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DOE OSTI2026

Nuclear Responses with Neural-Network Quantum States

We introduce a variational Monte Carlo framework that combines neural-network quantum states with the Lorentz integral transform technique to compute the dynamical properties of self-bound quantum many-body systems in continuous Hilbert spaces. While broadly applicable to various quantum systems, including atoms and molecules, in this initial application we focus on the photoabsorption cross section of light nuclei, where benchmarks against numerically exact techniques are available. Our accurate theoretical predictions are complemented by robust uncertainty quantification, enabling meaningful comparisons with experiments. Here, we demonstrate that a relatively simple nuclear Hamiltonian—based on a leading-order pionless EFT expansion and known to accurately reproduce ground-state energies of nuclei with 𝐴 ≤ 40—also provides a reliable description of the photoabsorption cross section.

Ab initio calculations↗

DOE OSTI2025

Spin Dynamics of Triple-𝐐 Magnetic Orderings in a Triangular Lattice: Implications for Multi-𝐐 Orderings in General Two-Dimensional Lattices

Multi-𝐐 magnetic structures on two-dimensional (2D) lattices provide a key route to realizing topological physics in 2D magnetism. A major experimental challenge is to unambiguously confirm their formation by excluding the possibility of topologically trivial multidomain single- or double-𝐐 magnetic orders, which cannot be distinguished using conventional diffraction techniques. Here, we propose that long-wavelength spin dynamics offers a universal diagnostic for triangular lattices: Triple-𝐐 orders that preserve rotational symmetry and single- or double-𝐐 orders that break it exhibit qualitatively distinct anisotropies in their Goldstone-mode velocities, stemming from fundamental differences in their underlying spin configurations. We validate this concept using the metallic triangular-lattice antiferromagnet Co 0.325 ⁢TaS 2 , which hosts both a stripe-type single-𝐐 state and a triple-𝐐 tetrahedral ordering at different temperatures. Using inelastic neutron-scattering and spin dynamics simulations, we first refine the spin Hamiltonian by fitting the paramagnetic excitation spectra, allowing us to develop an unbiased model independent of magnetic ordering. We then show that the observed velocity profiles of the Goldstone modes agree with the high-temperature model’s predictions: markedly anisotropic for the single-𝐐 phase and near isotropic for the triple-𝐐 phase. Importantly, this contrast persists across various exchange parameters, highlighting its model-independent nature and suggesting potential applicability to other 2D lattice systems. Beyond the long-wavelength regime, we present a substantial discrepancy between the measured and simulated magnon spectra exclusively in the triple-𝐐 phase. We attribute this discrepancy to magnon energy renormalization arising from order-of-magnitude-enhanced magnon-magnon interactions in the triple-𝐐 phase, due to its noncollinear configuration. This work provides universal insight into the dynamical properties of topological multi-𝐐 magnetic orderings in 2D lattice structures, offering a broadly applicable diagnostic to distinguishing them from topologically trivial single- or double-𝐐 counterparts. The unequivocal confirmation of the triple-𝐐 structure in Co 0.325 ⁢TaS 2 further establishes it as a prominent material platform for exploring topological spin textures in the genuine 2D limit.

Park, Pyeongjae [Oak Ridge National Laboratory (OR↗

DOE OSTI2025

Spin fluctuations, absence of magnetic order, and crystal electric field studies in the Yb 3+ -based triangular lattice antiferromagnet Rb 3 ⁢Yb⁢(VO 4 ) 2

Here, we report a comprehensive experimental investigation of the structural, thermodynamic, static, and dynamic properties of a triangular lattice antiferromagnet Rb 3 ⁢Yb(VO 4 ) 2 . Through the analysis of magnetic susceptibility, magnetization, and specific heat, complemented by crystal electric field (CEF) calculations, we confirm the Kramers' doublet with effective spin 𝐽 eff = 1/2 ground state. Magnetic susceptibility and isothermal magnetization analysis reveal a weak antiferromagnetic interaction among the 𝐽 eff = 1/2 spins, characterized by a small Curie-Weiss temperature (𝜃$^{\textrm{LT}}_{\textrm{CW}}$ ≃−0.26 K) or a reduced exchange coupling (𝐽/𝑘 B ≃ 0.18 K). The 51 V NMR spectra and spin-lattice relaxation rate (1/𝑇 1 ) show no evidence of magnetic long-range-order down to 1.6 K but reflect strong influence of CEF excitations in the intermediate temperatures. At low temperatures, 1/𝑇 1 ⁡(𝑇) shows pronounced frequency dependence and 1/𝑇 1 vs field at different temperatures follows the scaling behavior, highlighting the role of paramagnetic fluctuations. The CEF calculations using the point charge approximation divulge a large energy gap ( ∼18.61 meV) between the lowest and second lowest energy doublets, further establishing Kramers' doublet as the ground state. Our calculations also reproduce the experimental magnetization and specific heat data and indicate an in-plane magnetic anisotropy. These findings position Rb 3⁢ Yb(VO 4 ) 2 as an ideal candidate to explore intrinsic quantum fluctuations and possible quantum spin-liquid physics in a Yb 3+ -based triangular lattice antiferromagnet.

