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At least 379 records · Page 21

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DOE OSTI2026

Classical combinatorial optimization scaling for random Ising models on 2D heavy-hex graphs

Motivated by near term quantum computing hardware limitations, combinatorial optimization problems that can be addressed by current quantum algorithms and noisy hardware with little or no overhead are used to probe capabilities of quantum algorithms such as the quantum approximate optimization algorithm. In this study, a specific class of near term quantum computing hardware defined combinatorial optimization problems, Ising models on heavy-hex graphs both with and without geometrically local cubic terms, are examined for their classical computational hardness via empirical computation time scaling quantification. Specifically the time-to-solution (TTS) metric using the classical heuristic simulated annealing is measured for finding optimal variable assignments (ground states), as well as the time required for the optimization software Gurobi to find an optimal variable assignment. Because of the sparsity of these Ising models, the classical algorithms are able to find optimal solutions efficiently even for large instances (i.e. 100 000 spin variables). The Ising models both with and without geometrically local cubic terms exhibit average-case linear-time or weakly quadratic scaling when solved exactly using Gurobi, and the Ising models with no cubic terms show evidence of exponential-time TTS scaling when sampled using simulated annealing. These findings point to the necessity of developing and testing more complex, namely more densely connected, optimization problems in order for quantum computing to ever have a practical advantage over classical computing. Our results are another illustration that different classical algorithms can indeed have exponentially different running times, thus making the identification of the best practical classical technique important in any quantum computing vs. classical computing comparison.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Diabatic quantum annealing for the frustrated ring model

Abstract Quantum annealing (QA) is a continuous-time heuristic quantum algorithm for solving or approximately solving classical optimization problems. The algorithm uses a schedule to interpolate between a driver Hamiltonian with an easy-to-prepare ground state and a problem Hamiltonian whose ground state encodes solutions to an optimization problem. The standard implementation relies on the evolution being adiabatic: keeping the system in the instantaneous ground state with high probability and requiring a time scale inversely related to the minimum energy gap between the instantaneous ground and excited states. However, adiabatic evolution can lead to evolution times that scale exponentially with the system size, even for computationally simple problems. Here, we study whether non-adiabatic evolutions with optimized annealing schedules can bypass this exponential slowdown for one such class of problems called the frustrated ring model. For sufficiently optimized annealing schedules and system sizes of up to 39 qubits, we provide numerical evidence that we can avoid the exponential slowdown. Our work highlights the potential of highly-controllable QA to circumvent bottlenecks associated with the standard implementation of QA.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

On the competition between mixing rate and uniformity in a coaxial hydrodynamic focusing mixer

Fast microfluidic mixers for use with line-of-sight integrating detection schemes pose unique challenges. Such detectors typically cannot discriminate signal from slow moving (e.g. near internal walls) and fast-moving portions of the fluid stream. This convolves reaction rate dynamics with fluid flow residence time dynamics. Further, the small cross sections of typical three-dimensional hydrodynamic focusing devices lead to lower detection signals. The current study focuses on achieving both small time scales of mixing and homogenous residence times. This is achieved by injecting sample through a center capillary and hydrodynamically focusing using a sheath flow within a tapered second capillary. The current design also features a third, larger coaxial capillary. The mixed stream flows into the large cross-section of this third capillary to decelerate and expand the stream by up to 14-fold to improve line-of-sight signal strength of reaction products. Hydrodynamic focusing, mixing, and expansion are studied using analytical and numerical models and also studied experimentally using a fluorescein-iodide quenching reaction. The experimentally validated models are used to explore trade-offs between mixing rate and uniformity. For the first time, this work presents detailed analysis of the Lagrangian time history of species transport during mixing inside coaxial capillaries to measure mixing nonuniformity. The mixing region enables order 100 μs mixing times and residence time widths of the same order (140 μs).

