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At least 865 records · Page 48

The new ITER baseline, research plan and open R&D issues

A new baseline (NB) has been proposed by the ITER Project to ensure a robust achievement of the Projects’ goals, in view of past challenges including delays incurred due to the Covid-19 pandemic, technical challenges in completing first-of-a-kind components and in nuclear licensing. The NB includes modifications to the configuration of the ITER device and its ancillaries (e.g. change from beryllium to tungsten as first wall material, modification of the heating and current drive mix, etc.) as well as additional testing of components (e.g. toroidal field coils) or phased installation (start with inertially cooled first wall before later installation of the final actively water-cooled components) to minimise operational risks. In the NB, the ITER research plan (IRP) will be divided into three main phases: (a) start of research operation, with 40 MW of ECH and 10 MW of ICH, which will focus on the demonstration of 15 MA operation in L-mode, commissioning of all required systems, including disruption mitigation, and the demonstration of H-mode plasma operation in deuterium; (b) DT-1, with 60–67 MW of ECH, 33 MW of neutral beam injection (NBI) and 10–20 MW of ICH, which will demonstrate robust operation in high confinement H-mode plasmas in DT up to Q ⩾ 10 and for burn durations of 300–500 s within an accumulated neutron fluence of ∼1% of the ITER machine’s lifetime total, and; (c) DT-2, with up to 67 MW of ECH, up to 49.5 MW of NBI and up to 20 MW of ICH, with the ITER tokamak and ancillaries in their final configuration to demonstrate routine operation in DT plasmas at high Q and the Q ⩾ 5 long-pulse and steady-state scenarios to the final neutron fluence and to perform R&D on nuclear fusion reactor issues. The logic, physics basis, modelling and experimental evaluations carried out to support the NB and the associated IRP are described. These include the impact of the tungsten wall on plasma scenarios and associated risk mitigation measures, as well as the optimisation of the tokamak components and ancillaries to minimise Project risks. Open R&D issues related to these evaluations and mitigation measures are also described together with experimental, modelling and validation activities required to address them.

ITER↗

Optical Activity of Chiral Excitons

Recent activity in the area of chiroptical phenomena has been focused on the connection between structural asymmetry, electron spin configuration and light/matter interactions in chiral semiconductors. In these systems, spin‐splitting phenomena emerge due to inversion symmetry breaking and the presence of extended electronic states, yet the connection to chiroptical phenomena is lacking. Here, in this study, we develop an analytical effective mass model of chiral excitons, parameterized by density functional theory. The model accounts for parity mixing of the band edge Bloch functions resulting from polar distortions, resulting in allowed magnetic dipole transitions. Through the study of a prototypical chiral 2D hybrid perovskite semiconductor, we show that circular dichroism of the chiral exciton and its interband continuum emerges from spin‐splitting via cross‐coupling of Rashba‐like and chiral/helical spin‐texture components. To demonstrate the generality of our approach, and as a counterpoint, we apply our model to describe chiroptical properties of three‐dimensionally confined excitons in perovskite nanocrystals that occur without chiral lattice distortions.

14 SOLAR ENERGY↗

Leveraging Curvature on N–Doped Carbon Materials for Hydrogen Storage

Carbon sorbent materials have shown great promise for solid-state hydrogen (H 2 ) storage. Modification of these materials with nitrogen (N) dopants has been undertaken to develop materials that can store H 2 at ambient temperatures. In this work density functional theory (DFT) calculations are used to systematically probe the influence of curvature on the stability and activity of undoped and N-doped carbon materials toward H binding. Specifically, four models of carbon materials are used: graphene, [5,5] carbon nanotube, [5,5] D 5d -C 120 , and C 60 , to extract and correlate the thermodynamic properties of active sites with varying degrees of sp 2 hybridization (curvature). From the calculations and analysis, it is found that graphitic N-doping is thermodynamically favored on more pyramidal sites with increased curvature. In contrast, it is found that the hydrogen binding energy is weakly affected by curvature and is dominated by electronic effects induced by N-doping. These findings highlight the importance of modulating the heteroatom doping configuration and the lattice topology when developing materials for H 2 storage.

