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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 19 records

A Field Guide to Corralling the Chaos: A Conceptual Framework for Using Models to Guide Opportunistic Field Studies of Natural Disturbances

Watersheds regulate biogeochemical processes and provide ecosystem services to human societies, but disturbances can fundamentally alter these processes across space and time. Determining when and where to sample to capture disturbance impacts in watersheds remains a central challenge. Manipulation studies and long-term monitoring are often constrained by scope, and opportunistic studies often lack pre-disturbance data needed to statistically determine disturbance impacts. We identify a persistent knowledge gap: the absence of a clear, transferable framework to guide opportunistic disturbance research where pre-disturbance data collection is not a feasible option. To address this gap, we present a conceptual framework that intentionally integrates modeling and empirical observation in an iterative, stepwise model–experiment workflow. We demonstrate its application through two contrasting case studies: wildfire impacts on headwater streams using a pre-disturbance preparedness approach, and saltwater flooding impacts on coastal forests using an ‘ex-post-facto’ approach. From these applications, we assess strengths, limitations, and the critical role of team science for transferability across disturbance types and study designs. Broadly, this framework offers a scalable path towards more rigorous, timely, and actionable disturbance science that can inform watershed management, hazard risk reduction, and ecosystem resilience.

Coastal Biogeochemistry↗

lumicap v0.1

Automated HDR luminance imaging system designed for daylighting research and building science. It controls a fisheye-lens camera to capture time-lapse bracket sequences, merges them into calibrated HDR images, and runs a full post-processing pipeline — all unattended. Features: - Scheduled LDR bracket capture via gphoto2 - HDR merging with vignetting, ND filter, and fisheye projection corrections - Illuminance and luminance meter integration (Konica Minolta T-10A, LS-100/150) - Daylight glare probability (DGP) and solar position computation - Automated false-color rendering, JPEG thumbnails, and daily time-lapse video - CSV data logging per timestep Uses: - Long-term monitoring of daylight conditions in buildings - Glare analysis for occupant comfort research - Solar irradiance and sky luminance studies Advantages: - End-to-end automation — capture, calibration, analysis, and archiving run without manual intervention - Built on the proven Radiance toolchain, ensuring photometrically accurate HDR output - Hardware-agnostic meter support via serial auto-detection - Lightweight — no GUI overhead, deployable on a headless Raspberry Pi or similar embedded system

Wang, Taoning [Lawrence Berkeley National Laborato↗

Autonomous monitoring of algal biomass: Success stories and lessons learned from long-term field deployment

Autonomous, high-frequency monitoring of outdoor algal ponds is needed to quantify biomass productivity and detect culture decline in environments prone to contamination, grazers, and variable operating conditions. We report successes and lessons learned in translating a laboratory spectroradiometric monitoring approach to a multi-year autonomous field deployment at the Arizona Center for Algae Technology and Innovation (AzCATI). The system measures spectrally resolved pond reflectance by ratioing upwelling radiance from each raceway to simultaneous downwelling sky irradiance using fiber-coupled spectrometers. A physics-based reflectance model (ASHARP) is fit to each spectrum pair to estimate optical parameters, including a biomass-proxy coefficient (C a ) which enables near-real-time tracking of biomass accumulation and culture state at 2–5 min intervals. From May 2022 through September 2025 the platform operated continuously while scaling from two to six raceway ponds. Several strains of algae were monitored successfully, including the high productivity Tetraselmis striata and Picochlorum celeri. Transitioning data acquisition from a Windows laptop to a Raspberry Pi improved uptime from 57% (2022) to ~89% (2024–2025) and enabled routine real-time analysis. Further, we converted relative biomass estimates to absolute ash-free dry weight (AFDW) using experimentally-derived calibrations, providing field-relevant biomass predictions with conservative confidence bounds. These results demonstrate the feasibility of long-term, autonomous optical monitoring for well-mixed open-raceway algal cultivation and provide practical guidance for reliable field operation and scaling.

