers significant advantages in terms of target simplicity, improved energy coupling, and large fuel masses over indirect drive. However, performance degradations from hydrodynamic and laser-plasma instabilities seeded and driven by the direct illumination pose limitations on the parameter space available for achieving ignition. In this paper, new design improvements are identified to forge a path forward for a hydro-equivalent ignition demonstration. The first is related to a new formulation of the statistical model (SM) used to accurately predict target performance directly from input parameters such as laser pulse shape and target specifications. This new SM formulation provides direct guidance on target dimensions and laser beam-to-target radius to achieve the highest fusion yield on the OMEGA laser. The second improvement comes from cooling the deuterium–tritium (DT) ice layer below the triple point right before shot time leading to lower DT vapor densities and higher convergence. Guided by these design improvements, a Bayesian optimization algorithm was used to design an implosion that is predicted to closely approach a Lawson triple product that hydrodynamically scales to ignition if equivalent laser–target coupling is achieved at laser energies typical of the National Ignition Facility.

Deuterium↗

DOE OSTI2021

High performance protonic ceramic fuel cell systems for distributed power generation

The technology landscape around distributed generation continues to evolve in response to increasing demand for high-efficiency, low-emission, low-cost power generation. While emerging distributed power technologies, such as solid oxide fuel cells (SOFCs), continue to advance, they still face challenges due to their high capital costs, and shorter lifetimes that typically arise from electrochemical stack performance degradation at high operating temperatures (>750 °C). Recent advancements in protonic ceramic fuel cells (PCFCs) offer the potential to mitigate drawbacks of their higher temperature SOFC counterparts by enabling lower operating temperatures (550 °C–600 °C) with acceptable power densities. Here the present work leverages the recent progress in protonic ceramic cell and stack technology development to generate viable system configurations and evaluate the energetic performance potential of PCFC-based systems for stationary power generation. Process system engineering of two water-neutral system concepts, which provide 25 kW of electric power and process hot water, are presented and evaluated through sensitivity studies. Stack design parameters are altered and used to gauge the effect on system performance characteristics, including fuel cell stack and balance-of-plant sizing requirements, and electric and cogeneration efficiencies. The study finds that the potentially high per-pass fuel utilization capability of PCFC stacks could enable unprecedented electric efficiencies approaching 70% without hybridization with other prime movers.

25 ENERGY STORAGE↗

DOE OSTI2026

Comparison of the Effects of Bipolar Membrane Preparation Conditions on the Mechanical Durability and Electrochemical Performance for Electrodialysis Applications

Bipolar membranes (BPMs) are enabling materials for electrochemical conversion technologies such as water electrolysis, fuel cells, CO 2 electrolysis, and electrodialysis (ED) for direct air/ocean capture of CO 2 . However, current BPM durability can suffer from chemical, mechanical, and performance degradation when operated at high current density (ion flux) and physical scale. Therefore, this limits its adoption in a wider applications space. BPMs have several known degradation mechanisms, including chemical breakdown of ion-exchange polymers, loss of junction adhesion, or physical breakdown due to shearing force and pressure swings in an electrodialysis cell. To assess the electrochemical stability and mechanical durability of BPMs under operational conditions, we investigated how fabrication conditions (including preconditioning, hot-pressing temperature and pressure, and catalyst loading) impact the adhesion of custom-made BPMs. T-peel studies were performed ex situ to quantify adhesive forces of BPMs, and bipolar membrane electrodialysis (BPMED) experiments were performed to assess the electrochemical performance of the corresponding BPMs. The results of this systematic comparison indicate that hydration and heated pressing create improved adhesion during the fabrication of BPMs, and BPMED testing shows that these fabrication techniques are not detrimental to the electrochemical performance of the BPMs.

36 MATERIALS SCIENCE↗

DOE OSTI2020

In Situ Reliability Investigation of All-Vanadium Redox Flow Batteries by a Stable Reference Electrode

Redox flow batteries (RFBs) have been studied over the past several decades as a promising candidate for stationary energy storage applications. It is therefore important to understand the reliability of RFBs and the mechanisms that cause degradation with time. Contributions from individual electrodes (cathode or anode) are difficult to separate especially for long-term cycle testing, due to the lack of a stable reference electrode. In our work, the reliability and degradation mechanisms of an all-vanadium RFB were investigated by a stable reference electrode based on the dynamic hydrogen electrode (DHE). With factor exploration and design optimization, the newly developed DHE reference electrode demonstrated high accuracy and long-term stability that enables in-situ monitoring of individual electrode signals (potentials and impedances) over hundreds of cycles in a vanadium RFB. This approach enables the full cell degradation to be separated and the degradation attributed to contributions from the cathode and anode. The cathode and anode were found to play quite different roles in the increase in overpotential of the vanadium RFB during long-term cycling. The anode reaction limited both the charge and discharge capacity over 100 cycles. In addition, the negative side also appeared to be the rate limiting factor throughout cycling as determined by EIS measurement. The cathode contributed to the performance degradation as cycling exceeded 50 cycles.

