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DOE OSTI2024

Identifying a novel pathway for extracellular electron uptake in Methanosarcina barkeri using shotgun

The overarching goal of this project was to identify the genetic and/or enzymatic basis for extracellular electron uptake in Methanosarcina barkeri—an organism we previously characterized to be capable of this process using poised potential electrodes and a range of electrochemical techniques. In our first aim, we will utilized proteomic techniques that labels extracellular proteins with free amine groups with biotin and perform a selective purification of these proteins from the rest of the proteome. These were identified using mass spectrometry, providing us insight into the identity of the cell surface proteins, including redox active proteins present during extracellular electron uptake. We will also used an isobaric tagging technique (iTRAQ labeling) of proteomes from different experiment conditions to look at differential proteins expression and better understand the total pathway involved in extracellular electron uptake coupled to methanogenesis. In our final aim, we will investigated the electrochemical nature of electron uptake in co-cultures, compared to our pure culture data sets. We predict the process of electron uptake from electrodes replicates what goes on in nature when these organisms for co-cultures with electrogenic microbes such as Geobacter, and to test this hypothesis we have begun to probe co-cultures electrochemically during direct interspecies electron transfer. Our final aim took much longer than expected due to challenges replicating co-cultures between Geobacter metallireducens and Methanosarcina barkeri. We found the major problem with this work was the inability of the M. barkeri strain we used (and we tried strains from three different labs) to successfully grow on acetate in the absence of hydrogen. As such, we began to use the strain Methanosarcina acetivorans—another close relative that specializes on acetate growth. We are currently in the process of comparing electrochemical observations of this microorganism between pure and co-culture experiments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Radiative Reconnection-powered TeV Flares from the Black Hole Magnetosphere in M87

Abstract Active galactic nuclei in general, and the supermassive black hole in M87 in particular, show bright and rapid gamma-ray flares up to energies of 100 GeV and above. For M87, the flares show multiwavelength components, and the variability timescale is comparable to the dynamical time of the event horizon, suggesting that the emission may come from a compact region near the nucleus. However, the emission mechanism for these flares is not well understood. Recent high-resolution general-relativistic magnetohydrodynamic simulations show the occurrence of episodic magnetic reconnection events that can power flares near the black hole event horizon. In this work, we analyze the radiative properties of the reconnecting current layer under the extreme plasma conditions applicable to the black hole in M87 from first principles. We show that abundant pair production is expected in the vicinity of the reconnection layer, to the extent that the produced secondary pair plasma dominates the reconnection dynamics. Using analytic estimates backed by two-dimensional particle-in-cell simulations, we demonstrate that in the presence of strong synchrotron cooling, reconnection can produce a hard power-law distribution of pair plasma imprinted in the outgoing synchrotron (up to a few tens of MeV) and the inverse-Compton signal (up to TeV). We produce synthetic radiation spectra from our simulations, which can be directly compared with the results of future multiwavelength observations of M87* flares.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Reconnection-driven Flares in M87*: Proton–Synchrotron-powered GeV Emission

Magnetic reconnection in current layers that form intermittently in radiatively inefficient accretion flows onto black holes is a promising mechanism for particle acceleration and high-energy emission. It has been recently proposed that such layers, arising during flux eruption events, can power the rapid TeV flares observed from the core of M87. In this scenario, inverse-Compton scattering of soft radiation from the accretion flow by energetic electron–positron pairs produced near the reconnection layer was suggested as the primary emission mechanism. However, detailed calculations show that radiation from pairs alone cannot account for the GeV emission detected by the Fermi observatory. In this work, we combine analytic estimates with 3D radiative particle-in-cell simulations of pair–proton plasmas to show that the GeV emission can be naturally explained by synchrotron radiation from protons accelerated in the current sheet. Although the exact proton content of the layer is uncertain, our model remains robust across a broad range of proton-to-pair number density ratios. While protons are subdominant in number compared to pairs, our simulations demonstrate that they can be accelerated more efficiently, leading to a self-regulated steady state in which protons dominate the energy budget. Ultimately, proton synchrotron emission accounts for approximately 5%–20% of the total dissipation power. The majority is radiated as MeV photons via pair synchrotron emission, with a smaller fraction emitted as TeV photons through inverse-Compton scattering.

