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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Improving the Cyber Resiliency and Security Posture of Public Power (Final Report)

The key objective of Improving the Cyber Resiliency and Security Posture of Public Power (Project) was to develop a culture of cyber resiliency and security within the public power community. The relative smaller size and unique structure of community-owned electric utilities can sometimes present challenges in immediate recognition of threats and the escalation of potential incidents. The Project offered targeted education, coordination, capability building, and resources to help the public power community better understand, install, and implement cyber and physical resiliency and security systems. The American Public Power Association (APPA) accelerated efforts to develop resources for and with the public power community to understand and implement resiliency, cybersecurity and cyber-physical solutions, including refining and improving the adoption of advanced control concepts. The Project consisted of four major multi-pronged tasks which included: 1) Advance cyber resiliency and security assessments; 2) Conduct, evaluate, and use the results of onsite vulnerability assessments; 3) Research, evaluate, deploy, and integrate both commercial and pre-commercial security technologies; and 4) Research, evaluate, and implement information sharing mechanisms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Mesoscale to Microscale Simulations over Complex Terrain with the Immersed Boundary Method in the Weather Research and Forecasting Model

Improvements to the Weather Research and Forecasting (WRF) Model are made to enable multiscale simulations over highly complex terrain with dynamically downscaled boundary conditions from the mesoscale to the microscale. Over steep terrain, the WRF Model develops numerical errors that are due to grid deformation of the terrain-following coordinates. An alternative coordinate system, the immersed boundary method (IBM), has been implemented into WRF, allowing for simulations over highly complex terrain; however, the new coordinate system precluded nesting within mesoscale simulations using WRF’s native terrain-following coordinates. Here, the immersed boundary method and WRF’s grid-nesting framework are modified to seamlessly work together. This improved framework for the first time allows for large-eddy simulation over complex (urban) terrain with IBM to be nested within a typical mesoscale WRF simulation. Simulations of the Joint Urban 2003 field campaign in Oklahoma City, Oklahoma, are performed using a multiscale five-domain nested configuration, spanning horizontal grid resolutions from 6 km to 2 m. These are compared with microscale-only simulations with idealized lateral boundary conditions and with observations of wind speed/direction and SF 6 concentrations from a controlled release from intensive observation period 3. The multiscale simulation, which is configured independent of local observations, shows similar model skill predicting wind speed/direction and improved skill predicting SF 6 concentrations when compared with the idealized simulations, which require use of observations to set mean flow conditions. Use of this improved multiscale framework shows promise for enabling large-eddy simulation over highly complex terrain with dynamically downscaled boundary conditions from mesoscale models.

42 ENGINEERING↗
DOE OSTI2025

Electrochemical Random-Access Memory: Progress, Perspectives, and Opportunities

Non-von Neumann computing using neuromorphic systems based on analogue synaptic and neuronal elements has emerged as a potential solution to tackle the growing need for more efficient data processing, but progress toward practical systems has been stymied due to a lack of materials and devices with the appropriate attributes. Recently, solid state electrochemical ion-insertion, also known as electrochemical random access memory (ECRAM) has emerged as a promising approach to realize the needed device characteristics. ECRAM is a three terminal device that operates by tuning electronic conductance in functional materials through solid-state electrochemical redox reactions. This mechanism can be considered as a gate-controlled bulk modulation of dopants and/or phases in the channel. Early work demonstrating that ECRAM can achieve nearly ideal analogue synaptic characteristics has sparked tremendous interest in this approach. More recently, the realization that electrochemical ion insertion can be used to tune the electronic properties of many types of materials including transition metal oxides, layered two-dimensional materials, organic and coordination polymers, and that the changes in conductance can span orders of magnitude has further attracted interest in ECRAM as the basis for analogue synaptic elements for inference accelerators as well as for dynamical devices that can emulate a wide range of neuronal characteristics for implementation in analogue spiking neural networks. At its core, ECRAM shares many fundamental aspects with rechargeable batteries, where ion insertion materials are used extensively for their ability to reversibly store charge and energy. Computing applications, however, present drastically different requirements: systems will require many millions of devices, scaled down to tens of nanometers, all while achieving reliable electronic-state tuning at scaled-up rates and endurances, and with minimal energy dissipation and noise. Further, in this review, we discuss the history, basic concepts, recent progress, as well as the challenges and opportunities for different types of ECRAM, broadly grouped by their primary mobile ionic charge carrier, including Li, protons, and oxygen vacancies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Electrochemical Capacitance Traces with Interlayer Spacing in Two‐dimensional Conductive Metal–Organic Frameworks

