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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 289 records · Page 16

Modular chip-integrated photonic control of artificial atoms in diamond waveguides

A central goal in creating long-distance quantum networks and distributed quantum computing is the development of interconnected and individually controlled qubit nodes. Atom-like emitters in diamond have emerged as a leading system for optically networked quantum memories, motivating the development of visible-spectrum, multi-channel photonic integrated circuit (PIC) systems for scalable atom control. However, it has remained an open challenge to realize optical programmability with a qubit layer that can achieve high optical detection probability over many optical channels. Here, we address this problem by introducing a modular architecture of piezoelectrically actuated atom-control PICs (APICs) and artificial atoms embedded in diamond nanostructures designed for high-efficiency free-space collection. The high-speed four-channel APIC is based on a splitting tree mesh with triple-phase shifter Mach–Zehnder interferometers. This design simultaneously achieves optically broadband operation at visible wavelengths, high-fidelity switching (>40dB) at low voltages, submicrosecond modulation timescales (>30MHz), and minimal channel-to-channel crosstalk for repeatable optical pulse carving. Via a reconfigurable free-space interconnect, we use the APIC to address single silicon vacancy color centers in individual diamond waveguides with inverse tapered couplers, achieving efficient single photon detection probabilities (∼15%) and second-order autocorrelation measurements g (2) (0)<0.14 for all channels. The modularity of this distributed APIC–quantum memory system simplifies the quantum control problem, potentially enabling further scaling to thousands of channels.

47 OTHER INSTRUMENTATION↗

Networked Microgrid Operations: Supporting a Resilient Electric Power Infrastructure

Modern electric power systems operate using large generating units managed with a centralized control structure. The current systems are the result of over a hundred years of technological development and consolidation to leverage economies of scale. While the existing systems have proven cost effective and reliable, modern systems are experiencing a wide range of operational challenges that are causing a reexamination of the centralized control structure. Despite the nearly universal adoption of centralized control, electric power systems are fractal in their operational requirements. Specifically, the fundamental operational requirements are the same, regardless of the system size. While past technologies have not allowed for exploitation of this fractal behavior, emerging technologies are making it possible; these technologies include grid-forming inverters, modern telecommunications systems, and distributed control architectures. Here we show emerging technologies that allow the fractal operational requirements of electric power systems to be exploited as networked microgrids to increase the resiliency of the world’s critical electrical infrastructure.

Schneider, Kevin P.↗

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↗

Observation and Control of Unidirectional Ballistic Dynamics of Nanoparticles at a Liquid–Gas Interface by 4D Electron Microscopy

Understanding and controlling the dynamics of active Brownian objects far from equilibrium are fundamentally important for emerging technologies such as artificial micro/nanomotors for drug deliveries and noninvasive microsurgery. However, direct observation and control of unidirectional propulsion of individual nanoscale objects are technically challenging due to the required spatiotemporal resolution. Here, we report in situ visualization and manipulation of unidirectional superfast ballistic dynamics of a single-photon-activated gold nanoparticle (NP) along the liquid–gas interface by four-dimensional electron microscopy (4D EM) at nanometer and nanosecond scales. We observed that, upon repetitive femtosecond laser excitation, the NP at the liquid–gas interface exhibits a continuously superfast unidirectional translation with a linear dependence of its root mean squared velocity (νrms) on either the laser fluence or repetition rate. Under a single femtosecond pulse excitation, the NP exhibits a superfast ballistic translation at the nanosecond time scale. Combined experiment and physical modeling reveals that the superfast unidirectional, ballistic translation is driven by unidirectional random impulsive forces arising from the nanobubbles (NBs) induced by enhanced laser heating as a result of plasmonic excitation, which is controllable by tuning the laser characteristics. Furthermore, this directional plasmonic NB-propulsion mechanism sheds light on the design of light-controllable artificially intelligent micro/nanomotor systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Evaluating Stage Motion for Automated Electron Microscopy

Abstract Precise control is an essential and elusive quality of emerging self-driving transmission electron microscopes (TEMs). It is widely understood these instruments must be capable of performing rapid, high-volume, and arbitrary movements for practical self-driving operation. However, stage movements are difficult to automate at scale, owing to mechanical instability, hysteresis, and thermal drift. Such difficulties pose major barriers to artificial intelligence-directed microscope designs that require repeatable, precise movements. To guide design of emerging instruments, it is necessary to understand the behavior of existing mechanisms to identify rate limiting steps for full autonomy. Here, we describe a general framework to evaluate stage motion in any TEM. We define metrics to evaluate stage degrees of freedom, propose solutions to improve performance, and comment on fundamental limits to automated experimentation using present hardware.