Katinas, Christopher Michael [Sandia National Labo↗

Economic assessment of seismic monitoring for underground hydrogen storage

Underground hydrogen storage (UHS) plays a key role in the energy landscape. However, like other subsurface engineering technologies, UHS may cause leakage into the groundwater or atmosphere and possibly induce local seismicity. To reduce these risks, seismic monitoring could be a viable technique to track the UHS plume, detect leakages, and locate induced seismicity events. Seismic monitoring has been proposed to safely monitor UHS, but research in this area is still new and requires field studies. Lab and theoretical studies have demonstrated the validity of seismic monitoring for UHS. Therefore, it is imperative to analyze the economic feasibility of seismic monitoring for UHS. Hence, we develop a cost model and open-source Python code for seismic monitoring that considers types of seismometers, comprehensive operational scenarios, detection thresholds, and long-term leakage monitoring. A case study is further provided to validate the cost model on reservoir simulations of UHS. We find that the levelized cost for a 10-year operating UHS site will range on the order of ∼0.003 $\$$/kg. The methods developed in this study could also be applied to the monitoring of groundwater, gas, and/or wastewater injection.

08 HYDROGEN↗

Evolution of storage monitoring – update in response to commercial and regulatory drivers

Carbon Capture and Storage (CCS) is in transition from first-of-a kind projects and research-orientated pilots to commercially-motivated applications. Monitoring results from many newly developed and planned large scale commercial projects are limited; however, it is worthwhile to assess their evolution and consider new strategies as part of an effort to assess and document best practices. Commercial monitoring is targeted to activities that comply with regulatory drivers and de-risk investments. Commercial monitoring also supports accounting that storage has occurred and is tied to project financing. It deals with long time frames and large volumes injected into multiple wells and multiple projects in favorable areas. We see developing trends toward reproducible workflows that systematically reduce risks and clarify expectations for oversight and long-term surveillance. Monitoring techniques showing increasing trends include injection zone pressure as a history-matching and compliance tool. To reduce cost and environmental impact of time-lapse seismic data collection, deploying new approaches and tools, such as use of fibre and installed sources are increasingly applied. Concern over the risk of induced seismicity by regulatory bodies and the general public has increased, which has also resulted in increased monitoring. Some techniques used in the early research phases have been sidelined or used only in restricted applications. For example, geochemical analyses in the injection zone as well as the environment are now being deployed less than it was in research-oriented programs, except in the US where it is required by the permitting process. Expectations of frequent area-wide near surface monitoring have also decreased.

25 ENERGY STORAGE↗

Specimen sizing and remaining life sample calculations for high temperature reactor material surveillance

Advanced high-temperature nuclear reactors rely on structural components that will operate for decades under combined mechanical, thermal, and environmental loading. Materials surveillance programs are a promising strategy for managing the resulting uncertainty in long-term structural integrity by monitoring degradation in service using passively actuated mechanical test articles. Previous reports have developed a simplified, spreadsheetimplementable framework for sizing these test articles and for inferring accumulated creep damage and remaining life from ex-situ test data. This report advances that work toward practical deployment by providing a sample-problem book: a collection of worked, end-toend examples in which the ASME Section III, Division 5 design analysis of a representative high-temperature reactor component is carried through to a sized surveillance article, verified with detailed finite-element analysis, and concluded with a remaining-life assessment based on an assumed ex-situ creep-rate measurement on the retrieved specimen. The report also summarizes ongoing ANL engagement with ASTM Committee E10 on Nuclear Technology and Applications toward drafting a standard covering surveillance procedures for advanced reactors.