Sebastian, Sebin J. [Indian Institute of Science E↗

DOE OSTI2025

A Novel Secondary Frequency Regulation with Optimal Priority Selection of AGC Contributions

Automatic generation control (AGC) is used to maintain acceptable frequencies during operation owing to fluctuations in load and variable resources. In conventional industry applications, the AGC signal is allocated to each generator according to the predispatched frequency regulation capacity or the order of economic efficiency. However, with the increasing integration of inverter-based resources (IBRs), the retirement of conventional synchronous generators (SGs) has posed new challenges to frequency control schemes because fewer of them are optional for AGC regulation. In this paper, we propose a novel model predictive control (MPC)-based frequency regulation model to reduce control cost and ensure stability, by considering different critical dynamic factors when optimally selecting the AGC units. The proposed control model – developed in a general form – comprehensively embeds characteristics such as generator ramping rates, reserve capacity, and operation cost. The model predictive control–based two-timescale AGC scheme enhances the capability of immunizing the power disturbance from types of resources by coordinating the control signals between faster IBRs and slower SGs. The case study’s proposed model is verified to be effective in synergistically enforcing different dynamic properties of AGC units into the frequency regulation scheme.

Jiang, Sufan [The University of North Carolina at ↗

DOE OSTI2025

Amplified Mesoscale and Submesoscale Variability and Increased Concentration of Precipitation under Global Warming over Western North America

Abstract Cold-season precipitation statistics in simulations from the storm-resolving WRF Model at 6-km and 1-h resolution over western North America are analyzed. Pseudo–global warming future simulations for the 2041–80 period, constrained by GCMs under the RCP8.5 scenario, are compared to the 1981–2020 historical simulation. The analysis focuses on the dynamical properties of precipitation time series at subdaily scales and on the morphology of storms. The statistical distribution of precipitation intensities in each pixel of the simulation domain is characterized through nonparametric statistical indicators: frequency of wet hours, mean wet-hour precipitation intensity, and Gini coefficient as a measure of the temporal concentration of the precipitation volume. Additionally, the temporal and spatial Fourier power spectra of precipitation time series and precipitation fields are analyzed. The half-power period (HPP) and half-power wavelength (HPW) are defined as spectral measures of the characteristic scales of precipitation’s temporal and spatial patterns. The results show statistically significant increases in the mean wet-hour precipitation intensity and in the Gini coefficient in 99% of the pixels, indicating that the seasonal precipitation volume becomes more concentrated within a smaller number of hours with higher precipitation intensity. The statistics of change in the frequency of wet hours are more contrasted across the simulation domain. The changes are also reflected in the power spectra, which show the spatial and temporal variability increasing proportionally more with finer spatial and temporal scales and the HPW and HPP decreasing. These projected changes are expected to have consequences, not only in terms of hydrologic impacts but also in terms of the predictability of precipitation patterns. Significance Statement The precipitation characteristics of winter storms over the western United States and southwestern Canada are analyzed in future climate simulations for the 2041–80 period. As compared to present-day climate, the most intense parts of the storms are projected to produce a higher rainfall volume, with increased concentration over smaller areas and shorter time intervals. The propensity of rainfall intensity to vary rapidly over time will be enhanced in the future according to the simulations. These model predictions imply an increased risk of rapid flooding in small basins. They also suggest that predicting several hours ahead the time and location at which a storm will produce maximum rainfall may become more challenging in the future.

