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452 records · Page 21

SOLPS-ITER modeling of a dedicated divertor for negative triangularity operation on DIII-D

The design of a new dedicated divertor for negative triangularity (NT) operation on DIII-D with neutral baffles and pumping is informed by SOLPS-ITER transport modeling. This dedicated NT divertor is the latest step in a progression of NT shapes with various divertor characteristics explored on DIII-D, including NT shapes at reduced triangularity and a campaign with stronger shaping that included new armored components on the outboard side. SOLPS simulations played a key role in these divertor designs. Interpretive simulations, using cross-field diffusivities constrained by experimental data in the NT Shelf shape were used to inform the design of the 2023 armor campaign components. A similar procedure used armor campaign data to predict conditions for the dedicated NT divertor. The predictive simulations were used to assess the divertor fluxes, detachment threshold, pumped flux, and neutral leakage. For the dedicated NT divertor, SOLPS simulations and two-point-modeling were used to show the relative impact of magnetic topology (mainly longer connection length) and divertor closure on the divertor conditions relative to the armor campaign. It is predicted that the dedicated NT divertor reaches detachment (measured by target ion flux rollover) at a lower upstream density (≈(1.75−−2.4)×1⁢019m−3) as compared to the armor campaign shape. For the preliminary design geometry, divertor closure reduces the neutral leakage by ≈10%. Parametric optimization indicating further ≈20%–60% improvement in the leakage flux and recycled flux crossing the pump entrance is possible for relatively minor changes to the divertor and baffle layout.

Lore, Jeremy [ORNL] (ORCID:000000029192465X)

Temperature-dependent spin dynamics in Cr 2 O 3

Cr 2 ⁢O 3 emerges as a prominent candidate material for spintronics and magnetoelectronic applications. However, a comprehensive understanding of its temperature-dependent spin dynamics remains elusive, impeding the engineering of novel spintronics based on this material. Here, we delve into this through a combination of inelastic neutron scattering experiments and atomistic simulations. Our results unveiled the emergence of paramagnons above and below 𝑇 𝑁 . We demonstrated a significant softening of linear magnons upon heating in the antiferromagnetic state. Further analysis revealed that this softening primarily originated from four-magnon interactions, while thermal expansion played a minor role.

antiferromagnetism

Decoupling the capacity fade contributions in polymer electrolyte-based high-voltage solid-state batteries

Polymer electrolyte (PE)-based solid-state batteries (PE-SSBs) made with high-voltage cathodes are known to suffer from severe capacity fade, stemming primarily from the poor oxidative stability of most PEs under high-voltage cycling conditions. PEs also suffer from greater ion-transport limitations compared to liquid or solid electrolytes. However, often, these limitations are collectively stated to be responsible for the observed capacity fade, and it is challenging to decouple the contributions of different factors. Herein, a tunable cell fabrication platform was developed to systematically investigate and decouple the two primary capacity fade drivers (cell impedance growth and kinetic limitations), while keeping the other cell parameters constant. Three PE types with distinct transport characteristics were compared. By utilizing a voltage profile analysis method, the contribution of the cell's internal impedance growth was quantitatively decoupled from the kinetic limitations stemming from the high concentration gradient in the polymer catholyte and slow charge transfer reactions. We demonstrate that the high interfacial impedance did not necessarily correlate with the high capacity fade rate. Kinetic limitations that are not reflected by impedance measurements can play a dominant role in causing cumulative capacity decay.

Ock, Ji-young [Oak Ridge National Laboratory (ORNL

Experimental observation and integrated modelling of proton-beryllium fusion in He and D plasmas at JET

