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DOE OSTI2024

Quantitative proteomics reveals extensive lysine ubiquitination and transcription factor stability states in Arabidopsis

Abstract Protein activity, abundance, and stability can be regulated by post-translational modification including ubiquitination. Ubiquitination is conserved among eukaryotes and plays a central role in modulating cellular function; yet, we lack comprehensive catalogs of proteins that are modified by ubiquitin in plants. In this study, we describe an antibody-based approach to enrich ubiquitinated peptides coupled with isobaric labeling to enable quantification of up to 18-multiplexed samples. This approach identified 17,940 ubiquitinated lysine sites arising from 6,453 proteins from Arabidopsis (Arabidopsis thaliana) primary roots, seedlings, and rosette leaves. Gene ontology analysis indicated that ubiquitinated proteins are associated with numerous biological processes including hormone signaling, plant defense, protein homeostasis, and metabolism. We determined ubiquitinated lysine residues that directly regulate the stability of three transcription factors, CRYPTOCHROME-INTERACTING BASIC-HELIX-LOOP-HELIX 1 (CIB1), CIB1 LIKE PROTEIN 2 (CIL2), and SENSITIVE TO PROTON RHIZOTOXICITY1 (STOP1) using in vivo degradation assays. Furthermore, codon mutation of CIB1 to create a K166R conversion to prevent ubiquitination, via CRISPR/Cas9-derived adenosine base editing, led to an early flowering phenotype and increased expression of FLOWERING LOCUS T (FT). These comprehensive site-level ubiquitinome profiles provide a wealth of data for future functional studies related to modulation of biological processes mediated by this post-translational modification in plants.

Biochemistry & Molecular Biology↗

DOE OSTI2024

Diffuse scattering from dynamically compressed single-crystal zirconium following the pressure-induced α → ω phase transition

The prototypical α → ω phase transition in zirconium is an ideal test bed for our understanding of polymorphism under extreme loading conditions. After half a century of study, a consensus had emerged that the transition is realized via one of two distinct displacive mechanisms, depending on the nature of the compression path. However, recent dynamic-compression experiments equipped with diffraction diagnostics performed in the past few years have revealed new transition mechanisms, demonstrating that our understanding of the underlying atomistic dynamics and transition kinetics is in fact far from complete. We present classical molecular dynamics simulations of the α → ω phase transition in single-crystal zirconium shock compressed along the [0001] axis using a machine-learning-class potential. The transition is predicted to proceed primarily via a modified version of the two-stage Usikov-Zilberstein mechanism, whereby the high-pressure ω phase heterogeneously nucleates at boundaries between grains of an intermediate β phase. We further observe the fomentation of atomistic disorder at the junctions between β grains, leading to the formation of highly defective interstitial material between the ω grains. We directly compare synthetic x-ray diffraction patterns generated from our simulations with those obtained using femtosecond diffraction in recent dynamic-compression experiments, and show that the simulations produce the same unique, anisotropic diffuse scattering signal unlike any previously seen from an elemental metal. Our simulations suggest that the diffuse signal arises from a combination of thermal diffuse scattering, nanoparticlelike scattering from residual kinetically stabilized α and β grains, and scattering from interstitial defective structures. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗

DOE OSTI2025

Virtual Critical Coupling in High-Power Resonant Systems

Power reflections are a fundamental challenge in high-power resonant systems, causing energy loss, limiting per- formance, and potentially damaging critical components. This problem is particularly acute in applications such as lower hybrid current drive (LHCD) for tokamak-based nuclear fusion, where efficient, stable power transfer to the plasma is paramount. In this work, we introduce and experimentally demonstrate the virtual critical coupling (VCC) mechanism, a nonmechanical method to achieve reflection-free excitation in high-power S-band resonators. VCC utilizes a temporally shaped excitation signal with a precise complex frequency, tailored to the resonator’s characteristics to enable complete energy absorption. Using a custom low-level RF system and a 5-MW S-band klystron, we conducted experiments from low power (32 mW) to high power (600 kW). Furthermore, the results demonstrate a greater than ninefold reduction in the reflection coefficient compared to conventional monochromatic excitation. This signal processing-based approach offers a robust path toward enhancing the efficiency and stability of high-power resonant systems, with significant implications for particle accelerators and the advancement of nuclear fusion energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Fermilab PIP-II Master Oscillator and Precision Reference Line Design and Construction

