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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Multi-Differential Charged Current 𝝂_𝝁− Argon Cross Section without Pions in the Final State Measurement in MicroBooNE , and Current Status of Simultaneous Cross Section Extraction with ANNIE

MicroBooNE, an 85-tonne liquid argon time projection chamber detector is on-axis to the Booster Neutrino Beam (BNB) at Fermi National Accelerator Laboratory. MicroBooNE is elucidating neutrino interactions with argon through cross-section measurements to refine interaction models and reduce uncertainties. In this poster, we present recent published single and double multi-differential charged current (CC) cross section with zero pions in the final state (CC-0 ) as a function of muon momentum ( ) and the cosine of the muon angle ( ). We present the details of the event selection and the extraction of 1D and 2D cross sections. We further report on the status of a simultaneous cross-section extraction conducted in conjunction with the ANNIE experiment, which employs a Gd-H O target and operates on the same BNB beamline. This joint measurement enables a precision test of nuclear A-dependence between oxygen and argon, with shared flux and cross-section model correlations leading to the cancellation of systematic uncertainties.

Nguyen, Christian Van [Rutgers U., Piscataway] (OR↗
DOE OSTI2025

Nonlinear Ensemble Filtering with Diffusion Models: Application to the Surface Quasigeostrophic Dynamics

The intersection between classical data assimilation methods and novel machine learning techniques has attracted significant interest in recent years. Here, we explore another promising solution in which diffusion models are used to formulate a robust nonlinear ensemble filter for sequential data assimilation. Unlike standard machine learning methods, the proposed ensemble score filter (EnSF) is completely training free and can efficiently generate a set of analysis ensemble members. Here, in this study, we apply the EnSF to a surface quasigeostrophic model and compare its performance against the popular local ensemble transform Kalman filter (LETKF), which makes Gaussian assumptions in the analysis step. Numerical tests demonstrate that EnSF maintains stable performance in the absence of localization and for a variety of experimental settings. We find that while LETKF maintains optimal performance in the case of linear observations of the entire state and a perfect model, EnSF shows improvements over LETKF when nonlinear observations are assimilated and the system is subject to unexpected model errors. A spectral decomposition of the analysis results in this nonlinear observation regime shows that the largest improvements over LETKF occur at large scales (small wavenumbers), where LETKF lacks sufficient ensemble spread. Overall, this initial application of EnSF to a geophysical model of intermediate complexity motivates further development of the algorithm for more realistic problems.

Artificial intelligence↗
DOE OSTI2025

Calculating the Effects of Solids Input and Removal as a Temperature Control in the Advanced Scale Up Reactor Experiment (ASURE) Facility at NETL Using Aspen

The Advanced Scale Up Reactor Experiment (ASURE) facility at NETL is being designed to be a fuel-flexible multi-purpose reactor that can be used for pyrolysis/gasification or evaluation of other high pressure “circulating fluidized bed” (CFB) chemical processes. The initial system design calculations for pyrolysis/gasification are presented in this work showing the expected performance of the ASURE facility when used as a biomass conversion reactor. Several other areas of application include gasification of any carbonaceous fuel including biomass, coal, plastics, and other waste materials. The reactor can therefore be used to produce SYNGAS of various compositions and hydrogen as well as other high value chemicals resulting from a typical tuned gasification process. This paper discusses an ASPEN model of the facility, focusing on the riser of the CFB reactor and the solids recirculation loop. The ASPEN model divides the riser into two sections. A bottom section which receives ash, char and sand which have been recirculated from a return loop. In this section an inert fluidization gas, (N2 or CO2), is introduced which acts as the primary mover of the solids through the system. The bottom section is equipped with a restricted air feed so that the recirculated char can be partially oxidized. This oxidation process along with the inventory of recirculating sand are used to effectively control the temperature in the following two chemical conversion sections of the reactor which are the pyrolysis zone followed by a tar cracking zone. Fresh fuel is added to the pyrolysis zone and undergoes drying and devolatilization. The products ash, char, volatile matter, and water vapor exit the pyrolysis zone and enter the reaction block for tar cracking. Steam and CO2 gasification reactions will be incorporated into the tar cracking zone, however at the design operating temperature, conversion from these reactions is expected to be essentially zero. The unit when completed in 2026 will test mixtures of biomass, plastics, and waste coal. This presentation discusses the basic ASPEN engineering design model for this project and provides preliminary sensitivity studies to determine how the various parts of the reactor will perform.