Huang, Qian↗

DOE OSTI2020

Enabling Stable Cycling of 4.2 V High-Voltage All-Solid-State Batteries with PEO-Based Solid Electrolyte

Poly(ethylene oxide) (PEO)-based solid electrolytes are expected to be exploited in solid-state batteries with high safety. Its narrow electrochemical window, however, limits the potential for high voltage and high energy density applications. In this paper, the electrochemical oxidation behavior of PEO and the failure mechanisms of LiCoO 2 -PEO solid-state batteries are studied. It is found that although for pure PEO it starts to oxidize at a voltage of above 3.9 V versus Li/Li + , the decomposition products have appropriate Li + conductivity that unexpectedly form a relatively stable cathode electrolyte interphase (CEI) layer at the PEO and electrode interface. The performance degradation of the LiCoO 2 -PEO battery originates from the strong oxidizing ability of LiCoO 2 after delithiation at high voltages, which accelerates the decomposition of PEO and drives the self-oxygen-release of LiCoO 2 , leading to the unceasing growth of CEI and the destruction of the LiCoO 2 surface. When LiCoO 2 is well coated or a stable cathode LiMn 0.7 Fe 0.3 PO 4 is used, a substantially improved electrochemical performance can be achieved, with 88.6% capacity retention after 50 cycles for Li 1.4 Al 0.4 Ti 1.6 (PO 4 ) 3 coated LiCoO 2 and 90.3% capacity retention after 100 cycles for LiMn 0.7 Fe 0.3 PO 4 . The results suggest that, when paired with stable cathodes, the PEO-based solid polymer electrolytes could be compatible with high voltage operation.

25 ENERGY STORAGE↗

DOE OSTI2022

The straw tracking detector for the Fermilab Muon g-2 Experiment

The Muon g-2 Experiment at Fermilab uses a gaseous straw tracking detector to make detailed measurements of the stored muon beam profile, which are essential for the experiment to achieve its uncertainty goals. Positrons from muon decays spiral inward and pass through the tracking detector before striking an electromagnetic calorimeter. The tracking detector is therefore located inside the vacuum chamber in a region where the magnetic field is large and non-uniform. As such, the tracking detector must have a low leak rate to maintain a high-quality vacuum, must be non-magnetic so as not to perturb the magnetic field and, to minimize energy loss, must have a low radiation length. The performance of the tracking detector has met or surpassed the design requirements, with adequate electronic noise levels, an average straw hit resolution of (110 ± 20) μm, a detection efficiency of 97% or higher, and no performance degradation or signs of aging. The tracking detector's measurements result in an otherwise unachievable understanding of the muon's beam motion, particularly at early times in the experiment's measurement period when there are a significantly greater number of muons decaying. This is vital to the statistical power of the experiment, as well as facilitating the precise extraction of several systematic corrections and uncertainties. This paper describes the design, construction, testing, commissioning, and performance of the tracking detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Constrained Local Approximate Ideal Restriction for Advection-Diffusion Problems

Herein this paper focuses on developing a reduction-based algebraic multigrid (AMG) method that is suitable for solving general (non)symmetric linear systems and is naturally robust from pure advection to pure diffusion. Initial motivation comes from a new reduction-based AMG approach, $\ell \text{AIR}$ (local approximate ideal restriction), that was developed for solving advection-dominated problems. Though this new solver is very effective in the advection-dominated regime, its performance degrades in cases where diffusion becomes dominant. This is consistent with the fact that in general, reduction-based AMG methods tend to suffer from growth in complexity and/or convergence rates as the problem size is increased, especially for diffusion-dominated problems in two or three dimensions. Motivated by the success of $\ell \text{AIR}$ in the advective regime, our aim in this paper is to generalize the AIR framework with the goal of improving the performance of the solver in diffusion-dominated regimes. To do so, we propose a novel way to combine mode constraints as used commonly in energy-minimization AMG methods with the local approximation of ideal operators used in $\ell \text{AIR}$. The resulting constrained $\ell \text{AIR}$ algorithm is able to achieve fast scalable convergence on advective and diffusive problems. In addition, it is able to achieve standard low complexity hierarchies in the diffusive regime through aggressive coarsening, something that was previously difficult for reduction-based methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Assessment of CTF for Steady-state and Transient Post-CHF Conditions in Support of Time-at-Temperature Modeling Applications

