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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

Three-Dimensional Bubble Fluidics in Architected Porous Media

Gas bubble flows in porous media often exhibit complex and seemingly unpredictable behaviors that are difficult to control. This lack of control limits the ability to design effective devices which manage multiphase flows. Here, we show how the design of 3D printed pores can deterministically control the flow path of an injected gas stream. Open cell structures can be designed to shape the gas/liquid interface with fidelity to control how the two phases are distributed throughout a porous material. The distributed gas volume is free to interact physically and chemically with the surrounding liquid phase, an effect we exploit to create a logical control gate to redirect flows within a lattice. This also allows us to design architectures for reactive capture and aerating bioreactors, resulting in patterned boundaries which can make more effective use of the liquid and gas reagents.

3D microfluidics↗

Divide and conquer: separating the two probabilities in seismic phase picking

There are two fundamental probabilities in the seismic phase picking process—the probability of the existence of a seismic phase (detection probability) and the probability associated with the phase arrival time estimation (timing probability). The nearly ubiquitous approach in developing deep learning phase picking models is to use a kernel, such as a truncated Gaussian, to mask the labelled phase arrival time and train a segmentation model. Once a model is trained, the times of the peaks in the output are taken as phase arrival times (picks), and the height of the peaks are taken as ‘probability’ of the picks. Here, we show that this ‘probability’ represents neither the detection nor the timing probability because this approach forces the output to follow the shape of the kernel. We introduce an approach using two models to estimate these two distinct probabilities. We use a binary classifier with a calibrated confidence to address the detection probability and a multiclass classifier to obtain a probability mass function to address the timing probability. This new approach can make the deep learning-based phase picking process more interpretable and provide options to logically control seismic monitoring workflows.

58 GEOSCIENCES↗

Characterizing and Modeling the Influence of Geometry on the Performance of Superconducting Nanowire Cryotrons

The scaling of superconducting nanowire detectors to larger arrays is often limited by room-temperature-readout cabling. Cryogenic integrated circuits constructed from nanowire cryotrons, or nanocryotrons, can address this limitation by performing signal processing on chip. In this study, we characterize key performance metrics of the nanocryotron to elucidate its potential as a logical element in cryogenic integrated circuits and develop an electro-thermal model to connect material parameters with device performance. We find that the performance of the nanocryotron depends on the device geometry, and trade-offs are associated with optimizing the gain, jitter, and energy dissipation. Here, we demonstrate that nanocryotrons fabricated on niobium nitride can achieve a grey zone less than 210 nA wide for a 5 ns long input pulse corresponding to a maximum achievable gain of 48 dB, an energy dissipation of less than 20 aJ per operation, and a jitter of less than 60 ps.

