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DOE OSTI2022

Investigation of Ga 2 O 3 as a new transparent conductive oxide for photovoltaics applications

This small innovation project intended to leverage recent activity and advances in ultrawide-bandgap oxide power electronics toward the investigation of Ga 2 O 3 as a transparent conductive oxide (TCO) for use in photovoltaics (PV). Ga 2 O 3 ’s theoretical advantage over incumbent TCOs is its very large bandgap of 4.8 eV, ensuring optical transparency of photons with λ ≥ 260 nm, effectively the full terrestrial solar spectrum. At the time of proposal writing, literature on Ga 2 O 3 as a TCO/optical material was relatively sparse — what little existed was focused on for UV sensors and/or emitters, with none related to PV. As such, this project was intended to help determine the potential of Ga 2 O 3 as a PV-oriented TCO by investigating its deposition using tools common to the PV and electronics industries — atomic layer deposition (ALD) and RF sputtering (RS), both of which are already used in PV manufacturing — and its resultant optical and electronic properties. Final project goals were to test its application to Si and III-V solar cells. Controllable film thickness and excellent uniformity was established for both methods deposition methods, with ALD providing higher precision for thinner films and RS more effective for growing thicker films. The as-deposited films were found to be amorphous in nature. Spectroscopic ellipsometry (SE) confirmed bandgaps of at least 4.8 eV and non-parasitic absorption across both AM0 and AM1.5G spectra; a refractive index approaching the expected value of 1.8 was also observed, with some degree of tunability based on process parameters. Using this initial optical data, a transfer matrix model, which interfaces with in-house EQE and LIV models, was developed to simulate Ga 2 O 3 optical effects on various solar cells, included potential in antireflection coatings (ARCs). Despite promising optical properties, the resultant resistivity / conductivity metrics did not meet expectations, regardless of deposition process. Although thick RS-deposited films, using both undoped and 1 at% Ge (n-type) doped sintered targets — demonstrated high net carrier concentrations (via C-V), and low specific resistance Ohmic contacts were demonstrated, transmission line measurements (TLM) showed very high resistivity. Further analysis indicated high vertical film conductivity, but very low lateral conductivity. Deeper characterization revealed a relatively high density of nano/microcrystalline inclusions that were ostensibly the source of the vertical conductivity, with the amorphous matrix serving as an effective insulator (likely due to high concentrations of electronic trap states). Despite extensive work to increase film polycrystallinity — demonstrated via high temperature annealing — sufficient lateral conductivity for TCO use was not achieved. The final phase of the project shifted focus toward investigation of ALD-deposited Ga 2 O 3 ’s potential as a passivant and/or passivating contact for both Si and III-V solar cells, with expectation of performance similar to Al 2 O 3 . However, initial rounds of testing using our baseline ALD process yielded minimal (but not quite zero) passivation of both GaInP and Si surfaces. Dielectric passivation is well-known to be highly process sensitive; given the unoptimized nature of the process used, this work was deemed inconclusive. The final outlook with respect to feasibility of Ga 2 O 3 as a PV-oriented TCO is, ultimately, still uncertain. The work performed in this project confirmed the optical properties and deposition methods, but the achieved electrical properties do not meet technological needs; literature reports in recent years are somewhat inconsistent and potentially untrustworthy, but generally appear to be in line with our results. At the very least it is clear that, should Ga 2 O 3 still be under consideration for PV TCO and/or selective contact applications, a significant amount of optimization and study is still needed.

14 SOLAR ENERGY↗

DOE OSTI2014

Control and diagnosis of temperature, density, and uniformity in x-ray heated iron/magnesium samples for opacity measurements

Experimental tests are in progress to evaluate the accuracy of the modeled iron opacity at solar interior conditions, in particular to better constrain the solar abundance problem [S. Basu and H. M. Antia, Phys. Rep. 457, 217 (2008)]. Here, we describe measurements addressing three of the key requirements for reliable opacity experiments: control of sample conditions, independent sample condition diagnostics, and verification of sample condition uniformity. The opacity samples consist of iron/magnesium layers tamped by plastic. By changing the plastic thicknesses, we have controlled the iron plasma conditions to reach (1) T{sub e} = 167 ± 3 eV and n{sub e} = (7.1 ± 1.5)× 10{sup 21} cm{sup −3}, (2) T{sub e} = 170 ± 2 eV and n{sub e} = (2.0 ± 0.2) × 10{sup 22} cm{sup −3}, and (3) T{sub e} = 196 ± 6 eV and n{sub e} = (3.8 ± 0.8) × 10{sup 22} cm{sup −3}, which were measured by magnesium tracer K-shell spectroscopy. The opacity sample non-uniformity was directly measured by a separate experiment where Al is mixed into the side of the sample facing the radiation source and Mg into the other side. The iron condition was confirmed to be uniform within their measurement uncertainties by Al and Mg K-shell spectroscopy. The conditions are suitable for testing opacity calculations needed for modeling the solar interior, other stars, and high energy density plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