Abstract Electrically conductive metal–organic frameworks (MOFs) are promising candidates for electrochemical capacitors (EC) for fast energy storage due to their high specific surface areas and potential for redox activity. To maximize energy density, traditional inorganic pseudocapacitors have utilized faradaic processes in addition to double‐layer capacitance. Although conductive MOFs are usually comprised of redox active ligands which allow faradaic reactions upon electrochemical polarization, systematic studies providing deeper understanding of the charge storage processes and structure‐function relationships have been scarce. Here, we investigate the charge storage mechanisms of a series of triazatruxene‐based 2D layered conductive MOFs with variable alkyl functional groups, Ni 3 (HIR 3 ‐TAT) 2 (TAT=triazatruxene; R=H, Et, n ‐Bu, n ‐Pent). Functionalization of the triazatruxene core allows for systematic variation of structural parameters while maintaining in‐plane conjugation between ligands and metals. Specifically, R groups modulate interlayer spacing, which in turn shifts the charge storage mechanism from double‐layer capacitance towards pseudocapacitance, leading to an increase in molar specific capacitance from Ni 3 (HIH 3 ‐TAT) 2 to Ni 3 (HIBu 3 ‐TAT) 2 . Partial exfoliation of Ni 3 (HIBu 3 ‐TAT) 2 renders redox active ligand moieties more accessible, and thus increases the dominance of faradaic processes. Our strategy of controlling charge storage mechanism through tuning the accessibility of redox‐active sites may motivate further design and engineering of electrode materials for EC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Optical properties of differing nanolayered structures of divalent europium doped barium fluoride thin films synthesized by pulsed laser deposition

Optically-active thin films are employed in a variety of applications, such as LEDs and photovoltaics, due to their ability to act as up- or down-photon energy converters. Their performance depends critically on their composition and structure; thus, the use of novel synthesis techniques that allow for their control at the nanoscale level can result in improved efficiency and practicality. Here, layered thin films consisting of Eu 2+ - doped BaF 2 nanocrystalline layers separated by amorphous Al 2 O 3 were synthesized via sequential pulsed laser deposition using three separate targets for the different components; this synthesis technique provides precise control of layer thickness at the nanoscale along with dopant distribution within the film. Cross-sectional transmission electron microscopy analysis verified the desired nano-layering. Post-deposition heat treatments in a nitrogen atmosphere resulted in samples exhibiting steady emission with a broad peak ranging from 400 to 600 nm and a shoulder at 410 nm. The CIE 1931 chromaticity coordinates are x = 0.26-0.29 and y = 0.32-0.35 and vary as a function of the sample configuration. Because the chromaticity coordinates are close to those of a pure white light (x = 0.33, y = 0.33), these films demonstrate advantageous properties for applications with UV-pumped white light LEDs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Tuning the zeolite acidity enables selectivity control by suppressing ketene formation in lignin catalytic pyrolysis

Unveiling catalytic mechanisms at a molecular level aids rational catalyst design and selectivity control for process optimization. In this study, we find that the Brønsted acid site density of the zeolite catalyst efficiently controls the guaiacol catalytic pyrolysis mechanism. Guaiacol demethylation to catechol initiates the reaction, as evidenced by the detected methyl radicals. The mechanism branches to form either fulvenone (c-C 5 H 4 = C = O), a reactive ketene intermediate, by catechol dehydration, or phenol by acid-catalyzed dehydroxylation. At high Brønsted acid site density, fulvenone formation is inhibited due to surface coordination configuration of its precursor, catechol. By quantifying reactive intermediates and products utilizing operando photoelectron photoion coincidence spectroscopy, we find evidence that ketene suppression is responsible for the fivefold phenol selectivity increase. Complementary fulvenone reaction pathway calculations, along with 29 Si NMR-MAS spectroscopy results corroborate the mechanism. The proposed, flexible operando approach is applicable to a broad variety of heterogeneous catalytic reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