08 HYDROGEN↗

A comprehensive study of the radiative properties of NO—a first step toward a complete air opacity

Here, in this paper we propose a methodology to calculate the radiative properties of the diatomic molecular constituents of air, and utilize the present approach to model the radiative properties of nitrogen monoxide, NO. We also investigate the important physics involved in calculating accurate radiative quantities for air, such as the Planck and Rosseland mean opacities, and emission and absorption coefficients, as well as the couplings accounted for in rovibrational calculations. Complete active space self-consistent field multi-reference configuration interaction (CAS-MRCI) calculations were performed in order to model the NO X 2 Π, a 4 Π, b 4 Σ - , 1 2 Σ + , 2 2 Σ + , 3 2 Σ + , G 2 Σ - , B' 2 Δ, (C, B) 2 2 Π, (H', L) 3 2 Π, and 1 2 Φ adiabatic states, and calculate the respective molecular data. The γ X 2 Π - A 2 Σ + , ε X 2 Π - D 2 Σ + , β' X 2 Π - B' 2 Δ, '11 000 Å' A 2 Σ + - D 2 Σ + , 'infrared' X 2 Π - X 2 Π and X 2 Π - (C, B) 2 2 Π (δ and β) band systems are investigated in monochromatic spectra calculations, as well as the Ogawa a 4 Π - b 4 Σ - band and several other band systems. Several conclusions are drawn, such as the importance of including the Ogawa band, which has not been included in previous air radiative models or comprehensive line-list calculations, as well as the importance of performing coupled rovibrational line-list calculations in order to accurately calculate the Rosseland means. We also found that the additional band systems modeled here contribute significantly to the total Planck and Rosseland means.

74 ATOMIC AND MOLECULAR PHYSICS↗

Tomographic imaging of atmospheric pressure plasma on complex surfaces

Many plasma types and behaviors such as streamer, arcs, cathode spots, anode spots, ionization waves, and magnetic field interactions create non-symmetric, fully 3D plasma structures. The plasma distribution in 3D space is heavily influenced by complex surfaces and the coupling interactions between plasma properties and the interfacing material properties. For example, ionization waves propagate in directions where ionization rates are highest, leading to complex configurations that are not fully understood or well characterized. Recent advances in laser diagnostics and models have been able to investigate well-controlled idealized plasmas in 2D fashion, but the complex structure in actual plasmas requires a technique than can provide a more complete 3D picture. However, 3D plasma diagnostics do not currently exist. To address this limitation, this activity will leverage available equipment to build a new tomographic optical imaging capability and advance the state-of-the-art in plasma diagnostics to investigate 3D phenomena on complex surfaces.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multiphysics Analysis of the MSRE Experiment Using Griffin-SAM Coupled Code System

Molten salt reactors (MSRs) with flowing fuel have the unique feature of utilizing the fuel salt for heat generation and extraction at the same time since the fuel salt is circulating through the whole primary loop of the reactor. This movement of the fuel salt results in a partial decay of the delayed neutron precursors (DNPs) outside the core and corresponding redistribution in the active core region. To capture this phenomenon accurately, neutronics and thermal hydraulics computational tools need to be modified to handle the movement of the DNPs and their decay. Idaho and Argonne National Laboratories are actively working on developing neutronics and thermal hydraulics tools to model MSRs with flowing fuel. The neutronics code Griffin and the thermal hydraulics code SAM were extended to handle flowing fuel with the drift of the DNPs under the MOOSE framework. In this work, a simplified Multiphysics model of the Molten Salt Reactor Experiment (MSRE) is developed and utilized to perform steady-state and transient analyses. The MSRE experiments were designed to show the impact of the DNPs losses on core reactivity. The following section provides a description of the MSRE experiment with the core main parameters used to develop the model. Then, the developed Multiphysics model of the MSRE is presented. Finally, steady-state verification tests and unprotected loss of flow transient tests are discussed followed by a summary and conclusions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Machine Learning-Guided Identification of PET Hydrolases from Natural Diversity