ASSURE↗
DOE OSTI2025

Calculating the Effects of Solids Input and Removal as a Temperature Control in the Advanced Scale Up Reactor Experiment (ASURE) Facility at NETL Using Aspen

The Advanced Scale Up Reactor Experiment (ASURE) facility at NETL is being designed to be a fuel-flexible multi-purpose reactor that can be used for pyrolysis/gasification or evaluation of other high pressure “circulating fluidized bed” (CFB) chemical processes. The initial system design calculations for pyrolysis/gasification are presented in this work showing the expected performance of the ASURE facility when used as a biomass conversion reactor. Several other areas of application include gasification of any carbonaceous fuel including biomass, coal, plastics, and other waste materials. The reactor can therefore be used to produce SYNGAS of various compositions and hydrogen as well as other high value chemicals resulting from a typical tuned gasification process. This paper discusses an ASPEN model of the facility, focusing on the riser of the CFB reactor and the solids recirculation loop. The ASPEN model divides the riser into two sections. A bottom section which receives ash, char and sand which have been recirculated from a return loop. In this section an inert fluidization gas, (N2 or CO2), is introduced which acts as the primary mover of the solids through the system. The bottom section is equipped with a restricted air feed so that the recirculated char can be partially oxidized. This oxidation process along with the inventory of recirculating sand are used to effectively control the temperature in the following two chemical conversion sections of the reactor which are the pyrolysis zone followed by a tar cracking zone. Fresh fuel is added to the pyrolysis zone and undergoes drying and devolatilization. The products ash, char, volatile matter, and water vapor exit the pyrolysis zone and enter the reaction block for tar cracking. Steam and CO2 gasification reactions will be incorporated into the tar cracking zone, however at the design operating temperature, conversion from these reactions is expected to be essentially zero. The unit when completed in 2026 will test mixtures of biomass, plastics, and waste coal. This paper presents the basic ASPEN engineering design model for this project and provides preliminary sensitivity studies to determine how the various parts of the reactor will perform.

ASSURE↗
DOE OSTI2025

Model Development for the ACME Lab Modular Wall and A-Frame Assemblies

The structural frame used for conducting large structural tests was replaced by the ACME (Applied Combined Mechanical Environments) Lab in Building 860 of Sandia National Laboratories in Albuquerque, NM. This new design required simulation and analysis to verify maximum loads and corresponding factors of safety. Two major assemblies which are part of the ACME Lab, the Modular Wall and A-Frame, were designed to operate with a multitude of components in various configurations and with varying loads. Simulations of the Modular Wall and A-Frame structures were performed through explicit analysis to determine safety factors for numerous loading scenarios. The Modular Wall had safety factors of 1.1 for the lateral, diagonal, and gusset loading conditions. The A-Frame had safety factors of 2 for all loading conditions simulated.

42 ENGINEERING↗
DOE OSTI2025

AMR-Wind: A Performance-Portable, High-Fidelity Flow Solver for Wind Farm Simulations

We present AMR-Wind, a verified and validated high-fidelity computational-fluid-dynamics code for wind farm flows. AMR-Wind is a block-structured, adaptive-mesh, incompressible-flow solver that enables predictive simulations of the atmospheric boundary layer and wind plants. It is a highly scalable code designed for parallel high-performance computing with a specific focus on performance portability for current and future computing architectures, including graphical processing units (GPUs). In this paper, we detail the governing equations, the numerical methods, and the turbine models. Establishing a foundation for the correctness of the code, we present the results of formal verification and validation. The verification studies, which include a novel actuator line test case, indicate that AMR-Wind is spatially and temporally second-order accurate. The validation studies demonstrate that the key physics capabilities implemented in the code, including actuator disk models, actuator line models, turbulence models, and large eddy simulation (LES) models for atmospheric boundary layers, perform well in comparison to reference data from established computational tools and theory. We conclude with a demonstration simulation of a 12-turbine wind farm operating in a turbulent atmospheric boundary layer, detailing computational performance and realistic wake interactions.