Active galactic nuclei↗

DOE OSTI2025

ON THE EFFECTIVENESS OF LLMS IN UNIT TEST GENERATION FOR STRUCTURED TEXT PROGRAMS

The reliability of industrial automation systems heavily depends on the correctness of Programmable Logic Controller (PLC) programs, which are often written in Structured Text (ST). While Large Language Models (LLMs) have shown promise in automating test generation for mainstream programming languages, their effectiveness for the syntactically strict ST language remains underexplored. This thesis presents a systematic empirical evaluation of three state-of-the-art LLMs—GPT-4o, Gemini 2.5 Pro, and Claude Sonnet 4.5—for generating ST unit tests. We examine three prompting strategies: Natural Language (NL), Code Language (CL), and Chain-of-Thought (CoT), across a curated set of 11 ST function blocks. The quality of the generated tests is assessed using Compilation Success Rate (CSR), Statement Coverage (SC), and Branch Coverage (BC). In the zero-shot setting, Claude Sonnet 4.5 achieves the highest CSR, while Gemini 2.5 Pro consistently delivers the best statement and branch coverage, particularly under CL prompts. By incorporating a one-shot CL prompt, all models exhibit substantial improvements—most notably GPT-4o, whose CSR increases from 45.45% to 90.91%, with substantial gains in both SC and BC. To further contextualize these findings, we compare GPT-4o’s one-shot results with PLCAutoTester, a state-ofthe- art ST unit test generation tool, on an additional benchmark dataset. While LLMgenerated tests approach competitive coverage levels, PLCAutoTester maintains significantly higher and more stable coverage across programs. This study provides the first comprehensive benchmark of modern LLMs for ST unit testing, highlighting their strengths, limitations, and improvements through one-shot prompting, and positioning their performance relative to specialized automated testing tools in industrial automation.

42 ENGINEERING↗

DOE OSTI2022

Sensory stimulation for upper limb amputations modulates adaptability of cortical large-scale systems and combination of somatosensory and visual inputs

Abstract Touch-like phantom limb sensations can be elicited through targeted transcutaneous electrical nerve stimulation (tTENS) in individuals with upper limb amputation. The corresponding impact of sensory stimulation on cortical activity remains an open question. Brain network research shows that sensorimotor cortical activity is supported by dynamic changes in functional connections between relevant brain regions. These groups of interconnected regions are functional modules whose architecture enables specialized function and related neural processing supporting individual task needs. Using electroencephalographic (EEG) signals to analyze modular functional connectivity, we investigated changes in the modular architecture of cortical large-scale systems when participants with upper limb amputations performed phantom hand movements before, during, and after they received tTENS. We discovered that tTENS substantially decreased the flexibility of the default mode network (DMN). Furthermore, we found increased interconnectivity (measured by a graph theoretic integration metric) between the DMN, the somatomotor network (SMN) and the visual network (VN) in the individual with extensive tTENS experience. While for individuals with less tTENS experience, we found increased integration between DMN and the attention network. Our results provide insights into how sensory stimulation promotes cortical processing of combined somatosensory and visual inputs and help develop future tools to evaluate sensory combination for individuals with amputations.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Monotonic multi-state quantum f -divergences

We use the Tomita–Takesaki modular theory and the Kubo–Ando operator mean to write down a large class of multi-state quantum f-divergences and prove that they satisfy the data processing inequality. For two states, this class includes the (α, z)-Rényi divergences, the f-divergences of Petz, and the Rényi Belavkin-Staszewski relative entropy as special cases. The method used is the interpolation theory of non-commutative Lωp spaces, and the result applies to general von Neumann algebras, including the local algebra of quantum field theory. We conjecture that these multi-state Rényi divergences have operational interpretations in terms of the optimal error probabilities in asymmetric multi-state quantum state discrimination.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Ordering the topological order in the fractional quantum Hall effect