Superconductor↗

Synchronous Machine Governor Upgrade

Conventional generation sources play a critical role in the stability and reliability of the electrical grid, particularly as we transition towards more renewable energy sources. To understand and accurately emulate their behavior for optimizing grid operations and ensuring seamless integration with renewable technologies, it is essential to better emulate the grid- and plant-level impacts of conventional generation sources, such as natural gas (NG) driven heat recovery steam generators (HRSGs) and combustion turbines (CTs). Therefore, a governor model is developed in a programmable logic controller (PLC) to investigate the performance of the conventional generator under various dynamic operating conditions and to identify the impact on grid stability in a controlled environment. The governor model aims to enable the hardware-in-the-loop (HIL) based emulation of these conventional generation sources using the existing 2 MVA synchronous machine/generator that is driven by a flexible 2.5 MW variable speed drive. This setup will allow us to replicate the dynamic characteristics and response behaviors of NG-driven HRSGs and CTs. The controls for the emulated conventional plants follow the industry standard and are adjustable, ensuring they accurately reflect the operational capabilities and limitations of real-world systems. These controls include load-following capabilities, ramp rates, startup and shutdown sequences, and emissions characteristics. By incorporating these adjustable controls, we aim to capture the nuanced impacts of conventional generation, such as their ability to provide ancillary services like frequency regulation, voltage support, and spinning reserve. In this report, we simulate two types of dynamic operations: grid-connected and islanding. For each dynamic operation, representative starting sequences are tested, including turbine purge, ignition, speed ramping up, generator excitation and synchronizing, and breaker close. The HIL based tests provides insights for field deployment, specifically the high-fidelity governor model provides results to predict the potential stability and reliability risk and suggest possible integration measures (e.g., generation and load balancing, tuning of governor control parameters). Ultimately, this enhanced emulation capability will be integrated into our Advanced Research on Integrated Energy Systems (ARIES), enabling us to conduct comprehensive studies on the interactions between conventional and renewable energy sources. By better understanding these interactions, we can develop strategies to optimize the overall performance and reliability of the grid. This will support the deployment of advanced grid management techniques, such as demand response, grid-forming inverters, and energy storage systems. The main contributions are summarized as follows: (1) This report introduces a PLC-based governor model for gas turbines. This model accurately simulates the dynamic behavior of conventional generation sources under various operational scenarios; (2) The model is integrated with an HIL testbed that includes a 2.5 MW variable speed drive and a 2 MVA synchronous machine. This setup enables realistic, real-time emulation of conventional power plants, particularly NG driven HRSGs and CTs; (3) The developed model is adaptable to various gas turbine configurations and allows for precise control over parameters such as MW ramp rates. This flexibility makes it a valuable tool for future research and industry collaboration; and (4) By incorporating the model into the National Renewable Energy Laboratory's Advanced Research on Integrated Energy Systems, the report lays the groundwork for future studies on interactions between conventional and renewable energy sources, enhancing the ability to develop advanced grid management strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modeling and Power-Hardware-in-the-Loop Validation of Synchronous Machine Governor

This paper introduces the development of a high-fidelity gas turbine governor model using a programmable logic controller for power-hardware-in-the-loop (PHIL) validation. The governor model is integrated with the National Renewable Energy Laboratory's (NREL) PHIL test bed, featuring a 2-MVA synchronous machine and a 2.5-MW variable-speed drive, to emulate NG-driven HRSGs and CTs under various operational scenarios. The primary objective of this research is to study the grid-connected and islanding operations of conventional generation sources, with representative startup sequences including turbine purge, ignition, speed ramp-up, synchronization, and breaker closure. Preliminary results of the generator governor model on NREL PHIL platform, particularly using the 2.5-MW dynamometer system, offered significant insights into the modeling techniques, hardware integration, scaling, and real-world simulation dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Primary Pump Motor Area - Transfer Fan Replacement PLC Design

My poster is about a project that I have worked on in my time at ATR as an intern. The Heating and Ventilation Control Panel (HVB-1) controls thirty-five heating and ventilation fans within the Advanced Test Reactor. This control panel needs replacement, as many of the components inside the existing panel are becoming old and degrading. In preparation for this replacement effort, concepts and component identification for the new control panel needed to be developed. Instead of replacing the new panel with replacement mechanical components, a Programmable Logic Controller (PLC) is proposed as a solution. Although multiple fans are associated with this panel, my poster focuses on the replacement design for the Primary Pump Motor Area Transfer Fan. This will provide an example of how the entire cabinet may be upgraded.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Manipulating Spin–Lattice Coupling in Layered Magnetic Topological Insulator Heterostructure via Interface Engineering

Induced magnetic order in a topological insulator (TI) can be realized either by depositing magnetic adatoms on the surface of a TI or engineering the interface with epitaxial thin film or stacked assembly of 2D van der Waals (vdW) materials. Herein, the observation of spin-phonon coupling in the otherwise non-magnetic TI Bi 2 Te 3 is reported, due to the proximity of FePS 3 (an antiferromagnet (AFM), T N ≈ 120 K), in a vdW heterostructure framework. Temperature-dependent Raman spectroscopic studies reveal deviation from the usual phonon anharmonicity originated from spin-lattice coupling at the Bi 2 Te 3 /FePS 3 interface at/below 60 K in the peak position (self-energy) and linewidth (lifetime) of the characteristic phonon modes of Bi 2 Te 3 (106 and 138 cm –1 ) in the stacked heterostructure. The Ginzburg-Landau (GL) formalism, where the respective phonon frequencies of Bi 2 Te 3 couple to phonons of similar frequencies of FePS 3 in the AFM phase, is adopted to understand the origin of the hybrid magneto-elastic modes. At the same time, the reduction of characteristic TN of FePS 3 from 120 K in isolated flakes to 65 K in the heterostructure, possibly due to the interfacial strain, which leads to smaller Fe-S-Fe bond angles as corroborated by computational studies using density functional theory (DFT). Besides, inserting hexagonal boron nitride within Bi 2 Te 3 /FePS 3 stacking regains the anharmonicity in Bi 2 Te 3 . As a result, controlling interfacial spin-phonon coupling in stacked heterostructure can have potential application in surface code spin logic devices.