17 WIND ENERGY↗
DOE OSTI2025

Enhanced Power Grid Maintenance Planning and Quantum-Inspired Combinatorial Prospects

Efficient and reliable scheduling of maintenance for power generation and transmission infrastructure is essential for minimizing operational costs and ensuring grid stability. This paper introduces an integrated optimization framework for coordinated maintenance scheduling of generators and transmission lines under resource and reliability constraints. The model minimizes a composite cost function including maintenance and generation costs, as well as penalties for delayed maintenance, while satisfying N−1 security constraints, operational limits, and crew availability. Case studies on the IEEE 300-bus test system demonstrate the effectiveness of the proposed approach in producing feasible and cost-effective maintenance schedules. To address scalability and combinatorial complexity, the model is mapped into a Quadratic Unconstrained Binary Optimization (QUBO) problem, enabling exploration of solution approaches based on Quantum Imaginary Time Evolution (QITE). While the QUBO reformulation provides a foundation for future quantum-inspired optimization, this study focuses primarily on the development and demonstration of the classical optimization framework and illustrates the potential applicability of QITE in large-scale maintenance scheduling.

Chen, Yang [ORNL] (ORCID:0000000271693874)↗
DOE OSTI2026

Dielectric Spectroscopy Cable NDE for Unequal Aging Over Different Lengths

This Pacific Northwest National Laboratory milestone report assesses the effect of unequal aging over different lengths of cable on dielectric spectroscopy (DS) bulk impedance measurements from the cable end. DS measurements can indicate the remaining useful life of cables; however, most benchmark tests are based on accelerated aging of the entire cable. If only a portion of the cable is exposed to a harsh environment (as is frequently the case), the DS measurement will indicate a significantly less-aged cable than if the entire cable were exposed to a uniform environmental stress. The DS measurement is primarily related to the intrinsic insulation material relative permittivity—typically between 1.5 and 3.0. Insulation aging increases permittivity and, correspondingly, the cable’s overall capacitance measured from the cable end. To judge the health of the overall cable system, operators are primarily interested in the condition of the most severely aged section since that is where a failure is most likely to occur. This can be expressed as the dimensionless relative permittivity of the severely aged section divided by the permittivity of a pristine cable. This relative permittivity is an intrinsic material parameter independent of cable length and can serve as a quantitative indication of the insulation condition. If the relative percentages of cable exposed to a harsh and benign environment are known, the DS measurement of the entire cable length, including both pristine and aged sections, can be compensated to predict the relative permittivity (relative to pristine permittivity) of the most severly aged segment. A test was performed on three 50 ft (16 m) cables with 10%, 50%, and 90% of the cable inside a thermal aging oven. Predictably, the aging effect on the DS response was greatest in the 90% sample, followed by the 50% sample, and then the 10% sample. The more interesting result is the ratio of the aged insulation permittivity to the pristine insulation permittivity. Based on prior work, an end-of-life cable has a value of approximately 1.35. If the relative percentages of pristine and severely aged cable lengths are known, and the total cable-length capacitance of the initial pristine cable and the combined pristine plus aged cable are known, the relative aged permittivity (ratio of aged section permittivity / pristine section permittivity) can be estimated. The relative cable lengths exposed to a harsh environment may be known or estimated based on plant layout drawings or cable reflectometry tests that can locate the oven entry and exit points. The compensation was verified using a lumped-parameter model to predict the aged-segment permittivity e2/e1, where e2 is the aged-segment permittivity and e1 is the pristine-segment permittivity. For all three percentages of aged cable lengths, the ratio was quite similar, as would be expected since all cable segments were exposed to the same aging environment. This ratio of aged permittivity to pristine permittivity can be compared to other damage indicating tests, including elongation at break, to assess cable condition.