Barua, Bipul (ORCID:0000000247184113)↗

Effect of Fe on Co-Based SiO2Al2O3 Mixed Support Catalyst for Fischer–Tropsch Synthesis in 3D-Printed SS Microchannel Microreactor

This research explores the effect of a composite support of SiO2 and Al2O3 with Fe and Co incorporated as catalysts for Fischer–Tropsch synthesis (FTS) using a 3D-printed stainless steel (SS) microchannel microreactor. Two mesoporous catalysts, FeCo/SiO2Al2O3 and Co/SiO2Al2O3, were synthesized via a one-pot (OP) method and extensively characterized using N2 physisorption, XRD, SEM, TEM, H2-TPR, TGA-DSC, FTIR, and XPS. H2-TPR results revealed that the synthesis method significantly affected the reducibility of metal oxides, thereby influencing the formation of active FTS sites. SEM-EDS and TEM further revealed a well-defined hexagonal matrix with a porous surface morphology and uniform metal ion distribution. FTS reactions, carried out in the 200–350 °C temperature range at 20 bar with a H2/CO molar ratio of 2:1, exhibited the highest activity for FeCo/SiO2Al2O3, with up to 80% CO conversion. Long-term stability was evaluated by monitoring the catalyst performance for 30 h on stream at 320 °C under identical reaction conditions. The catalyst was initially active for the methanation reaction for up to 15 h, after which the selectivity for CH4 declined. Correspondingly, the C4+ selectivity increased after 15 h of time-on-stream, indicating a shift in the product distribution toward longer-chain hydrocarbons. This trend suggests that the catalyst undergoes gradual activation or restructuring under reaction conditions, which enhances chain growth over time. The increase in C4+ products may be attributed to the stabilization of the active sites and suppression of methane or light hydrocarbon formation.

Biochemistry & Molecular Biology↗

PV Durability at Scale: Assessing Bifacial and TOPCon Field Performance

Recent field performance results of TOPCon and PERC Bifacial modules are presented based on small-scale deployments at NLR, and a selection of 3rd-party residential data. Bifacial PERC degradation rates are a median of -1 % / yr with bifacial TOPCon modules at a similar rate of -1.1 %/yr over the first couple of years. Comparable PERC Monofacial modules have a degradation rate of -0.5%/yr. Some TOPCon modules exhibited an indoor dark metastability effect which requires recovery by light soaking or UV exposure prior to IV curve measurement. Further monitoring is needed to confirm the long-term stability of TOPCon modules.

14 SOLAR ENERGY↗

Machine Learning–Based Condition Monitoring of a Circulating Water System of a Canadian Nuclear Plant

With the need to maintain long-term reliable energy using nuclear power plants, there is an underlying demand to ensure that the maintenance of plant components and systems is also done in an efficient and cost-effective manner. One way to achieve this is by moving from time-based maintenance to condition-based maintenance. The research presented in this paper focuses on applying statistical and machine-learning-based methods to capture anomalies within data for fault detection to further develop into condition monitoring. This paper focuses on system data for a circulating water system (CWS) of a pressurized heavy-water reactor for detecting anomalies. The different methodologies used for detecting and capturing anomalies in the CWS data are matrix profile, density-based spatial clustering of applications with noise (DBSCAN), and support vector machines (SVMs). Matrix profile and DBSCAN are used to distinguish between normal data and anomalous data. This paper presents a hybrid method using DBSCAN and SVM when a portion of the data is used for DBSCAN to generate clusters. This portion of data is then used to train the SVM along with the clusters generated by DBSCAN as output. SVM is then tested on unseen data as a predictive tool, which can work in real time to categorize data points as either normal or anomalous. This paper presents results that show the high accuracies of DBSCAN and SVM in capturing anomalies within the data for a CWS for fault detection. Thus, the maintenance plan would be focused on component condition rather than a time-based schedule by switching to an automated system to identify and predict faults within a CWS.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Innovative Biomonitoring and Remediation of Heavy Metals Using Phytotechnologies at the Savannah River Site (SRS) Coal Combustion Product (CCP) Impoundment Sites