The enzymatic depolymerization of poly(ethylene terephthalate) (PET) is emerging as a leading chemical recycling technology for waste polyester. As part of this endeavor, new candidate enzymes identified from natural diversity can serve as useful starting points for enzyme evolution and engineering. In this study, we improved upon HMM searches by applying an iterative machine learning strategy to identify 400 putative PET-degrading enzymes (PET hydrolases) from naturally occurring homologs. Using high-throughput (HTP) experimental techniques, we successfully expressed and purified >200 enzyme candidates and assayed them for PET hydrolysis activity as a function of pH, temperature, and substrate crystallinity. From this library, we discovered 91 previously unknown PET hydrolases, 35 of which retain activity at pH 4.5 on crystalline material, which are conditions relevant to developing more efficient commercial processes. Notably, four enzymes showed equal to or higher activity than LCC-ICCG, a benchmark PET hydrolase, at this challenging condition in our screening assay, and 11 of which have pH optima <7. Using these data, we identified regions of PETases statistically correlated to activity at lower pH. We additionally investigated the effect of condition-specific activity data on trained machine learning predictors and found a precision (putative hit rate) improvement of up to 30% compared to a Hidden Markov Model alone. Our findings show that by pointing enzyme discovery toward conditions of interest with multiple rounds of experimental and machine learning, we can discover large sets of active enzymes and explore factors associated with activity at those conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nucleon Decays into Light New Particles in Neutrino Detectors

Proton and neutron decays into light new particles 𝑋 can drastically change the experimental signatures and benefit from the complementarity of large water-Cherenkov neutrino detectors such as Super- and Hyper-Kamiokande and tracking detectors such as JUNO and DUNE. The proton decays 𝑝 → ℓ + ⁢𝑋 and 𝑝 → 𝜋 + ⁢𝑋 with 𝑚 𝑋 near phase-space closure lead to charged particles below the Cherenkov threshold, rendering them practically invisible in Super- and Hyper-Kamiokande but not in JUNO and DUNE, which are therefore uniquely positioned for these baryon-number-violating signatures despite their smaller size. As an additional signature, such nucleon decays in the Earth can produce a sizable flux of 𝑋 particles in underground detectors. We present a simple model in which nucleons decay into sub-GeV sterile neutrinos that subsequently decay through active-sterile neutrino mixing, with a promisingly large number of events in Super-Kamiokande even in the seesaw-motivated parameter space.

Baryon & lepton number symmetries↗

Validation of Simulation Models for Wall-Connected Scrape off Layer Currents during MHD Activity in the HBT-EP Tokamak

This is the final report for the DOE award DE-SC0021657, titled “Validation of Simulation Models for Wall-Connected Scrape off Layer Currents during MHD Activity in the HBT-EP Tokamak” for the period September 1, 2020 – April 30, 2025. This award is part of a broader collaborative project, which supported training of a PhD student at Columbia University under the joint supervision of Dr. Levesque and Dr. Hansen (on award DE-SC0021325). The award supported research into computational models for plasma and 3D conducting structures in the vicinity relevant to tokamak disruptions and other mode activity (eg. RWMs) using the NIMROD and PSI-Tet codes. Additional detail on progress in support of these tasks is provided below.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Real-Space Local Dynamics in 1,2,3-Triazole Using Inelastic Neutron Scattering

