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At least 379 records · Page 21

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DOE OSTI2021

Optimizing thermodynamic trajectories using evolutionary and gradient-based reinforcement learning

Here using a model heat engine, we show that neural-network-based reinforcement learning can identify thermodynamic trajectories of maximal efficiency. We consider both gradient and gradient-free reinforcement learning. We use an evolutionary learning algorithm to evolve a population of neural networks, subject to a directive to maximize the efficiency of a trajectory composed of a set of elementary thermodynamic processes; the resulting networks learn to carry out the maximally efficient Carnot, Stirling, or Otto cycles. When given an additional irreversible process, this evolutionary scheme learns a previously unknown thermodynamic cycle. Gradient-based reinforcement learning is able to learn the Stirling cycle, whereas an evolutionary approach achieves the optimal Carnot cycle. Our results show how the reinforcement learning strategies developed for game playing can be applied to solve physical problems conditioned upon path-extensive order parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Summary of Working Group 3: Laser and High-Gradient Structure-Based Acceleration

Accelerating particles at high gradients with high efficiencies is essential for reduction of size and cost of future accelerators for science and industry. This includes a future multi-TeV e+e- collider for particle, free-electron lasers for basic energy sciences and national security, industrial accelerators for energy and environmental applications, and accelerators for other applications. One way to achieve this is to use advanced externally-powered structures, both laser and RF driven. Working Group 3 (WG3) discussed novel accelerating structures with new geometries, new materials, frequencies from microwave to THz and optical spectrum, and operating conditions from room temperature to cryogenic. Presentations included recent advances in understanding RF breakdown and multipactor phenomena at different frequencies and materials, and other physics limitations to the accelerating gradient. Other relevant topics, such as developing high-gradient photoinjectors, high-efficiency RF power sources, and RF structures for a potential muon collider were discussed also. More details on each of the WG3 topics can be found in the articles published in these proceedings.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

DP-TwoLevel: two-stage gradient subspace learning for differentially private federated learning

Federated learning (FL) enables collaborative model training across distributed data sources without sharing raw data, but faces fundamental challenges in communication efficiency and privacy. Differentially private (DP) training mitigates information leakage but introduces noise that degrades model performance, especially in high-dimensional settings. We propose DP-TwoLevel, a hierarchical gradient projection method that improves utility under fixed DP constraints by exploiting low-dimensional structure in model updates. Our approach learns a two-level PCA-based representation of gradients and applies DP noise in a reduced-dimensional subspace, thereby lowering the effective noise magnitude while preserving dominant signal components. We evaluate the method across three datasets (MNIST, Fashion-MNIST, CIFAR-10) and three privacy regimes (ϵ∈0.5, 1.0, 2.0). Across nine experimental settings, DP-TwoLevel consistently outperforms DP-FedAvg, achieving an average accuracy improvement of 9.44%, with larger gains observed in lower ϵ(higher-noise) regimes (up to +22.31%). We further analyze scalability across models ranging from 100K to 1.49M parameters and identify a variance-based success criterion: performance remains strong when the projection preserves more than 75% of gradient variance, degrades in a marginal regime (65–75%), and fails below this threshold. Our results demonstrate that structure-aware dimensionality reduction can significantly improve the privacy–utility tradeoff in FL without modifying formal privacy guarantees. We also provide empirical evidence of scaling limitations for global projections and motivate per-layer extensions for larger models.

Kotevska, Olivera [ORNL] (ORCID:0000000316772243)↗

DOE OSTI2021

Gradient cell–structured high-entropy alloy with exceptional strength and ductility

We report that similar to conventional materials, most multicomponent high-entropy alloys (HEAs) lose ductility as they gain strength. In this study, we controllably introduced gradient nanoscaled dislocation cell structures in a stable single-phase HEA with face-centered cubic structure, thus resulting in enhanced strength without apparent loss of ductility. Upon application of strain, the sample-level structural gradient induces progressive formation of a high density of tiny stacking faults (SFs) and twins, nucleating from abundant low-angle dislocation cells. Furthermore, the SF-induced plasticity and the resultant refined structures, coupled with intensively accumulated dislocations, contribute to plasticity, increased strength, and work hardening. These findings offer a promising paradigm for tailoring properties with gradient dislocation cells at the nanoscale and advance our fundamental understanding of the intrinsic deformation behavior of HEAs.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Plasticizer-Free Gradient-Crosslinked Polyurethane Electrolyte for Room-Temperature Solid-State Lithium Batteries