36 MATERIALS SCIENCE↗

Spatially Precise Light‐Activated Dedoping in Wafer‐Scale MoS 2 Films

2D materials, particularly transition metal dichalcogenides (TMDCs), have shown great potential for microelectronics and optoelectronics. However, a major challenge in commercializing these materials is the inability to control their doping at a wafer scale with high spatial fidelity. Interface chemistry is used with the underlying substrate oxide and concomitant exposure to visible light in ambient conditions for photo-dedoping wafer scale MoS 2 . It is hypothesized that the oxide layer traps photoexcited holes, leaving behind long-lived electrons that become available for surface reactions with ambient air at sulfur vacancies (defect sites) resulting in dedoping. Additionally, high fidelity spatial control is showcased over the dedoping process, by laser writing, and fine control achieved over the degree of doping by modulating the illumination time and power density. This localized change in MoS 2 doping density is very stable (at least 7 days) and robust to processing conditions like high temperature and vacuum. The scalability and ease of implementation of this approach can address one of the major issues preventing the “Lab to Fab” transition of 2D materials and facilitate its seamless integration for commercial applications in multi-logic devices, inverters, and other optoelectronic devices.

14 SOLAR ENERGY↗

On the Ordering Mechanism of Cu + in 2D van der Waals Multiferroic CuCrP 2 S 6

CuCrP 2 S 6 is a van der Waals multiferroic where the tunable Cu + sublattice underpins its exceptional ferroelectric and electronic switching properties. Yet, the microscopic mechanism governing Cu + ordering has remained elusive. Here, we combine single-crystal X-ray and neutron diffraction with pair distribution function analysis to uncover a temperature-driven evolution of Cu + ordering, giving rise to an incommensurate quasi-antipolar phase between the paraelectric and antiferroelectric states. The modulation originates from correlated Cu + occupancy redistribution coupled to breathing distortion of surrounding S 3 triangles, establishing a symmetry-adapted lattice distortion mode. Diffuse scattering persisting over 35 K above the transition confirms that the structural instability follows an order-disorder mechanism. The spontaneous off-centering of Cu + positions CuCrP 2 S 6 as a model platform for correlated order-disorder phenomena in 2D layered ferroics, and provides design principles for next-generation memory and logic devices.

ferroelectrics↗

Redefining Design for Remanufacturing: A Practical Methodology for Prioritizing Remanufacturing Design Rules

Products are often discarded when they fail or no longer meet user needs. These outcomes are frequently shaped by early design decisions. While remanufacturing offers a sustainable alternative by restoring products to like‐new condition, its potential is often limited by designs that do not consider remanufacturing from the outset. This research addresses that challenge by introducing a structured Design for Remanufacturing (DfRem) methodology and a CAD‐integrated tool to support real‐time design decisions. The DfRem framework introduces a new primary design function focused on preserving product functionality across its life cycle. It is supported by a fault tree that identifies failure modes that limit remanufacturing potential and a hierarchy of design principles including Prevent, Minimize, Relocate, Restore, and others. Each principle is linked to actionable design rules that help engineers reduce the need for remanufacturing or improve its efficiency when necessary. To operationalize this framework, we developed CAD plugins for Autodesk Inventor and PTC Creo. These tools use a state machine model to present prioritized design rules based on selected failure modes and user input. By embedding DfRem logic directly into widely used CAD environments, the tool enables engineers to make sustainability‐informed decisions without disrupting existing workflows. Furthermore, this approach highlights the critical role of design in enabling circular and resource‐efficient product development, making remanufacturing a more practical and accessible strategy during the early stages of product design.