Enhancing proton transport in polymer electrolytes is crucial for advancing next-generation solid-state batteries, yet our understanding of proton conductivity in nonaqueous environments remains limited due to a lack of atomic-scale insights. Here, in this study, we investigated the atomic-scale dynamics of 1,2,3-triazole, a small molecule capable of dynamic hydrogen bonding, as a model system for proton hopping in nonaqueous environments. Using the real-space correlation function determined by the double Fourier transformation of inelastic neutron scattering spectra, we identified that the self-motion of protons and intermolecular dynamics occur on comparable time scales. Furthermore, we observed that the activation energy associated with the intermolecular dynamics matches the energy barrier for molecular rotations determined through Density Functional Theory calculations. These findings underscore the importance of controlling molecular dynamics at the atomic scale to control proton transport. Additionally, we demonstrated that intermolecular dynamics in systems involving protons can be studied using inelastic neutron scattering even without deuteration, thereby providing a broader avenue for studying atomic-scale dynamics in soft matter systems.

Shinohara, Yuya [Oak Ridge National Laboratory (OR↗

Survey of U.S. Research Reactor Auxiliary Facilities Used for Material Testing and Basic Neutron Science

A catalogue of and attributes of the Materials Irradiation and Testing facilities (MIF) and the Basic Neutron Science facilities (BSF) of auxiliary (AUX) facilities of research reactors are compiled. The survey of these facilities is drawn from the set of U.S. university and DOE research reactor facilities and should be considered as a reference point when comparing commonalities in international AUX facilities. The size and shielding capabilities of the facilities, the typical characterization equipment used, and the neutron flux and irradiation capabilities of the facilities are listed. Short descriptions of experimental activities and current practices are detailed for MIFs and BSFs. The attributes are important in consideration of the reconfiguration of the facilities for purposes other than stated mission, i.e., for proliferation of weapons-usable nuclear material (WUNM). An evaluation of the capacity for production rate of WUNM from neutron beams-on-targets or a sample that has been placed in an irradiation position for a period is provided. Further evaluation of reconfiguration of these MIF and BSF are recommended to refine the proliferation risks. Specifically, MIF hot cells and potential configurations, additional modeling of facility throughput and development of methods for determining levels of concern for MIF and BSF have all been identified as steps for refinement of determination of the risks associated with these facilities. Future work will focus on: 1. A model of projected throughput for different MIF and BSF configurations that will be used to provide a window of potential operational misuse for a facility and better understand the capability of production and the rate of processing for WUNM in these facilities. 2. A misuse study for various configurations of MIF hot cell layouts detailing capacity, specifications, shielding constraints for MIF operations, identification of a maximum shielding thickness, and reasonable need associated with each activity performed in a MIF. 3. Development of a rule of thumb rating system utilizing data gathered from previous reports to show levels of concern at a given power level, flux, and experiment set.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Quantum oscillations in the activated conductivity in excitonic insulators: Possible application to monolayer WTe 2

A recent paper on the insulating state of monolayer WTe 2 reported the observation of large oscillations in the conductivity that are periodic in 1/B, resembling quantum oscillations in metals. This remarkable observation has inspired suggestions of exotic physics such as spin-charge separation. Here, we show that a rather more conventional but still nontrivial explanation in terms of gap modulation may be possible in a model of an excitonic insulator subject to a magnetic field.

2-dimensional systems↗

NEXTorch: A Design and Bayesian Optimization Toolkit for Chemical Sciences and Engineering

Automation and optimization of chemical systems require well-informed decisions on what experiments to run to reduce time, materials, and/or computations. Data-driven active learning algorithms have emerged as valuable tools to solve such tasks. Bayesian optimization, a sequential global optimization approach, is a popular active-learning framework. Past studies have demonstrated its efficiency in solving chemistry and engineering problems. Here we introduce NEXTorch, a library in Python/PyTorch, to facilitate laboratory or computational design using Bayesian optimization. NEXTorch offers fast predictive modeling, flexible optimization loops, visualization capabilities, easy interfacing with legacy software, and multiple types of parameters and data type conversions. It provides GPU acceleration, parallelization, and state-of-the-art Bayesian optimization algorithms and supports both automated an d human-in-the-loop optimization. The comprehensive online documentation introduces Bayesian optimization theory and several examples from catalyst synthesis, reaction condition optimization, parameter estimation, and reactor geometry optimization. NEXTorch is open-source and available on GitHub