Validated integrated modelling of JET ITER-like wall experiments in which fusion performance is driven by reactions between fast ions and intrinsically present metal wall impurities is presented. A steady-state L-mode plasma with dominant proton-beryllium fusion and neutron yields of up to ≈ 6·10 13 s -1 is developed in He and D, via radiofrequency heating of a H minority. The fusion drive is unambiguously confirmed by the neutral particle analyser, fast ion loss detector, and γ-ray diagnostics. Experiments are analysed via an integrated modelling framework, developed to model the two-stage proton beryllium-fusion chain and produce high-fidelity fusion product source terms. The modelling chain comprises TRANSP and JETTO for plasma core modelling, LOCUST for full orbit product tracking and collisional slowing-down, DRESS to resolve two- and three-body fusion kinematics, and MCNP for neutron transport calculations. Modelling shows that the primary 9 Be(p,n) 9 B reaction is the dominant neutron emitter at naturally present concentrations of beryllium in these experiments. The yield contribution of secondary reactions between fusion products and beryllium, 9 Be(d,n) 10 B and 9 Be(α,n) 12 C, is found to be negligible. The proton-deuteron knock-on effect in D plasmas is modelled, which is calculated to contribute ≈ 25% to the total neutron yield. For both He and D discharges the total computed neutron rates match fission chamber (FC) measurements within the combined experimental and computational uncertainty, with an average discrepancy of ≈ ± 20%. Realistic proton-beryllium neutron sources are propagated through JET’s MCNP neutron transport model which shows that 235 U FCs’ response is sensitive to p–Be source changes, with up to ≈ 10% variation compared to a D–D neutron source. We show that the high-energy tail of the fast proton minority can be studied with multi-foil neutron activation. The framework is also applied to the study of interactions between fast protons and boron impurities, of relevance to ITER. We calculate that in JET conditions a significant alpha source with DT-like energies could be generated through 11 B(p, α)2α fusion, and detected via γ-emission in secondary interactions between fast alphas and boron. The work represents an important step towards validating predictive integrated modelling capabilities for non-standard fusion reactions.

JET

The phase diagram of quantum chromodynamics in one dimension on a quantum computer

The quantum chromodynamics (QCD) phase diagram, which reveals the state of strongly interacting matter at different temperatures and densities, is key to answering open questions in physics, ranging from the behaviour of particles in neutron stars to the conditions of the early universe. However, classical simulations of QCD face significant computational barriers, such as the sign problem at finite matter densities. Quantum computing offers a promising solution to overcome these challenges. Here, we take an important step toward exploring the QCD phase diagram with quantum devices by preparing thermal states in one-dimensional non-Abelian gauge theories. We experimentally simulate the thermal states of SU(2) and SU(3) gauge theories at finite densities on a trapped-ion quantum computer using a variational method. This is achieved by introducing two features: Firstly, we add motional ancillae to the existing qubit register to efficiently prepare thermal probability distributions. Secondly, we introduce charge-singlet measurements to enforce colour-neutrality constraints. This work pioneers the quantum simulation of QCD at finite density and temperature for two and three colours, laying the foundation to explore QCD phenomena on quantum platforms.

Quantum information

Final Report: Process Intensification of Hydrogen Production through Sorption-Enhanced Gasification of Biomass

The University of Utah, in partnership with Idaho National Laboratory (INL), evaluated Sorption-Enhanced Gasification (SEG) as a transformative pathway for producing hydrogen with the potential for negative CO 2 emissions. SEG integrates gasification, water-gas shift, and in-situ carbon capture within a dual fluidized bed reactor to enable efficient clean hydrogen production. Key challenges related to biomass variability and process complexity were addressed through feedstock engineering, reaction optimization, and process validation. A co-pelletized biomass–limestone feedstock was developed to simplify feeding and introduction of makeup limestone. Kinetic and sorbent studies identified optimal operating conditions and confirmed the suitability of low-cost limestone, while catalysts were developed to reduce tar formation. Reactor modeling and techno-economic analysis indicated that SEG can achieve competitive hydrogen production costs, particularly when combined with carbon incentives, supporting its potential for scale-up and carbon-negative operation.

08 HYDROGEN

Lessons learned from the development and implementation of a workforce training curriculum for advanced controls for high performance HVAC systems

Over the past decade, academic research on advanced controls has slowly transitioned into new software platforms, giving rise to various companies developing and deploying these innovative products, including solutions for light commercial HVAC systems. However, the current workforce remains widely unprepared to install, maintain and operate these systems, particularly complex software-based control platforms, as most workforce training programs still focus on traditional building automation for large commercial buildings. This paper presents the development and piloting of curriculum for three key types of professionals: ● Technicians (trade-level): installing and maintaining modern high-performance HVAC systems and controls ● Programmers (undergrad-level): developing and implementing advanced controls ● Engineers and energy professionals (undergrad/grad-level): managing and evaluating system performance We share details of the material developed including training videos, open-source software, instruction manuals. We also present the results of a pilot implementation of the training materials with real students.