47 OTHER INSTRUMENTATION↗

Cavity-altered superconductivity

Is it feasible to alter the ground-state properties of a material by engineering its electromagnetic environment? Inspired by theoretical predictions, experimental realizations of such cavity-controlled properties without optical excitation are beginning to emerge. Here we devised and implemented a new platform to realize cavity-altered materials. Single crystals of hyperbolic van der Waals (vdW) compounds provide a resonant electromagnetic environment with enhanced density of photonic states and prominent mode confinement. We interfaced hexagonal boron nitride (hBN) with the molecular superconductor κ-(BEDT-TTF) 2 Cu[N(CN) 2 ]Br (κ-ET). The frequencies of infrared hyperbolic modes (HMs) of hBN match the infrared-active carbon–carbon (C=C) stretching molecular resonance of κ-ET implicated in superconductivity. Nano-optical data supported by first-principles molecular Langevin dynamics simulations confirm the presence of resonant coupling between the hBN hyperbolic cavity modes and the C=C stretching mode in κ-ET. Meissner-effect measurements using magnetic force microscopy (MFM) demonstrate a strong suppression of superfluid density near the hBN/κ-ET interface. Non-resonant control heterostructures, including RuCl 3 /κ-ET and hBN/Bi 2 Sr 2 CaCu 2 O 8+x (BSCCO), do not show the pronounced superfluid suppression. These observations suggest that hBN/κ-ET realizes a cavity-altered superconducting ground state. Our work highlights the potential of dark cavities devoid of external photons for engineering electronic ground-state properties of complex quantum materials.

36 MATERIALS SCIENCE↗

Magnetic control over the fundamental structure of atomic wires

When reducing the size of materials towards the nanoscale, magnetic properties can emerge due to structural variations. Here, we show the reverse effect, where the structure of nanomaterials is controlled by magnetic manipulations. Using the break-junction technique, we find that the interatomic distance in platinum atomic wires is shorter or longer by up to ~20%, when a magnetic field is applied parallel or perpendicular to the wires during their formation, respectively. The magnetic field direction also affects the wire length, where longer (shorter) wires are formed under a parallel (perpendicular) field. Our experimental analysis, supported by calculations, indicates that the direction of the applied magnetic field promotes the formation of suspended atomic wires with a specific magnetization orientation associated with typical orbital characteristics, interatomic distance, and stability. A similar effect is found for various metal and metal-oxide atomic wires, demonstrating that magnetic fields can control the atomistic structure of different nanomaterials when applied during their formation stage.

36 MATERIALS SCIENCE↗

Networked Microgrid Energy Management Considering Ownership and Control Structures: A Comparison

With the growing deployment of microgrids, networked microgrids have emerged for their additional advantages of economy, reliability and resilience by coordinating the operation of multiple microgrids. As microgrids are operated with different ownership, objectives and functionalities, the formed networked microgrids show characteristics of mixed ownership, inconsistent objectives and various functionalities. To enable the coordinated operation of networked microgrids, three control structures, i.e., centralized, distributed and decentralized, have been constructed in the literature. However, the data sharing enabling these different paradigms and the resulted value propositions are not well defined, leading to poor resource management and resilience, etc. To solve this issue, a complete comparison of networked microgrid energy management under centralized, distributed and decentralized structures are performed. As a novel contribution, the required minimum data exchange of networked microgrid energy management under three control structures are identified, respectively. The value propositions are calculated and compared against each other by the results of case studies.

control structures↗

Spatial coherence of room-temperature monolayer WSe 2 exciton-polaritons in a trap

The emergence of spatial and temporal coherence of light emitted from solid-state systems is a fundamental phenomenon intrinsically aligned with the control of light-matter coupling. It is canonical for laser oscillation, emerges in the superradiance of collective emitters, and has been investigated in bosonic condensates of thermalized light, as well as exciton-polaritons. Our room temperature experiments show the strong light-matter coupling between microcavity photons and excitons in atomically thin WSe 2 . We evidence the density-dependent expansion of spatial and temporal coherence of the emitted light from the spatially confined system ground-state, which is accompanied by a threshold-like response of the emitted light intensity. Additionally, valley-physics is manifested in the presence of an external magnetic field, which allows us to manipulate K and K’ polaritons via the valley-Zeeman-effect. Our findings validate the potential of atomically thin crystals as versatile components of coherent light-sources, and in valleytronic applications at room temperature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Charaterization of Emerging Computing Architectures for Dynamic Simulation of Future Power Grids with Large-Scale Power Electronics