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Loss and Isotopic Fractionation of Alkali Elements during Diffusion-Limited Evaporation from Molten Silicate: Theory and Experiments

Moderately volatile elements (MVEs) are variably depleted in planetary bodies, reflecting the imprints of nebular and planetary processes. Among MVEs, Na, K, and Rb are excellent tracers for unraveling the history of MVE depletion in planetary bodies because they have similar geochemical behaviors but can be chemically fractionated by evaporation and condensation processes. Furthermore, K and Rb are amenable to high-precision isotopic analyses, which can help constrain the conditions of evaporation and condensation. To quantitatively understand why Na, K, and Rb are depleted in planetary bodies, we have carried out vacuum evaporation experiments from basaltic melt at 1200 and 1400 °C to study their evaporation kinetics and isotopic fractionations. We chose this composition because it is relevant to evaporation from small differentiated planetesimals. The Rb isotopic compositions of the evaporation residues were measured by multicollector inductively coupled plasma mass spectrometry (MC-ICPMS), and the K isotopic compositions were measured along profiles across the residues by secondary ion mass spectrometry (SIMS). In the 1400 °C run products, we found that the concentrations of both K and Rb in the run products decreased from core to rim, which was accompanied by a heavy K isotope enrichment near the surface. This indicates that, in this run, evaporation was limited by diffusion. To use those data quantitatively, we derive analytical equations that describe the evaporation rate and isotopic fractionation associated with diffusion-limited evaporation from a sphere, slab, and cylinder in transient and quasi-steady state regimes. This model is used to tease out the roles that diffusive transport in the melt and evaporation at the melt/gas interface play in setting the elemental depletion and isotopic composition of the residue. Under our experimental conditions, volatility decreases in the order of Na, Rb, and K. Using our experimental results in a thermodynamic model, we have estimated the product γΓ of activity coefficients × evaporation coefficients of Na, Rb, and K. The measured isotopic compositions of the residues are well explained using Rayleigh distillations, whereby the relative volatilities of K and Rb isotopes are given by the square root of their masses. We use our results and previously published data to predict how K and Rb could have been lost as a function of temperature, melt composition, oxygen fugacity, and saturation degree relevant to Vesta’s building blocks. We find that the K and Rb depletions, K/Rb elemental fractionation, and δ 41 K and δ 87 Rb isotopic fractionations of Vesta (as sampled by howardite-eucrite-diogenite (HED) meteorites) are best explained by evaporation of submillimeter size objects for 0.1-10 years at moderate temperatures (~1050 °C) in a medium ~98.8% saturated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupled Hydromechanical Modeling of Induced Seismicity From CO 2 Injection in the Illinois Basin

Injection of CO 2 for geologic carbon sequestration into deep sedimentary formations involves fluid pressure increases that engage hydromechanical processes that can cause seismicity by activation of existing faults. In this work, we use a coupled multiphase fluid flow and geomechanical simulator to model spatiotemporal fluid pressure and stress changes in order to study the poroelastic effect of CO 2 injection on faults in crystalline basement rock below the injection zone. The seismicity rate along features interpreted to be basement faults is modeled using Dieterich's rate-and-state earthquake nucleation model. The methodology is applied to microseismicity detected during CO 2 injection into the Mount Simon formation during the Illinois Basin—Decatur Project. The modeling accurately captures an observed reduction in seismicity rate when the injection in the second well was into a slightly shallower zone above the base of the Mount Simon formation. Moreover, the modeling shows that it is important to consider poroelastic stress changes, in addition to fluid pressure changes for accurately modeling of the observed seismicity rate.

