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DOE OSTI2025

Molecular diversity of dissolved organic matter reflects macroecological patterns in river networks

Deciphering dissolved organic matter (DOM) molecular complexity is crucial for understanding ecosystem function. Using the continental-scale Worldwide Hydrobiogeochemistry Observation Network for Dynamic Rivers Systems (WHONDRS) Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) dataset, we reveal fundamental scaling patterns of DOM chemodiversity with watershed characteristics. Analysis of 54 river sites shows local and regional watershed features significantly influence DOM chemodiversity (2500–8718 unique formulae), exhibiting consistent scaling patterns across compound classes and a novel latitudinal gradient (decreasing diversity with increasing latitude). Scaling relationships for DOM composition vary by compound class. Crucially, the scaling parameters (B, baseline chemodiversity; Z, sensitivity) are linearly interrelated. This B–Z relationship is most robust for potentially bio-labile carbohydrates (coefficient of determination R 2 ≈ 0.85), diminishing for recalcitrant, plant-derived molecules (such as lignin), and indicates (potential) biolability-dependent coupling between baseline diversity and environmental responsiveness. These quantitative scaling relationships, with scaling exponents ranging from − 2.1 to 2.2 across compound classes, enable prediction of DOM composition across watersheds, offering a framework to understand ecosystem responses to environmental change. This research bridges biogeochemistry and ecology, providing tools to anticipate molecular transformations across scales.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass‐based biofuel production

Abstract This study investigates uncertainties in greenhouse gas (GHG) emission factors related to switchgrass‐based biofuel production in Michigan. Using three life cycle assessment (LCA) databases—US lifecycle inventory (USLCI) database, GREET, and Ecoinvent—each with multiple versions, we recalculated the global warming intensity (GWI) and GHG mitigation potential in a static calculation. Employing Monte Carlo simulations along with local and global sensitivity analyses, we assess uncertainties and pinpoint key parameters influencing GWI. The convergence of results across our previous study, static calculations, and Monte Carlo simulations enhances the credibility of estimated GWI values. Static calculations, validated by Monte Carlo simulations, offer reasonable central tendencies, providing a robust foundation for policy considerations. However, the wider range observed in Monte Carlo simulations underscores the importance of potential variations and uncertainties in real‐world applications. Sensitivity analyses identify biofuel yield, GHG emissions of electricity, and soil organic carbon (SOC) change as pivotal parameters influencing GWI. Decreasing uncertainties in GWI may be achieved by making greater efforts to acquire more precise data on these parameters. Our study emphasizes the significance of considering diverse GHG factors and databases in GWI assessments and stresses the need for accurate electricity fuel mixes, crucial information for refining GWI assessments and informing strategies for sustainable biofuel production.

Kim, Seungdo↗

DOE OSTI2024

Geometry-aware training of factorized layers in tensor Tucker format

Reducing parameter redundancies in neural network architectures is crucial for achieving feasible computational and memory requirements during train and inference of large networks. Given its easy implementation and flexibility, one promising approach is layer factorization, which reshapes weight tensors into a matrix format and parameterizes it as the product of two rank-r matrices. However, this family of approaches often requires an initial full-model warm-up phase, prior knowledge of a feasible rank, and it is sensitive to parameter initialization.In this work, we introduce a novel approach to train the factors of a Tucker decomposition of the weight tensors. Our training proposal proves to be optimal in locally approximating the original unfactorized dynamics and stable for the initialization. Furthermore, the rank of each mode is dynamically updated during training.We provide a theoretical analysis of the algorithm, showing convergence, approximation and local descent guarantees. The method's performance is further illustrated through a variety of experiments, showing remarkable training compression rates and comparable or even better performance than the full baseline and alternative layer factorization strategies.