A Review of Advanced Test Reactor Fuel and Assessment of Its Compatibility with the ZIRCEX Chlorination Process

Advanced Test Reactor (ATR) fuel has been identified as a resource for high-assay low-enriched uranium (HALEU) production. A survey was performed on the published literature describing ATR fuel. The geometry of the fuel is complex; different parts of the fuel compact experience differing neutron flux and burnup. The literature is sparse, and access is controlled. Therefore, fundamental studies of fuel reprocessing must use a model fuel that represents the main chemical and structural features. Advanced chlorination, or chlorination with sulfur-chlorine bearing reagents is being investigated as way to separate the fuel from metal matrix alloys. A UAl x alloy will be fabricated with x = 3, 4, and 5. The potential chlorination of individual UAl x intermetallics will be assessed in the advanced chlorination process of Al-8001 and Al-6061 as well as a representative mixture. Initial studies will track the alloying elements of the Al, which are Si, Fe, Cu, Mn, Mg, Cr, Zn, and Ti, in addition to the U itself. Further studies will include fission product simulants. Because advanced chlorination solvents include sulfur, the chemistry of sulfur with major and minor constituents will also be investigated. The experimental work accompanied by neutronic calculations will allow the assessment of the feasibility of advanced chlorination to separate aluminum from uranium. If bench-scale testing appears promising, then small-scale tests in shielded facilities with irradiated cladding, lightly irradiated fuel, and spent nuclear fuel are recommended to track the complete inventory of fissile actinides, fission product impurities, and reagent solids and liquids.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Advanced grid-forming (GFM) inverter controls, modeling and system impact study for inverter dominated grids

Our main goals in this project are to understand: 1) the stability of the power system with very high penetration of PV or other inverter-based resources (IBR), 2) the interactions among IBRs and traditional generators, and 3) the impact of the GFM inverters on bulk power system. To achieve these goals, we took a holistic research and development approach. First, an impedance-based large system modeling and stability analysis tool was developed to aid the large IBR system small-signal stability analysis. Second, consensus-based control and transient overload ride through were developed to control and coordinate multiple GFM inverters in a large system to maintain transient stability during big grid events. Third, high fidelity electromagnetic transient (EMT) IBR models were developed and integrated into a large reduced WECC model to study the system impact from IBRs. Lastly, extensive validation tests of the GFM control which was developed in this project and implemented in two 1MW commercial solar inverters were performed using different validation platforms, e.g., control hardware-in-the-loop (CHIL) platform, power hardware- in-the-loop (PHIL) platform, and a real PV plant.

14 SOLAR ENERGY↗

DOE OSTI2017

{sup 18}F-Fluorodeoxyglucose/Positron Emission Tomography Predicts Patterns of Failure After Definitive Chemoradiation Therapy for Locally Advanced Non-Small Cell Lung Cancer

