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At least 523 records · Page 29

Freestanding self-assembled sulfonated pentablock terpolymer membranes for high flux pervaporation desalination

Pervaporation desalination has several advantages over competing desalination technologies, most notably an ability to select for or against volatile organic compounds and the ability to process high salinity feeds at a low transmembrane pressure. Pervaporation has not been commercialized for desalination applications because of its energy intensity. However, emerging processes such as hydraulic fracturing produce high total dissolved solids (>30-45 g/L) byproduct streams that exceed the operational limits of traditional reverse osmosis and could be treated by pervaporation. Here, we demonstrate free-standing pervaporation membranes with excellent permeance and high salt removal based on a partially sulfonated pentablock terpolymer with the tradename Nexar™. Pervaporation membranes were easily cast from this material with desalination performances comparable or superior to commercially available membranes. We found that the polymer degree of sulfonation and casting solvent polarity had a significant impact on the membranes’ water uptake but only a modest impact on the pervaporation desalination performance. Membranes with a degree of sulfonation of 52% (2.0 meq g –1 IEC) and a casting solution composed of 50 wt% n-propanol and 50 wt% toluene achieved a water flux of 3.32 kg m -2 h -1 (permeance 135 kg m -2 h -1 bar -1 ) with 99.5% salt removal in pervaporation from a 32 g/L –1 sodium chloride feed solution at room temperature. We demonstrated that dense, non-porous NexarTM pervaporation membrane permeance and salt separation performance were superior to commercial pervaporation membranes and equivalent to commercial membrane distillation membranes, which have much larger pores. Here, this study demonstrates that commercially available sulfonated pentablock terpolymers are excellent membranes for pervaporation desalination because of their ease of casting and excellent performance.

42 ENGINEERING↗

Ergodicity, lack thereof, and the performance of reservoir computing with memristive networks

Abstract Networks composed of nanoscale memristive components, such as nanowire and nanoparticle networks, have recently received considerable attention because of their potential use as neuromorphic devices. In this study, we explore ergodicity in memristive networks, showing that the performance on machine leaning tasks improves when these networks are tuned to operate at the edge between two global stability points. We find this lack of ergodicity is associated with the emergence of memory in the system. We measure the level of ergodicity using the Thirumalai-Mountain metric, and we show that in the absence of ergodicity, two different memristive network systems show improved performance when utilized as reservoir computers (RC). We highlight that it is also important to let the system synchronize to the input signal in order for the performance of the RC to exhibit improvements over the baseline.

97 MATHEMATICS AND COMPUTING↗

Information-Guided Dynamic Nuclear Polarization

A spin ensemble in thermal equilibrium continuously undergoes random fluctuations analogous to those observed in Brownian motion, a process known as spin noise. Here, we investigate the dynamics of a system comprising a spin-1 paramagnetic center and a hyperfine-coupled spin-1/2 nucleus in the vicinity of a level crossing. We theoretically show that nuclear spins polarize efficiently under the combined action of thermal fluctuations and a closed-loop feedback protocol. The latter articulates periodic observations of the electronic magnetization and radio-frequency pulses connecting hybrid states with opposite nuclear spin alignment. Since nuclear polarization emerges from electronic spin fluctuations, not spin order, this microwave-free technique generically benefits from warmer, not colder, operation temperatures. Furthermore, because the spin dynamics at play near a level crossing is rather insensitive to the absolute value of the magnetic field, our work promises opportunities for high-field dynamic nuclear polarization, which is difficult to attain through present methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Relaxed PV Bus Model in Linear Power Flow

The emerging multimodal active energy resource units make it necessary to introduce constant voltage amplitude buses (PV bus) in the operation of modern distribution systems. To enable the analysis of PV bus using linear power flow models, this letter proposes a relaxed PV bus model for solving power flow related problems using an indirect modeling approach. The developed PV bus model can be applied to linear power flow models in both rectangular and polar coordinates. Besides, the approximation error of the relaxed PV bus model can also be controlled and quantified. Lastly, the proposed relaxed PV bus model is validated using different test systems. According to the numerical studies, the maximum error on the PV bus approximation in all case studies is only 0.61%, and the maximum error of the supporting power at the PV buses is 6.5%.