The phase averaging reference line system pro- vides the RF phase reference, LO and clock sig- nals to the LLRF and other accelerator sub- systems. The PIP-II linac has RF systems at three frequencies – 162.5 MHz, 325 MHz and 650 MHz. A temperature-stabilized, low-phase- noise oscillator is used as the master oscil- lator. Phase reference signals at 162.5 MHz, 325 MHz, and 650 MHz, along with LO signals at 182.5 MHz, 345 MHz, 670 MHz and LLRF clocks at 1320 MHz and 1300 MHz, are generated in temperature-controlled RF modules at each fre- quency section. A phase reference from each module travels to the next section, where it is doubled to produce required frequencies. The reference also travels alongside the accelerating cavities in the tunnel, allowing cavity probe and reference cables to temperature track and reduce measurement errors from temperature changes or phase drift.

Syed, Ahmed [Fermilab]↗

DOE OSTI2025

Symmetry-violation-driven hysteresis loops as measurands for noise-resilient sensors

Sublinear resonant deviations from an exceptional point degeneracy (EPD) has been recently promoted as a sensing scheme. However, there is still an ongoing debate whether the sensitivity advantage is negated by an increase in fundamental noise – especially when active elements induce self-oscillations. In this case, nonlinearities are crucial in stabilizing amplifying modes and mitigating noise effects. A drawback is the formation of hysteresis loops that signal a transition to unstable modes. This can only be alleviated by precise cavity symmetry management. Here, utilizing two coupled nonlinear (RLC) tanks with balanced amplification and attenuation, we demonstrate that an explicit symmetry violation, induced by sweeping the resonant detuning of the (RLC) tanks, reveals a hysteresis loop near the EPD whose width scales sublinearly with the inter-tank coupling. Furthermore, our proposal re-envisions this disadvantageous feature as a sensing protocol with diverging sensitivity, enhanced signal-to-noise ratio, and self-calibration without requiring delicate symmetry control. As such, it opens new avenues in metrology as well as for optical/RF switching and triggering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Wireless Pulse-Width Modulation Control of Power Converters Using Ultra-Wideband Technology for Distributed High-Voltage Systems

In this study, we present a new approach for wireless pulse-width modulation (PWM) control of a power converter, applicable to numerous power converters within a complex electrical distribution system. This method eliminates the need for multiple physical connections of gating/PWM signals among distributed converter modules. By using ultra-wideband-based communication, the PWM control signals can be wirelessly transmitted from a central controller to multiple converters simultaneously and seamlessly. System stability is thoroughly analyzed, and experimental results validate the efficacy of the wireless control scheme for a buck converter operating at a 50-kHz switching frequency. The minimum latency obtained from this setup is 5.38 ..mu..s. This control concept offers easier implementation of distributed control in high-voltage power systems, especially in multilevel architectures, even under harsh conditions with ambient noise.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Wireless Pulse-Width Modulation Control of Power Converters Using Ultra-Wideband Technology for Distributed High-Voltage Systems: Preprint

In this study, we present a new approach for wireless pulse-width modulation (PWM) control of a power converter, applicable to numerous power converters within a complex electrical distribution system. This method eliminates the need for multiple physical connections of gating/PWM signals among distributed converter modules. By using ultra-wideband-based communication, the PWM control signals can be wirelessly transmitted from a central controller to multiple converters simultaneously and seamlessly. System stability is thoroughly analyzed, and experimental results validate the efficacy of the wireless control scheme for a buck converter operating at a 50-kHz switching frequency. The minimum latency obtained from this setup is 5.38 mus. This control concept offers easier implementation of distributed control in high-voltage power systems, especially in multilevel architectures, even under harsh conditions with ambient noise.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