ARENA Test Bed↗
DOE OSTI2025

Advancing Development of Emissions Detection (Final Report)

This document is the final report to the U.S. Department of Energy (DOE for contract DE-FE0031873) awarded to Colorado State University (CSU). CSU and partners at Harrisburg University of Science and Technology, University of Texas Arlington, and University of Texas at Austin organized several testing rounds to provide knowledge focused on advancing the detection capabilities of emissions monitoring devices. With this funding opportunity the research group began by establishing the Advancing the Development of Emission Detection (ADED) program, with the goal focused on enhancing the accuracy, reliability, and field applicability of methane detection technologies. This effort aimed to address the critical challenges of identifying and quantifying methane emissions while enabling industry stakeholders to meet regulatory compliance and environmental sustainability goals. The program engaged with industry, government, and technology stakeholders to promote adoption and consensus on testing techniques for methane detection solutions. Methane, a potent greenhouse gas, contributes significantly to global warming, and the oil and natural gas (O&G) sector is a primary source of methane emissions. Regulatory measures such as leak detection and repair (LDAR) programs have been implemented to address emissions. However, traditional LDAR approaches, reliant on handheld and component-level measurements, are resource-intensive. To address these limitations and move with evolving regulations, advanced methane technologies are emerging. These solutions include ground-based sensors, mobile systems (e.g., drones, vehicles, and aircraft), and satellite-based platforms. They offer innovative capabilities for autonomous monitoring, larger spatial coverage, and emission quantification using methods such as tracer gas techniques and inverse modeling with Gaussian plume analysis. The ADED program began with creating protocols for methane controlled release (CR) testing these continuous monitoring (CM) and survey technologies that detect and monitor methane emissions at O&G facilities. The protocols were then implemented throughout testing of CM and survey devices at CSU’s Methane Emissions Technology Evaluation Center (METEC) facility from 2021 through 2024. As apart of the protocol, solutions that tested under the ADED program installed their solutions at METEC, documented their system under test, and provided detection reports to the METEC team for analysis. The METEC team would provide the solutions with analyzed reports of their emissions and ground truth data of the releases conducted during their testing session. Under the ADED program, CMs were also tested at O&G facilities for a six week test run of challenge release (ChR) releases. The findings from the ADED program underscore the critical role of collaborative research and innovation in tackling methane emissions, offering a pathway for the oil and gas sector to achieve significant environmental and economic benefits. Results from METEC testing saw improvement of performance and accuracy across all solutions over the extent of the ADED experiments. The results also showed a variance in CM solution performance between CRs and ChRs. That variance pushed the team to further analyze the differences between CR testing environments and field conditions. With the drive from regulations and that variance in field conditions, the ADED team began designing a new CR testing protocol and additions to the METEC testing facility. The METEC team is furthering the progress made through the ADED program with awarded funding from DE-FE0032276. This funding pushes the development of METEC’s addition with new equipment, allowing for an updated facility layout. METEC still facilitates for traditional facilities, with a legacy pad, while expanding an new design based on how O&G infrastructure has Final Report - Contract Number: DE-FE0031873 been changed over the last decade. Throughout the ADED program the team has also been working with international partners to ensure staying in the trend globally. International partners have been essential in moving the new protocol forward to implement into CR testing at the METEC facility in Spring 2025.

42 ENGINEERING↗
DOE OSTI2026

Neural Network‐Based Methods for Ocean Surface Wave Measurement Using Submarine Distributed Acoustic Sensing (DAS)

Two new data-driven models for estimating ocean surface waves from distributed acoustic sensing (DAS) submarine cable strain rate are developed using supervised machine learning on a 10-day data set collected offshore of Oliktok Point, Alaska. The new models were trained on target data from seafloor pressure moorings at three sites spaced evenly along 27.1 km of cable and were benchmarked against an empirical transfer function method previously used to estimate waves from DAS. A model which uses convolutional neural networks to transform 2-km frequency-wavenumber strain spectra to seafloor pressure spectra outperforms the benchmark in wave height prediction (RMSE of 0.15 vs. 0.41 m) and period prediction (0.29 vs. 0.37 s) when evaluated on a held-out test data set. When applied to a DAS data set collected on the same cable 2 years prior, the CNN-based model maintained similar significant wave height performance (RMSE = 0.23 m) relative to available satellite altimetry data. A two-hidden-layer, fully connected neural network which transforms 1-D strain spectra to seafloor pressure spectra also outperforms the benchmark in wave height prediction (RMSE of 0.19 vs. 0.41 m), but does not generalize as well to the prior data. Regression-based machine learning is useful for estimating waves from DAS data when the pressure-strain relationship varies temporally and spatially across different wave conditions. Models can be applied to DAS data to measure waves with higher spatial resolution and longer temporal coverage than traditional methods, which often measure waves only at a single point.

