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DOE OSTI2024

Dual-energy electron storage ring

A dual-energy electron storage ring is a novel concept initially proposed to cool hadron beams at high energies. The design consists of two closed rings operating at significantly different energies: the low-energy ring and the high-energy ring. These two rings are connected by an energy recovery linac (ERL) that provides the necessary energy difference. The ERL features superconducting radio-frequency (SRF) cavities that first accelerate the beam from the low energy E L to the high energy E H and then decelerate the beam from E H to E L in the next pass. The different SRF cavities in the ERL section can be adjusted based on the applications. In this paper, we present a possible layout of a dual-energy electron storage ring. The preliminary optics of the ring is designed to optimize chromaticity correction, dynamic aperture, momentum aperture, beam lifetime, radiation damping, and intrabeam scattering effects. The primary focus of this paper is on the stability conditions and beam dynamics studies associated with this storage ring. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Dynamical logical qubits in the Bacon-Shor code

The Bacon-Shor code is a quantum error correcting subsystem code composed of weight-2 check operators that admits a single logical qubit, and has distance 𝑑 on a 𝑑×𝑑 square lattice. We show that when viewed as a Floquet code, by choosing an appropriate measurement schedule of the check operators, it can additionally host several dynamical logical qubits. Specifically, we identify a period-4 measurement schedule of the check operators that preserves logical information between the instantaneous stabilizer groups. Such a schedule not only measures the usual stabilizers of the Bacon-Shor code, but also measures and promotes gauge operators of the parent subsystem code to additional temporary stabilizers that protect the dynamical logical qubits against errors. We show that the code distance of these Floquet-Bacon-Shor codes scales as Θ⁢(𝑑/√𝑘) on an 𝑛=𝑑×𝑑 lattice with 𝑘 dynamical logical qubits, along with the logical qubit of the parent subsystem code. Unlike the usual Bacon-Shor code, the Floquet-Bacon-Shor code family introduced here can therefore saturate the subsystem bound 𝑘⁢𝑑=𝑂⁡(𝑛). Moreover, several errors are shown to be self-corrected purely by the measurement schedule itself. This work provides insights into the design space for dynamical codes and expands the known approaches for constructing Floquet codes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Stabilizing Non-Abelian Topological Order Against Heralded Noise via Local Lindbladian Dynamics

An important open question for the current generation of highly controllable quantum devices is understanding which phases can be realized as stable steady states under local quantum dynamics. In this work, we show how robust steady-state phases with both Abelian and non-Abelian mixed-state topological order can be stabilized, in two spatial dimensions, against generic “heralded” noise using active dynamics that incorporate measurement and feedback, modeled as a fully local Lindblad master equation. These topologically ordered steady states are two-way connected to pure topologically ordered ground states using local quantum channels, and preserve quantum information for a time that is exponentially large in the system size. Specifically, we present explicit constructions of families of local Lindbladians for both Abelian (ℤ 2 ) and non-Abelian (𝐷 4 ) topological order whose steady states host mixed-state topological order when the noise is below a threshold strength. As the noise strength is increased, these models exhibit first-order transitions to intermediate mixed-state phases where they encode robust classical memories, followed by (first-order) transitions to a trivial steady state at high noise rates. When the noise is imperfectly heralded, steady-state order disappears but our active dynamics significantly enhances the lifetime of the encoded logical information. To carry out the numerical simulations for the non-Abelian 𝐷 4 case, we introduce a generalized stabilizer tableau formalism that permits efficient simulation of the non-Abelian Lindbladian dynamics.

Monte Carlo methods↗

DOE OSTI2025

Optimization of an aerostructural machining process using physics-guided Bayesian stability modelling

Existing algorithms for predicting milling chatter have not been widely adopted in industry since they require specialized instruments to measure the stability inputs. This study describes how the machining process for a meter-scale aluminum aerostructure was optimized using a physics-guided Bayesian stability model. The study was performed in collaboration with an industrial partner on production machines to evaluate the practicality of the proposed method under real-world conditions. For each cutting tool, the Bayesian approach automatically selected a small number of cutting tests, which were monitored using a microphone to observe the chatter frequency. The algorithm learned the system dynamics, cutting forces, and stability map from these test results. A novel algorithm for predicting tool bending stress was incorporated into the test selection algorithm to avoid tool breakage. On average, each set of optimized cutting parameters required less than six tests to identify and were 97% more productive than baseline parameters from the cutting tool manufacturer. The machining program was then further optimized using commercial feedrate scheduling software to remove cutting force spikes and reduce air cutting time. Five components were machined using the optimized process. These results demonstrate the potential for physics-guided Bayesian models to improve productivity in industrial settings.