Zangrando, Emanuele [Gran Sasso Science Institute ↗

DOE OSTI2025

Temperature sensitivity of the equilibrium neutronics and accident analysis of the HTR-10

Pebble-Bed High-Temperature Gas-cooled Reactors (PB-HTGR) are moderated by the graphite in the fuel pebbles and the graphite reflector surrounding the pebble-bed. Because graphite is by far the most abundant material in PB-HTGRs and the primary moderator, accurate modeling of the graphite material, including density, impurities, and temperatures, is crucial for accurate computational modeling and simulation of these reactors. While main characteristics of the graphite components are often known, the local temperature is less well known and often averaged over all components. Here, this work studies the impact of considering accurate temperature profiles in the graphite material on the generation of a small PB-HTGR model at the state of equilibrium operation and on short-term accident progression. The fuel compositions for the PB-HTGR were determined using a jump-in equilibrium modeling method, the Axial Radial Zone Equilibrium Modeling (AR-ZEM) method. In contrast to previous work, the AR-ZEM method was used considering thermal-hydraulic feedback from the MELCOR code to determine temperatures of the fuel pebbles and the surrounding graphite reflector. The consideration of an axial and radial temperature profile in the core and reflector, as opposed to uniform material temperatures, had an impact of almost 1,300 pcm on the equilibrium core eigenvalue and caused significant differences in the discharged plutonium fuel inventory with up to 4.9% and 11.0% for Pu-239 and Pu-242, respectively. To assess the impact on short-term accident progression, two Anticipated Transient Without SCRAM (ATWS) events, a Pressurized Loss of Forced Coolant (PLOFC) and a Control Rod Withdrawal (CRW) with loss of flow, were simulated with MELCOR. The use of temperature profiles in the equilibrium core models did not reveal a significant impact on the temperature, power, or reactivity responses during the transients. In conclusion, a need for consideration of accurate temperature profiles, in particular for the graphite reflector, was found for the generation of equilibrium PB-HTGRs core models using jump-in methods, but detailed temperature profiles may not be necessary when performing conservative transient analysis.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

3D modeling of deep borehole electromagnetic measurements with energized casing source for fracture mapping at the Utah Frontier Observatory for Research in Geothermal Energy

Here, we present a 3D numerical modelling analysis evaluating the deployment of a borehole electromagnetic measurement tool to detect and image a stimulated zone at the Utah Frontier Observatory for Research in Geothermal Energy geothermal site. As the depth to the geothermal reservoir is several kilometres and the size of the stimulated zone is limited to several 100 m, surface-based controlled-source electromagnetic measurements lack the sensitivity for detecting changes in electrical resistivity caused by the stimulation. To overcome the limitation, the study evaluates the feasibility of using a three-component borehole magnetic receiver system at the Frontier Observatory for Research in Geothermal Energy site. To provide sufficient currents inside and around the enhanced geothermal reservoir, we use an injection well as an energized casing source. To efficiently simulate energizing the injection well in a realistic 3D resistivity model, we introduce a novel modelling workflow that leverages the strengths of both 3D cylindrical-mesh-based electromagnetic modelling code and 3D tetrahedral-mesh-based electromagnetic modelling code. The former is particularly well-suited for modelling hollow cylindrical objects like casings, whereas the latter excels at representing more complex 3D geological structures. In this workflow, our initial step involves computing current densities along a vertical steel-cased well using a 3D cylindrical electromagnetic modelling code. Subsequently, we distribute a series of equivalent current sources along the well's trajectory within a complex 3D resistivity model. We then discretize this model using a tetrahedral mesh and simulate the borehole electromagnetic responses excited by the casing source using a 3D finite-element electromagnetic code. This multi-step approach enables us to simulate 3D casing source electromagnetic responses within a complex 3D resistivity model, without the need for explicit discretization of the well using an excessive number of fine cells. We discuss the applicability and limitations of this proposed workflow within an electromagnetic modelling scenario where an energized well is deviated, such as at the Frontier Observatory for Research in Geothermal Energy site. Using the workflow, we demonstrate that the combined use of the energized casing source and the borehole electromagnetic receiver system offer measurable magnetic field amplitudes and sensitivity to the deep localized stimulated zone. The measurements can also distinguish between parallel-fracture anisotropic reservoirs and isotropic cases, providing valuable insights into the fracture system of the stimulated zone. Besides the magnetic field measurements, vertical electric field measurements in the open well sections are also highly sensitive to the stimulated zone and can be used as additional data for detecting and imaging the target. We can also acquire additional multiple-source data by grounding the surface electrode at various locations and repeating borehole electromagnetic measurements. This approach can increase the number of monitoring data by several factors, providing a more comprehensive dataset for analysing the deep-localized stimulated zone. The numerical analysis indicates that it is feasible to use the combination of the energized casing and downhole electromagnetic measurements in monitoring localized stimulated zone at large depths.