Davis, Jacob R. [Univ. of Washington, Seattle, WA ↗
DOE OSTI2026

Pore-Scale Study on the Positive Feedback Between Stress and Porosity Caused by Pressure Solution in Porous Media

Pressure solution is an important process in the evolution of sedimentary rocks, which provide storage space for most of our petroleum resources. It directly influences the generation, migration, and storage of petroleum fluids in subsurface sedimentary rocks. Here, in this paper, we develop a pore-scale, mechanochemical model to demonstrate a possible positive feedback between the local porosity and pore surface stress, in which a higher local porosity causes a higher local pore surface stress, thus enhancing pressure solution and consequently further increasing the local porosity. Pore surface stress represents stress on a solid grain adjacent to a pore. Specifically, the pore-scale, mechanochemical model directly simulates the stress distribution over solid and pore surfaces using a finite element model. The dissolution of solids at the solid-pore interfaces under a far-from-equilibrium condition is simulated using a first-order kinetics model that accounts for the local stress distribution. The updated pore geometry, caused by pore surface dissolution, is then used in the stress simulation in the next numerical iteration. Two types of porous media, the Oriskany sandstone and an artificial porous medium with spherical pores, were tested in the mechanochemical simulation. The positive stress-porosity feedback during pressure solution was observed in both samples. In addition, the model quantitatively illustrated the distribution of local mineral dissolution rates on all pore surfaces, as well as its relation to the effective mineral dissolution rate of the entire sample. Based on the comparison between the two porous media, the local mineral dissolution was regulated by pore space distribution, geometry, and coalescence during pressure solution. This work is the first that uses direct, pore-scale numerical simulation to demonstrate the positive stress-porosity feedback during pressure solution, which has the potential to advance the understanding of the mechanical-chemical (MC) coupling in many geological processes that are relevant to subsurface energy systems, such as the recovery of petroleum hydrocarbons and geothermal energy.

CT scanning↗
DOE OSTI2026

Intelligent Experiments Through Real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and Future EIC Detectors (Final Report)

The overall vision of this project was to integrate real-time artificial intelligence (AI) directly into the data acquisition and detector-control systems of nuclear physics experiments, including both fast online event selection and an autonomous detector-control feedback loop. The work carried out under the award focused on the fast online event-selection half of that vision: the efficient recording of low-momentum heavy-flavor (HF) hadron decays in proton-proton collisions at the sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC)—an observable that requires fast tracking and topological trigger selection not previously demonstrated at RHIC, and that is essential for QCD studies at future facilities such as the Electron-Ion Collider (EIC). The autonomous detector-control (GPU-based feedback) component named in the project title remained a design concept and was not implemented under this award. The Massachusetts Institute of Technology (MIT) group led the offline simulation and data processing needed to train the machine-learning (ML) models, the translation of trained models to Field-Programmable Gate Array (FPGA) firmware using the hls4ml framework, and the physics validation of heavy-flavor reconstruction. Over the award period, the team developed and hardware-tested the principal components of an AI-based heavy-flavor trigger on simulated and recorded sPHENIX tracker data: a software Bipartite Graph Attention Network (BiGAT) trigger model reaching > 95% signal efficiency at 99% background rejection; an FPGA-native hit clusterizer matching the offline clustering; smaller networks synthesized to FPGA within the required sub-10 µs latency; and an assembled decoder–clusterizer–inference firmware chain exercised on the FELIX readout board. A complete, fully integrated hardware demonstrator was not finished within the award period. This report documents the project goals, the MIT group’s contributions, the technical accomplishments, and the outlook toward applications at the future EIC ePIC detector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Microstructure Clones