24 POWER TRANSMISSION AND DISTRIBUTION↗

On the properties of qudits

Motivated by the growing interest in the applications of quantum information science in astrophysical settings, especially for the neutrino transport in compact objects where three-flavors of neutrinos need to be mapped on qutrits, we review properties of one- and two-qudit systems. Here, we contrast two-qubit and two-qudit systems by pointing out how some of the properties of two-qubit systems generalize to higher dimensions and explore emerging new properties for dimensions three or higher. One example is provided by the Werner states:when the density operator is written in the fundamental representation,we show that only two-qubit Werner states can be pure states, but not two-qudit Werner states when the qudit dimension is larger than two.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ergodicity, lack thereof, and the performance of reservoir computing with memristive networks and nanowire

Networks composed of nanoscale memristive components, such as nanowire and nanoparticle networks, have recently received considerable attention because of their potential use as neuromorphic devices. In this study, we explore ergodicity in memristive networks, showing that the performance on machine leaning tasks improves when these networks are tuned to operate at the edge between two global stability points. We find this lack of ergodicity is associated with the emergence of memory in the system. We measure the level of ergodicity using the Thirumalai-Mountain metric, and we show that in the absence of ergodicity, two different memristive network systems show improved performance when utilized as reservoir computers (RC). We highlight that it is also important to let the system synchronize to the input signal in order for the performance of the RC to exhibit improvements over the baseline.

97 MATHEMATICS AND COMPUTING↗

Draft Prototype Microreactor Transportation Safety Program

Microreactors are compact reactors capable of producing less than 50 megawatts of electrical energy. Typically, these reactors are factory-fabricated and designed to be easily transportable by truck, rail, vessel, or air. Microreactor designs often assume that the unit can be transported containing either unirradiated or irradiated fuel. The interest in microreactors is driven by several factors, including the need to generate power on at remote locations, at military installations, at facilities such as data centers, and in areas recovering from natural disasters. The U.S. Department of Defense is actively pursuing the microreactor concept to meet the increasing energy demands of military operations that require portable and dense power sources. Commercial vendors are also exploring microreactor concepts. The report Microreactor Transportation Emergency Planning Challenges (Maheras et al. 2024) outlined the emergency planning challenges associated with the transportation of microreactors by road, rail, and by barge/ship. The successful commercial deployment and redeployment of microreactors will also require the development of microreactor transportation safety programs. The elements in these safety programs are not specific to microreactors; however, the transport of microreactors may pose unique challenges in these areas. This report builds on the report Microreactor Transportation Emergency Planning Challenges (Maheras et al. 2024) and develops the elements of a prototype microreactor transportation safety program that describes the elements that should be contained vendor-developed microreactor transportation safety programs, identifying the unique elements associated with microreactor transport. This will provide vendors and their transportation contractors a basis for their transportation planning and will accelerate the commercial deployment and redeployment of microreactors by identifying those issues unique to microreactor transport. The emphasis of this report is on highway transport of microreactors. This is based on a U.S. Nuclear Regulatory Commission transportation package approval strategy of crawl-walk-run, where transport by highway is evaluated first (Coles et al. 2021, 2024, Maheras et al. 2021), then other surface modes (rail and barge/ship), and finally air transport. Evaluation of maritime transport of microreactors was recently initiated (Rigato et al. 2024, Maheras et al. 2025). The report first discusses microreactors in general and microreactor transportation safety program planning assumptions. The report then provides a description of the transportation safety planning process and provides an extensive discussion of the elements of transportation safety programs. Specific elements examined included transportation roles and responsibilities, transportation planning, transportation mode and route selection, carrier selection, transportation packaging, advance notification of shipments, public information and communications, emergency response plans and procedures, inspections, security, safe parking, shipment tracking, weather and road conditions, medical preparedness, training and exercises, and program evaluation. The report then identifies the unique elements of a transportation safety program associated with microreactor transport. These unique elements were in the areas of: the unusual nature of microreactor designs, compensatory measures, increased radiation dose rates in the vicinity of microreactors, transportation package approval versus 10 CFR 50.59, and the use of a risk-informed transportation package approval process.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Simulating Energy and Security Interactions in Semiconductor Manufacturing: Insights from the Intel Minifab Model

Semiconductor manufacturing is a highly complex. Fabrication plants must deal with re-entrant flows to support multiple types of wafers being produced simultaneously, each with their own deadlines and specifications. The manufacturing process itself depends upon the ability to control and programmatically adjust a variety of environmental conditions including temperature, humidity, and air quality. In addition, wafer fabrication consumes large amounts of electricity. Emerging technologies may help reduce the energy footprint of such facilities but can introduce cybersecurity risks. Therefore, this paper presents a modeling and simulation framework to quantify tradeoffs between operational measures of performance, energy consumption, and cybersecurity controls. We augment the Intel Minifab model, with the Purdue Enterprise Reference Architecture (PERA) for cybersecurity as well as tool-level energy consumption data from a real-world semiconductor manufacturing testbed. In this manner, we intend to provide stakeholders with a systematic, data-driven approach to evaluate emerging risks within the manufacturing process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Survey on the Expanding Scope and Interdisciplinary Opportunities for Processing-in-Memory Techniques