The Savannah River Site (SRS) contains legacy coal combustion product (CCP) impoundments that are impacted by elevated concentrations of heavy metals and radionuclides, posing long-term risks to soil health, ecosystem functioning, and environmental sustainability. Traditional environmental monitoring approaches rely primarily on chemical analyses to quantify contaminant concentrations but often provide limited information regarding biological responses or ecosystem recovery. This project addressed these limitations by integrating environmental chemistry, microbial ecology, artificial intelligence (AI), and bioremediation into a comprehensive framework for environmental diagnostics and restoration of contaminated soils. The overarching goal of this collaborative project between Florida A&M University (FAMU) and the University of Georgia's Savannah River Ecology Laboratory (SREL) was to develop innovative biomonitoring and remediation strategies for heavy metal-contaminated CCP impoundment sites at the Savannah River Site. Specifically, the project sought to (i) characterize heavy metal contamination, (ii) determine microbial responses to contamination, (iii) isolate indigenous heavy metal-resistant microorganisms for remediation applications, (iv) develop a microbial ecological health index using machine learning, and (v) optimize fungal-mediated bioremediation using artificial intelligence.

01 COAL, LIGNITE, AND PEAT↗

Operational Evolution of FTS3: A DevOps Driven Approach to Elastic Operations

The File Transfer Service (FTS3) is a distributed data movement service developed at CERN and widely used to transfer data across the Worldwide LHC Computing Grid (WLCG). At Fermilab, FTS3 supports data transfers for multiple experiments, including Intensity Frontier experiments such as DUNE, enabling reliable data movement between WebDAV endpoints in Europe and the Americas.​ At CHEP 2021, we reported on the initial containerized deployment of FTS3 on OKD, the community Kubernetes distribution of Red Hat OpenShift. In this work, we present the subsequent evolution of this deployment, focusing on new operational capabilities introduced to improve scalability, robustness, and long-term maintainability.​ We describe the adoption of more secure and reproducible container build workflows, the integration of DevOps-driven operational practices, and enhancements in monitoring and automation. A key new result is the introduction of horizontal scaling and elastic resource management, allowing FTS3 components to dynamically adapt to workload variations while maintaining service reliability. We also discuss improvements in fault tolerance and operational procedures derived from production experience.​ Finally, we summarize lessons learned from operating FTS3 as a Kubernetes-native service and outline how these developments have improved the resilience and efficiency of data movement operations at Fermilab.

Munoz Flores, Victor Leopoldo [Fermilab]↗

Development of On-Line Spectroscopic pH Monitoring for Nuclear Fuel Reprocessing Plants: Weak Acid Schemes

Knowledge of real-time solution properties and composition is a necessity for any spent nuclear fuel reprocessing method. Metal-ligand speciation in aqueous solutions derived from the dissolved commercial spent fuel is highly dependent upon the acid concentration/pH, which influences extraction efficiency and the resulting speciation in the organic phase. Spectroscopic process monitoring capabilities, incorporated in a counter current centrifugal contactor bank, provide a pathway for on-line real-time measurement of solution pH. The spectroscopic techniques are process-friendly and can be easily configured for on-line applications, while classic potentiometric pH measurements require frequent calibration/maintenance and have poor long-term stability in aggressive chemical and radiation environments. Our research is focused on developing a general method for on-line determination of pH of aqueous solutions through chemometric analysis of Raman spectra. Interpretive quantitative models have been developed and validated under the range of chemical composition and pH using a lactic acid/lactate buffer system. The developed model was applied to spectra obtained on-line during solvent extractions performed in a centrifugal contactor bank. The model predicted the pH within 11% for pH > 2, thus demonstrating that this technique could provide the capability of monitoring pH on-line in applications such as nuclear fuel reprocessing.

pH, spectroscopic monitoring, on-line monitoring, ↗

Suppressing Phase Segregation and Improving Stability in Mixed-Halide Perovskites through Spinel Oxide-Directed Epitaxy