The increasing penetration of power electronics in power grids significantly raises the computing requirements in a real-time (and/or fast) simulation of the power grid. The real-time simulation is an enabler for evaluating controllers, protection systems, new equipment, and twinning. In this paper, emerging computing architectures such as tensor processing units (TPU), neural/neuromorphic processing units (NPU), and quantum processing units (QPU) are introduced and characterized for the real-time (and/or fast) simulation of power electronics-dominated power grids. The metrics and the process to characterize emerging computing architectures to perform real-time (and/or fast) simulations of future power grids with power electronics are discussed. Three of the emerging computing units are characterized based on these metrics and the process developed. This characterization will enable identification and comparison of emerging computing architectures that can perform real-time (and/or fast) simulation of future power grids.

Choi, Jongchan↗

Lighting Control in Patient Rooms: Understanding Nurses’ Perceptions of Hospital Lighting Using Qualitative Methods

Here, this study differs in its methodological approach from previously published research by interpreting qualitative results against existing literature to understand how nurses conceptualize medical–surgical patient rooms as productive settings in relation to lighting, as well as the ways in which nurses believe these spaces could be enhanced for patient satisfaction. Content analysis was used to interpret themes emerging from nurses’ subjective responses to open-ended items. Three of the facilities had older, traditional lighting systems; one had a contemporary framework. A theme of environmental control over both overhead and task lighting emerged from data from all items. Although controllability was among the “best” lighting attributes, more refinement is necessary for optimal staff productivity and patient satisfaction. Daylighting was also considered to be among the best attributes. Control over light level via additional dimming capability for patients, as well as additional light sources, was prominent across the four hospitals. Unique to the more modern facility, trespassing of light was problematic for nurses considering the experiences of patients—even where modern models exist, more attention can be paid to the ways in which window shades, and light sources outside of rooms, penetrate spaces and affect users. Finally, the finding that nurses and patients desire greater control over the lighting in patient rooms is consistent with Ulrich’s theory of supportive design for healthcare and coincides with advances in lighting technology. Despite differences in the level of sophistication in lighting among the four facilities, control continues to be a primary concern for nurses.

60 APPLIED LIFE SCIENCES↗

Quantifying microbial control of soil organic matter dynamics at macrosystem scales

Soil organic matter (SOM) stocks, decomposition and persistence are largely the product of controls that act locally. Yet the controls are shaped and interact at multiple spatiotemporal scales, from which macrosystem patterns in SOM emerge. Theory on SOM turnover recognizes the resulting spatial and temporal conditionality in the effect sizes of controls that play out across macrosystems, and couples them through evolutionary and community assembly processes. For example, climate history shapes plant functional traits, which in turn interact with contemporary climate to influence SOM dynamics. Selection and assembly also shape the functional traits of soil decomposer communities, but it is less clear how in turn these traits influence temporal macrosystem patterns in SOM turnover. Here, we review evidence that establishes the expectation that selection and assembly should generate decomposer communities across macrosystems that have distinct functional effects on SOM dynamics. Representation of this knowledge in soil biogeochemical models affects the magnitude and direction of projected SOM responses under global change. Yet there is high uncertainty and low confidence in these projections. To address these issues, we make the case that a coordinated set of empirical practices are required which necessitate (1) greater use of statistical approaches in biogeochemistry that are suited to causative inference; (2) long-term, macrosystem-scale, observational and experimental networks to reveal conditionality in effect sizes, and embedded correlation, in controls on SOM turnover; and (3) use of multiple measurement grains to capture local- and macroscale variation in controls and outcomes, to avoid obscuring causative understanding through data aggregation. Here, when employed together, along with process-based models to synthesize knowledge and guide further empirical work, we believe these practices will rapidly advance understanding of microbial controls on SOM and improve carbon cycle projections that guide policies on climate adaptation and mitigation.

59 BASIC BIOLOGICAL SCIENCES↗

Metallurgical alloy approach to two-dimensional supramolecular materials

Alloys are normally mixtures of metallic elements used to search for superior functional properties compared with their individual components. Although a quintessential approach to better materials in metallurgy, the concept of alloying has been expanded to other inorganic materials and covalent polymers. In this work, we report on alloy formation of small organic molecules structured as amphiphilic chromophores in water. Using X-ray scattering, microscopy, and optical spectroscopy, we unambiguously demonstrate the formation of supramolecular alloys with changes in physical, photophysical, and mechanical properties. Additionally, we identify single-crystalline, two-dimensional supramolecular polymers containing multiple molecular species, analogous to intermetallic compounds. The mechanism of alloy formation suggests the possibility of controlled growth in these supramolecular assemblies to create emergent functional structures.