Here, we discuss the possible topological order/topological quantum field theory of different quantum Hall systems. Given the value of the Hall conductivity, we constrain the global symmetry of the low-energy theory and its anomaly. Specifically, the one-form global symmetry and its anomaly are presented as the organizing principle of these systems. This information is powerful enough to lead to a unique minimal topological order (or a small number of minimal topological orders). Almost all of the known experimentally discovered topological orders are these minimal theories. Since this work is interdisciplinary, we made a special effort to relate to researchers with different backgrounds by providing translations between different perspectives.

Anyons↗

DOE OSTI2025

Greedy emulators for nuclear two-body scattering

Applications of reduced basis method emulators are increasing in low-energy nuclear physics because they enable fast and accurate sampling of high-fidelity calculations, enabling robust uncertainty quantification. Here, in this paper, we develop, implement, and test two model-driven emulators based on the (Petrov-)Galerkin projection using the prototypical test case of two-body scattering with the Minnesota potential and a more realistic local chiral potential. The high-fidelity scattering equations are solved with the matrix Numerov method, a reformulation of the popular Numerov recurrence relation for solving special second-order differential equations as a linear system of coupled equations. A novel error estimator based on reduced-space residuals is applied to an active learning approach (a greedy algorithm) to choosing training samples (“snapshots”) for the emulator and contrasted with a proper orthogonal decomposition (POD) approach. Both approaches allow for computationally efficient offline-online decompositions, but the greedy approach requires many fewer snapshot calculations. These developments set the groundwork for emulating scattering observables based on chiral nucleon-nucleon and three-nucleon interactions and optical models, where computational speed-ups are necessary for Bayesian uncertainty quantification. Our emulators and error estimators are widely applicable to linear systems.

Bayesian methods↗

DOE OSTI2022

Clinical 6 MV X-Ray Facility Photo-Neutron/Fission Interrogations with TMFD Sensors

Detection of several targets (U, Be, D2O) of interest to national security has been achieved at Purdue University’s 6 MV (~104 R/h) X-Ray clinical linear accelerator (CLINAC), from photoneutron/fission induced neutron signatures using a Centrifugally Tensioned Metastable Fluid Detector (CTMFD). Traditional neutron detection schemes were saturated and ineffective under the intense (to ~104 R/h) photon environment; however, the CTMFD sensor technology was capable of measuring the relatively insignificant (~10-12x lower intensity) neutron field produced from 6 MeV-end point X-Ray beam interactions with the CLINAC components and surroundings. This is in stark contrast to published results based on conventional belief for immeasurable neutron dose in 6 MV CLINAC facilities. Photoneutron and photofission neutron production rates were detected and analyzed at various standoffs from the isocenter, with and without special nuclear material (SNM) related targets ranging in mass from 5 g of Be, to ~0.6 kg of UO2. It was confirmed that 6 MV X-Ray photons do result in measurable neutron dose above normal cosmic background. Additionally, in threshold mode, the CTMFD operating under a tensioned metastable pressure of -5bar, enabled conclusive rejection of background photoneutrons, while enabling the rapid detection of: Be, D2O, C and U targets within seconds to minutes while operating in and around 104 R/h photon fields.

Ozerov, Stepan↗

DOE OSTI2022

Prospects for ${B}_{(s)}^0 $ → π$^0$π$^0$ and ${B}_{(s)}^0 $ → ηη modes and corresponding CP asymmetries at Tera-Z