Background: We previously reported that pretreatment positron emission tomography (PET) identifies lesions at high risk for progression after concurrent chemoradiation therapy (CRT) for locally advanced non-small cell lung cancer (NSCLC). Here we validate those findings and generate tumor control probability (TCP) models. Methods: We identified patients treated with definitive, concurrent CRT for locally advanced NSCLC who underwent staging {sup 18}F-fluorodeoxyglucose/PET/computed tomography. Visible hypermetabolic lesions (primary tumors and lymph nodes) were delineated on each patient's pretreatment PET scan. Posttreatment imaging was reviewed to identify locations of disease progression. Competing risks analyses were performed to examine metabolic tumor volume (MTV) and radiation therapy dose as predictors of local disease progression. TCP modeling was performed to describe the likelihood of local disease control as a function of lesion size. Results: Eighty-nine patients with 259 hypermetabolic lesions (83 primary tumors and 176 regional lymph nodes) met the inclusion criteria. Twenty-eight patients were included in our previous report, and the remaining 61 constituted our validation cohort. The median follow-up time was 22.7 months for living patients. In 20 patients, the first site of progression was a primary tumor or lymph node treated with radiation therapy. The median time to progression for those patients was 11.5 months. Data from our validation cohort confirmed that lesion MTV predicts local progression, with a 30-month cumulative incidence rate of 23% for lesions above 25 cc compared with 4% for lesions below 25 cc (P=.008). We found no evidence that radiation therapy dose was associated with local progression risk. TCP modeling yielded predicted 30-month local control rates of 98% for a 1-cc lesion, 94% for a 10-cc lesion, and 74% for a 50-cc lesion. Conclusion: Pretreatment FDG-PET identifies lesions at risk for progression after CRT for locally advanced NSCLC. Strategies to improve local control should be tested on high-risk lesions, and treatment deintensification for low-risk lesions should be explored.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2024

Efficient particle control in systems with large density gradients

Simulations of large density gradients present a number of challenges for direct Monte Carlo methods, since they lead to too few particles in dilute regions and prohibitively many in the dense regions. Here, we propose a particle control methodology that gives the user more control of the number of particles per cell by introducing a variable weight for each particle. The proposed scheme is based on the stochastic weighted particle method, requires only small modifications to DSMC, and exactly conserves mass, momentum, and energy. In validation tests of systems with density ratios of order 102-104, we observe 101-102 times less variance in the dilute region compared to a DSMC solution with the same number of system particles, while introducing a moderate additional computational cost.

DSMC↗

DOE OSTI2023

Validating continuum theory for Cottrell atmosphere solute drag by molecular dynamics simulations

When a dislocation moves through a field of mobile solute atoms, solutes segregate to the dislocation and form Cottrell atmospheres which exert solute drag forces. Over the last 70 years, continuum theory has been used extensively to estimate these drag forces and their dependence on the dislocation velocity, however few prior works have validated the accuracy of continuum theories. Here, in this work, molecular dynamics (MD) simulations of dislocation motion in face-centered cubic Ni containing interstitial H atoms were performed in order to test the accuracy of continuum theory predictions. Our results demonstrate that continuum theory provides an accurate estimate of the solute drag force for velocities below the critical velocity at which the solute drag force is maximized. Above the critical velocity, continuum theory systematically deviates from MD. Additional analysis reveals that this deviation results from the multi-valued and unstable nature of solute drag under load control, and also from the transition to random solute drag which occurs at high velocities.

Dislocations↗

DOE OSTI2013

Semiclassical Monte-Carlo approach for modelling non-adiabatic dynamics in extended molecules

Modelling of non-adiabatic dynamics in extended molecular systems and solids is a next frontier of atomistic electronic structure theory. The underlying numerical algorithms should operate only with a few quantities (that can be efficiently obtained from quantum chemistry), provide a controlled approximation (which can be systematically improved) and capture important phenomena such as branching (multiple products), detailed balance and evolution of electronic coherences. Here we propose a new algorithm based on Monte-Carlo sampling of classical trajectories, which satisfies the above requirements and provides a general framework for existing surface hopping methods for non-adiabatic dynamics simulations. In particular, our algorithm can be viewed as a post-processing technique for analysing numerical results obtained from the conventional surface hopping approaches. Presented numerical tests for several model problems demonstrate efficiency and accuracy of the new method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

Fables of reconstruction: controlling bias in the dark energy equation of state

We develop an efficient, non-parametric Bayesian method for reconstructing the time evolution of the dark energy equation of state w(z) from observational data. Of particular importance is the choice of prior, which must be chosen carefully to minimise variance and bias in the reconstruction. Using a principal component analysis, we show how a correlated prior can be used to create a smooth reconstruction and also avoid bias in the mean behaviour of w(z). We test our method using Wiener reconstructions based on Fisher matrix projections, and also against more realistic MCMC analyses of simulated data sets for Planck and a future space-based dark energy mission. While the accuracy of our reconstruction depends on the smoothness of the assumed w(z), the relative error for typical dark energy models is ∼<10% out to redshift z = 1.5.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Cybersecurity Assessment in DER-rich Distribution Operations: Criticality Levels and Impact Analysis