Processing-in-Memory (PIM) is emerging as a practical path to overcome the limitations of traditional von Neumann architectures. At its core, PIM systems implement computing primitives such as logic operations and multiply-accumulate acceleration through compute-in-memory, near-memory processing, or hybrid designs. The role of memory cells varies widely across technologies, acting as inputs, outputs, or analog accumulators through bit-lines and sense amplifiers. This diversity creates trade-offs in precision, bandwidth, latency, and programmability, making it difficult to build a unified understanding on the progress of the field. In this survey, we organize recent advances of PIM into three areas. First, we discuss the progress on the architectural optimizations of PIM and its integration with both DRAM and emerging non-volatile memories. Second, we examine how PIM is being used to accelerate key computing domains, including generative AI workloads and high-performance kernels, along with new approaches. Third, we highlight the growing adoption of PIM in computational sciences, where it is being applied to solve interdisciplinary problems such as genome analysis, mRNA quantification, mass spectrometry, quantum circuit simulation, wave modeling, and secure computation. Finally, we synthesize the major challenges that continue to slow PIM adoption, including manufacturing constraints, power delivery, thermal reliability, data consistency, runtime and memory-management coordination, and the difficulty of building portable software abstractions without sacrificing commercial viability. This work provides an updated, structured perspective on PIM’s potential across computing and computational sciences and the barriers that must be solved for it to reach its full impact.

Asifuzzaman, Kazi [Oak Ridge National Laboratory (↗

Stochastic AC optimal power flow: A data-driven approach

There is an emerging need for efficient solutions to stochastic AC Optimal Power Flow (AC-OPF) to ensure optimal and reliable grid operations in the presence of increasing demand and generation uncertainty. Herein this paper presents a highly scalable data-driven algorithm for stochastic AC-OPF that has extremely low sample requirement. The novelty behind the algorithm’s performance involves an iterative scenario design approach that merges information regarding constraint violations in the system with data-driven sparse regression. Compared to conventional methods with random scenario sampling, our approach is able to provide feasible operating points for realistic systems with much lower sample requirements. Furthermore, multiple sub-tasks in our approach can be easily paralleled and based on historical data to enhance its performance and application. We demonstrate the computational improvements of our approach through simulations on different test cases in the IEEE PES PGLib-OPF benchmark library.

42 ENGINEERING↗

Coupled Experimental–Theoretical Characterization of a Carbon Electrode in Vanadium Redox Flow Batteries using X-ray Absorption Spectroscopy

Vanadium redox flow batteries (VRFBs) have emerged as promising solutions for stationary grid energy storage due to their high efficiency, scalability, safety, near room-temperature operation conditions, and the ability to independently size power and energy capacities. The performance of VRFBs heavily relies on the redox couple reactions of V 2+ /V 3+ and VO 2+ /VO 2 + on carbon electrodes. Therefore, a thorough understanding of the surface functionality of carbon electrodes and their propensity for degradation during electrochemical cycles is crucial for designing VRFBs with extended lifespans. In this study, we present a coupled experimental–theoretical approach based on carbon K edge X-ray absorption spectroscopy (XAS) to characterize carbon electrodes prepared under different conditions and identify relevant functional groups that contribute to unique spectroscopic features. Atomic models were created to represent functional groups, such as hydroxyl, carboxyl, methyl, and aldehyde, bonded to carbon atoms in either sp 2 or sp 3 environments. The interactions between functionalized carbon and various solvated vanadium complexes were modeled using density functional theory. A library of carbon K-edge XAS spectra was generated for distinct carbon atoms in different functional groups, both before and after interacting with solvated vanadium complexes. Here we demonstrate how these simulated spectra can be used to deconvolve ex situ experimental spectra measured from carbon electrodes and to track changes in the electrode composition following immersion in different electrolytes or extended cycling within a functional VRFB. By doing so, we identify the active species present on the carbon electrodes, which play a crucial role in determining their electrochemical performance.