58 GEOSCIENCES↗

DOE OSTI2026

Meta-analysis of North American Arctic and boreal aboveground biomass datasets: assessing accuracy, dynamics, and similarities

The North American arctic and boreal regions (ABRs) are rapidly warming and experiencing intensifying disturbances. Accurately quantifying aboveground biomass (AGB) is critical for understanding the impacts of these changes on the carbon cycle and for designing climate change mitigation strategies. Several AGB maps have been developed for the North American ABRs, including recent contributions from National Aeronautics and Space Administration’s Arctic-Boreal Vulnerability Experiment (ABoVE) campaign. However, these maps differ widely in training data, methodology, and resulting AGB density estimates. Presently, a comprehensive comparative evaluation is lacking, making it difficult for users to select datasets suited to their research or management needs. Here, in this study, we conducted a comparative analysis of nine AGB density datasets across North American ABRs, specifically for Alaska and Canada. We (1) summarized AGB by ecoregion and Canadian provinces, (2) evaluated their accuracy against field-based measurements, (3) analyzed spatial and temporal similarities among datasets, and (4) assessed their ability to capture disturbance (fire and harvest) impacts on AGB. We found substantial variation in regional and local AGB estimates across datasets, with overall accuracy ranging from R 2 = 0.25–0.62 and Bias% from −47.8% to 69.9% when validated against field plots. Despite these differences, most datasets have comparatively consistent spatial patterns in AGB (r > 0.8 for most cases). In contrast, agreement on the temporal patterns of AGB change is generally low. We found datasets with spatial resolutions ⩽300 m are capable of capturing disturbance impacts on AGB dynamics, though sensitivity varies across products. Our findings and dataset summary provide guidance for selecting appropriate AGB datasets for different applications within our study area. Our analysis also highlights the need to decrease map bias and increase capability to detect temporal change to decrease uncertainty of AGB datasets potentially by using training data which is representative of major plant functional types within the mapped area.

ABoVE↗

DOE OSTI2024

Enhancing Distribution System Resilience: A First-Order Meta-RL Algorithm for Critical Load Restoration

The increasing frequency of extreme events and the integration of distributed energy resources (DERs) into modern grids have elevated the need for resilient and efficient critical load restoration strategies in distribution systems. However, the stochastic nature of renewable DERs, limited energy resource availability and the intricate nonlinearities inherent in complex grid control problem make the problem challenging. Although reinforcement learning (RL) and warm-start RL methods have shown promising results, their performance often falls short in rapidly adapting to new, unseen situations and typically requires exhaustive problem-specific tuning. To address these gaps, we propose a First-Order Meta-based RL (FOM-RL) algorithm within an online framework for adaptive and robust critical load restoration. By harnessing local DERs as the enabling technology, FOM-RL allows the RL agent to swiftly adapt to new unseen scenarios by leveraging previously acquired knowledge of different tasks. Experimental results provide evidence that proposed algorithm learns more efficiently and showcases generalization capabilities across diverse set of operational scenarios. Moreover, a rigorous theoretical analysis yields a tight sublinear regret bound, sensitive to temporal variability, with a task-averaged optimality gap bounded by O(VM+D*/(Tsquare root(M))). These results suggest that optimality improves with task similarity and an increased number of tasks M, reaffirming the efficacy and scalability of the proposed approach in addressing the complexities of critical load restoration in distribution systems.

complexity theory↗

DOE OSTI2026

Archi: Agentic Operations at the CMS Experiment

We present Archi, an open-source, end-to-end framework for scientific collaborations that combines the systematic ingestion and organization of heterogeneous data sources with the deployment of configurable, private, and extensible agents that retrieve and reason over them. An instance of Archi has been deployed for the Computing Operations team of the CMS experiment at CERN's LHC since February 2026 as a support agent for technical operators, offering retrieval and analysis capabilities by combining documentation, historical data, and live monitoring systems. We evaluate the system on operator feedback and a question set collected from production usage, graded by human and automated panels. The system proves effective at operational tasks, resolving real-world queries posed by CMS operators. We also observe that locally-hosted, open-weight models perform competitively, enabling fully private management of sensitive data.