Cornelius, Aaron [UT Knoxville]↗

DOE OSTI2026

A State-Space Model for Stability Boundary Analysis of Grid-Following Voltage Source Converters Considering Grid Conditions

With the growing significance of renewable energy resources and energy storage systems, the number of grid-connected inverters has been rising at an increasingly rapid pace. Generally, these inverters are directly integrated with the distribution network by synchronizing with the grid voltage at the point of common coupling. However, the low grid strength and varying R/X ratios, as the common characteristics of most distribution networks or weak grids, can lead to dynamic interactions that comprise stability and limit the power transfer capacity of grid-connected inverters. To ensure stable operation of the inverters, researchers must determine the stability boundary, described as the maximum power transfer capacity of grid-connected inverters under the premise of maintaining system small-signal stability. For this purpose, we propose to formulate a state-space model of the system in the synchronously rotating dq-frame of reference and perform eigenvalue analysis to determine the stability boundary. With a detailed model of the control structure and parameters of the grid-connected inverters, the stability boundary is identified as a surface with respect to different grid strengths and R/X ratios. Case study results of proposed eigenvalue analysis are compared with those of admittance model-based stability analysis as well as time-domain simulation using a switching model in Matlab/Simulink, validating the effectiveness and accuracy of the proposed eigenvalue analysis for stability boundary identification.

grid-connected inverters↗

DOE OSTI2024

Conducting polymer-based electrochemical sensors: Progress, challenges, and future perspectives

Conducting polymers are promising due to their unique properties, such as excellent electrical and optical properties, physical and chemical stability, high conductivity, and effective redox properties with high-temperature stability and biocompatibility. Due to these properties, conducting polymers are useful in diverse applications like sensors, batteries, oil industries, biosensors, biomedicines, catalysis, cancer treatment, etc. This review article aims to discuss the recent trends and analysis of conducting polymer-based electrochemical sensors in diverse areas with all required sensor characteristics, such as the derived limit of detection, utilized techniques for the sensing analysis and derived linear dynamic range with the stability of the sensors. Conducting polymers and their nanocomposites-based electrochemical sensors have demonstrated exceptional capabilities towards detecting various biomolecules, heavy metals, pesticides, and viruses like SARS-COV-2. Incorporation of redox mediators, use of conducting hydrogels, and molecular imprinting are promising strategies for better performance of the derived sensor. The article has demonstrated the existing challenges and limitations and provided solutions in the field. In the future, conducting polymers-based electrochemical sensors can be utilized in wearable sensors and integrated with IoT devices for better reach in real-time applications. They can also be made more accessible with precise control and data output by following specific methodologies. Utilizing green and sustainable conducting polymers can be crucial in advancing eco-friendly practices in the future. Conducting polymer-based electrochemical sensors has affectivity in neurochemical and pathogen sensing, which is essential for brain function and mental health.

42 ENGINEERING↗

DOE OSTI2025

Stability and Performance of 3d Transition Metal Carbo‐Sulfides: A Density Functional Theory Exploration for Li‐Ion Battery Anodes

As the demand for high-performance and reliable energy storage devices continues to rise, identifying new anode materials is crucial for advancing Li-ion battery (LIB) technology. Inspired by recent experimental breakthroughs in synthesizing two-dimensional transition metal carbo-chalcogenides (2D-TMCCs), density functional theory calculations are performed to systematically explore their sulfide variants (TM 2 S 2 C) spanning all 3d transition metals in three possible phases. Through comprehensive evaluations of thermodynamic, dynamic, mechanical, and thermal stabilities, seven stable 2D-TMCC candidates are identified, four of which exhibit superior battery performance. Notably, V-based 2D-TMCCs across all three phases deliver moderate open-circuit voltages (OCV), efficient Li diffusion, and substantial capacities, making them promising candidates for industrial applications without requiring specific phase controls. A Cr-based 2D-TMCC (with sulfur atoms above carbon atoms) offers the highest capacity of 515.40 mAh g −1 , the lowest Li diffusion barrier, and an optimal OCV, highlighting its appealing potential as an anode material for LIBs. Furthermore, significant Li–Li spacing and pronounced electron delocalization in these four 2D-TMCCs suggest a reduced risk of dendrite formation. This work expands the 2D-TMCC family and identifies up-and-coming candidates for next-generation LIB anodes.