Climate change↗

DOE OSTI2022

Heterosynaptic plasticity in biomembrane memristors controlled by pH

Abstract In biology, heterosynaptic plasticity maintains homeostasis in synaptic inputs during associative learning and memory, and initiates long-term changes in synaptic strengths that nonspecifically modulate different synapse types. In bioinspired neuromorphic circuits, heterosynaptic plasticity may be used to extend the functionality of two-terminal, biomimetic memristors. In this article, we explore how changes in the pH of droplet interface bilayer aqueous solutions modulate the memristive responses of a lipid bilayer membrane in the pH range 4.97–7.40. Surprisingly, we did not find conclusive evidence for pH-dependent shifts in the voltage thresholds ( V* ) needed for alamethicin ion channel formation in the membrane. However, we did observe a clear modulation in the dynamics of pore formation with pH in time-dependent, pulsed voltage experiments. Moreover, at the same voltage, lowering the pH resulted in higher steady-state currents because of increased numbers of conductive peptide ion channels in the membrane. This was due to increased partitioning of alamethicin monomers into the membrane at pH 4.97, which is below the pKa (~5.3–5.7) of carboxylate groups on the glutamate residues of the peptide, making the monomers more hydrophobic. Neutralization of the negative charges on these residues, under acidic conditions, increased the concentration of peptide monomers in the membrane, shifting the equilibrium concentrations of peptide aggregate assemblies in the membrane to favor greater numbers of larger, increasingly more conductive pores. It also increased the relaxation time constants for pore formation and decay, and enhanced short-term facilitation and depression of the switching characteristics of the device. Modulating these thresholds globally and independently of alamethicin concentration and applied voltage will enable the assembly of neuromorphic computational circuitry with enhanced functionality. Impact statement We describe how to use pH as a modulatory “interneuron” that changes the voltage-dependent memristance of alamethicin ion channels in lipid bilayers by changing the structure and dynamical properties of the bilayer. Having the ability to independently control the threshold levels for pore conduction from voltage or ion channel concentration enables additional levels of programmability in a neuromorphic system. In this article, we note that barriers to conduction from membrane-bound ion channels can be lowered by reducing solution pH, resulting in higher currents, and enhanced short-term learning behavior in the form of paired-pulse facilitation. Tuning threshold values with environmental variables, such as pH, provide additional training and learning algorithms that can be used to elicit complex functionality within spiking neural networks. Graphical abstract

36 MATERIALS SCIENCE↗

DOE OSTI2023

Experimental 4D Tracking of a Single Electron in IOTA

We present the results of the first experiments on 4-dimensional phase-space tracking of a single electron in a storage ring, using a linear multi-anode photomultiplier tube for simultaneously measuring transverse coordinates and arrival times of synchrotron-radiation pulses. During the next few months, full 6D tracking will be implemented. This technology makes it possible to characterize the motion of a single particle, i.e. simultaneously tracking of amplitudes and phases for slow synchrotron oscillations and fast betatron oscillations. Complete tracking of a single particle enables the first direct measurements of dynamical properties, including invariants, amplitude-dependent tunes, and chaotic behavior.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Complete 6D tracking of a single electron in the IOTA ring

We present the results of the first experiments on 6-dimensional phase-space tracking of a single electron in a storage ring, using a linear multi-anode photomultiplier tube for simultaneously measuring transverse coordinates and arrival times of synchrotron-radiation pulses. This technology makes it possible to fully reconstruct turn-by-turn positions and momentums in all three planes for a single particle. Complete experimental particle tracking enables the first direct measurements of dynamical properties, including invariants, amplitude and energy dependence of tunes with exceptional precision, and chaotic behavior.

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

Image Processing Algorithms for Tuning Quantum Devices and Nitrogen-Vacancy Imaging

Semiconductor quantum dot devices can be challenging to configure into a regime where they are suitable for qubit operation. This challenge arises from variations in gate control of quantum dot electron occupation and tunnel coupling between quantum dots on a single device or across several devices. Furthermore, a single control gate usually has capacitive coupling to multiple quantum dots and tunnel barriers between dots. If the device operator, be it human or machine, has quantitative knowledge of how gates control the electrostatic and dynamic properties of multiqubit devices, the operator can more quickly and easily navigate the multidimensional gate space to find a qubit operating regime. We have developed and applied image analysis techniques to quantitatively detect where charge offsets from different quantum dots intersect, so called anticrossings. In this document we outline the details of our algorithm for detecting single anticrossings, which has been used to fine-tune the inter-dot tunnel rates for a three quantum dot system. Additionally, we show that our algorithm can detect multiple anticrossings in the same dataset, which can aid in the coarse tuning the electron occupation of multiple quantum dots. We also include an application of cross correlation to the imaging of magnetic fields using nitrogen vacancies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Interface-Driven Chiral Magnetism in Ultrathin Metallic Ferromagnets: Towards Skyrmion Spintronics