36 MATERIALS SCIENCE↗

Predicting lake surface water phosphorus dynamics using process-guided machine learning

Phosphorus (P) loading to lakes is degrading the quality and usability of water globally. Accurate predictions of lake P dynamics are needed to understand whole-ecosystem P budgets, as well as the consequences of changing lake P concentrations for water quality. However, complex biophysical processes within lakes, along with limited observational data, challenge our capacity to reproduce short-term lake dynamics needed for water quality predictions, as well as long-term dynamics needed to understand broad scale controls over lake P. Here we use an emerging paradigm in modeling, process-guided machine learning (PGML), to produce a phosphorus budget for Lake Mendota (Wisconsin, USA) and to accurately predict epilimnetic phosphorus over a time range of days to decades. In our implementation of PGML, which we term a Process-Guided Recurrent Neural Network (PGRNN), we combine a process-based model for lake P with a recurrent neural network, and then constrain the predictions with ecological principles. We test independently the process-based model, the recurrent neural network, and the PGRNN to evaluate the overall approach. The process-based model accounted for most of the observed pattern in lake P; however it missed the long-term trend in lake P and had the worst performance in predicting winter and summer P in surface waters. The root mean square error (RMSE) for the process-based model, the recurrent neural network, and the PGRNN was 33.0 μg P L -1 , 22.7 μg P L -1 , and 20.7 μg P L -1 , respectively. All models performed better during summer, with RMSE values for the three models (same order) equal to 14.3 μg P L -1 , 10.9 μg P L -1 , and 10.7 μg P L -1 . Although the PGRNN had only marginally better RMSE during summer, it had lower bias and reproduced long-term decreases in lake P missed by the other two models. For all seasons and all years, the recurrent neural network had better predictions than process alone, with root mean square error (RMSE) of 23.8 μg P L -1 and 28.0 μg P L -1 , respectively. The output of PGRNN indicated that new processes related to water temperature, thermal stratification, and long term changes in external loads are needed to improve the process model. By using ecological knowledge, as well as the information content of complex data, PGML shows promise as a technique for accurate prediction in messy, real-world ecological dynamics, while providing valuable information that can improve our understanding of process.

54 ENVIRONMENTAL SCIENCES↗

A review of zirconia oxygen, NO x , and mixed potential gas sensors – History and current trends

Zirconia-based electrochemical sensors have revolutionized oxygen monitoring and combustion control. Here, these robust, solid-state devices are found in virtually every internal combustion engine today providing feedback information for tight air to fuel ratio control thus minimizing unwanted emissions and improving engine efficiency. Variations on the sensor design and operational mode enable the measurement of nitrogen oxides to part per million levels, providing control information for exhaust after-treatment systems. Emerging designs include the development of "gas analyzers on a chip" capable of monitoring oxygen, carbon monoxide, nitrogen oxides, ammonia and hydrocarbons.

47 OTHER INSTRUMENTATION↗

(111) Faceted Metal Oxides: A Review of Synthetic Methods

Material design and synthesis have made tremendous impacts in the scientific community by unleashing a material's true potential via enhanced properties and applications. Over the years, advanced synthetic strategies have emerged and have been expanded to not only control the size and shape of nanoparticles but also to control the preferential growth of surface facets, paving the way for new materials with facet-dependent properties. Metal oxide (111) facets as compared to their potentially more stable counterpart facets (e.g., (100), (110)) have recently exhibited enriched chemical properties owing to their unique surface arrangement. As a result, metal oxide (111) faceted surfaces have been used in applications such as catalysis, sorbents, batteries, etc. This work aims to provide a perspective on the synthetic processes utilized to expose (111) surfaces and the governing factors/synthetic parameters that expose them across various metal oxides of different crystal structures as well as some of their applications.

36 MATERIALS SCIENCE↗

Sequence-Structure–Property Relationships in Short-Chain Polyesters: How Primary Structure Governs Macroscopic Performance

While polymer properties are fundamentally linked to their nanostructure, the influence of monomer sequence remains less understood than stereochemical factors like tacticity. This study examines how sequence distribution affects the thermal behavior and morphology of homo- and copolyesters, specifically comparing polymers derived from constitutionally identical monomers but with varying degrees of sequence regularity depending on monomer structure or polymerization selectivity. Our findings show that increasing sequence defects progressively diminish thermal stability, crystallinity, melting temperatures, and morphological order. As new materials become more compositionally complex, this work underscores the importance of sequence control in the design of advanced polymers for emerging applications.

Bocharova, Vera [Oak Ridge National Laboratory (OR↗