anode materials↗

DOE OSTI2026

Ternary and Quaternary Nickel-Iron-Oxide-Based Thin Films as Oxygen Evolution Reaction Catalysts in Alkaline Media

Alkaline water electrolyzers are a promising technology for energy storage and conversion through the electrochemical production of hydrogen, however the slow kinetics of the oxygen evolution reaction (OER) pose a major challenge. The alkaline environment enables the use of non-Pt-group metals as OER catalysts, in particular NiFe-based materials. In this study, Mn and/or Cr were elementally mixed with NiFe to further improve the OER catalyst properties through a controlled, systematic synthesis process involving thin films prepared by electron beam-induced physical vapor deposition (PVD). By exploring both simultaneous co-deposition and serial deposition of the different metals, the OER performance was investigated as a function of both the location of Mn or Cr in the multi-metal NiFe-based catalysts and the difference between surface versus bulk mixing. The distinct differences in the redox dynamics, surface oxidation, and stability of the seven studied catalysts reveal metal Cr- and/or Mn-overlayers as a promising synthesis approach for fine-tuning of catalyst properties and improving the OER performance.

Alkaline Water Electrolysis↗

DOE OSTI2025

Polyethylene Upcycling to Liquid Alkanes in Molten Salts under Neat and External Hydrogen Source-Free Conditions

Development of facile approaches to convert plastic waste into liquid fuels under neat conditions is highly desired but challenging, particularly without noble metal catalysts and an external hydrogen source. Herein, highly efficient and selective polyethylene-to-gasoline oil (branched C 6 –C 12 alkanes) conversion was achieved under mild conditions (<170 °C) using commercially available AlCl 3 -containing molten salts as reaction media and to provide catalytic sites (no extra solvents, additives, or hydrogen feeding). The high catalytic efficiency and selectivity was ensured by the abundant active Al sites with strong Lewis acidity (comparable to the Al type in acidic zeolite) and highly ionic nature of the molten salts to stabilize the carbenium intermediates. Dynamic genesis of the Al sites was elucidated via time-resolved Al K-edge soft X-ray and 27 Al NMR, confirming the tricoordinated Al 3+ as active sites and its coordination with the as-generated alkene/aromatic intermediates. Further, the carbenium formation and polyethylene chain variation was illustrated by inelastic neutron scattering (INS) and an isotope-labeling experiment. Theoretical simulations further demonstrated the successive hydride abstraction, β-scission, isomerization, and internal hydrogen transfer reaction pathway with AlCl 3 as active sites. This facile catalytic system can further achieve the conversion of robust, densely assembled, and high molecular weight plastic model compounds to liquid alkane products in the diesel range.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Basal Melting and Oceanic Observations Beneath Central Fimbulisen, East Antarctica

Abstract Basal melting of ice shelves is fundamental to Antarctic ice sheet mass loss, yet direct observations remain sparse. We present the first year‐round melt record (2017–2021) from a phase‐sensitive radar on Fimbulisen, one of the fastest flowing ice shelves in Dronning Maud Land, East Antarctica. The observed long‐term mean ablation rate at 350 m depth below the central ice shelf was 1.0 ± 0.5 m yr −1 , marked by substantial sub‐weekly variability ranging from 0.4 to 3.5 m yr −1 . 36‐h filtered basal melt rate fluctuations closely align with ocean velocity. On seasonal time scales, melt rates peak during austral spring to autumn (September–March), driven by both elevated ocean velocities and thermal driving near the base. The combined effect of thermal driving and current speed explains the majority of the melt rate variability ( r = 0.84), highlighting the dominant role of shear‐driven turbulence. This relationship enables parameterization of melt rates for the decade‐long ocean record (2010–2021), although deviations appear under low and high forcing conditions. Both observed and parameterized melt rates show similar yearly mean magnitudes compared to satellite‐derived melt rates but with a tenfold lower seasonal amplitude and a 3‐month delay in seasonality. These detailed concurrent ice–ocean observations provide essential validation data for remote sensing and numerical models that aim to quantify and project ice‐shelf response to a change in ocean forcing. In situ measurements and continued monitoring are crucial for accurately assessing and modeling future basal melt rates, and for understanding the complex dynamics driving ice‐shelf stability and sea‐level change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