Magnetic skyrmions are localized chiral magnetic textures in the form of nanoscale vortices or bubbles that are topologically protected from being ‘unwound’. Their topological nature gives rise to rich behaviors including ordered lattice formation, emergent electrodynamics and robust current-driven displacement at remarkably low current densities. However, magnetic skyrmions have so far been restricted to just a few materials and observed only at low temperatures, limiting the experimental accessibility and technological application of these unique topological objects. This project aimed to realize magnetic skyrmions at room temperature in a new class of engineered chiral ferromagnets that exploit broken mirror symmetry at interfaces to generate helical magnetic order. Ultrathin magnetic heterostructures were engineered and patterned into laterally-confined nanostructures in which skyrmions were stabilized, manipulated, and detected for the first time under ambient conditions. Static and dynamic properties were examined using advanced x-ray imaging to provide a fundamental understanding of topological magnetic phases. The interactions between magnetic skyrmions and electron charge and spin currents were studied to identify fundamental new physics and enable device applications. These experimental studies, supported by detailed modeling, will help launch a new subfield of skyrmion-based spintronics in which individual skyrmions can be used to encode, store, and transport information in high-performance, low power memory and logic devices.

36 MATERIALS SCIENCE↗

DOE OSTI2021

In Situ Machine Learning for Intelligent Data Capture on Exascale Platforms. Final Report

In many dynamic systems, interesting events occur locally in time and space. Examples of such systems include ignition events in combustion simulations, material fractures in mechanics simulations, and extreme weather events in climate simulations. Due to memory constraints and data I/O costs, current simulation workflows save data at regularly spaced time-steps, at a fixed rate determined before the start of the simulation. Often this mode of operation results in missed events of interest, necessitating a simulation restart from before an event occurred with more frequent data saves. This data saving workflow is grossly inefficient and is already a bottleneck in the computing process. We propose to develop machine learning algorithms that can detect when interesting dynamical events are occurring, triggering data saves. These machine learning algorithms will perform in situ anomaly detection to flag regions with different dynamical properties than those previously recorded. The adaptive data saves would be local in time and space to match the event of interest, thereby enabling a much more efficient workflow that will reduce data I/O costs and data storage memory requirements. The algorithms will be tested on two applications: auto-ignition simulations and climate simulations. A critical component of this project will be developing machine learning algorithms that can be deployed efficiently in situ on HPC platforms with out-of-the-box functionality. The development of in situ machine learning methods to detect anomalous events would enable a more efficient and effective workflow, in which all the relevant data are saved in a single simulation run, without re-starts or scientist intervention.

42 ENGINEERING↗

DOE OSTI2021

Equations of Motion for the Vertical Rigid-Body Rotor: Linear and Nonlinear Cases

Centuries ago, the prolific mathematician Leonhard Euler (1707–1783) wrote down the equations of motion (EOM) for the heavy symmetrical top with one point fixed. The resulting set of equations turned out to be nonlinear and had a limited number of closed-form solutions. Today, tools such as transfer matrix and finite elements enable the calculation of the rotor dynamic properties for rotor-bearing systems. Some of these tools rely on the “linearized” version of the EOM to calculate the eigenvalues, unbalance response, or transients in these systems. In fact, industry standards mandate that rotors be precisely balanced to have safe operational characteristics. However, in some cases, the nonlinear aspect of the EOM should be considered. The purpose of this paper is to show examples of how the linear vs. nonlinear formulations differ. This paper will also show how excessive unbalance is capable of dramatically altering the behavior of the system and can produce chaotic motions associated with the “jump” phenomenon.

42 ENGINEERING↗

DOE OSTI2022

Dynamics and Transport in Strongly-Anisotropic Quantum Magnets (Final Report)

This DOE Award has evolved from a set of projects centered on the thermal transport phenomena in quantum magnets to the broader effort in the theory of dynamical properties of complex magnets, with the focus on their enigmatic ground states, disorder-induced phenomena, and novel spectroscopic and transport effects in them. Most recent emphasis of the research under the umbrella of this Award has been on the rare-earth- and transition-metal-based strongly-anisotropic magnets, the effort that has utilized a significant experience of our group in the studies of excitations, transport, and disorder in these new materials. The studies performed in our group have advanced basic understanding of fundamental physical properties of a diverse group of materials and yielded predictions of new phenomena in them. The research under this Award has targeted the problems that are at the forefront of the modern condensed matter physics and has also addressed the need for the theoretical understanding of experiments. Our work has influenced experiments conducted at the national and international facilities and provided an impact on the DOE basic energy science missions and areas of thrust in new electronic materials, energy transport, neutron- and X-ray scattering science, and in nanoscale science.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Uranium Carbide and Uranium-Metal Thermal Scattering Law Evaluations and Cross Sections [Slides]