Mixed-cation mixed-halide perovskite compositions are essential for achieving the required bandgaps for high-efficiency multijunction photovoltaics, yet their stability remains limited by interfacial defects, phase segregation, and degradation. Here, we introduce spinel oxides as a new family of lattice-matched substrates that enable crystalline, phase-pure, compositionally-uniform, bromide-rich perovskite film growth. The effect of spinel oxides is two-fold: reducing defects at the bottom interface by templating film growth and inducing beneficial compressive strain through mismatch-dependent substrate-perovskite lattice coupling. Spinel oxide substrates facilitate growth of highly crystalline films and eliminate detrimental secondary phases across thicknesses. Using grazing incidence X-ray diffraction, X-ray fluorescence, cathodoluminescence–scanning electron microscopy, cryogenic photoluminescence, and density functional theory, we reveal that Mg-halide bonds at the bottom interface induce lattice mismatch-dependent compressive strain that suppresses halide segregation and further reduces defect formation. In addition, films grown on spinel oxides maintain over 87% of the perovskite phase after 12 h under 100% relative humidity, as monitored by in situ grazing incidence wide-angle X-ray scattering (GIWAXS), compared to less than 70% for control samples. This work extends lattice matching from vapor-deposited epitaxial semiconductors to solution-processed halide perovskites to establish a broadly applicable strategy for defect suppression, phase homogenization, and long-term stability. Based on the fundamental science explored here, we set the stage for the development of lattice-matched spinel oxide charge transport layers to be integrated into perovskite solar cells and other optoelectronic devices.

36 MATERIALS SCIENCE↗

Understanding Discharge‐Driven Growth of Cathode Impedance in Ni‐Rich NMC Cathodes

Degradation of LiNi x Mn y Co 1-x-y O 2 (NMC)-based lithium-ion batteries depends strongly on cut-off voltage ranges. In addition to the high upper cut-off voltage, a high depth of discharge (i.e., lower cut-off voltage) significantly worsens cathode impedance growth and capacity fade during long-term cycling. However, there is currently no consensus on the mechanism behind the negative role of a deep discharge. Here, this phenomenon was investigated in graphite||NMC cells with single-crystal cathodes (LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NMC622) or LiNi 0.76 Co 0.14 Mn 0.10 O 2 (NMC76)) using targeted aging protocols (constant high-voltage holds vs. charge–discharge cycling), while monitoring transition-metal (TM) dissolution, cathode-electrolyte interface (CEI) impedance, and NMC surface composition. We demonstrate a correlation between discharge-driven CEI impedance growth and increased TM dissolution. Furthermore, this degradation pathway is more pronounced in lower-Ni NMC622 than in higher-Ni (NMC76) under comparable delithiation states at charge, with both compositions undergoing the H2→H3 phase transition. X-ray photoelectron spectroscopy (XPS) reveals NMC composition-dependent evolution of surface lattice oxygen and restructured surface layer composition between charged and discharged states. These findings add mechanistic depth to the role of discharge as an active driver of interfacial degradation and provide new insights into its composition dependence.

25 ENERGY STORAGE↗

LSST Scheduler & Progress Monitoring

The NSF-DOE Vera C. Rubin Observatory scheduling team is providing a set of tools for monitoring the scheduler and progress on the Legacy Survey of Space and Time (LSST). These slides provide an overview of available pages and assorted figures on them: the night summary provides an overview of a completed night of observing, including maps of exposures and plots of data quality metrics; the pre-night briefing, an analysis of a simulation of an upcoming night; and a handful of figures that provide information on long-term progress toward LSST survey goals.