The physics potential of measuring $B^0_{(s)}$ → $π^0π^0$ and $B^0_{(s)}$ → $ηη$ decays via four-photon final states at Tera-Z phase of CEPC or FCC-ee is investigated in this paper. We propose an electromagnetic calorimeter (ECAL) with both high energy resolution and excellent separation power to efficiently reconstruct $π^0$ and $η$ from hadronic final states with high photon multiplicity. The resulting B-meson mass resolution is approximately 30 MeV, allowing 3 $σ$ separation between B 0 and $B^0_{(s)}$. With the assistance of the b-jet tagging, the relative sensitivities to B 0 → $π^0π^0$, $B^0_{(s)}$ → $π^0π^0$, B 0 → $ηη$, and $B^0_{(s)}$ → $ηη$ signal strengths at Tera-Z are projected as 0.45%, 4.5%, 18%, and 0.95%, respectively. Their dependence on various detector performances is also discussed. In addition, B 0 → $π^0π^0$ and its two isospin-related modes are paid special attention due to their roles in the determination of the CKM angle α (Φ 2 ). The anticipated precisions of their branching-ratio and CP-asymmetry measurements at Tera-Z are evaluated. We show that the measurement of the time-integrated B 0 → $π^0π^0$ CP asymmetry at Tera-Z is complementary to B-factory ones. The precision on α combining Z- and B-factory results reaches 0.4°, lower than the systematic uncertainties attached to isospin breaking.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

All-Atom Simulation of 3D Hot Spot Formation in Shocked TATB Explosive

TATB is an insensitive high explosive (IHE) critical to the stockpile that is challenging to model at the continuum scale. Advanced detonation models in the Cheetah high explosive chemistry code require validation though subscale simulations. High explosive initiation is determined by micron-scale physics of hot spots formed a shock-collapsed pores. Pore sizes between 100 nm and 1 μm are believed to be the most important for determining the shock sensitivity of TATB. This range of pore sizes is difficult to access at the atomic scale through allatom molecular dynamics (MD) simulations, even with Sierra-class computers. Quasi-2D simulations are widely used and allow much larger pore sizes (up to 400 nm) to be studied, but the applicability of 2D simulations to the actual 3D pore response is not understood. Resolving these uncertainties through “full physics” MD modeling is key for generalizing, parameterizing, and validating the kinds of continuum models used to inform design, safety, and performance. This work was a continuation of FY20 efforts pushing simulations to full 3D with the largest-ever all-atom simulations of an explosive. These were the first all-atom full-3D simulations of large hot spots thought to govern explosive detonation and required over a billion atoms. Simulations were performed using LAMMPS, an open SNL science code. MD explosive models present unique challenges, even for established codes such as LAMMPS. Their model forms are more complex than typical models for metals, while simulating high temperature-pressure conditions is demanding and increases computational cost. Scaling problems in GPU-enabled MD algorithms initially limited simulations to <100 million atoms but were resolved through collaboration with SNL. An overall 24x speedup was obtained relative to CPU machines. Specialized analysis of these simulations required a bottom-up refactoring and algorithm parallelization of in-house codes and application of computer vision algorithms to extract meaningful information.

36 MATERIALS SCIENCE↗

DOE OSTI2025

MoRE-Brain: Routed Mixture of Experts for Interpretable and Generalizable Cross-Subject fMRI Visual Decoding

Decoding visual experiences from fMRI offers a powerful avenue to understand human perception and develop advanced brain-computer interfaces. However, current progress often prioritizes maximizing reconstruction fidelity while overlooking interpretability, an essential aspect for deriving neuroscientific insight. To address this gap, we propose MoRE-Brain, a neuro-inspired framework designed for high-fidelity, adaptable, and interpretable visual reconstruction. MoRE-Brain uniquely employs a hierarchical Mixture-of-Experts architecture where distinct experts process fMRI signals from functionally related voxel groups, mimicking specialized brain networks. The experts are first trained to encode fMRI into the frozen CLIP space. A finetuned diffusion model then synthesizes images, guided by expert outputs through a novel dual-stage routing mechanism that dynamically weighs expert contributions across the diffusion process. MoRE-Brain offers three main advancements: First, it introduces a novel Mixture-of-Experts architecture grounded in brain network principles for neuro-decoding. Second, it achieves efficient cross-subject generalization by sharing core expert networks while adapting only subject-specific routers. Third, it provides enhanced mechanistic insight, as the explicit routing reveals precisely how different modeled brain regions shape the semantic and spatial attributes of the reconstructed image. Extensive experiments validate MoRE-Brain’s high reconstruction fidelity, with bottleneck analyses further demonstrating its effective utilization of fMRI signals, distinguishing genuine neural decoding from over-reliance on generative priors. Consequently, MoRE-Brain marks a substantial advance towards more generalizable and interpretable fMRI-based visual decoding.