CAD↗

A Review of Software for Designing and Operating Quantum Networks

Quantum networks development is crucial to realizing a production-grade network that can support distributed sensing, secure communication, and utility-scale quantum computation. However, the transition from laboratory demonstration to deployable networks requires software implementations of architectures and protocols tailored to the unique constraints of quantum systems. This paper reviews the current state of software implementations for quantum networks, organized around a three-plane abstraction of infrastructure, logical, and control/service planes. We cover software for both designing quantum network protocols (e.g., SeQUeNCe, QuISP, and NetSquid) and operating testbeds, with a focus on essential control/service plane functions such as entanglement, topology, and resource management, in a proposed taxonomy. Our review highlights a persistent gap between theoretical architecture and protocol proposals and their realization in simulators or testbeds, particularly in dynamic topology and network management. We conclude by outlining open challenges and proposing a roadmap for developing scalable software architectures to enable hybrid, large-scale quantum networks.

Network Design↗

Multi‐Objective Optimization for Rapid Identification of Novel Compound Metals for Interconnect Applications

Abstract Interconnect materials play the critical role of routing energy and information in integrated circuits. However, established bulk conductors, such as copper, perform poorly when scaled down beyond 10 nm, limiting the scalability of logic devices. Here, a multi‐objective search is developed, combined with first‐principles calculations, to rapidly screen over 15,000 materials and discover new interconnect candidates. This approach simultaneously optimizes the bulk electronic conductivity, surface scattering time, and chemical stability using physically motivated surrogate properties accessible from materials databases. Promising local interconnects are identified that have the potential to outperform ruthenium, the current state‐of‐the‐art post‐Cu material, and also semi‐global interconnects with potentially large skin depths at the GHz operation frequency. The approach is validated on one of the identified candidates, CoPt, using both ab initio and experimental transport studies, showcasing its potential to supplant Ru and Cu for future local interconnects.

Chemistry↗

Epitaxial Thin Film Growth on Recycled SrTiO 3 Substrates Toward Sustainable Processing of Complex Oxides

Complex oxide thin films cover a range of physical properties and multifunctionalities that are critical for logic, memory, and optical devices. Typically, the high‐quality epitaxial growth of these complex oxide thin films requires single crystalline oxide substrates such as SrTiO 3 (STO), MgO, LaAlO 3 , a‐Al 2 O 3, and many others. Recent successes in transferring these complex oxides as free‐standing films not only offer great opportunities in integrating complex oxides on other devices, but also present enormous opportunities in recycling the deposited substrates after transfer for cost‐effective and sustainable processing of complex oxide thin films. In this work, the surface modification effects introduced on the recycled STO are investigated, and their impacts on the microstructure and properties of subsequently grown epitaxial oxide thin films are assessed and compared with those grown on the pristine substrates. Detailed analyses using high‐resolution scanning transmission electron microscopy and geometric phase analysis demonstrate distinct strain states on the surfaces of the recycled STO versus the pristine substrates, suggesting a pre‐strain state in the recycled STO substrates due to the previous deposition layer. These findings offer opportunities in growing highly mismatched oxide films on the recycled STO substrates with enhanced physical properties. Specifically, yttrium iron garnet (Y 3 Fe 5 O 12 ) films grown on recycled STO present different ferromagnetic responses compared to that on the pristine substrates, underscoring the effects of surface modification. The study demonstrates the feasibility of reuse and redeposition using recycled substrates. Via careful handling and preparation, high‐quality epitaxial thin films can be grown on recycled substrates with comparable or even better structural and physical properties toward sustainable process of complex oxide devices.