H.Neilsen, Eric, Jr. [Fermilab] (ORCID:00000002735↗

Measuring Climate and Water Risk across the Bulk Power System

As climate impacts increase and power systems transition to renewables, planners and operators need insights into climate risks to power generation and infrastructure to ensure reliable decision-making in the short and long-term. We present a standardized, consistent mechanism for utilities and system operators to evaluate the climate- and water-related risks of their current and future grid assets. Using a risk-based approach on the combined outcomes of high-fidelity climate drivers together with water and power system models, we examine the temperature and water availability impacts within the contiguous United States to power system assets at the water basin level in three different time periods and report resulting outcomes on lost capacity across different expansion scenarios and climate models. The results indicate that air temperature has the highest effect on derating. Changes in streamflow do not have a large impact on generation capacity at the national level. Electric sector buildout scenarios each have a unique regional risk profile, depending on the technology mix and total capacity, although risks from high temperatures are significant for both traditional and renewable energy generation. Stakeholders can use this approach to monitor effects of generation capacity losses and potential impacts as climate, generation mix, and infrastructure change.

24 POWER TRANSMISSION AND DISTRIBUTION↗

FLIP-FLOP ACTIVITY ON THE W UMa-TYPE BINARY SYSTEM HH UMa

We report the discovery of flip-flop activity in a W UMa-type binary. A long-term multi-color photometric surveillance of HH UMa was carried out with three sets of light curves obtained over six weeks. The light curves of the eclipsing binary presented marked asymmetry and rapid interchange between the two light maxima. During the observations from 2014 February to 2014 April, the spot distortion phase jumped between phases 0.25 and 0.75 twice, a typical indication of flip-flop activity. We applied the Wilson–Devinney method to analyze the three light curves. The results indicate that HH UMa is a partially eclipsing contact system of A subtype with an obviously asymmetric light curve. The observed light curves can be modeled by assuming that there are two dark spots on the massive primary component that are almost persistently located around phases 0.25 and 0.75, but can interchange their intensities. We further suggest that a plausible scenario for explaining the properties of those dark spots is strong surface magnetic activity with a sudden reversal of the more active longitude. We therefore conclude that HH UMa is very likely a W UMa-type system displaying flip-flop activity.

79 ASTRONOMY AND ASTROPHYSICS↗

Long-term thermal stability and calibration of Type-II fiber Bragg grating array inscribed in radiation-hardened fibers

This paper investigates the long-term thermal stability of Type-II fiber Bragg grating (FBG) arrays, inscribed by femtosecond laser in radiation-hardened fiber, for potential applications as multiplexed sensors in high-temperature energy systems. The thermal stability of FBG sensors was assessed through 16 thermal cycles from room temperature (RT) to 750 ℃ about two months, involving 100 FBG sensors. The results show that the absolute temperature drift of FBG sensors can be reduced to less than 0.4 pm/day after 54 h thermal annealing process at a constant temperature of 800 ℃. As temperature sensors, the FBGs demonstrated stable performance, achieving a standard deviation (STD) of 1.8 pm (corresponding to a temperature resolution of 0.118 ℃) post-annealing. Repeated thermal cycles revealed a random drift of 2.3 pm in the FBG wavelength at RT. Polynomial fitting was explored as a calibration method to convert FBG wavelength shifts into absolute temperature measurements. By optimizing calibration temperature points (RT, 200 ℃, 400 ℃, and 750 ℃), the study shows that cubic polynomial calibration using four points yields an average R2 of 0.9997 and an RMSE of 3.58 ℃ across the entire temperature range (RT to 750 ℃). This approach represents an 11.53-fold improvement over empirical slope calibration and a 1.34-fold improvement over four-point piecewise fitting. The findings indicate that Type-II FBGs inscribed in radiation-hardened fibers can function as accurate temperature sensors, with performance on par with or exceeding that of thermocouples. With their multiplexing capability, robust signal transmission over long lead cables, and immunity to electromagnetic interference, FBG sensors offer a promising alternative to traditional electronic sensors for energy system monitoring.

Dominguez-Ontiveros, Elvis [ORNL] (ORCID:000000018↗