Background: A material’s microstructure drives its material performance. Contemporary crystal plasticity experiments compare full-field strain measurements of polycrystal specimens to models. Because each specimen is unique, it is impossible to know which features of the observed deformation are deterministic vs statistical; thus, differences between model and experiment may or may not be significant. Objective: This paper introduces the invention of microstructure clones. Microstructure clones are 2D oligocrystal specimens that have nearly identical microstructures to remedy the aforementioned experimental limitations. Having specimens with nearly identical microstructures will allow for multiple destructive tests of a microstructure (either as repeats or intentionally different experiments), an ability to “see the future” by providing insight into how a specimen will deform, variability quantification, and experimental investigations of response to small microstructural changes. Methods: This work introduces microstructure clones. Repeatability of these clones is demonstrated in tensile bars of pure nickel. Local strain measurements from digital image correlation are compared between clone specimens and compared to results from a crystal plasticity finite element model. Results: Two sets of microstructure clones were tested in this study and displayed very consistent deformation responses within each clone set. Small observed differences in deformation invite investigation into microstructure stochasticity and the effect of small microstructural and loading differences. Conclusions: Microstructure clones represent a significant shift in understanding structure–property relationships. This work reshapes experimental crystal plasticity to allow for experiments that control for specific variables, quantification of microstructural stochasticity (and other sources of stochasticity), and opportunities for replicating experiments.

Crystal Plasticity↗
DOE OSTI2025

Time-Varying Output Delay Compensation-A Model-Free Approach and its Application on Cooperative On-Ramp Merging

This paper presents a model-free approach to compensate for time-varying output delay in networked control systems. The proposed architecture combines a model-free observer and the Smith predictor. The model-free observer estimates the current state while handling modeling errors and uncertainties of the system. The Smith predictor moves the effect of time delay outside the control closed-loop using the estimated delayed output and the actual output of the plant. The proposed method is applied to a cooperative on-ramp merging problem. First, an ultra-local model predictive control is implemented to provide a computationally efficient online speed planner agnostic to the vehicle dynamics. After that, a model-free observer is designed to estimate the current state. Finally, the proposed architecture is tested against a time-varying output delay with an upper bound of 200 milliseconds. The results demonstrate the effectiveness of the proposed method with improved tracking of intervehicle distance.

Waleed khan, Muhammad [The University of Texas at ↗
DOE OSTI2024

Noncollinear polar magnet Fe 2 (SeO 3 ) 3 (H 2 O) 3 with inequivalent Fe 3+ sites

The emergence of novel magnetic states becomes more likely when the inversion symmetry of the crystal field, relative to the center between two spins, is broken. We propose that placing magnetic spins in inequivalent sites in a polar lattice can promote a realization of nontrivial magnetic states and associated magnetic properties. To test our hypothesis, we study Fe 2 (SeO 3 )(H 2 O) 3 as a model system that displays two distinct Fe(1) and Fe(2) magnetic sites in a polar structure (R3c space group). At low fields μ 0 H≤ 0.06 T, the material undergoes an antiferromagnetic ordering with T N1 = 77 K and a second transition at T N2 ≈ 4 K. At μ 0 H≥ 0.06 T and 74 K ≤T≤ 76 K, a positive entropy change of ∼0.12 mJ mol −1 K −1 can be associated with a metamagnetic transition to possibly nontrivial spin states. At zero field, Fe(1) is nearly fully ordered at T≈ 25 K, while Fe(2) features magnetic frustration down to T = 4 K. The magnetic ground state, a result corroborated by single-crystal neutron diffraction and 57 Fe Mössbauer spectroscopy, is a noncollinear antiparallel arrangement of ferrimagnetic Fe(1)–Fe(2) dimers along the c-axis. The results demonstrate that placing distinct magnetic sites in a polar crystal lattice can enable a new pathway to modifying spin, orbital, and lattice degrees of freedom for unconventional magnetism.