Wei, Yuxiang [Georgia Institute of Technology]↗

DOE OSTI2020

Guest Editorial: Planning and operation of resilient distribution system for integrated multi-energy

Resilience is the ability of power systems to prepare for and adapt to low-probability, high-impact incidents and withstand and recover rapidly from disruptions. With the ageing of electricity distribution infrastructure and increasing threats of weather-related incidents and natural disasters, the need to effectively enhance the resilience of the electricity distribution system has become urgent and has attracted worldwide attention. Although there are an increasing number of publications related to enhancing resilience strategies, resilience is an emerging concept in power systems. Existing practices are mostly focused on deploying distributed energy resources (DERs) and microgrids, hardening the existing infrastructures and building redundant capacities. However, from a broader perspective, resilience enhancement of power distribution system is a systematic engineering, involving long-term system planning and upgrading (e.g., deployment of smart grid technologies and intelligent switches), short-term proactive scheduling, real-time robust and resilient control of DERs, and post-event restoration and recovery strategies. Based on this point, this Special Issue in IET Energy System Integration focuses on soliciting the most recent and original technologies, scheduling and control strategies for improving the resilience of power distribution system. Eight papers are presented in this Special Issue, covering various aspects related to resilience enhancement of power distribution system, including fault-tolerant frequency measurement, robust scheduling of integrated electricity and district heating systems, robust control of DERs, efficient methods for safety verification as well as novel graph theory-based approach to restore the distribution systems after multiple simultaneous faults. A brief introduction of these 8 papers is provided below.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

The connection between nonzero density and spontaneous symmetry breaking for interacting scalars

We consider U(1)-symmetric scalar quantum field theories at zero temperature. At nonzero charge densities, the ground state of these systems is usually assumed to be a superfluid phase, in which the global symmetry is spontaneously broken along with Lorentz boosts and time translations. We show that, in d > 2 spacetime dimensions, this expectation is always realized at one loop for arbitrary non-derivative interactions, confirming that the physically distinct phenomena of nonzero charge density and spontaneous symmetry breaking occur simultaneously in these systems. We quantify this result by deriving universal scaling relations for the symmetry breaking scale as a function of the charge density, at low and high density. Moreover, we show that the critical value of μ above which a nonzero density develops coincides with the pole mass in the unbroken, Poincaré invariant vacuum of the theory. The same conclusions hold non-perturbatively for an O(N) theory with quartic interactions in d = 3 and 4, at leading order in the 1/N expansion. We derive these results by computing analytically the zero-temperature, finite-μ one-loop effective potential, paying special attention to subtle points related to the iε terms. We check our results against the one-loop low-energy effective action for the superfluid phonons in λΦ 4 theory in d = 4 previously derived by Joyce and ourselves, which we further generalize to arbitrary potential interactions and arbitrary dimensions. As a byproduct, we find analytically the one-loop scaling dimension of the lightest charge-n operator for the λΦ 6 conformal superfluid in d = 3, at leading order in 1/n, reproducing a numerical result of Badel et al. For a λΦ 4 superfluid in d = 4, we also reproduce the Lee-Huang-Yang relation and compute relativistic corrections to it. Finally, we discuss possible extensions of our results beyond perturbation theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Evaluation of a positron-emission-tomography-based SiPM readout for compact segmented neutron imagers