New Uranium Carbide and Uranium Metal evaluations have been developed using the FLASSH platform. Ab initio LD/MD models converged electronic, magnetic, and dynamical properties and demonstrate good agreement with experimental data. Thermal scattering cross sections generate inelastic and elastic thermal neutron scattering libraries in FLASSH . New TSL evaluations occurred in the production of ENDF File 7 data for Uranium Carbide and Uranium Metal submitted to NNDC for ENDF/B-VIII.1 release.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE) C-band Radar Deployment Field Campaign Report

Convective clouds play a critical role in the Earth’s climate system, acting as sinks of total water in the atmospheric column through precipitation, thereby contributing to the atmospheric energy balance. They serve as a primary mechanism for the transfer of heat, moisture, and momentum through the troposphere, significantly impacting the large-scale atmospheric circulation and local environment, and affecting the probability of subsequent cloud formation (e.g., Hartmann et al. 1984, Su et al. 2014, Sherwood et al. 2014). Convective characteristics including convective core size (reflectivity and updraft), cloud lifetime, precipitation intensity, total precipitation amount, precipitation efficiency, and lightning flash rates can be strongly related to environmental factors (e.g., wind shear, humidity). Since cumulus clouds evolve rapidly, their microphysical and dynamical properties and life cycles are challenging to resolve in models, and even in observations (e.g., Fridlind et al. 2017, Ladino et al. 2017).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Thermal Scattering Law Data Development for Paraffin Wax

Paraffin wax is often used as a nuclear moderator to slow down the fast neutrons in experimental critical assemblies [1]. It is a colorless and soft solid material that consists primarily of straight-chain alkanes (n-alkanes), which are hydrocarbons with the general formula CnH2n+2 [2-3]. The length of the hydrocarbon chain ranges from C20 to C30 and higher [2]. It is distinguished by its solid state at room temperature and begins to melt above approximately 310 K [4]. Paraffin wax is a commonly employed substance in the manufacture of shielding. One of its noteworthy characteristics is its ability to effectively absorb the neutrons. Also, it possesses a high macroscopic cross section, which enables it to efficiently moderate neutrons. As a result, paraffin wax is extensively utilized in various applications where moderation and shielding of neutrons are needed. For simulations, it is necessary to evaluate its thermal scattering law (TSL) and cross sections. Computationally, classical molecular dynamics (CMD) simulations provide the capability of simulating atomic details. For example, several unary, binary, and few multi component mixtures have been investigated of the paraffin model by using molecular dynamics simulations [5-12]. An assessment of thermal neutron scattering in a heavy paraffinic oil treated both as a solid and a viscous fluid containing 25% linear branched paraffin (C30H62), 35% one ring cycloalkane (C30H60), 15% two rings cycloalkane (C30H58), and 25% aromatic (C30H60) chains has been studied using CMD simulations for producing TSL data [13]. Nevertheless, there is lack of TSL and cross section data for paraffin wax as most of the reported analyses focus on the unary and binary mixture of n-alkanes, which is not consistent with actual paraffin wax [2]. In this work, we applied the equilibrium CMD simulations technique to explore the structure and dynamical properties of wax, which are fundamental input to calculate the TSL. A paraffin wax system was modeled using the CMD code LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) [14-15] with the semi-empirical COMPASS [16] force field. The density of state (DOS) was calculated from the normalized velocity autocorrelation function (VACF), which is the Fourier transform of the normalized VACF. The DOS was used for the calculation of the TSL and thermal scattering cross sections. The paraffin wax atomic system was constructed by using the MedeA material design platform [17], and was benchmarked using available properties (i.e., density, bond lengths, angles, diffusivity, and viscosity).

Nuclear Criticality Safety Program (NCSP)↗

DOE OSTI2024

Single-Electron Tracking (SETI)

We present the results of the first experiments on 6-dimensional phase-space tracking of a single electron in a storage ring, using a linear multi-anode photomultiplier tube for simultaneously measuring transverse coordinates and arrival times of synchrotron-radiation pulses. This technology makes it possible to fully reconstruct turn-by-turn positions and momentums in all three planes for a single particle. Complete experimental particle tracking enables the first direct measurements of dynamical properties, including invariants, tunes dependence on amplitudes with exceptional precision.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Complete 6D Tracking of a Single Electron in the IOTA Ring

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