58 GEOSCIENCES↗

Energy Gap of the Even-Denominator Fractional Quantum Hall State in Bilayer Graphene

Bernal bilayer graphene hosts even-denominator fractional quantum Hall states thought to be described by a Pfaffian wave function with non-Abelian quasiparticle excitations. Here, in this study, we report the quantitative determination of fractional quantum Hall energy gaps in bilayer graphene using both thermally activated transport and by direct measurement of the chemical potential. We find a transport activation gap of 5.1 K at B = 12 T for a half filled N = 1 Landau level, consistent with density matrix renormalization group calculations for the Pfaffian state. However, the measured thermodynamic gap of 11.6 K is smaller than theoretical expectations for the clean limit by approximately a factor of 2. We analyze the chemical potential data near fractional filling within a simplified model of a Wigner crystal of fractional quasiparticles with long-wavelength disorder, explaining this discrepancy. Our results quantitatively establish bilayer graphene as a robust platform for probing the non-Abelian anyons expected to arise as the elementary excitations of the even-denominator state.

36 MATERIALS SCIENCE↗

Artificial Intelligence-Driven Management of Sustainable Energy Resources: Visibility, Operation, and Control

The rapid global transition toward sustainable energy resources (SERs) is reshaping how modern power systems are observed, optimized, and controlled. While SERs have significantly advanced decarbonization, their weather dependence, variability, and inverter-dominated characteristics challenge traditional, centralized, and deterministic grid operation. At the same time, the proliferation of high-resolution data from inverters, smart meters, and sensors offers unprecedented visibility into system dynamics. Yet, it also exceeds the analytical capability of conventional model-based approaches. Artificial intelligence (AI) provides a new foundation for addressing these challenges by bridging physical laws with data-driven learning, enabling accurate state awareness, adaptive operation, and coordinated control across distributed assets. This article examines how AI transforms the management of SER-rich power systems along three critical dimensions: 1) enhancing visibility by inferring behind-the-meter (BTM) activities, assessing SER flexibility, and reconstructing system states from sparse or noisy measurements; 2) improving operation through AI-enhanced SER service provision, volt/var control (VVC), and dynamic operating envelopes (DOE) for efficiency and security; and 3) advancing control by embedding learning-based intelligence into inverter coordination, voltage and frequency regulation, and long-term dispatch. Together, these developments reveal how AI can convert the variability of SERs from an operational challenge into a source of flexibility, resilience, and intelligence, paving the way toward sustainable, adaptive, and self-optimizing power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

New Virtual Test Bed Capabilities: Virtual DOME Model and New Updates to Repository

The Department of Energy (DOE) Office of Nuclear Energy National Reactor Innovation Center accelerates the deployment of novel reactor concepts by establishing both physical and virtual spaces for building and testing various components, systems, and complete pilot plants. The Virtual Test Bed represents the virtual arm of the National Reactor Innovation Center and is a joint effort with the DOE Nuclear Energy Advanced Modeling and Simulation Program. The Virtual Test Bed mission is to accelerate the deployment of advanced reactors by facilitating the adoption of cutting-edge DOE advanced modeling and simulation tools to design, evaluate, and license reactors. This is primarily achieved by storing example challenge problems in an externally available repository and by developing models to fill the M&S gaps needed for potential demonstrators. Activities conducted this fiscal year focused on developing of a Demonstration of Microreactor Experiments shield model to help accelerate the confirmatory analysis required for the reactor demonstration. This model and workflow will allow developers to leverage advanced modeling and simulation tools to ensure their reactor demonstration concept will meet dose requirements and that the surrounding shield will stay within concrete temperature limits during steady-state and transient operation conditions. An initial model has been developed to evaluate the temperature distribution in the concrete shield during steady-state operation, including neutron and gamma heating effects. Various modeling strategies have been examined to understand their applicability and limitations with different reactor designs to make the workflow as reactor-agnostic as possible and computationally effective to maximize its usability. In addition to describing the Demonstration of Microreactor Experiments shield model and associated results, this report summarizes other accomplishments regarding repository maintenance and improvement and new external models hosted on the repository.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