The US nuclear industry is exploring options to improve operational economics and uprate the current fleet of light-water reactors by investigating transitioning to cladding performance–based safety criteria as opposed to the current limit, which requires complete avoidance of critical heat flux (CHF)/dryout. Past experience has shown that not all events leading to a dryout are severe enough to cause fuel performance degradation. Allowing temporary dryout of the fuel—that is, using a time-at-temperature (TaT) strategy—could allow for economic improvements via large power uprates and enhanced operational flexibility for current plants without compromising fuel integrity. To support this effort, the US Department of Energy is executing a comprehensive program that includes generating cladding material data under TaT conditions, developing new mechanistic models, and demonstrating modeling and simulation capabilities for transients of interest. This paper presents work performed to assess the CTF thermal-hydraulics subchannel code. CTF is a package used in the VERA core simulator, which will ultimately be used for TaT analysis. CTF will provide the thermal-hydraulic boundary conditions that will be needed for fuel performance analysis in the BISON code. Quantifying both the accuracy and uncertainty of post-CHF models will therefore be necessary. This paper outlines the strategy for the assessment of TaT and presents the results of using the steady-state and transient dryout experiments of the Boiling Fine-mesh Bundle Tests for CTF validation. The results show that the current model tends to overpredict steady-state critical power. This behavior translates to the transient tests, in which CTF is unable to capture transient dryout behavior. Some discussion of sensitivity analysis work being performed is provided to indicate which models must be further analyzed to properly model transient dryout and its uncertainty.

Salko Jr, Robert [ORNL] (ORCID:0000000253566679)↗

DOE OSTI2025

Dynamic disulfide bond networks enable self-healable and mechanically resilient intrinsically stretchable organic solar cells

A dynamic disulfide network introduced into donor/acceptor blends enables room-temperature self-healing and mechanical resilience in intrinsically stretchable organic solar cells, achieving performance recovery after high mechanical strain. The development of intrinsically stretchable organic solar cells (IS-OSCs) faces significant challenges in balancing mechanical durability and optoelectronic performance. Conventional π-conjugated polymer-based donor/acceptor blend films often exhibit limited stretchability and irreversible performance degradation under mechanical strain. To address these limitations, we propose a novel self-healable donor/acceptor blended film with a dual-network morphology, achieved by incorporating a dynamic disulfide bond-based crosslinked network into the bulk-heterojunction film. The resulting thin films demonstrate a power conversion efficiency (PCE) of 16.39% in rigid OSC devices and a fracture strain of 15.6%. Remarkably, the IS-OSCs retain 80% of their initial PCE under 30% strain and exhibit performance recovery after multiple stretch-release cycles at 40% strain through a room-temperature self-healing process. This work provides a proof-of-concept for highly stretchable and durable IS-OSCs, offering valuable insights for advancing the field of wearable energy systems, adaptive solar textiles, and sustainable electronics.

Yang, Wenyu↗

DOE OSTI2025

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Towards Superior Software Portability with SHAD and HPX C++ Libraries

As hardware architectures and software stacks complexity grows, development productivity, performance and software portability, quickly evolve from desirable features to actual needs. SHAD, the Scalable High-performance Algorithms and Data-structures C++ library is designed to mitigate these issues: it provides general purpose building blocks as well as high-level custom utilities, and offers a shared-memory programming abstraction which facilitates the programming of complex systems, scaling up to High Performance Computing clusters. SHAD’s portability is achieved through an abstract runtime interface, which decouples the upper layers of the library and hides the low level details of the underlying architecture. This layer enables SHAD to interface with different runtime/threading systems, e.g. Intel TBB and Global Memory and Threading (GMT). However, current backends targeting distributed systems, rely on a centralized controller which may possibly limit scalability up to hundreds of nodes and creates a network hot spot due to all to one communication for synchronization, and possibly resulting in degraded performance at high process counts. In this research, we explore HPX, the C++ standard library for parallelism and concurrency, as an additional backend in support of the SHAD library, and present the methodologies in support of local and remote task executions in SHAD with respect to HPX. Finally, we evaluate the proposed system by comparing against existing backends of SHAD and analyzing their performance on C++ Standard Template Library algorithms.

Wu, Nanmiao↗

DOE OSTI2024

Effect of Wettability Gradient on the Scale Formation in Falling Film Flow

Mitigation of scale formation and performance degradation remains a vital challenge for falling film evaporators in various industries. In this work, an experimental study of falling film flow on a horizontal tube is conducted to investigate the effects of wettability gradients on thermal, hydraulic, and fouling behavior. It is revealed that certain hydrophobic coating patterns, such as strip, ring, and grid patterns, lead to unwetted heat transfer area, which results in decreased heat transfer compared to fully wetted plain tube. By adjusting the geometry and position of the wettability gradient, the hybrid coating demonstrates improved heat transfer performance. Based on the characteristics of horizontal tube falling film flow, impinging jet, thin film flow, and liquid retention at the tube bottom, a hybrid coating pattern is developed to improve surface wetting and mitigate the scaling coverage. It is revealed that scale deposition is regulated by wettability gradient. Crystals tend to be dense and compact in hydrophilic areas, while they appear scattered or even absent in hydrophobic regions, depending on the dimension of the hydrophobic area. While at the hydrophilic/hydrophobic boundary, a noticeable scale thickness step is observed, which raises the potential for self-cleaning. Furthermore, the balance of minimization of scaling layer coverage and maximization of wetting area requires an optimal design in coating dimensions, for which a systemic study of both flow dynamics and fouling characteristics on the falling film is necessary in the future.

42 ENGINEERING↗