The Role of Cooperative Interactions Among Surfaces, Solvents, and Reactive Intermediates on Catalysis at Liquid–Solid Interfaces (Final Report DE-SC0020224)

This project established quantitative links between inner‑sphere chemistry (active metal identity, coordination, and zeolite topology) and outer‑sphere organization (solvent identity, hydrogen‑bond networks, and pore condensation) that govern rates, activation barriers, and selectivities for alkene epoxidation and epoxide ring‑opening at solid–liquid and quasi‑liquid–solid interfaces. We deconvoluted contributions from covalent interactions at active sites and noncovalent, solvent‑mediated interactions within pores by pairing well‑defined metal substituted zeolites with controlled solvent environments. We then mapped those contributions onto measurable kinetics (ΔH‡, ΔS‡), adsorption thermodynamics (ITC), and in situ spectroscopy. The transferrable outcomes include a set of design rules that include the following understandings. First, tune silanol ((SiOH)x) density and pore topology to organize solvent networks that selectively stabilize transition states. Second, exploit activity‑coefficient‑normalized rates and adsorption– barrier correlations to diagnose when solvent reorganization rather than surface chemistry limits performance. Third, use partial pore condensation (e.g., acetonitrile, water but also generalizable to other solvents) to elicit liquid‑like stabilization effects even in nominally vapor‑phase reactors. Collectively, these results provide strategies to increase epoxidation rates, improve oxidant utilization (i.e., selectivities), and steer regioselectivity in zeolite‑based catalytic processes relevant to sustainable oxidation chemistry. These outcomes should be transferable to other classes of reactions that proceed in microporous materials and under confinement provided by organized solvents (e.g., electrochemical double layers).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Distributed optimization for multi-commodity urban traffic control

A distributed method for concurrent traffic signal and routing control of traffic networks is proposed. The method is based on the multi-commodity store-and-forward model, in which the destinations are the commodities. The system benefits from the communication between vehicles and infrastructure, providing optimal signal timings to intersections and routes to vehicles on a link-by-link basis. Using the augmented Lagrangian to model the constraints into the objective, the baseline centralized problem is decomposed into a set of objective-coupled subproblems, one for each intersection, enabling the solution to be computed by a distributed- gradient projection algorithm. Further, the intersection agents only need to communicate and coordinate with neighboring intersections to ensure convergence to the optimal solution while tolerating suboptimal iterations that offer more flexibility, unlike other distributed approaches. Through microsimulation, we demonstrate the effectiveness of the proposed algorithm in traffic networks with time-varying demand. Computational analysis shows that the distributed problem is suitable for real-time applications. A robustness analysis show that the distributed formulation enables a graceful degradation of the system in case of failure.

Augmented Lagrangian↗
DOE OSTI2026

Endogenous Interface Pricing for Consistent Transmission–Distribution Co-Optimization With Discrete Distribution Controls

This paper proposes an endogenous interface pricing model for day-ahead transmission–distribution co-optimization that co-determines the interface locational marginal price (LMP) and the transmission–distribution exchange, ensuring price–dispatch consistency while optimally scheduling discrete distribution controls. The formulation couples a DC optimal power flow (OPF) with a branch-flow AC OPF that schedules distributed energy resources (DERs), tap-changer settings, capacitor banks (CBs), and multi-period energy storage systems (ESSs) under feeder voltage and current limits, and is solved as a mixed-integer second-order cone program (MISOCP). In a T14–D33 system, coordinated device scheduling recovers about 90% of the distribution-to-transmission export achievable in a reference case that ignores distribution network (DN) limits, while satisfying a 1.05 p.u. voltage upper bound. In a T39–D34/D37/D123 system, a sequential decoupled benchmark produces interface LMP distortions up to 12.5% and a 7.28% mismatch in net export energy, whereas the proposed model removes these distortions and the associated settlement mismatches. Second-order cone (SOC) relaxation gaps remain below $10^{-3}$ in all cases.