Casillas, Armando

Nuclear Safety [Vol. 37, No. 2, April-June 1996]

Nuclear Safety is a journal that covers significant issues in the field of nuclear safety. Its primary scope is safety in the design, construction, operation, and decommissioning of nuclear power reactors worldwide and the research and analysis activities that promote this goal, but it also encompasses the safety aspects of the entire nuclear fuel cycle, including fuel fabrication, spent-fuel processing and handling, and nuclear waste disposal, the handling of fissionable materials and radioisotopes, and the environmental effects of all these activities. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 97 The Nuclear Community and the Public: Cognitive and Cultural Influences on Thinking About Nuclear Risk, M. A. Meyer; 109 Twenty-Third Water Reactor Safety Information Meeting, D. A. Copinger; ACCIDENT ANALYSIS: 126 Analysis of a PWR LBLOCA Without SCRAM, Trevor N. Tyler, Rafael Macian-Juan and John H. Mahaffy; DESIGN FEATURES: 139 Vulnerability of Multiple-Barrier Systems, N. C. Lind; ENVIRONMENTAL EFFECTS: 149 A Study of Wet Catalytic Oxidation of Radioactive Spent Ion Exchange Resin by Hydrogen Peroxide, Xingchao Jian, Tianbao Wu, and Guichun Yun; 157 A Comparison Study and Resolution of Differences Between Emergency Response and Safety Analysis Codes Used at the Savannah River Site, A. A. Simpkins; OPERATING EXPERIENCES: 164 Reactor Shutdown Experience, Compiled by J. W. Cletcher; RECENT DEVELOPMENTS: 167 Reports, Standards, and Safety Guides, D. S. Queener; 172 Proposed Rule Changes as of Dec. 31,1995; ANNOUNCEMENTS: 178 American Nuclear Society 1997 Annual Meeting; 178 American Nuclear Society Nuclear Criticality and Safety Division Topical Meeting; 176 The Authors.

05 NUCLEAR FUELS

Ultrafast Nanoimaging of Carrier Funneling in Composition-Graded Semiconductor Nanowires

Recent advances in bandgap engineering of low-dimensional semiconductors have enabled high-efficiency carrier transport in miniaturized electronic and optoelectronic devices. The physical properties and functionalities of these materials are governed by complex carrier dynamics coupled with multiple transport mechanisms in tailored band structures. Here, we report ultrafast nanoimaging of carrier funneling and recombination in composition-grade CdSxSe1-x nanowires using pump-probe near-field nanoscopy. Leveraging the high resolution of this technique in both space and time, we resolve nanoscale local carrier dynamics along composition-graded nanowires, revealing the local variation of composition-dependent carrier mobilities and lifetimes that significantly differ from their uniform composition counterparts. Furthermore, we demonstrate a length-dependent behavior wherein shorter nanowires exhibit enhanced funneling effects, accelerating carrier transport by up to 33%. Our findings provide direct visualization of nanoscale carrier transport while supporting an effective approach for investigating complex carrier interactions in inhomogeneous semiconductor nanostructures, with implications for optimizing next-generation optoelectronic devices.

Yang, Rundi

Learning Nonlinear Reduced Models from Data with Operator Inference

This review discusses Operator Inference, a nonintrusive reduced modeling approach that incorporates physical governing equations by defining a structured polynomial form for the reduced model, and then learns the corresponding reduced operators from simulated training data. The polynomial model form of Operator Inference is sufficiently expressive to cover a wide range of nonlinear dynamics found in fluid mechanics and other fields of science and engineering, while still providing efficient reduced model computations. The learning steps of Operator Inference are rooted in classical projection-based model reduction; thus, some of the rich theory of model reduction can be applied to models learned with Operator Inference. This connection to projection-based model reduction theory offers a pathway toward deriving error estimates and gaining insights to improve predictions. Furthermore, through formulations of Operator Inference that preserve Hamiltonian and other structures, important physical properties such as energy conservation can be guaranteed in the predictions of the reduced model beyond the training horizon. This review illustrates key computational steps of Operator Inference through a large-scale combustion example.