42 ENGINEERING↗

DOE OSTI2022

Clump survival and migration in VDI galaxies: an analytical model versus simulations and observations

ABSTRACT We address the nature of the giant clumps in high-z galaxies that undergo violent disc instability, distinguishing between long-lived and short-lived clumps. We study the evolution of long-lived clumps during migration through the disc via an analytical model tested by simulations and confront theory with CANDELS-HST observations. The clump ‘bathtub’ model, which considers gas and stellar gain and loss, involves four parameters: the accretion efficiency α, the star formation rate (SFR) efficiency ϵd, and the outflow mass-loading factors for gas and stars, η and ηs. The corresponding time-scales are comparable to the migration time, two-three orbital times. The accretion-rate dependence on clump mass, gas, and stars, allows an analytical solution involving exponential growing and decaying modes. For the fiducial parameter values there is a main evolution phase where the SFR and gas mass are constant and the stellar mass is rising linearly with time. This makes the inverse specific SFR an observable proxy for clump age. When η or ϵd are high, or α is low, the decaying mode induces a decline of SFR and gas mass till the migration ends. Later, the masses and SFR approach an hypothetical exponential growth with a constant specific SFR. The model matches simulations with different, moderate feedbacks, both in isolated and cosmological settings. The observed clumps agree with our predictions, indicating that the massive clumps are long-lived and migrating. A challenge is to model feedback that is non-disruptive in massive clumps but suppresses SFR to match the galactic stellar-to-halo mass ratio.

Dekel, Avishai↗

DOE OSTI2025

Intercomparison of Deep Learning Model Architectures for Atmospheric River Prediction

With a rapid surge in the application of machine learning (ML) for a diverse range of tasks in climate science, the present study addresses a challenge for climate scientists when selecting the optimal ML or deep learning (DL) architecture for a given application. In particular, a DL intercomparison study was performed with a focus on forecasting the position of atmospheric rivers (ARs) on short-range time scales (up to 5-day lead times). AR predictions from multiple DL architectures, including various types of convolutional autoencoders and a vision transformer (ViT), were compared against ECMWF ERA5 reanalysis and hindcasts from a global climate model. DL models with similar trainable parameters were trained on ERA5 reanalysis data and AR positions derived from a thresholding algorithm to ensure a fair comparison among the DL models. Each model’s performance and accuracy in forecasting AR location and key input fields within a 5-day window were assessed using metrics of root-mean-square error, anomaly correlation, and mean intersection over union. The ViT architecture outperformed other autoencoder models in most of the metrics. Incorporating additional meteorological fields only yielded slight improvements in forecasting certain fields at longer lead times. The results also suggest that a smaller number of input time steps or smaller number of autoregressive steps can achieve better prediction skills, while also improving the overall computational efficiency. This research offers valuable insights into the strengths and weaknesses of different DL techniques for AR forecasting, hopefully guiding the development of improved models for forecasting this phenomenon.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Collaborative Research: Unveiling the Interplay Between Magnetic Reconnection and Turbulence — Theory and Modeling

This is the final technical report for the project "Collaborative Research: Unveiling the Interplay Between Magnetic Reconnection and Turbulence — Theory and Modeling." This project investigated the interplay between two fundamental plasma processes — turbulence and magnetic reconnection — and the associated heating and particle acceleration. In particular, we focused on a new regime where the plasmoid instability mediates the turbulent energy cascade. In this new regime, reconnecting current sheets are disrupted by the growth of plasmoids/flux ropes on time scales shorter than the typical turnover times of eddies, speeding up the energy cascade and steepening the turbulence energy spectrum. This project addressed the following outstanding open questions: (1) What are the fundamental differences between plasmoid‐mediated turbulence cascade in three dimensions (3D) and two dimensions (2D)? (2) What are the essential features of plasmoid‐mediated turbulence in weakly collisional or collisionless regimes beyond resistive MHD? (3) How does the interplay of turbulence and reconnection regulate the energy release and dissipation in space and astrophysical plasmas? To address these questions, we have carried out three investigations: (1) Three-dimensional plasmoid-mediated turbulence energy cascade; (2) plasmoid-mediated reconnection and turbulence in three-dimensional Hall MHD; (3) reconnection and heating in coronal loops. This technical report summarizes the key findings of these investigations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Benchmarking numerical methods for impact and cratering applications

Large scale computational models are important for studying impact cratering events that are prevalent both on Earth and, more broadly, in this solar system. To address these problems, models must reliably account for both large length scales (e.g., kilometers) and relatively long time scales (hundreds of seconds). This work benchmarks two such approaches, a more traditional hydrodynamics approach and a finite-discrete element method (FDEM), for impact cratering applications. Both 2D and 3D results are discussed for two different impact velocities, 5 km/s and 20 km/s, striking normal to the target and, for 3D simulations, 45° from vertical. In addition, comparisons to previously published data are presented. Finally, differences in how these methods model damage are discussed. Ultimately, both approaches show successful modeling of several different impact scenarios.