Gamma-ray emission from special nuclear material (SNM) is relatively easy to shield from detection using modest amounts of high-Z material. In contrast, fast-neutrons are much more penetrating and can escape relatively thick high-Z shielding without losing significant energy. Furthermore, fast neutrons provide a clear and unambiguous signature of the presence of SNM with few competing natural background sources. The challenge of detecting fast neutrons is twofold. First, the neutron flux from SNM are only a fraction of the corresponding gamma-ray flux. Second, fast neutrons can be difficult to differentiate from gamma rays. The ability to discriminate gamma rays from neutrons, combined with a neutron imaging capability, can in some situations enable the localization of SNM neutron sources distinct from background. With the developments of pulse-shape-sensitive plastic scintillators that offer excellent gamma-ray/neutron discrimination, and arrays of silicon photomultipliers combined with highly scalable and fast positron-emission-tomography (PET) multi-channel readout systems, field-deployable neutron imagers suitable for SNM detection might now be within reach. In this paper, we present a characterization of the performance of a recently available commercial PET-scanner readout, including its sensitivity to pulse-shape differences between fast neutrons and gamma rays, energy and timing resolution. Here, we find that, while the pulse-shape discrimination is achievable with stilbene, further improvement of the readout is required to achieve it with the PSD-capable available plastic scintillators.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

AFM Special Issue Summary - Integrating Surface Flux with Boundary Layer Measurements

To help bridge science topics related to land-atmosphere interactions, we organized a virtual special issue in this journal (Agricultural and Forest Meteorology [AFM]) entitled, “Land-Atmosphere Interactions: Integrating Surface Flux with Boundary Layer Measurements.” The motivation for the special issue was driven by existing disciplinary barriers between research areas that all address land-atmosphere interactions. In particular, it addressed research silos between those who study features of the land surface, surface fluxes (including water, energy, and trace gases), atmospheric boundary layer growth and thermodynamics, and atmospheric composition and aerosols. The special issue sought to bring these communities together to integrate multiple observations across the soil-vegetation-atmosphere continuum with the aim of 1) improving broader understanding of land-atmosphere interactions, feedbacks, and coupling, 2) fostering new collaborations between atmospheric and surface flux scientists, and 3) identifying new paths for integrative research. In this report we provide an overview and synthesis of the special issue.

58 GEOSCIENCES↗

DOE OSTI2020

Recovering the QNEC from the ANEC

We study the relative entropy in QFT comparing the vacuum state to a special family of purifications determined by an input state and constructed using relative modular flow. We use this to prove a conjecture by Wall that relates the shape derivative of relative entropy to a variational expression over the averaged null energy (ANE) of possible purifications. Furthermore, this variational expression can be used to easily prove the quantum null energy condition (QNEC). We formulate Wall’s conjecture as a theorem pertaining to operator algebras satisfying the properties of a half-sided modular inclusion, with the additional assumption that the input state has finite averaged null energy. We also give a new derivation of the strong superadditivity property of relative entropy in this con- text. We speculate about possible connections to the recent methods used to strengthen monotonicity of relative entropy with recovery maps.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Comparison and multi-model inference of excess risks models for radiation-related solid cancer

In assessments of detrimental health risks from exposures to ionising radiation, many forms of risk to dose–response models are available in the literature. The usual practice is to base risk assessment on one specific model and ignore model uncertainty. The analysis illustrated here considers model uncertainty for the outcome all solid cancer incidence, when modelled as a function of colon organ dose, using the most recent publicly available data from the Life Span Study on atomic bomb survivors of Japan. Seven recent publications reporting all solid cancer risk models currently deemed plausible by the scientific community have been included in a model averaging procedure so that the main conclusions do not depend on just one type of model. The models have been estimated with different baselines and presented for males and females at various attained ages and ages at exposure, to obtain specially computed model-averaged Excess Relative Risks (ERR) and Excess Absolute Risks (EAR). Monte Carlo simulated estimation of uncertainty on excess risks was accounted for by applying realisations including correlations in the risk model parameters. Three models were found to weight the model-averaged risks most strongly depending on the baseline and information criteria used for the weighting. Fitting all excess risk models with the same baseline, one model dominates for both information criteria considered in this study. Based on the analysis presented here, it is generally recommended to take model uncertainty into account in future risk analyses.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