Polymer-based solid-state electrolytes are promising for next-generation lithium metal batteries, yet their limited ionic conductivity and mechanical stability at ambient conditions remain key challenges. Herein, we report a novel gradient crosslinked polymer electrolyte (PU/PUA/PU) synthesized via a sequential in situ UV-curing process that integrates a mechanically robust polyurethane acrylate (PUA) core with soft linear polyurethane (PU) interfaces. This all-solid membrane operates without any liquid plasticizer and the interfacial PU layers ensure low interfacial resistance and intimate electrode contact, while the PUA core provides enhanced dimensional stability and dendrite suppression. As a result, the gradient electrolyte delivers an impressive ∼2.6 × 10 −4 S cm −1 ionic conductivity at 25 °C (two orders of magnitude higher than conventional PEO) and remains electrochemically stable >5 V (vs Li + /Li). Structural analysis confirms the formation of a well-defined crosslinked network with suppressed crystallinity and expanded interchain spacing. Electrochemical impedance spectroscopy (EIS) and linear sweep voltammetry (LSV) further validate these properties. When applied in a Li||NMC811 cell, the PU/PUA/PU electrolyte delivers stable cycling with high capacity at both 60 °C and 25 °C, demonstrating its potential for room-temperature solid-state battery applications without reliance on plasticizers or heating. In conclusion, this gradient design offers a practical path toward ambient-condition operation of solid-state lithium batteries, providing a paradigm for overcoming the traditional trade-off between ionic conductivity and mechanical robustness.

25 ENERGY STORAGE↗

DOE OSTI2022

Electron Temperature Gradient Driven Transport Model for Tokamak Plasmas

A new model for electron temperature gradient (ETG) modes is developed as a component of the Multi-Mode anomalous transport module [T. Rafiq \textit{et al.,} Phys Plasmas \textbf{20}, 032506 (2013)] to predict a time dependent electron temperature profile in conventional and low aspect ratio tokamaks. This model is based on two-fluid equations that govern the dynamics of low-frequency short- and long-wavelength electromagnetic toroidal ETG driven drift modes. A low collisionality NSTX discharge is used to scan the plasma parameter dependence on the ETG real frequency, growth rate, and electron thermal diffusivity. Electron thermal transport is discovered in the deep core region where modes are more electromagnetic in nature. Several previously reported gyrokinetic trends are reproduced, including the dependencies of density gradients, magnetic shear, $\beta$ and gradient of $\beta$ $(\betap)$, collisionality, safety factor, and toroidicity, where $\beta$ is the ratio of plasma pressure to the magnetic pressure. The electron heat diffusivity associated with the ETG mode is discovered to be on a scale consistent with the experimental diffusivity determined by power balance analysis.

ETG↗

DOE OSTI2022

Automatic Tuner for the Step Sizes of Gradient-Based RT-OPF DERMS Control Systems [SWR-22-50]

Gradient-based controllers have parameters called step sizes that determine how sensitive its control actions are to received inputs. Finding a practical setting for a step size is important. If it is too small, the controller is ineffective by not reacting in a significant manor to its received inputs. On the other hand, if it is too large, the actions implemented by the controller may be excessive and cause the controlled system to become unstable. The main objective of the Automatic Tuner for the Step Sizes of Gradient-Based RT-OPF DERMS Control Systems is to speed up the implementation of gradient-based control schemes by automatically tuning its step sizes instead of having a practitioner spend considerable time doing the task manually. Only simple adjustments need to be made to the code of each controller with a step size to allow the addition of an individual automatic tuner. This can be applied to any RT-OPF based control for DER management.