Noh, Seung-Gil↗
DOE OSTI2022

Deep Reinforcement Learning From Demonstrations to Assist Service Restoration in Islanded Microgrids

Microgrids can be operated in island mode during utility grid outages to support service restoration and improve system resilience. To schedule and dispatch distributed energy resources (DERs) in an islanded microgrid, conventional model-based methods rely on accurate distribution network models and lack generalization and adaptability. Data-driven methods are promising for DER coordination but face practical challenges such as potential hazards to microgrids during online training and insufficient online training opportunities due to low outage rates. This paper presents a novel two-stage learning framework that builds on the deep deterministic policy gradient from demonstrations to identify an optimal restoration strategy. At the pre-training stage, imitation learning is applied to equip the control agent with expert experiences to guarantee acceptable initial performance. At the online training stage, action clipping, reward shaping, and expert demonstrations are leveraged to ensure safe exploration while accelerating the training process. In conclusion, the proposed method is illustrated using the IEEE 123-node system and compared with a representative model-based method and the standard deep deterministic policy gradient method to prove solution accuracy and demonstrate increased computational efficiency.

Du, Yan↗
DOE OSTI2022

3D Printed Parahydrophobic Surfaces as Multireaction Platforms

We report Parahydrophobic surfaces (PHSs) composed of arrays of cubic μ-pillars with a double scale of roughness and variable wettability were systematically obtained in one step and a widely accessible stereolithographic Formlabs 3D printer. The wettability control was achieved by combining the geometrical parameters (H = height and P = pitch) and the surface modification with fluoroalkyl silane compounds. Homogeneous distribution of F and Si atoms onto the pillars was observed by XPS and SEM-EDAX. A nano-roughness on the heads of the pillars was achieved without any post-treatment. The smallest P values lead to surfaces with static contact angles (CAs) >150° regardless of the H utilized. Interestingly, the relationship 0.6 ≤ H/P ≤ 2.6 obtained here was in good agreement with the H/P values reported for nano- and submicron pillars. Furthermore, experimental CAs, advancing and receding CAs, were consistent with the theoretical prediction from the Cassie–Baxter model. Structures covered with perfluorodecyltriethoxysilane with high H and short P lead to PHSs. Conversely, structures covered with perfluorodecyltrimethoxysilane exhibited a superhydrophobic behavior. Finally, several aqueous reactions, such as precipitation, coordination complex, and nanoparticle synthesis, were carried out by placing the reactive agents as microdroplets on the parahydrophobic pillars, demonstrating the potential application as chemical multi-reaction array platforms for a large variety of relevant fields in microdroplet manipulation, microfluidics systems, and health monitoring, among others.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Atomic Ordering-Induced Ensemble Variation in Alloys Governs Electrocatalyst On/Off States

The catalytic behavior of a material is influenced by ensembles—the geometric configuration of atoms. Traditional approaches, mainly utilizing solid-solution alloys in electrocatalysis, have often overlooked the challenges posed by concurrent changes in the electronic structure (i.e. d-band center) when the composition is altered. Here, this study introduces a methodology that distinctly separates the geometric effects (i.e. ensembles) from the electronic structure. We compare the reactivity of compositionally identical, but structurally different Pd 3 Bi ordered intermetallic and solid-solution alloys. Remarkably, we find that Pd 3 Bi intermetallics display nearly no reactivity for the methanol oxidation (MOR), while their solid-solution counterparts have significant reactivity. This highlights a unique case where materials with identical chemical compositions demonstrate drastically different catalytic behavior underscoring the critical importance of ensembles in electrocatalysis. Specifically, Pd 3 Bi intermetallics form smaller ensembles (average coordination number: 4.5 ± 1.6) with almost no measurable MOR activity at room temperature, in contrast to the solid-solution Pd 3 Bi that exhibit larger ensembles (average coordination number: 6.8 ± 0.9) and considerable MOR reactivity (0.5 mA cm −2 Pd ). An ordered Pd 3 Bi alloy, with an intermediate ensemble size (average coordination number: 5.3 ± 1.2), displays moderate MOR activity (0.1 mA cm −2 Pd ), further confirming the direct correlation between ensemble size and catalytic activity. Notably, all Pd 3 Bi alloys maintain similar electronic structures, because the chemical composition of the alloys is fixed, indicating that the differences in reactivity are predominantly from changes to the ensemble size. Our findings offer an approach for precisely controlling catalytic activity through manipulating the geometric configuration of the atoms within an alloy, paving the way for more efficient catalyst design.