The integration of distributed energy resources (DERs) in distribution networks has become a pivotal strategy for achieving decarbonization, enhancing grid resilience, and optimizing grid efficiency. Remote monitoring and control op- erations of such resources rely on a network of sensors and communication infrastructure, exposing the system to potential cyber threats. Therefore, as the deployment of DERs increases, ensuring secure monitoring and control becomes an imperative challenge. This paper utilizes real-time feeder models, which are instrumental in developing cybersecurity testbeds tailored for hardware-in-loop (HIL) systems. These models enable users to simulate cyber attacks in a real-world environment and analyze the power distribution operations during vulnerabilities. Furthermore, we discuss several practical sets of grid parameters to identify critical levels of DERs and evaluate various scenarios that simulate cyber threats on sensitive DERs. The modified IEEE 123-bus model is used as the test case for demonstrating the proposed scenarios. The findings from this study provide valuable insights into the vulnerabilities and potential consequences of cyber attacks on DERs, allowing for better mitigation strategies and improved cyber resilience in future distribution networks.

Maharjan, Manisha↗

DOE OSTI2019

Distributed Load Restoration in Unbalanced Active Distribution Systems

We present that the resilience of modern power systems has been constantly threatened by various natural disasters and manmade attacks. Under those threats, fast and automatic restoration actions are critical for restoring impacted systems to normal operating conditions and preventing from additional disastrous consequences. Smart grid technologies, such as distributed energy resources (DERs) and microgrids, provide both opportunities and challenges for distribution system restoration. In this paper, distributed load restoration (DLR), in unbalanced active distribution networks is developed using the alternating direction method of multipliers (ADMM) algorithm. The step-by-step restoration actions are provided to schedule the output of DERs and distribution system control devices, as well as the power consumption from transmission system restoration. The nonlinearities from three-phase unbalanced power flow and distribution components modeling are relaxed into a convex quadratic programming model. Then, the problem is decomposed into subproblems for each node by applying ADMM-DLR; and solves through each agent by exchanging limited information with neighboring nodes in an iterative procedure. The developed models and algorithms are validated and demonstrated through testing of the IEEE 13-node and 123-node test feeders. Lastly, simulation results demonstrate the effectiveness of restoring unbalanced distribution system with the hybrid bottom-up and top-down restoration strategies.

14 SOLAR ENERGY↗

DOE OSTI2019

Physical Security Model Development of an Electrochemical Facility.

Nuclear facilities in the U.S. and around the world face increasing challenges in meeting evolving physical security requirements while keeping costs reasonable. The addition of security features after a facility has been designed and without attention to optimization (the approach of the past) can easily lead to cost overruns. Instead, security should be considered at the beginning of the design process in order to provide robust, yet efficient physical security designs. The purpose of this work is to demonstrate how modeling and simulation can be used to optimize the design of physical protection systems. A suite of tools, including Scribe3D and Blender, were used to model up a generic electrochemical reprocessing facility. Physical protection elements such as sensors, portal monitors, barriers, and guard forces were added to the model based on best practices for physical security. One outsider theft scenario was examined with 4-8 adversaries to determine security metrics. This work fits into a larger Virtual Test Bed 2020 Milestone in the Material Protection, Accounting, and Control Technologies (MPACT) program through the Department of Energy (DOE). The purpose of the milestone is to demonstrate how a series of experimental and modeling capabilities across the DOE complex provide the capabilities to demonstrate complete Safeguards and Security by Design (SSBD) for nuclear facilities. ACKNOWLEDGEMENTS This work was funded by the Materials Protection, Accounting, and Control Technologies (MPACT) working group as part of the Nuclear Technology Research and Development Program under the U.S. Department of Energy, Office of Nuclear Energy.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2020

Corroborative Evaluation of the Real-World Energy Saving Potentials of InfoRich Eco-Autonomous Driving (iREAD) System