Lugato, Pietro [MIT; CERN]↗

DOE OSTI2025

Resource assessment of ocean thermal energy conversion in Puerto Rico and U.S. Virgin Islands

Island communities often struggle to establish and maintain traditional electric grids and are therefore heavily reliant on costly imported fossil fuels. In the case of Puerto Rico, these challenges are enhanced by extreme weather and other natural hazards that threaten the local electricity generation and transmission infrastructure. Ocean thermal energy conversion (OTEC) could play an important role in establishing a more resilient electrical grid in the region. Here, in this study, a detailed analysis is conducted to characterize the ocean thermal resource and power potential of OTEC in Puerto Rico based on a 14-year dataset of modeled ocean temperature. The assessment considers seasonal and interannual variability in the region's thermal resource and examines the operational limitations associated with minimal thermal gradients required to run a typical OTEC heat engine. Notably, the local thermal resource is found to be sensitive to El Niño-Southern Oscillation (ENSO) climate patterns, with La Niña conditions linked to greater OTEC power availability. Seven areas of opportunity are identified based on their resource potential and proximity to existing electrical distribution lines, including two that could benefit the nearby U.S. Virgin Islands. The greatest OTEC power potential is observed to the south of the main island of Puerto Rico in the Caribbean Sea with an estimated capacity of 138 MW for a plant pumping cold water from a depth of 1,000 m, or the equivalent amount of electricity required to power 219,000 households.

OTEC↗

DOE OSTI2025

Raman spectroscopic investigation of UCl 4

Uranium chloride salts are a proposed fuel source for molten salt reactors (MSRs). However, despite their relevance to nuclear energy, they remain understudied, in part because of their air and moisture sensitivity. Here, this work provides the first Raman spectra of UCl 4 from 45 to 3200 cm −1 collected with 532 and 785 nm excitation sources as well as the assignment of 10 identified peaks to their respective vibrational modes. These Raman bands are compared to those for isostructural ThCl 4 , the compositionally related UCl 3 , and the computed Raman bands for UCl 4 from local vibrational mode analysis. The observed spectrum of UCl 4 is in accord with that of ThCl 4 and the computed spectra of UCl 4 . We posit that the observed differences between the spectra of UCl 4 and UCl 3 are useful in differentiating these species for applications such as in situ monitoring of MSR operations.

Anoxic spectroscopy↗

DOE OSTI2024

Rejection of low-molecular weight neutral organics is highly sensitive to reverse osmosis system design and operation

A computational model was developed to investigate the significance of system design and operating conditions on the rejection of neutral, low-MW organics by reverse osmosis for potable reuse. Here, the model demonstrated that the decrease in local rejection as net driving pressure decreases is substantially greater for moderately rejected compounds than for highly rejected compounds. At recovery values less than 70%, the local permeate concentration can exceed the pressure vessel feed concentration for moderately rejected compounds. System-level rejection of moderately rejected compounds is likewise substantially more sensitive to operating conditions than highly rejected compounds. The findings highlight a drawback of relying on rejection results from bench-scale testing that operates at low recovery, which invariably has higher rejection than full-scale systems operating at similar pressure. The analysis demonstrates a trade-off in which the low-pressure, high-recovery operation desired for potable reuse systems can be detrimental to the removal of low-MW neutral organics. The removal of low-MW neutral organics can be improved if organics rejection is explicitly evaluated during the design process.