Crystal lattices↗
DOE OSTI2025

Lepton flavor violation by three units

The conservation of lepton flavor is a prediction of the Standard Model and is still an excellent approximate symmetry despite our observation of neutrino oscillations. Lepton flavor violation by one or two units has been discussed for decades, with several dedicated experiments exploring the vast model landscape but no discoveries so far. Here, we explore operators and processes that violate at least one lepton flavor by three units and identify testable signatures. In the Standard Model effective field theory, such operators already arise at mass dimension 7 and can be tested through their contributions to Michel parameters in leptonic decays. True neutrinoless charged-lepton flavor violation arises at mass dimension 10 and can realistically only be seen in the tau decay channels 𝜏 → $𝑒⁢𝑒⁢𝑒⁢\bar{𝜇}⁢\bar{𝜇}$ or 𝜏 → $𝜇⁢𝜇⁢𝜇\bar{𝑒}\bar{𝑒}$, for example in Belle II. Testable rates for these tau decays require light new particles and subsequently predict an avalanche of remarkably clean but so-far unconstrained collider signatures.

Feynman diagrams↗
DOE OSTI2025

Variational Simulation of the Lipkin-Meshkov-Glick Model on a Neutral Atom Quantum Computer

We simulate the Lipkin-Meshkov-Glick model using the variational-quantum-eigensolver algorithm on a neutral atom quantum computer. We test the ground-state energy of spin systems with up to 15 spins. Two different encoding schemes are used: an individual spin encoding where each spin is represented by one qubit, and an efficient Gray code encoding scheme that only requires a number of qubits that scales with the logarithm of the number of spins. This more efficient encoding, together with zero-noise extrapolation techniques, is shown to improve the fidelity of the simulated energies with respect to exact solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Microbes display broad diversity in cobamide preferences

ABSTRACT Cobamides, the vitamin B 12 (cobalamin) family of cofactors, are used by most organisms but produced by only a fraction of prokaryotes, and are thus considered key shared nutrients among microbes. Cobamides are structurally diverse, with multiple different cobamides found in most microbial communities. The ability to use different cobamides has been tested for several bacteria and microalgae, and nearly all show preferences for certain cobamides. This approach is limited by the commercial unavailability of cobamides other than cobalamin. Here, we have extracted and purified seven commercially unavailable cobamides to characterize bacterial cobamide preferences based on growth in specific cobamide-dependent conditions. The tested bacteria include engineered strains of Escherichia coli , Sinorhizobium meliloti , and Bacillus subtilis expressing native or heterologous cobamide-dependent enzymes, cultured under conditions that functionally isolate specific cobamide-dependent processes such as methionine synthesis. Comparison of these results to those of previous studies of diverse bacteria and microalgae revealed that a broad diversity of cobamide preferences exists not only across different organisms but also between different cobamide-dependent metabolic pathways within the same organism. The microbes differed in the cobamides that support growth most efficiently, cobamides that do not support growth, and the minimum cobamide concentrations required for growth. The latter differ by up to four orders of magnitude across organisms from different environments and by up to 20-fold between cobamide-dependent enzymes within the same organism. Given that cobamides are shared, required for use of specific growth substrates, and essential for central metabolism in certain organisms, cobamide preferences likely impact community structure and function. IMPORTANCE Nearly all bacteria are found in microbial communities with tens to thousands of other species. Molecular interactions such as metabolic cooperation and competition are key factors underlying community assembly and structure. Cobamides, the vitamin B 12 family of enzyme cofactors, are one such class of nutrients, produced by only a minority of prokaryotes but required by most microbes. A unique aspect of cobamides is their broad diversity, with nearly 20 structural forms identified in nature. Importantly, this structural diversity impacts growth as most bacteria that have been tested show preferences for specific cobamide forms. We measured cobamide-dependent growth in several model bacteria and compared the results to those of previous analyses of cobamide preference. We found that cobamide preferences vary widely across bacteria, showing the importance of characterizing these aspects of cobamide biology to understand the impact of cobamides on microbial communities.

Mok, Kenny C. (ORCID:0000000252276987)↗