A scalable superconducting nanowire memory array with row–column addressing

Scalable superconducting memory is required for the development of low-energy superconducting computers and fault-tolerant quantum computers. Conventional superconducting logic-based memory cells possess a large footprint that limits scaling; nanowire-based superconducting memory cells, although more compact, have high error rates, which hinders integration into large arrays. Here we report a 4 × 4 superconducting nanowire memory array that is designed for scalable row–column operations and has a functional density of 2.6 Mbit cm −2 . Each memory cell is based on a nanowire loop consisting of two temperature-dependent superconducting switches and a variable kinetic inductor. The arrays operate at 1.3 K, where we implement and characterize multiflux quanta state storage and destructive read-out. By optimizing the write- and read-pulse sequences, we minimize bit errors and maximize operating margins. We achieve a minimum bit error rate of 10 −5 . Here, we also use circuit-level simulations to understand the memory cell’s dynamics, performance limits and stability under varying pulse amplitudes.

Electrical and electronic engineering↗

DOE OSTI2025

Blocking C-terminal processing of KRAS4b via a direct covalent attack on the CaaX-box cysteine

RAS is the most frequently mutated oncogene in cancer. RAS proteins show high sequence similarities in their G-domains but are significantly different in their C-terminal hypervariable regions (HVR). These regions interact with the cell membrane via lipid anchors that result from posttranslational modifications (PTM) of cysteine residues. KRAS4b is unique as it has only one cysteine that undergoes PTM, C185. Small molecule covalent modification of C185 would block any form of prenylation and subsequently inhibit attachment of KRAS4b to the cell membrane, blocking its biological activity. We translated this concept to the discovery and development of disulfide tethering screen hits into irreversible covalent modifiers of C185. These compounds inhibited proliferation of KRAS4b-driven mouse embryonic fibroblasts, but not cells driven by N-myristoylated KRAS4b that harbor a C185S mutation and are not dependent on C185 prenylation. Top–down proteomics was used to confirm target engagement in cells. These compounds bind in a pocket formed when the HVR folds back between helix 3 and 4 in the G-domain (HVR-α3-α4). This interaction can happen in the absence of small molecules as predicted by molecular dynamics simulations and is stabilized in the presence of C185 binders as confirmed by small-angle X-ray scattering and solution NMR. NOESY-HSQC, an NMR approach that measures internuclear distances of 6 Å or less, and structure analysis identified the critical residues and interactions that define the HVR-α3-α4 pocket. Further development of compounds that bind to this pocket could be the basis of a new approach to targeting KRAS cancers.

C185↗

DOE OSTI2026

Free Energy and Flexibility Analysis of Autoinhibited Human BRAF

The RAF serine/threonine protein kinases function as direct effectors of RAS in the intracellular transmission of extracellular growth signals, and they are key targets for drug discovery, given the high incidence of oncogenic mutations in RAF and other components of this signaling pathway. In its inactive state, RAF is held in an autoinhibited conformation in the cytosol through a combination of intramolecular interactions and binding to a regulatory 14−3−3 protein dimer. Activation of RAF is initiated by its interaction with membrane-localized GTP-bound RAS, which induces conformational changes that release RAF from its autoinhibited state. However, the molecular mechanisms governing RAF activation remain incomplete, largely due to the challenges in experimentally capturing the intermediate conformational states in this process. To address this gap, we developed a comprehensive all-atom model of BRAF based on existing cryo-EM structures. Using this model, we performed extensive molecular dynamics simulations to evaluate the stability and free energy landscape of autoinhibited BRAF in solution. Our analysis reveals conformational flexibility within the autoinhibited complex, suggesting that this dynamic behavior may play a role in facilitating BRAF activation upon engagement with the membrane-bound RAS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

New horizons in the holographic conformal phase transition

Abstract We describe 5D dynamical cosmological solutions of the stabilized holographic dilaton and their role in completion of the conformal phase transition. This analysis corresponds, via the AdS/CFT dictionary, to a study of out-of-equilibrium dynamics where trajectories of the dilaton do not depend solely on thermodynamic quantities in the early universe, but have sensitivity also to initial conditions. Unlike the well-studied thermal transition, which requires quantum tunneling of an infrared brane through the surface of an AdS-Schwarzschild horizon, our approach instead invokes an early epoch in which the cosmology is fully 5-dimensional, with highly relativistic brane motion and with Rindler horizons obscuring the infrared brane at early times. In this context, we demonstrate the existence of a large class of natural initial conditions that seed trajectories where the brane simply passes through the Rindler horizon and into the basin of attraction of the stabilized dilaton potential. This corresponds to successful completion of the phase transition without sacrificing perturbativity of the 5D theory.