42 ENGINEERING↗

DOE OSTI2025

Searches for direct slepton production in the compressed-mass corridor in $\sqrt{\textrm{s}}$ = 13 TeV pp collisions with the ATLAS detector

This paper presents searches for the direct pair production of charged light-flavour sleptons, each decaying into a stable neutralino and an associated Standard Model lepton. The analyses focus on the challenging ``corridor'' region, where the mass difference, $Δm$, between the slepton ($\tilde{e}$ or $\tildeμ$) and the lightest neutralino ($\tildeχ^{0}_{1}$) is less or similar to the mass of the $W$ boson, $m(W)$, with the aim to close a persistent gap in sensitivity to models with $Δm \lesssim m(W)$. Events are required to contain a high-energy jet, significant missing transverse momentum, and two same-flavour opposite-sign leptons ($e$ or $μ$). The analysis uses $pp$ collision data at $\sqrt{s} = 13$ TeV recorded by the ATLAS detector, corresponding to an integrated luminosity of 140 fb$^{-1}$. Several kinematic selections are applied, including a set of boosted decision trees. These are each optimised for different $Δm$ to provide expected sensitivity for the first time across the full $Δm$ corridor. The results are generally consistent with the Standard Model, with the most significant deviations observed with a local significance of 2.0 $σ$ in the selectron search, and 2.4 $σ$ in the smuon search. While these deviations weaken the observed exclusion reach in some parts of the signal parameter space, the previously present sensitivity gap to this corridor is largely reduced. Constraints at the 95% confidence level are set on simplified models of selectron and smuon pair production, where selectrons (smuons) with masses up to 300 (350) GeV can be excluded for $Δm$ between 2 GeV and 100 GeV.

hadron-hadron scattering↗

DOE OSTI2025

Non-destructive identification of absorptive damage sites by photoluminescence brightening

We present a non-destructive photoluminescence (PL) imaging strategy for probing damage growth behavior in fused silica under laser irradiation. Transient wide-field PL image measurements were conducted at varying excitation intensities to investigate the dynamics of radiative defect generation and annihilation in laser-induced damage sites. Our results reveal that, while low excitation intensities predominantly induce PL quenching due to defect annihilation, high-intensity excitation (>0.3 GW/cm 2 at 532 nm) triggers pronounced PL brightening (PLB), indicative of radiative defect generation. Image analysis demonstrates that PLB events are strongly correlated with subsequent damage growth (10 J/cm 2 at 351 nm), whereas overall PL intensity is not. No optically detectable morphological changes were observed during PLB, confirming the non-destructive nature of the technique. We propose that PLB arises from defect-assisted absorption of multiple photons at pre-existing absorptive centers, which enhances local absorptivity and initiates further defect formation. These findings establish PLB monitoring as a sensitive diagnostic tool for identifying damage sites with elevated absorptivity, enabling targeted maintenance and improved laser damage management in optical materials.

Materials science↗

DOE OSTI2026

The Interplay of Pauli Repulsion, Electrostatics, and Field Inhomogeneity for Blueshifting and Redshifting Vibrational Probe Molecules

Many molecules' vibrational frequencies are sensitive to intermolecular electric fields, enabling them to probe the field in complex molecular environments. However, it is often unclear whether the probe is responding to the local electric field or other types of intermolecular interactions, inhibiting interpretation of the frequency and effectiveness as probes. This is especially true for molecules whose vibrational frequencies blueshift instead of the more typical redshift in hydrogen bonding configurations. In this work, we computationally investigate the causes of redshifting versus blueshifting over a range of vibrational reporters. First, we apply adiabatic energy decomposition analysis to a paradigmatic set of probes, finding that redshifting only occurs when electrostatic interactions are strong enough to overcome the dominant and large blueshifting contribution of Pauli repulsion. Furthermore, we demonstrate that field inhomogeneity can further shift the frequency of many probes substantially to either reinforce or counteract the shift expected from a homogeneous field. We find that redshifting is reinforced by electric field inhomogeneity, otherwise field inhomogeneity further weakens the electrostatic contribution relative to Pauli repulsion, leading to blueshifting. Further calculations indicate that the probe's response to field inhomogeneity can be understood by considering the mass of the atoms involved in the stretching mode and sign of the electric field. In explaining the interplay of different intermolecular interactions and field inhomogeneity for many probes, our results should enable the use and interpretation of spectroscopic probes and their connection to electric fields in more complex systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Wide-field microwave magnetic field imaging with nitrogen-vacancy centers in diamond