Comden, Joshua↗

DOE OSTI2025

Files and scripts to support manuscript Needham et al. Canopy Gradients of Respiration

This dataset includes the parameter files, relevant output files, and scripts to perform analysis with Jupyter notebooks that support the manuscript Needham et al 2025 “Canopy Gradients of Respiration Drive Plant Carbon Budgets and Leaf Area Index.” We add functionality to the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) to allow flexible vertical gradients of leaf maintenance respiration (Rdark) and maximum carboxylation rate (Vcmax) through the canopy. We test the sensitivity of FATES to canopy gradients in Rdark, both in global simulations to assess broad scale impacts on leaf area index (LAI) and vegetation carbon, and in single site simulations where we assess impacts on plant functional type (PFT) competitive dynamics. Parameter files are netcdf files that can be converted to human readable .cdl files using NCO tools. Analysis scripts are Jupyter notebook files. These can be opened and run using the open source Jupyter notebook software. Model outputs are netcdf files.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Collection of Aerosol Particles in a Single-Stage, High Gradient Magnetic Collector

The collection of aerosol particles that have magnetic components such as actinides, Co/Ni/Fe, brass, and alloys are of interest in the nuclear industry and for regulatory applications. The collection of these particles is important for monitoring and a number of collection approaches have been developed based on separations mechanisms including size, mass, electrical or thermal properties. In this work, we present the performance of a single-stage, high gradient magnetic collector with a nickel foam matrix for removing airborne magnetic particles. The collection efficiencies for two different particle size regimes and compositions (NaCl and Fe 3 O 4 below 200 nm and SiO 2 and Fe 3 O 4 at 1-2 μm) were measured to assess the performance of the magnetic collector. The high gradient magnetic collector did not remove nanosized magnetic Fe 3 O 4 particles any more effectively than non-magnetic NaCl particles. However, in the larger size range, the collector more efficiently removed Fe 3 O 4 particles compared to SiO 2 with a collection efficiency of 99% compared to 84% for SiO 2 . The removal mechanism could be attributed to both filtration and the high gradient magnetic field.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

C-band high gradient research and facilities at Los Alamos National Laboratory [Slides]

Achieving high-gradient performance (low breakdown rates, low field emission, new materials for HOM absorption, cathodes at high gradient etc.) is a materials science problem. Los Alamos is, at core, a materials science laboratory with particular expertise in metallurgy. Los Alamos also considers itself the steward of accelerator science for the NNSA part of the DOE complex. Thus, Los Alamos has both an institutional interest in, and capability to address, this problem space. High gradient C-band work directly aligns with future NNSA and LANL missions.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Hierarchical Optimal Power Flow with Improved Gradient Evaluation

Existing algorithms to solve alternating-current optimal power flow (AC-OPF) often exploit linear approximations to simplify system models and accelerate computations. In this paper, we improve a recent hierarchical OPF algorithm, which rested on primal-dual gradients evaluated in a linearized distribution power flow model. Specifically, we identify a risk of voltage violation arising from the model linearization, and propose a more accurate gradient evaluation method to eliminate that risk. We further develop a hierarchical primal-dual algorithm to solve OPF based on the proposed gradient evaluation method. Numerical results on IEEE networks show that our algorithm can enhance voltage safety with satisfactory computational efficiency.

distributed algorithm↗

DOE OSTI2023

A perfused multi-well bioreactor platform to assess tumor organoid response to a chemotherapeutic gradient

There is an urgent need to develop new therapies for colorectal cancer that has metastasized to the liver and, more fundamentally, to develop improved preclinical platforms of colorectal cancer liver metastases (CRCLM) to screen therapies for efficacy. To this end, we developed a multi-well perfusable bioreactor capable of monitoring CRCLM patient-derived organoid response to a chemotherapeutic gradient. CRCLM patient-derived organoids were cultured in the multi-well bioreactor for 7 days and the subsequently established gradient in 5-fluorouracil (5-FU) concentration resulted in a lower IC 50 in the region near the perfusion channel versus the region far from the channel. We compared behaviour of organoids in this platform to two commonly used PDO culture models: organoids in media and organoids in a static (no perfusion) hydrogel. The bioreactor IC 50 values were significantly higher than IC 50 values for organoids cultured in media whereas only the IC 50 for organoids far from the channel were significantly different than organoids cultured in the static hydrogel condition. Using finite element simulations, we showed that the total dose delivered, calculated using area under the curve (AUC) was similar between platforms, however normalized viability was lower for the organoid in media condition than in the static gel and bioreactor. Our results highlight the utility of our multi-well bioreactor for studying organoid response to chemical gradients and demonstrate that comparing drug response across these different platforms is nontrivial.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Geographic patterns and determinants of antibiotic resistomes in coastal sediments across complex ecological gradients