A Reinforcement Learning Approach to Augment Conventional PID Control in Nuclear Power Plant Transient Operation

The ability of nuclear reactors to operate their power conversion cycles more flexibly will enhance their value to energy grids with variable pricing. Current nuclear control systems are typically classical controllers that are often based on proportional-integral-derivative (PID) control. This paper presents a method of augmenting the existing PID control for difficult transient operations in nuclear power plants using a reinforcement learning–derived feedforward signal applied in real time. The agents, which are trained on a test thermal load-following problem, are designed to improve steam generator outlet temperature control for a range of fast load-following scenarios covering ramp rates from 9%/min to 15%/min. Several reinforcement learning algorithms were initially investigated for the training of the feedforward agents with deep Q-learning (DQN) and proximal policy optimization (PPO) networks, which were found to be the most promising. The DQN controllers utilize discrete actions, giving them a better disturbance rejection at steady state but inconsistent response to initial temperature deviations. In contrast, PPO-trained agents, which take continuous actions except for a dead zone around zero, were shown to have the best combination of high disturbance rejection at steady state and good tracking of the desired temperature value. The ability of the PPO agent was also examined, with the average time of decision making found to be on the order of 1 ms. The fault properties of the controller under the loss of the reinforcement learning agent feedforward signal were also examined. The controller showed strong performance in situations of “no-signal” faults. but was less good at handling “stuck-at” faults, where the feedforward signal remains at a set value. In both cases, however, the PID was able to successfully maintain stability, eventually returning the system to a steady state. It is hoped that this work will allow for the proposed control architecture to be examined for more difficult control problems such that it may eventually be used to adapt existing nuclear plants for more aggressive load-following on grids of the future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Characterization of high-flux cadmium zinc telluride detectors coupled to MM-PAD readout ASICs for high-flux X-ray applications

High-flux cadmium zinc telluride (HF-CZT) is a promising material for next-generation X-ray imaging due to its high stopping power, wide bandgap, and improved resistance to radiation-induced polarization [1]. We bonded 2 mm thick HF-CZT sensors with Cornell's Mixed-Mode Pixel Array ASICs, which combine analog charge integration and in-pixel digital counting to achieve single X-ray sensitivity, large full well capacity, and frame rates up to 10 kHz [2,3]. Detector characterization showed stable electron collection above 150 V bias, while hole collection remained limited by trapping even at 700 V. Temporal studies revealed non-negligible afterglow, with an unexpected increase in afterglow at higher biases, which was reduced by infrared illumination, suggesting that injected carriers reduce trapping near contact interfaces. Polarization measurements confirmed improved stability compared to conventional CZT, though polarization effects persisted, particularly with hole collection, with up to 5% signal loss and spatial distortion at high doses.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Deep-learning methods for contrast enhancement and artifact reduction in cryo-electron tomography: a systematic analysis of the state of the art and proposed improvements

Cryo-electron tomography (cryo-ET) has emerged as the preferred technique for visualizing the organization of macromolecular complexes in situ and resolving their structures at subnanometre resolution [Tegunov et al. (2021)View full citation, Nat. Methods, 18, 186–193]. Despite improvements in data quality as a result of advances in detector technology, microscope stability and stage precision, the analysis and interpretation of tomograms remains challenging due to a low signal-to-noise ratio and reconstruction artifacts stemming from experimental constraints in specimen tilt during data collection resulting in a missing wedge in the Fourier space. Recently, self-supervised deep-learning methods have been proposed for contrast enhancement and reduction of resolution anisotropy in reconstructed tomograms. Here, we evaluate several state-of-the-art deep-learning methods which aim to improve the interpretability of cryo-ET reconstructions, with a focus on their performance on downstream tasks of template matching, subtomogram averaging and segmentation. We propose new training architectures and a loss function based on Fourier shell correlation that show improved performance over the standard U-Net with L1/L2 losses. We demonstrate our analysis on four diverse experimental datasets: purified 80S ribosomes, in situ Chlamydomonas reinhardtii, immature HIV-1 virus-like particles and INS-1E cells.