25 ENERGY STORAGE↗

Bridging Nano- and Microscale X-Ray Tomography for Battery Research by Leveraging Artificial Intelligence

X-ray computed tomography (CT) is a non-destructive imaging technique in which contrast originates from the materials' absorption coefficient. The recent development of laboratory nanoscale CT (nano-CT) systems has pushed the spatial resolution for battery material imaging to voxel sizes of 50 nm, a limit previously achievable only with synchrotron facilities. Given the non-destructive nature of CT, in situ and operando studies have emerged as powerful methods to quantify morphological parameters, such as tortuosity factor, porosity, surface area and volume expansion, during battery operation or cycling. Combined with artificial intelligence and machine learning analysis techniques, nano-CT has enabled the development of predictive models to analyse the impact of the electrode microstructure on cell performances or the influence of material heterogeneities on electrochemical responses. In this Review, we discuss the role of X-ray CT and nano-CT experimentation in the battery field, discuss the incorporation of artificial intelligence and machine learning analyses and provide a perspective on how the combination of multiscale CT imaging techniques can expand the development of predictive multiscale battery behavioural models.

diagnostics↗

Internal rotation of ELM filaments on NSTX

Edge localized modes (ELMs) are a threat to tokamaks due to their high heat and particle loads on plasma facing components. A significant portion of this energy is carried and deposited by the emerging ELM filaments, whose dynamics are directly connected to their impact. Therefore, understanding their underlying physics is important for the operation of future fusion reactors. Our paper extends our knowledge of ELM filaments by reporting on their internal rotation (spinning) around the magnetic field lines along which they are extended. Our analysis of gas-puff imaging data on National Spherical Torus Experiment shows that ELM filaments are characterized by internal rotation in the direction of the ion-gyromotion with ω = 15:2 krad/s median angular velocity, which is approximately three times faster than the blob rotation in the background turbulence. The characteristic size of the ELM filament was also assessed and found to be similar to the blobs. A nearly linear trend was found between the angular velocity and the radial velocity of the ELM filament. The angular velocity was found to be linearly dependent on the distance of the filament from the separatrix, as well. An analytical model called the shear-induced rotation model was identified as a candidate for explaining the physics of the observations. Our results show that the modeled mechanism could significantly influence the rotation of the ELM filament; however, it cannot be a sole contributor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High-quality composite Pati-Salam axion

We present a composite QCD axion model where the Peccei-Quinn symmetry emerges as a high-quality, accidental symmetry. The axion potential is only modified by eight-fermion, dimension-12 operators, which if present at the Planck scale, allow for axion dark matter from misalignment while solving the strong 𝐶⁢𝑃 problem. The model is an SU⁡(𝑁 𝑐 ) gauge theory with ten flavors where the Pati-Salam unified subgroup SO⁡(6) × SO⁡(4) ⊂ SU⁢(10)𝐿 and Sp⁡(10) ⊂ SU⁢(10) 𝑅 are weakly gauged. The dynamics breaks SU⁢(10) 𝐿 × SU⁢(10) 𝑅 → SU⁢(10) 𝑉 and the weakly gauged groups to U⁡(3) × U⁡(2) ⊃ SU⁢(3) 𝑐 × SU⁢(2) 𝐿 × U⁡(1) 𝑌 , with the QCD axion identified as one of the Nambu-Goldstone bosons. This axion has a relatively large coupling to photons while a residual $\bar{𝜃}$ eff may be just below the current limit on the neutron electric dipole moment. If the dimension-12 operators are present near the grand unified theory scale, they can cause domain wall networks to decay, allowing for axion dark matter even for the postinflationary scenario.

Gherghetta, Tony [University of Minnesota, Minneap↗

Strange Metals as Ersatz Fermi Liquids

Here, a long-standing mystery of fundamental importance in correlated electron physics is to understand strange non-Fermi liquid metals that are seen in diverse quantum materials. A striking experimental feature of these metals is a resistivity that is linear in temperature (T). In this Letter we ask what it takes to obtain such non-Fermi liquid physics down to zero temperature in a translation invariant metal. If in addition the full frequency (ω) dependent conductivity satisfies ω/T scaling, we argue that the T-linear resistivity must come from the intrinsic physics of the low energy fixed point. Combining with earlier arguments that compressible translation invariant metals are “ersatz Fermi liquids” with an infinite number of emergent conserved quantities, we obtain powerful and practical conclusions. We show that there is necessarily a diverging susceptibility for an operator that is odd under inversion and time reversal symmetries, and has zero crystal momentum. We discuss a few other experimental consequences of our arguments, as well as potential loopholes, which necessarily imply other exotic phenomena.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optimal Power Sharing Speed Compensation in On-road Wireless EV Charging Systems