There has been an increasing interest in exploring the potential to reduce energy consumption of future connected and automated vehicles. People have extensively studied various eco-driving implementations that leverage preview information provided by on-board sensors and connectivity, as well as the control authority enabled by automation. Quantitative real-world evaluation of eco-driving benefits is a challenging task. The standard regulatory driving cycles used for measuring exhaust emissions and fuel economy are not truly representative of real-world driving, nor for capturing how connectivity and automation might influence driving trajectories. To adequately consider real-world driving behavior and potential “off-cycle” impacts, this paper presents four collaborative evaluation methods: large-scale simulation, in-depth simulation, vehicle-in-the-loop testing, and vehicle road testing. These four approaches, spanning simulation and testing aspects, evaluate real-world fuel economy benefits with different ranges and resolutions. The large-scale simulations leverage an extensive real-world driving database to assess overall eco-driving benefits across a range of road network and driving scenarios. The real-world driving data are further leveraged to generate representative driving routes for deeper evaluation. Based on the representative routes, in-depth simulation relying on high-fidelity models investigates how different traffic scenarios can impact the eco-driving performance. The vehicle-in-the-loop setup reinforces the in-depth simulations by conducting tests with an actual vehicle operated on a chassis dynamometer; the measured energy savings were indeed found to agree with the in-depth simulation savings estimates. Finally, limited but representative road testing with the fully integrated vehicle will be conducted to demonstrate the eco-driving capability and conclude the overall evaluation regimen.

ARPA-E↗

DOE OSTI2024

Is a Generator the Only Solution When the Grid Fails? Optimizing Systems for Resiliency and Carbon Reduction: Preprint

Traditionally, buildings are dependent on utility infrastructure, and when a grid failure happens, end users rely on the closest source of energy storage to sustain operation until power is restored. For buildings, that typically means using an electric generator. This electric generator either uses on-site energy storage such as fossil fuels in a tank or a gas connection which is, in turn, tied to gas wells—also a form of energy storage. Generators are popular for their ease of implementation and low capital costs; however, they have limited value outside of disruptions, and they are a source of scope 1 emissions, or direct greenhouse gas emissions from sources controlled by the building owner. In contrast, some power generation and storage systems, such as photovoltaic (PV) panels and battery energy storage systems (BESS), can serve the same purpose during grid disruptions while presenting advantages outside of power failure. This paper explores methods for storing and converting energy on-site to increase building resiliency, focusing on solutions that minimize scope 1 emissions. We analyze the cost and carbon impacts of energy efficiency measures, PV arrays, and BESS, with and without generators, in a simulation test case. We find significant benefits can be achieved both during and outside of power failure events when designing systems that integrate the on-demand capability of generators, the low carbon energy supplied by PV, and the storage capabilities of BESS. Specifically, adding even minimal BESS and PV can result in downsizing the generator, increasing generator efficiency and requiring less fuel.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

DOE OSTI2016

Nitrogen ion implantation into various materials using 28 GHz electron cyclotron resonance ion source

The installation of the 28 GHz electron cyclotron resonance ion source (ECRIS) ion implantation beamline was recently completed at the Korea Basic Science Institute. The apparatus contains a beam monitoring system and a sample holder for the ion implantation process. The new implantation system can function as a multipurpose tool since it can implant a variety of ions, ranging hydrogen to uranium, into different materials with precise control and with implantation areas as large as 1–10 mm{sup 2}. The implantation chamber was designed to measure the beam properties with a diagnostic system as well as to perform ion implantation with an in situ system including a mass spectrometer. This advanced implantation system can be employed in novel applications, including the production of a variety of new materials such as metals, polymers, and ceramics and the irradiation testing and fabrication of structural and functional materials to be used in future nuclear fusion reactors. In this investigation, the first nitrogen ion implantation experiments were conducted using the new system. The 28 GHz ECRIS implanted low-energy, multi-charged nitrogen ions into copper, zinc, and cobalt substrates, and the ion implantation depth profiles were obtained. SRIM 2013 code was used to calculate the profiles under identical conditions, and the experimental and simulation results are presented and compared in this report. The depths and ranges of the ion distributions in the experimental and simulation results agree closely and demonstrate that the new system will enable the treatment of various substrates for advanced materials research.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Design, Preparation, and Execution of the 100-AV Field Test for the CIRCLES Consortium: Methodology and Implementation of the Largest Mobile Traffic Control Experiment to Date