contrast enhancement↗

DOE OSTI2024

Structural and biochemical analyses of the nuclear IκBζ protein in complex with the NF-κB p50 homodimer

As part of the efforts to understand nuclear IκB function in NF-κB-dependent gene expression, we report an X-ray crystal structure of the IκBζ ankyrin repeat domain in complex with the dimerization domain of the NF-κB p50 homodimer. IκBζ possesses an N-terminal α helix that conveys domain folding stability. Affinity and specificity of the complex depend on a small portion of p50 at the nuclear localization signal. The model suggests that only one p50 subunit supports binding with IκBζ, and biochemical experiments confirm that IκBζ associates with DNA-bound NF-κB p50:RelA heterodimers. Comparisons of IκBζ:p50 and p50:κB DNA complex crystallographic models indicate that structural rearrangement is necessary for ternary complex formation of IκBζ and p50 with DNA.

Cell Biology↗

DOE OSTI2024

Anomaly Detection and Mitigation for Dynamic Frequency Regulation in Hydropower-Battery Systems

Hydropower operators and energy storage providers are increasingly interested in participating in frequency regulation services, driven by the incentives offered by independent system operators, such as the PJM Interconnection. This transition, however, unfolds against the backdrop of a modernizing and rapidly digitizing power grid, exposing the integrated legacy infrastructure to a multitude of cybersecurity threats. This work presents an approach for developing an anomaly detection and mitigation system to address cybersecurity challenges during the participation of a hydropower-integrated battery energy storage system (BESS) in a frequency regulation market. The applied anomaly detector utilizes machine learning algorithms to provide detailed classification of cyber-physical events. Later, the applied mitigation system triggers predefined corrective actions to minimize the impact of data integrity attacks on the regulation market and system stability. We evaluated the proposed approach on a hydropower-integrated BESS topology, specifically analyzing the slow regulation signal (Reg A) coming from the PJM market. Our simulation results demonstrate that the proposed approach performs well in detecting data integrity attacks within the allocated time frame and also minimizes the system's transient instability during the participation of hydropower and BESS in the regulation market.

battery energy storage system↗

DOE OSTI2025

Development of BPM Electronics for PIP-II at Fermilab

This paper presents the uTCA4.0-based BPM electronics for PIP-II, featuring four 250 MSPS ADCs and a Xilinx UltraScale+ MPSoC FPGA with 10 GbE uplink. Design elements include signal conditioning, clock, and thermal management. The FPGA performs signal processing, time tagging, digital down-conversion, and phase drift compensation. Position and phase resolution, and thermal stability is validated through dedicated testing.

Liu, Shengli [Fermilab] (ORCID:0009000128436936)↗

DOE OSTI2025

Development of BPM electronics for PIP-II at Fermilab

Liu, Shengli [Fermilab] (ORCID:0009000128436936)↗

DOE OSTI2026

Development of electron source feedback for enhanced X-ray beam stability at NSLS-II

Future synchrotron light sources are being designed to deliver significantly higher brightness and coherence, enabling faster scanning and more advanced imaging techniques. However, realizing these capabilities requires improved X-ray beam stability, as vibrations directly limit measurement accuracy and image quality. At the NSLS-II Hard X-ray Nanoprobe (HXN), a local mechanical feedback system mitigates low-frequency motion but provides only limited suppression of dominant vibrations at 27 Hz and 120 Hz. To address this limitation, this work explores the use of the electron beam itself as the actuator for feedback by integrating X-ray beam position monitor signals into the fast orbit feedback system through a dedicated electrometer. Experimental results show that this approach effectively suppresses the dominant vibration peaks and enhances stability at the focusing point. Benchmark ptychography measurements further confirm that electron-beam-based feedback reduces background fluctuations and mitigates vibration-induced artifacts under fast-scanning conditions. These results establish the feasibility of using the electron beam as a feedback actuator for next-generation synchrotron applications and provide an experimental assessment of its potential and limitations.