Coastal areas are highly influenced by terrestrial runoffs and anthropogenic disturbances, commonly leading to ecological gradients from bay, nearshore, to offshore areas. Although the occurrence and distribution of sediment antibiotic resistome are explored in various coastal environments, little information is available regarding geographic patterns and determinants of coastal sediment antibiotic resistomes across ecological gradients at the regional scale. Here, using high-throughput quantitative PCR, we investigated the geographic patterns of 285 antibiotic resistance genes (ARGs) in coastal sediments across a ~ 200 km scale in the East China Sea. Sediment bacterial communities and physicochemical properties were characterized to identify the determinants of sediments antibiotic resistome. Higher richness and abundance of ARGs were detected in the bay samples compared with those in nearshore and offshore samples, and significant negative correlations between the richness and/or abundance of ARGs and the distance to coastline (DTC) were identified, whereas different types of ARGs showed inconsistency in their relationships with DTC. The composition of antibiotic resistome showed significant correlations with nutrition-related variables (including NH 4 + -N, NO 3 − -N, and total phosphorus) and metals/metalloid (including As, Cu, Ni, and Zn), suggesting that terrestrial disturbances largely shape the antibiotic resistome. The Bipartite network showed strong associations between ARGs and mobile genetic elements (MGEs), and Partial Least Squares Path Modeling further revealed that terrestrial disturbance strength (as indicated by DTC) directly affected abiotic environmental conditions and bacterial community composition, and indirectly affected antibiotic resistome via MGEs. These findings provide insights into regional variability of sediment antibiotic resistome and its shaping path across complex ecological gradients, highlighting terrestrial disturbances as determinative forces in shaping coastal sediment antibiotic resistomes.

Xiong, Shangling↗

DOE OSTI2022

Fed-DeepONet: Stochastic Gradient-Based Federated Training of Deep Operator Networks

The Deep Operator Network (DeepONet) framework is a different class of neural network architecture that one trains to learn nonlinear operators, i.e., mappings between infinite-dimensional spaces. Traditionally, DeepONets are trained using a centralized strategy that requires transferring the training data to a centralized location. Such a strategy, however, limits our ability to secure data privacy or use high-performance distributed/parallel computing platforms. To alleviate such limitations, in this paper, we study the federated training of DeepONets for the first time. That is, we develop a framework, which we refer to as Fed-DeepONet, that allows multiple clients to train DeepONets collaboratively under the coordination of a centralized server. To achieve Fed-DeepONets, we propose an efficient stochastic gradient-based algorithm that enables the distributed optimization of the DeepONet parameters by averaging first-order estimates of the DeepONet loss gradient. Then, to accelerate the training convergence of Fed-DeepONets, we propose a moment-enhanced (i.e., adaptive) stochastic gradient-based strategy. Finally, we verify the performance of Fed-DeepONet by learning, for different configurations of the number of clients and fractions of available clients, (i) the solution operator of a gravity pendulum and (ii) the dynamic response of a parametric library of pendulums.

Moya, Christian↗

DOE OSTI2023

Optimization of Conductive Fins to Minimize UO2 Fuel Temperature and Radial Temperature Gradient

To further the development of low-enriched uranium fuels, precedence has been placed on delivering the same amount of power while lowering the fuel temperature and radial temperature gradient. To address this, modeling efforts have resulted in a novel design featuring conductive fins of varying thermal conductivities and geometries inserted into the fuel matrix. These conductive inserts were not allowed to exceed 6% of the original fuel volume. This constraint was imposed due to other designs displacing 10% of fuel volume. A parametric study was performed that consisted of 2.56 million BISON simulations involving varying fin characteristics (i.e., fin thermal conductivity, number, and geometry) to determine the optimal geometric configuration for a desired amount of fuel volume displaced. The results from this study show that the thickness and length of each fin affect the fuel temperature and temperature gradient more than varying the number and thermal conductivity of the fins. The parametric study resulted in the development of an optimized combination to produce the lowest peak fuel temperature, lowest radial temperature gradient, and highest temperature reduction for the amount of original fuel volume displaced. The simulations presented in this work will eventually be compared with irradiation experiments of similar fuel designs at Idaho National Laboratory’s Advanced Test Reactor.