Dynamic wireless charging of electric vehicles (EV) is an emerging technology with the potential to address range anxiety and reduce the size of batteries or provide charge-sustaining operation. Charging demand for dynamic wireless charging systems (DWCS) varies greatly in response to location-specific traffic behaviors including the number and speed of vehicles. This paper highlights the potential reduction of load variation with speed compensation and simulates opportunities to maximize the number of cars charged concurrently through “power sharing” or altering power output to slower cars while maintaining a maximum delivered energy. An improved sub-minute model for synthetic traffic is proposed to effectively model DWCS load on high speed roadways and a power electronics model is created based on an existing prototype developed by ORNL to investigate the potential for power sharing. Reductions in the average speed of traffic can greatly increase instantaneous DWCS load by as much as 26%, complicating capacity sizing. Parametric studies with a LCC-S power electronics model shows feasible power reduction of more than 20%, while maintaining a maximum achievable efficiency greater than 90%. Speed compensation on a roadway with large speed variation can reduce average power expected by 21% and increase the maximum number of cars charged simultaneously by 30%. The application of power sharing may significantly reduce load variability due to speed, allow for increased car hosting capability, and guarantee a maximum energy delivered.

Lewis, Donovin D.↗

Characterization of Temperature Heterogeneity in Utility-Scale Power Plant Boilers by Spatially Distributed Ultrasonic Measurements

In extreme environments, even hardened insertion sensors fail quickly. For such environments, we have developed an ultrasonic (US) method for measuring the spatial distribution of temperatures in solid materials and, specifically, across containments of extreme processes. By deploying US sensors in multiple locations, spatial heterogeneity in temperatures inside harsh environments may be characterized. In this note, we update our progress on testing the developed approach in an industrial setting and its performance in describing the temperature distribution inside a 500 MW (electrical) coalfired utility boiler of an electrical power generation plant. We use waveguides (WG) structured to contain echogenic features that produce a train of echoes in response to an excitation pulse. The time of flight between echoes encodes the information on the temperature distribution in the corresponding segment of the WG, which we reconstruct using its parametrization. Five waveguides were welded to the boiler’s heat exchange surface (waterwall) and different locations at the same boiler elevation and produced reliable US waveforms 18 months after the installation. For several weeks during the latest trial, we performed US measurements in five locations spanning half of the boiler’s 14-meter width. The measurements were acquired during regular operation, including load cycling to adjust for demand and intermittent contributions of renewable power sources, and during boiler shutdown for emergency maintenance and the subsequent restart. The interpretation of US waveforms by signal processing resulted in an accurate estimation of temperature distribution along the waveguides. We captured daily cyclical variations in demand-following load. Measurements performed in multiple locations revealed unexpected temperature variations across the boiler. We conclude that an array of developed sensors can provide responsive and spatial temperature measurements while maintaining functionality despite prolonged exposure to an extreme environment.

Walton, Kenneth↗

Phase stability and tensorial thermal expansion properties of single to high-entropy rare-earth disilicates

Temperature limitations in nickel-base superalloys have resulted in the emergence of SiC-based ceramic matrix composites as a viable replacement for gas turbine components in aviation applications. Higher operating temperatures allow for reduced fuel consumption but present a materials design challenge related to environmental degradation. Rare-earth disilicates (RE 2 Si 2 O 7 ) have been identified as coatings that can function as environmental barriers and minimize hot component degradation. In this work, single- and multiple-component rare-earth disilicate powders were synthesized via a sol-gel method with compositions selected to exist in the monoclinic C 2/m phase (β phase). Phase stability in multiple cation compositions was shown to follow a rule of mixtures and the C 2/m phase could be realized for compositions that contained up to 25% dysprosium, which typically only exists in a triclinic, P $\bar1$, phase. All compositions exhibited phase stability from room temperature to 1200°C as assessed by X-ray diffraction. The thermal expansion tensors for each composition were determined from high-temperature synchrotron X-ray diffraction and accompanying Rietveld refinements. It was observed that ytterbium-containing compositions had larger changes in the α 31 shear component with increasing temperature that led to a rotation of the principal axes. Principal axes rotation of up to 47° were observed for ytterbium disilicate. The results suggest that microstructure design and crystallographic texture may be essential future avenues of investigation to ensure thermo-mechanical robustness of rare-earth disilicate environmental barrier coatings.

36 MATERIALS SCIENCE↗