Mechanics

CO2 Handling & Electrolyzer Efficiency Scaling Evaluator

CHEESE is an interactive dashboard tool for estimating the performance and material requirements of carbon dioxide electrolysis systems. It helps users evaluate how electrode area, current density, product selectivity, gas flow, cell voltage, and the number of cells in a stack affect system operation. The dashboard provides simple and advanced modes so it can be used for both quick estimates and more detailed engineering analysis. Users can estimate product output, carbon dioxide use, electrical power, electrode area, gas and liquid flow rates, energy efficiency, material cost per test, and the effect of scaling from a single cell to a multi cell stack. It also includes tools for examining carbon balance, equipment durability, component replacement, and changes in performance over time. This is intended to help both academia and industry researchers who are either getting into CO2 electrolysis on lab-scale or are trying to establish a larger footprint. CHEESE presents results through tables, charts, and simplified cell and stack diagrams. It is intended to support research planning, experimental design, comparison of operating conditions, and early stage scale up studies.

Prajapati, Aditya [Lawrence Livermore National Lab

Reflection and refraction of directrons at the interface

Reflection and refraction are ubiquitous phenomena with extensive applications, yet minimizing energy loss and information distortion during these processes remains a significant challenge. This study examines the behavior of structurally stable solitons, known as directrons, in nematic liquid crystals interacting with an interface where the director field orientation changes, despite identical physical properties, external potentials, and boundary anchoring in the two regions. During reflection and refraction, the directrons maintain nearly constant structure and velocity, ensuring energy conservation and information integrity. Microscopic analyses of the director field and macroscopic evaluations of effective potential are employed to elucidate the dependence of reflection and refraction probabilities on the directron’s incident angle and the orientation difference across the interface. The findings provide valuable insights into the dynamics of solitary waves in structured liquid crystal systems, offering significant implications for the development of tunable photonic devices, reconfigurable optical systems, and nanoscale material engineering.

Science & Technology - Other Topics

Integrated Approach to Post-Irradiation Examination of Nuclear Materials at Idaho National Laboratory

Idaho national Laboratory (INL) is the U.S. lead national laboratory for the Department of Energy’s Office of Nuclear Energy (DOE-NE), providing much of the nuclear research, development and demonstration capability needed to move nuclear innovation forward to deployment. INL’s Materials and Fuels Complex hosts a unique combination of personnel, facilities and infrastructure and offers the ability to perform post-irradiation examinations (PIE) of nuclear materials spanning multiple length scales. The ability to combine engineering-scale analysis and sub-microscopic characterization provides valuable insights into fuel and structural material behavior and degradation mechanisms. The holistic approach is used to accelerate these materials demonstration and deployment. Selected studies will be presented, highlighting the impact of these techniques on improving fuel reliability, safety, and efficiency, thereby advancing the development of sustainable and advanced nuclear energy technologies.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS

A Compact Cryogenic Environment for In Situ Neutron Diffraction Under Mechanical Loading

Understanding the deformation mechanisms of materials at cryogenic temperatures is crucial for cryogenic engineering applications. In situ neutron diffraction is a powerful technique for probing such mechanisms under cryogenic conditions. In this study, we present the development of a compact cryogenic environment (CCE) designed to facil-itate in situ neutron diffraction experiments under mechanical loading at tempera-tures as low as 77 K. The CCE features a polystyrene foam cryogenic chamber, alumi-num blocks serving as neutron-transparent cold sinks, a liquid nitrogen dosing system for cryogen delivery, a nitrogen gas flow control system for thermal management, a process controller for temperature control, and a pair of thermally isolated grip adapt-ers for mechanical testing. The CCE achieves reliable temperature control with mini-mal neutron attenuation. Utilizing this setup, we conducted three in situ neutron dif-fraction tensile tests on a 316L stainless steel at 77 , 173 , and 298 K, respectively. The results highlight the pronounced effects of cryogenic temperatures on the material's deformation mechanisms, underscoring both the significance of cryogenic deformation studies and the effectiveness of the CCE.