58 GEOSCIENCES↗

DOE OSTI2022

Study of Protein Dynamics via Neutron Spin Echo Spectroscopy

Most human body proteins' activity and functionality are related to configurational changes of entire subdomains within the protein crystal structure. The crystal structures build the basis for any calculation that describes the structure or dynamics of a protein, most of the time with strong geometrical restrictions. However, these restrictions from the crystal structure are not present in the solution. The structure of the proteins in the solution may differ from the crystal due to rearrangements of loops or subdomains on the pico to nanosecond time scale (i.e., the internal protein dynamics time regime). This study describes how slow motions on timescales of several tens of nanoseconds can be accessed using neutron scattering. In particular, the dynamical characterization of two major human proteins, an intrinsically disordered protein that lacks a well-defined secondary structure and a classical antibody protein, is addressed by neutron spin echo spectroscopy (NSE) combined with a wide range of laboratory characterization methods. Further insights into protein domain dynamics were achieved using mathematical modeling to describe the experimental neutron data and determine the crossover between combined diffusive and internal protein motions. The extraction of the internal dynamic contribution to the intermediate scattering function obtained from NSE, including the timescale of the various movements, allows further vision into the mechanical properties of single proteins and the softness of proteins in their nearly natural environment in the crowded protein solution.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Concept of Dynamic Heat Insulation for Rotating Detonation Engines

This work introduces a new class of materials concept to dynamically reduce instantaneous heat fluxes in Rotating Detonation Engine (RDE) combustor chamber walls. The high-frequency and high-amplitude surface heat fluxes observed in RDEs arise from large instantaneous temperature differences between the detonation shockwave and chamber wall surface. These temperature gradients drive substantial energy loss and reduce the chamber gas pressure, ultimately limiting the cycle’s thermodynamic efficiency. This work introduces a concept for dynamically insulating the combustion chamber surfaces using surface layers or coatings with low thermal time scale. With such coatings, the surface temperature may follow the fluctuations of the cyclic detonation wave temperature, thus reducing the instantaneous heat flux therefore cycle-mean heat flux. To analyze these cyclic thermal phenomena, a one-dimensional analytical conduction solver was utilized with the capability to handle multilayered structures. Parametric modeling was performed using transient heat flux boundary conditions representative of a hydrogen–air RDE across a broad range of coating thermal properties and engine conditions. The coating effectiveness scaled with the product of thermal time constant and detonation wave frequency and the results were non-dimensionalized to guide future materials development. This strategy may offer benefits in increasing material survivability, reducing cooling requirements, and enhancing pressure gain.

heat transfer↗

DOE OSTI2021

Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data With Spatial Information

Efficient processing of large-scale time series data is an intricate problem in machine learning. Conventional sensor signal processing pipelines with hand engineered feature extraction often involve huge computational cost with high dimensional data. Deep recurrent neural networks have shown promise in automated feature learning for improved time-series processing. However, generic deep recurrent models grow in scale and depth with increased complexity of the data. This is particularly challenging in presence of high dimensional data with temporal and spatial characteristics. Consequently, this work proposes a novel deep cellular recurrent neural network (DCRNN) architecture to efficiently process complex multi-dimensional time series data with spatial information. Here, the cellular recurrent architecture in the proposed model allows for location-aware synchronous processing of time series data from spatially distributed sensor signal sources. Extensive trainable parameter sharing due to cellularity in the proposed architecture ensures efficiency in the use of recurrent processing units with high-dimensional inputs. This study also investigates the versatility of the proposed DCRNN model for classification of multi-class time series data from different application domains. Consequently, the proposed DCRNN architecture is evaluated using two time-series datasets: a multichannel scalp EEG dataset for seizure detection, and a machine fault detection dataset obtained in-house. The results suggest that the proposed architecture achieves state-of-the-art performance while utilizing substantially less trainable parameters when compared to comparable methods in the literature.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Observation of critical scaling in spin glasses below T c using thermoremanent magnetization