Non-invasive imaging of microwave (MW) magnetic fields with microscale lateral resolution is pivotal for various applications, such as MW technologies and integrated circuit failure analysis. Diamond nitrogen-vacancy (NV) center magnetometry has emerged as an ideal tool, offering micrometer-scale resolution, millimeter-scale field of view, high sensitivity, and non-invasive imaging compatible with diverse samples. However, up until now, it has been predominantly used for imaging of static or low-frequency magnetic fields or, concerning MW field imaging, to directly characterize the same microwave device used to drive the NV spin transitions. In this work, we leverage an NV center ensemble in diamond for wide-field imaging of MW magnetic fields generated by a test device employing a differential measurement protocol. The microscope is equipped with a MW loop to induce Rabi oscillations between NV spin states, and the MW field from the device-under-test is measured through local deviations in the Rabi frequency. This differential protocol yields magnetic field maps of a 2.57 GHz MW field with a sensitivity of ∼9 μT Hz −1/2 for a total measurement duration of T=357 s, covering a 340 × 340 μm 2 field of view with a micrometer-scale spatial resolution and a device-under-test input power dynamic range of 30 dB. This work demonstrates a novel NV magnetometry protocol, based on differential Rabi frequency measurement, that extends NV wide-field imaging capabilities to imaging of weak MW magnetic fields that would be difficult to measure directly through standard NV Rabi magnetometry.

crystallographic defects↗

DOE OSTI2026

Structured illumination for surface-resolved grazing-incidence X-ray scattering

Grazing-incidence (GI) scattering techniques are widely used to characterize thin films, offering high surface sensitivity and insight into morphology and structure. However, these approaches typically provide statistical averaged information due to elongated footprint or limited spatial resolution due to beam size. Here we introduce a method that combines structured illumination with GI X-ray scattering and leverages our computational imaging approach to resolve local structural details. We demonstrate that our method captures local features of an organic semiconductor thin film without the need for sample rotation as in tomography. The method expands GI techniques from statistical averaging to high-resolution imaging, thereby providing the capability for detailed analysis of local material properties, such as domain shape, orientation and polymorphism, which are critical for advancing material design towards more efficient and tailored materials.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Charging Hub Scenario Sheet Screenshot

The Excel-based CHECT tool estimates the LCOC ($/kWh) by charger type (Level 1, Level 2, and DC fast charging) for a given charging hub scenario. CHECT requires users to input certain charging hub scenario parameters, including the number of chargers, daily utilization, and charger replacement frequency by charger type. Additional inputs such as the charging schedule, local utility rates, capital/operational costs, and financial inputs can be customized by the user, or the tool can generate results using appropriate default values from literature for the charging hub scenario and service location(s). Using the above inputs, CHECT performs a robust techno-economic analysis to generate the LCOC by charger type, broken down by cost category (e.g., capital, operational, utility, taxes) for various combinations of charging hub types (multiunit dwelling or public) and ownership models (residential, utility, or private company). It also outputs the annual discounted cash flows and determines the most sensitive input variables. In addition, the tool allows users to easily compare the LCOC across various ownership models or across different states.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

A quantitative imaging framework for lithium morphology: Linking deposition uniformity to cycle stability in lithium metal batteries

Characterizing the morphology of lithium (Li) is crucial for developing long-lasting lithium metal batteries. It is well established that more uniform Li deposition correlates with better cell performance. Li morphology is often characterized through qualitative analysis of scanning electron microscopy (SEM) images; however, there are no widely accepted metrics to quantitatively describe deposition uniformity. Here, we propose a framework to quantify uniformity through SEM image analysis via the index of dispersion (ID) metric, which is defined and presented in the context of Li metal batteries. We also explore experimental impacts of sampling protocols onIDmeasurements. Our results demonstrate that theIDmetric is highly sensitive to variations in deposition uniformity, including the coexistence and uniformity of multiple morphologies, uniformity within a single morphology, and particle size distribution uniformity. Furthermore, it is demonstrated that uniformity, as measured by theID, can be related to the average potential of Li||Li symmetric cells over cycling. Higher capacity cycling leads to more pronounced changes in bothIDand average cell potential. Local minima/maxima are found consistently in bothIDand average cell potential immediately before cells short-circuit, which we suggest may indicate a collapse of the microstructure prior to failure. We put forward this framework as a more robust approach to quantify Li deposition uniformity, advancing the development of Li metal batteries that are safer and longer lasting.

Science & Technology - Other Topics↗