Paaren, Kyle M.↗

DOE OSTI2024

Improving Cathode Testing with a High-Gradient Cryogenic Normal Conducting RF Photogun

Future electron accelerator applications such as X-ray free electron lasers and colliders are dependent on significantly increasing beam brightness. With the observation that linac beam manipulation’s best preservation of max brightness is at the cathode, we are incentivized to create an environment where we can study how to achieve the highest possible photogun brightness. In order to do so, we intend to extract beams from high-brightness photocathodes with the highest achievable accelerating gradients we can manage in a klystron-powered radiofrequency (RF) photogun. We utilize here cryogenic normal conducting cavities to achieve ultra-high gradients via limitation of breakdown rates (BDR). The low temperatures should also reduce cathode emittance by reducing the mean transverse energy (MTE) of electrons near the photoemission threshold. To this end, we have designed and produced a new CrYogenic Brightness-Optimized Radiofrequency Gun (CYBORG) for use in a new beamline at UCLA. We will introduce the enabling RF and photoemission physics as a primer for the new regime of high field low temperature cathodes we intend to enter. We further report the current status of the beamline commissioning, including the cooling of the photogun to 100 K, and producing 0.5 MW of RF feed power, which corresponds to cathode accelerating fields in the range of 80–90 MV/m. We further plan iterative improvements to both to 77 K and 1 MW corresponding to our ultimate goal >120 MV/m. Our discussion will include future beamline tests and the consideration of the initial realization of an ultra-high-gradient photoinjector concept.

Lawler, Gerard Emile (ORCID:0000000160113435)↗

DOE OSTI2024

Experimental Study of Alfvén Wave Reflection from an Alfvén-speed Gradient Relevant to the Solar Coronal Holes

Abstract We report the first experimental detection of a reflected Alfvén wave from an Alfvén-speed gradient under conditions similar to those in coronal holes. The experiments were conducted in the Large Plasma Device at the University of California, Los Angeles. We present the experimentally measured dependence of the coefficient of reflection versus the wave inhomogeneity parameter, i.e., the ratio of the wavelength of the incident wave to the length scale of the gradient. Two-fluid simulations using the Gkeyll code qualitatively agree with and support the experimental findings. Our experimental results support models of wave heating that rely on wave reflection at low heights from a smooth Alfvén-speed gradient to drive turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Applying the Velocity Gradient Technique in NGC 1333: Comparison with Dust Polarization Observations

Magnetic fields (B-fields) are ubiquitous in the interstellar medium (ISM), and they play an essential role in the formation of molecular clouds and subsequent star formation. However, B-fields in interstellar environments remain challenging to measure, and their properties typically need to be inferred from dust polarization observations over multiple physical scales. In this work, we seek to use a recently proposed approach called the velocity gradient technique (VGT) to study B-fields in star-forming regions and compare the results with dust polarization observations in different wavelengths. The VGT is based on the anisotropic properties of eddies in magnetized turbulence to derive B-field properties in the ISM. We investigate that this technique is synergistic with dust polarimetry when applied to a turbulent diffused medium for the purpose of measuring its magnetization. Specifically, we use the VGT on molecular line data toward the NGC 1333 star-forming region ( 12 CO, 13 CO, C 18 O, and N 2 H + ), and we compare the derived B-field properties with those inferred from 214 and 850 μm dust polarization observations of the region using Stratospheric Observatory for Infrared Astronomy/High-Resolution Airborne Wide-band Camera Plus and James Clerk Maxwell Telescope/POL-2, respectively. We estimate both the inclination angle and the 3D Alfvénic Mach number M A from the molecular line gradients. Crucially, testing this technique on gravitationally bound, dynamic, and turbulent regions, and comparing the results with those obtained from polarization observations at different wavelengths, such as the plane-of-sky field orientation, is an important test on the applicability of the VGT in various density regimes of the ISM. We in general do not find a close correlation between the velocity gradient inferred orientations and the dust inferred magnetic field orientations.

79 ASTRONOMY AND ASTROPHYSICS↗