Time-dependent thermoremanent magnetization (TRM) studies have been instrumental in probing energy dynamics within the spin glass phase. In this paper, we review the evolution of the TRM experiment over the last half century and discuss some aspects related to how it has been used in the understanding of spin glasses. We also report on recent experiments using high-resolution DC SQUID magnetometry to probe the TRM at temperatures less than but near to the transition temperature T c . These experiments have been performed as a function of waiting time, temperature, and five different magnetic fields. We find that as the transition temperature is approached from below, the characteristic time scale of TRM is suppressed up to several orders of magnitude in time. In the highest-temperature region, we find that the waiting time effect subsides, and a waiting time-independent crossover line is reached. We also find that increasing the magnetic field further suppresses the crossover line. Using a first-principles energy argument across the crossover line, we derive an equation that is an excellent fit to the crossover lines for all magnetic fields probed. The data show strong evidence for critical slowing down and an H = 0 Oe phase transition.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A detailed study of pre-heating effects in electron beam melting powder bed fusion process

Metal-based additive manufacturing processes, such as powder bed fusion with electron beam (PBF-EB) process, also referred to as electron beam melting (EBM), can produce high-density parts with minimal residual stresses due to the uniform and coherent preheating of the powder bed. However, understanding and controlling the multiple stages of preheating is required to enable the production of high-quality, consistent parts of various materials. This work presents a large-scale, multi-layer, three-dimensional numerical analysis focused on studying the preheating stages for predicting thermal history during the PBF-EB process. The model follows a continuous multi-stage cyclic process, that incorporates all the main stages of the PBF-EB process for 316 L stainless steel. This includes the gradual deposition of a new powder layer, the first and second preheating levels of the powder bed, and the energy deposition during melting (excluding the actual melt-pool behavior simulation). The model employs an adaptive time-scaling approach that automatically adjusts the energy deposition for each solution time-increment. This allows for localized changes in time-resolution over an otherwise computationally expensive multi-layer procedure. The material property variations are also taken into account, with an emphasis on the subtle irreversible changes in powder effective thermal conductivity after the two requisite preheating stages of the powder bed. This effect is studied using simplified conductivity models from the literature for partially sintered powder, validated by a dedicated experiment and numerical simulation. The large-scale model is then used to estimate the actual temperatures during first and second preheating levels for 316 L steel, which is not yet fully supported commercially for PBF-EB. Model predictions are corroborated by experiments, using and analyzing IR images, taken at the completion of each layer by the machine’s built-in infrared camera. The current model also incorporates a qualitative assessment for the effects of conductivity change during pre-heating, as well as evaluates the applicability of the time-scaling approach.

36 MATERIALS SCIENCE↗

DOE OSTI2022

High speed ultraviolet digital image correlation (UV-DIC) for dynamic strains at extreme temperatures

Digital Image Correlation (DIC) is a camera-based method of measuring full-field displacements and strains from the surface of a deforming object. It can be applied at any length scale (determined by the lenses) and any time scale (determined by the camera), and because it is non-contacting, it can also be used at temperatures much higher than can be withstood by bonded strain gauges. At extreme temperatures, materials emit light in the form of blackbody radiation, which can saturate the camera sensor. It has previously been shown that the emitted light can be effectively screened by using ultraviolet (UV) cameras, lenses, and filters; however, commercially available UV cameras are relatively slow, which limits the speed of combined UV-DIC measurements. In this study, a UV intensifier was paired with a high-speed camera, and its ability to perform UV-DIC at high temperature and high speed was investigated. The system was compared over three different experiments: (A) a quasi-static thermal expansion test at high temperature, (B) a vibration test at room temperature, and (C) the same vibration test repeated at high temperature. The system successfully performed DIC up to at least 1600 °C at frame rates of 5000 fps, which is more than 100 times faster than other examples of UV-DIC in the literature. In all cases, measurements made using the UV intensifier were much noisier than those made without the intensifier, but the intensifier enabled measurements at temperatures well above those which an unfiltered high-speed camera otherwise saturates.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Revealing Excited‐State Trajectories on Potential Energy Surfaces with Atomic Resolution in Real Time