Physics↗

DOE OSTI2025

A Dynamic Pricing Method to Manage the Impact of EV Charging on the Grid Using RL

This work addresses the challenge of managing electrical vehicle (EV) charging loads on distribution feeders with the increase in deployment of fast charging stations. To mitigate the adverse impacts on feeder health, a novel dynamic grid-informed pricing approach is proposed. This approach leverages reinforcement learning (RL) to determine hourly charging prices based on real-time grid conditions. A synthetic environment was developed to train the reinforcement learning agent. A model of an IEEE 34-bus distribution feeder with EV charging stations has been developed in OpenDSS utilizing Caldera for realistic EV charging profiles. Test cases demonstrate that the dynamic pricing strategy achieves higher energy delivery to the EV end user at a lower cost compared to constant pricing methods, while lowering voltage deviations and congestion. This approach offers more granular price adjustments, responding dynamically to feeder conditions and potentially improving grid stability and efficiency. The communication architecture to implement this dynamic pricing method is described. This research contributes to the development of smart grid-informed charging solutions that can reduce the cost of charging to the end user while also helping the grid.

EV charging, dynamic pricing, grid-informed chargi↗

DOE OSTI2025

A dynamic pricing method to manage the impact of EV charging on the grid using RL

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Polytype selection in the antisolvent-free crystallization of formamidinium lead iodide using alkylammonium chlorides

This work presents a systematic study of how the size of the C 0 –C 4 alkylammonium chloride additive directs the crystallization pathway in antisolvent-free FAPbI 3 films. We find that larger cations promote the intermediate formation of hexagonal polytypes, correlating with enhanced film crystallinity. Understanding the nucleation, crystallization, and phase transition mechanisms in perovskite thin films produced without antisolvent quenching is crucial for improving phase stability and optoelectronic performance at scale. By means of in situ grazing incidence wide-angle X-ray scattering experiments, we show that the nature of alkylammonium chloride (RACl) additives significantly influences the crystallization dynamics and temperature-dependent stability of formamidinium lead iodide (FAPbI 3 ) perovskite films formed using antisolvent-free processes. The in situ experiments reveal that the effective radius of the RA + cation and the vapor pressure of the RA 0 conjugate base are critical factors affecting the crystallization pathway and film morphology. C 2 –C 3 additives with moderate chain lengths may strike a balance between promoting the early crystallization of the cubic 3C phase while suppressing unwanted phases. This balance promotes the formation of highly crystalline cubic perovskite phase with well-oriented structure and better optoelectronic properties. These findings provide guidance regarding the design of additives to crystallize more stable and efficient perovskite films for optoelectronic applications.

Marchezi, Paulo E↗

DOE OSTI2025

Intelligently Partitioned Phasor-EMT Hybrid Simulations of Large-Scale, High-IBR Power Systems

As the penetration level of power electronics-interfaced renewables such as photovoltaics (PV) and wind has surged in modern electric grids, new operational risks caused by the dynamics of those inverter-based resources (IBRs) are emerging in parallel. Lessons learned from various grid events include that the impact of IBRs on system-level grid stability will become prominent along with the increase of renewables and that the short-timescale dynamic impacts of IBRs on grid stability are not fully captured by current commercial dynamic simulation tools [1] [2]. For example, IBRs can be controlled to mitigate those destabilizing interactions, but conventional phasor-domain tools (e.g. PSS/E, PSLF) often cannot capture that; likewise, the existing electromagnetic transient (EMT) simulation tools (e.g. PSCAD, EMTP) can simulate detailed IBR controls, but for large power systems with many IBRs, slow simulation speeds severely impede the ability to study dynamic events [3] [4]. Massively paralleling simulations using high-performance computing (HPC) can help address this, especially now that cloud-based HPC capability is widely available, but today s EMT tools are not HPC-compatible, and parallelization of dynamic simulation solvers is not trivial because each region can dynamically affect the others. Thus, dynamic simulation of grids with very large numbers of IBRs potentially poses a barrier to the ongoing energy transition.

24 POWER TRANSMISSION AND DISTRIBUTION↗