36 MATERIALS SCIENCE↗

DOE OSTI2026

A data-driven approach to real-time vertical position estimation for NSTX-U vertical stability control

In this paper, a database of 77 996 plasma equilibrium reconstructions from 727 discharges during the initial operation of the NSTX-U spherical tokamak is analyzed to develop a statistically robust model of the plasma vertical position for real-time control. A variety of regression models are developed and tested, ranging in complexity from linear models to deep neural networks, and including input signals ranging from the four pairs of flux loops used historically on NSTX-U up to the full set of 389 real-time signals available to the plasma control system. A linear model based on 140 real-time magnetics signals is found to offer excellent accuracy, with a coefficient of determination R 2 = 0.906. The robustness of this model to limited training data, new operating scenarios, and signal errors is tested, and a procedure is demonstrated to tune the model parameters to optimize its robustness. A time-dependent plasma equilibrium solver, TokaMaker, is used to simulate vertical stability control in NSTX-U, demonstrating that it should be possible to iteratively tune the parameters of a linear vertical position model to stabilize both positive and negative triangularity plasmas in future experiments.

magnetic diagnostics↗

DOE OSTI2026

A Pulsar-Inspired Timing Framework for Power System: Optimization and Performance Evaluation

Due to their excellent stability, neutron pulsar stars are considered promising candidate timing sources for power system applications. However, the complexity of pulsar signals necessitates advanced processing algorithms to provide accurate timing references. This paper presents the foundational framework for pulsar signal processing, serving as the basis for further optimization. To enhance the timing accuracy and computation efficiency in pulsar period searches, three algorithms are proposed as the initial optimization step: wavelet de-noising, fast folding, and cross-correlation for profile evaluation. Wavelet de-noising improves signal-to-noise ratio (SNR) by 36%–70%. Fast folding reduces computation time from hundreds of seconds to mere milliseconds. Cross-correlation works better than traditional SNR-based methods by effectively identifying the optimal period. The performance of the proposed algorithms is evaluated using observation data from telescopes. Together, these algorithms significantly improve pulsar timing performance, reducing the error of the Pulse Per Second (PPS) signal from hundreds to tens of microseconds.

Wu, Ori [ORNL] (ORCID:0000000326723410)↗

DOE OSTI2025

Analysis Background & Noise in Stretched Wire Alignment Technique Measurements

The Stretched-Wire Alignment Technique (SWAT) is one method of magnet alignment for linear induction accelerators. The applications of SWAT have been implemented for aligning solenoid magnets on the Scorpius linear induction accelerator which will be sited at the Nevada National Security Site and the Flash X-Ray (FXR) linear induction accelerator at Lawrence Livermore National Laboratory’s Contained Firing Facility. This article describes both systematic (repeatable) and random sources of background and noise as well as practical ways to eliminate or reduce them to acceptable levels. Systematic sources include reflections from wire ends, rapid sag due to ohmic heating of the wire, magnetic materials, and shot rate. Random sources include air currents, vibration of nearby equipment, mechanical stability of test equipment, and the instruments used to measure the wire motion. Mitigations include curve fitting and adaptive noise signal cancellation, and mechanical damping. Finite Element Analysis (FEA) was used to identify and resolve a repeatable wire vibration frequency interfering with the signal resolution. Two stretched wire alignment technique set ups from Sandia National Labs and Lawrence Livermore National Lab have shown background noise sources and ways of mitigating them by either analysis methods or change of mechanical configuration. Conclusions that were drawn included the severe sensitivity of the deflection to even small external interferences of the SWAT wire such that it requires attention to detail in mechanical set up and analysis.

Linear Inductive Accelerator↗