Abstract Photoexcited molecular trajectories on potential energy surfaces (PESs) prior to thermalization are intimately connected to the photochemical reaction outcome. The excited‐state trajectories of a diplatinum complex featuring photo‐activated metal–metal σ ‐bond formation and associated Pt−Pt stretching motions were detected in real time using femtosecond wide‐angle X‐ray solution scattering. The observed motions correspond well with coherent vibrational wavepacket motions detected by femtosecond optical transient absorption. Two key coordinates for intersystem crossing have been identified, the Pt−Pt bond length and the orientation of the ligands coordinated with the platinum centers, along which the excited‐state trajectories can be projected onto the calculated PESs of the excited states. This investigation has gleaned novel insight into electronic transitions occurring on the time scales of vibrational motions measured in real time, revealing ultrafast nonadiabatic or non‐equilibrium processes along excited‐state trajectories involving multiple excited‐state PESs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Revealing Excited‐State Trajectories on Potential Energy Surfaces with Atomic Resolution in Real Time

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Strong Coupling Between Plasmons and Molecular Excitons in Metal–Organic Frameworks

This Letter describes strong coupling of densely packed molecular emitters in metal–organic frameworks (MOFs) and plasmonic nanoparticle (NP) lattices. Porphyrin-derived ligands with small transition dipole moments in an ordered MOF film were grown on Ag NP arrays. Angle-resolved optical measurements of the MOF-NP lattice system showed the formation of a polariton that is lower in energy and does not cross the uncoupled MOF Q 1 band. Modeling predicted the upper polariton energy and a calculated Rabi splitting of 110 meV. The coupling strength was systematically controlled by detuning the plasmon energy by changing the refractive index of the solvents infiltrating the MOF pores. Through transient absorption spectroscopy, we found that the lower polariton decays quickly at shorter time scales (<500 ps) and slowly at longer times because of energy transfer from the upper polariton. Furthermore, this hybrid system demonstrates how MOFs can function as an accessible excitonic material for polariton chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Trace Key Mechanistic Features of the Arsenite Sequestration Reaction with Nanoscale Zerovalent Iron

Nanoscale zerovalent iron (nZVI) is considered as a highly efficient material for sequestrating arsenite, but the origin of its high efficacy as well as the chemical transformations of arsenite during reaction is not well understood. Here, in this study, we report an in situ X-ray absorption spectroscopy (XAS) study to investigate the complex mechanism of nZVI reaction with arsenite under anaerobic conditions at the time scale from seconds to days. The time-resolved XAS analysis revealed a gradual oxidation of As III to As V in the course of minutes to hours in both the solid and liquid phase for the high (above 0.5 g/L) nZVI dose system. When the reaction time increased up to 60 days, As V became the dominant species. The quick-scanning extended X-ray absorption fine structure (QEAXFS) was introduced to discover the transient intermediate at the highly reactive stage, and a small red-shift in As K-edge absorption edge was observed. The QEAXFS combined with density functional theory (DFT) calculation suggested that the red-shift is likely due to the electron donation in a Fe-O-As complex and possible active sites of As sequestrations include Fe(OH) 4 and 4-Fe cluster. This is the first time that the transient reaction intermediate was identified in the As-nZVI sequestration system at the fast-reacting early stage. This study also demonstrated usefulness of in situ monitoring techniques in environmental water research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Resistive wall tearing mode disruptions

Abstract This paper deals with resistive wall tearing mode (RWTM) disruptions. RWTMs are closely related to resistive wall modes. RWTMs are tearing modes whose linear and nonlinear behavior is strongly dependent on the resistive wall outside the plasma. The consequence for ITER, is that the thermal quench timescale could be much longer than previously conjectured. Active feedback stabilization is another possible way to mitigate or prevent RWTM disruptions. Simulations of RWTM disruptions are reviewed for DIII-D and MST. MST has a longer resistive wall time than ITER, and disruptions are not observed experimentally when MST is operated as a standard tokamak. Simulations indicate that the RWTM disruption time scale is longer than the experimental shot time. Edge cooling causes contraction of the current profile, which can destabilize RWTMs. The equilibria studied here have the q = 2 rational surface close to the edge of the plasma, and low current density between the q = 2 surface and the wall. A sequence of low edge current model equilibria has major disruptions only for a resistive, not ideal, wall, and edge q ⩽ 3.4 . This is consistent with regimes of tokamak disruptivity, suggesting that tokamak disruptions caused by edge cooling at low edge q could be RWTMs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