Yu, Dunji [ORNL] (ORCID:0000000189467851)

Mapping the Microhardness of Al Matrix in U-7Mo/Al Dispersion Fuels at Medium and High Burn-up by in situ Nanoindentation

The mechanical degradation of the Al matrix in U-7Mo dispersion fuels was detected after irradiation in previous studies, but more details of the degradation mechanism are not clear yet to clarify the root cause. In this study, microhardness mapping in fresh and irradiated U-7Mo dispersion fuels coated with ZrN, with burn-up of 3.35 × 10 21 and 6.28 × 10 21 f/cm 3 , are measured to reveal the hardening of the Al matrix as a function of distance to fuel particles. Micro cubes were pulled by plasma focused ion beam scanning electron microscopy and tested by in situ nanoindenter with Berkovitch tip. Size effects are measured in medium and high burn-up samples. The higher burn-up specimen exhibits a more pronounced size effect when indent load is lower than 20 mN. Size effect correction models are also calculated by plots fitting, which predicts the true microhardness without size effect. Results shows that the hardness of the Al matrix near the ZrN coating has the highest value, then decreases moving away from the coating and become stable when the distance reaches ∼10 µm. The hardness starts increasing again getting closer to the next fuel particle, which makes the hardness distribution between two fuel particles to be “U” shape.

36 - MATERIALS SCIENCE

Maximizing Free Energy Gain

Maximizing the amount of work harvested from an environment is important for a wide variety of biological and technological processes, from energy-harvesting processes such as photosynthesis to energy storage systems such as fuels and batteries. Here, we consider the maximization of free energy—and by extension, the maximum extractable work—that can be gained by a classical or quantum system that undergoes driving by its environment. We consider how the free energy gain depends on the initial state of the system while also accounting for the cost of preparing the system. We provide simple necessary and sufficient conditions for increasing the gain of free energy by varying the initial state. We also derive simple formulae that relate the free energy gained using the optimal initial state rather than another suboptimal initial state. Finally, we demonstrate that the problem of finding the optimal initial state may have two distinct regimes, one easy and one difficult, depending on the temperatures used for preparation and work extraction. We illustrate our results on a simple model of an information engine.

Physics

Neuromorphic overparameterisation and few-shot learning in multilayer physical neural networks

Abstract Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to its reliance on single systems. This constrains output dimensionality and dynamic range, limiting performance to a narrow range of tasks. Here, we engineer a suite of nanomagnetic array physical reservoirs and interconnect them in parallel and series to create a multilayer neural network architecture. The output of one reservoir is recorded, scaled and virtually fed as input to the next reservoir. This networked approach increases output dimensionality, internal dynamics and computational performance. We demonstrate that a physical neuromorphic system can achieve an overparameterised state, facilitating meta-learning on small training sets and yielding strong performance across a wide range of tasks. Our approach’s efficacy is further demonstrated through few-shot learning, where the system rapidly adapts to new tasks.

Science & Technology - Other Topics

Block-Type Antiferromagnetism in Single Chain Quasi-One-Dimensional K 3 ⁢Fe 2 ⁢Se 4

One-dimensional (1D) structures provide a unique platform to study the correlated quantum interactions and phase transitions such as unconventional magnetism and superconducting states. Here, we report that iron chalcogenide K 3 ⁢Fe 2 ⁢Se 4 exhibits an unusual block-type canted antiferromagnetic (AFM) order with a clear single chain quasi-1D structure, which is structurally different from the two-leg ladder BaFe 2 ⁢Se 3 , through both experimental measurements and density matrix renormalization group (DMRG) calculations. The narrow bandgap semiconductor K 3 ⁢Fe 2 ⁢Se 4 has a quasi-1D edge-shared FeSe4 tetrahedra chain structure and orders antiferromagnetically below 110 K. The magnetic moments couple antiferromagnetically along the quasi-1D chain direction of the 𝑏 axis and form an up-down-down-up (↑−↓−↓−↑)–like spin structure with a commensurate propagation vector 𝒌=⁢(0,0,0), where block-type spin ↑−↑ or ↓−↓ coupling are between the longer Fe-Fe bonds of the quasi-1D chain. DMRG results show that block antiferromagnetic state is stable in K 3 ⁢Fe 2 ⁢Se 4 and reveal that the block-ordered arrangement of Fe 2.5+ ions spins arise from the competition between ferromagnetic and AFM interaction in the presence of strong electronic correlation. Our research results not only report the discovery of a clear block-type canted antiferromagnetic structure in a real quasi-1D chain material but also provide a theoretical approach to understand the block-type antiferromagnetism in quasi-1D iron chalcogenides.

antiferromagnetism