pre-strained STO surfaces↗

Wrong signs are alright

It has been shown that some Lorentz-invariant quantum field theories, such as those with higher-dimensional operators with negative coefficients, lead to superluminality on some classical backgrounds. While superluminality by itself is not logically inconsistent, these theories also predict the formation of closed time-like curves at the classical level, starting from initial conditions without such curves. This leads to the formation of a Cauchy Horizon which prevents a complete description of the time evolution of such systems. Inspired by the chronology protection arguments of General Relativity, we show that quantum mechanical effects from low energy quanta strongly backreact on such configurations, exciting unknown short-distance degrees of freedom and invalidating the classical predictions. Thus, there is no obvious low-energy obstruction to the existence of these operators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Superselection rules, quantum error correction, and quantum chromodynamics

We investigate the relationship between superselection rules and quantum error correcting codes. We demonstrate that the existence of a superselection rule implies the Knill-Laflamme condition in quantum error correction. As an example, we examine the code built from quantum chromodynamics, where the proton and neutron states in the model are explored as different superselection sectors that protect logical information. Finally we comment on topological quantum error correcting codes and supersymmetric quantum field theory within this framework.

97 MATHEMATICS AND COMPUTING↗

Celestial Quantum Error Correction. Part II. From qudits to celestial CFT

A holographic CFT description of asymptotically flat spacetimes inherits vacuum degeneracies and IR divergences from its gravitational dual. We devise a Quantum Error Correcting (QEC) framework to encode both effects as correctable fluctuations on the CFT dual. The framework is physically motivated by embedding a chain of qudits in the so-called Klein spacetime and then taking a continuum 𝑁 → ∞ limit. At finite 𝑁 the qudit chain 1) enjoys a discrete version of celestial symmetries and 2) supports a Gottesman-Kitaev-Preskill (GKP) code. The limit results in hard states with quantized BMS hair in the celestial torus forming the logical subspace, robust under errors induced by soft radiation. Technically, the construction leverages the recently studied 𝑤 1+∞ hierarchy of soft currents and its realization from a sigma model in twistor space.

79 ASTRONOMY AND ASTROPHYSICS↗

Developing a Control Strategy for Minimum Airflow Setting Considering CO2 Level and Energy Consumption in a Variable Air Volume System

In an office building equipped with a Variable Air Volume (VAV) system, this paper introduces a novel method for controlling the minimum supply airflow fraction in each zone’s VAV box, having a capability to consider indoor CO2 level and energy consumption. The EnergyPlus simulation using the medium office prototype model was employed, which evaluated the performance of the energy and CO2 concentration for five VAV box airflow control strategies. The paper focuses on CO2 concentration-based airflow control method and compares it with other four methods including conventional single-max, reduced minimum single-max, demand-controlled ventilation(DCV), and dualmax control methods according to guidelines and common practices. The newly proposed control strategy directly correlates the minimum airflow fraction to CO2 concentration. A general trend emerged when comparing CO2 concentrations—lower minimum airflow fractions were associated with higher concentrations. The proposed control method effectively maintained low CO2 concentrations and enabled a lower airflow fraction contributing to energy consumption reduction. It was confirmed that heating energy consumption in climate zone 4A, 5B, and 6A showed a maximum saving of approximately 30% compared to the conventional single-max and dual max control strategies. It was found that cooling energy consumption in climate zone 4A and 6A can achieve a maximum saving of approximately 10% compared to the conventional control strategies. The proposed CO2 concentration-based control logic is promising as it not only improves the indoor air quality lowering the CO2 concentration in the occupied spaces, but also contributes to HVAC energy savings.

Lee, Jong Man↗

Machine learning for arbitrary single-qubit rotations on an embedded device

Here, in this study, we present a technique for using machine learning (ML) for single-qubit gate synthesis on field-programmable logic for a superconducting transmon-based quantum computer based on simulated studies. Our approach is multi-stage. We first “bootstrap” a model based on simulation with access to the full state vector for measuring gate fidelity. We next present an algorithm, named adapted randomized benchmarking (ARB), for fine-tuning the gate on hardware based on measurements of the devices. We also present techniques for deploying the model on programmable devices with care to reduce the required resources. While the techniques here are applied to a transmon-based computer, many of them are portable to other architectures.

97 MATHEMATICS AND COMPUTING↗