This article presents the comprehensive design, setup, execution, and evaluation of the MegaVanderTest (MVT) experiment conducted by the Congestion Impacts Reduction via CAV-in-the-Loop Lagrangian Energy Smoothing (CIRCLES) Consortium, which aimed to mitigate traffic congestion using partially autonomous vehicles (AVs) (see “Summary”). The experiment involved 100 vehicles on Nashville’s Interstate 24 (I-24) highway, utilizing various control algorithms to smooth stop-and-go traffic waves. The execution of the MVT experiment required a coordinated effort from multiple teams. This article details the meticulous planning process, the coordinated efforts of multiple teams, and the innovative use of a dynamic agent-based simulation framework for traffic evaluation. Here, the contributions of this work include demonstrating and providing a detailed roadmap for large-scale live traffic experiments, illustrating the lessons learned from the MVT experiment, and introducing the other articles in this issue and their complementary relationship in the MVT experiment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Reaction and diffusion at the reservoir/shale interface during CO 2 storage: Impact of geochemical kinetics

Here we use a reactive diffusion model to investigate what happens to CO 2 injected into a subsurface sandstone reservoir capped by a chlorite- and illite-containing shale seal. The calculations simulate reaction and transport of supercritical (SC) CO 2 at 348.15 K and 30 MPa up to 20,000 a. Given the low shale porosity (5%), chemical reactions mostly occurred in the sandstone for the first 2000 a with some precipitation at the ss/sh interface. From 2000 to 4000 a, ankerite, dolomite and illite began replacing Mg–Fe chlorite at the sandstone/shale interface. Transformation of chlorite to ankerite is the dominant reaction occluding the shale porosity in most simulations: from 4000 to 7500 a, this carbonation seals the reservoir and terminates reaction. Overall, the carbonates (calcite, ankerite, dolomite), chlorite and goethite all remain close to local chemical equilibrium with brine. Quartz is almost inert from the point of its dissolution/precipitation. However, the rate of quartz reaction controls the long-term decline in aqueous silica activity and its evolution toward equilibrium. The reactions of feldspars and clays depend strongly on their reaction rate constants (microcline is closer to local equilibrium than albite). The timing of porosity occlusion mostly therefore depends on the kinetic constants of kaolinite and illite. For example, an increase in the kaolinite kinetic constant by 0.25 logarithmic units hastened porosity closure by 4300 a. The earliest simulated closure of porosity occurred at approximately 108 a for simulations designed as sensitivity tests for the rate constants. These simulations also emphasize that the rate of CO 2 immobilization as aqueous bicarbonate (solubility trapping) or as carbonate minerals (mineral trapping) in sandstone reservoirs depends upon reaction kinetics – but the relative fraction of each trapped CO 2 species only depends upon the initial chemical composition of the host sandstone. For example, at the point of porosity occlusion the fraction of bicarbonate remaining in solution depends upon the initial Na and K content in the host rock but the fraction of carbonate mineralization depends only on the Ca, Mg, Fe content. Since ankerite is the dominant mineral that occludes porosity, the dissolved concentration of ferrous iron is also an important parameter. Finally, future efforts should focus on cross-comparisons and ground-truthing of simulations made for standard case studies as well as laboratory measurements of the reactivities of clay minerals.

58 GEOSCIENCES↗

DOE OSTI2026

Neural operator transformers capture bifurcating drift-wave turbulence in fusion plasma simulations

Self-consistent modeling of turbulence-driven transport is critical for optimizing confinement in magnetically confined fusion plasmas, such as tokamaks and stellarators. In particular, capturing the long-term co-evolution of turbulence, flow, and background plasma profiles remains computationally challenging. Direct numerical simulation of these multiscale, highly nonlinear processes is often demanding and impractical for real-time control or design optimization. To address this bottleneck, we investigate transformer-based neural operator partial differential equation surrogates for emulating the dynamics of drift-wave turbulence bifurcation mediated by zonal flows, using the modified Hasegawa–Wakatani (MHW) model as a prototypical system. We find that the finetuned neural operator model has excellent performance in capturing the multi-spatiotemporal-scales of MHW turbulence bifurcation and is robust to testing on rare and out-of-distribution dynamics. Specifically, we demonstrate that a single unified model accurately predicts both quasi-steady-state turbulence and a wide range of dynamical transition processes, such as nonlinear saturation, spontaneous suppression of turbulence, and the emergence of macroscopic zonal flows, over time horizons vastly exceeding the local turbulence correlation time. This computationally efficient approach establishes a strong foundation for fast, AI-based modeling of complex, multiscale phenomena in magnetized fusion plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