alloys↗
DOE OSTI2026

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

WiP Abstract: Edge-Based Privacy of Naturalistic Driving Data Collection

Collecting large driving datasets is important for data-driven transportation research and studied in naturalistic driving [3]. Due to the standard implementation of a Controller Area Network (CAN) bus for a vehicle’s inter-module communication, many off-the-shelf devices can easily transform a vehicle into a rich data collection utility [2]. Vehicles with Adaptive Cruise Control (ACC) are an example of a feature resulting in emergent traffic behavior when scaled [4]. While these utilities were designed with particular data use cases, data may be publicly shared to benefit other researchers through online tools like CyVerse [1]. However, such data should only be shared when any private information is removed. This private information may exist as a set of GPS coordinates, since the start and end points of a trip may designate a driver’s place of residence or work. When considering larger continuously-collected data sets with a focus on naturalistic driving, many drivers are needed to make data collection feasible. Removal of private information becomes much more of a challenge since every driver may uniquely define their geographic privacy. This project aims to build upon the foundation of libpanda [2] by adding features of edge-based data privacy enforcement. In it’s current form, libpanda uses a GPS in conjunction with a CAN interface to record data. Libpanda feature s a set of startup and shutdown scripts to perform automatic data collection and upload. With additional support hardware on a Raspberry Pi, the Pi can maintain power on vehicle shutdown to automatically upload data before shutdown.

Bunting, Matt↗
DOE OSTI2025

A Roadmap for the Future of Systems Biology in Cancer Research

Cancer systems biology seeks to understand how cancer arises as a system of interconnected molecules, cells, and tissues, with the goal of understanding, predicting, and controlling the disease. In the last decade, the field has rapidly grown as advances in experimental, computational, and analytic technologies have improved our ability to capture and recapitulate the complexities of cancer at multiple scales. However, the field’s promise to understand how specific molecular changes give rise to altered cancer outcomes remains incompletely fulfilled. Fortunately, an opportunity exists to accelerate progress by better coordinating modeling and data-gathering efforts across the cancer systems biology community. This will create the foundation for building accurate, multiscale cancer models that can better predict and identify improved therapeutic interventions. Here, in this study, we outline some of the current challenges in cancer systems biology research, how they can be addressed, and actions that the community can take to accelerate progress in the field.

Modeling & Simulation↗
DOE OSTI2026

Sap Velocity Data for Urban Trees in Chicago, Illinois (2024-2025)

This dataset contains uncorrected sap velocity measurements using the heat ratio method (HRM) collected using ICT International SFM1x sensors at five urban sites in Chicago, Illinois, as part of the DOE CROCUS project. The data includes continuous monitoring of sap velocity from various tree species, including Maples (Acer spp.): Sugar Maple (Acer saccharum), Silver Maple (Acer saccharinum), and Red Maple (Acer rubrum); Oaks (Quercus spp.): Swamp White Oak (Quercus bicolor); American Elm (Ulmus americana); Honey Locust (Gleditsia triacanthos); Cottonwood (Populus deltoides); and Tree of Heaven (Ailanthus altissima) across Chicago State University (CSU), Northeastern Illinois University (NEIU), Northwestern University (NU), University of Illinois Chicago (UIC), and West Woodlawn "Blacks in Green" (BIG). These include both street trees and those in urban park locations. Measurements were collected at 15-20 minute intervals, depending on the sensor, and transmitted via Long Range Wide Area Network (LoRaWAN) protocols. The wireless data was collected by Sage Network (https://sagecontinuum.org/) nodes. The dataset includes sensor ID, Global Positioning System (GPS) coordinates, tree species (common and scientific names), tree identification number, diameter at breast height (DBH in cm), uncorrected sap velocity measurements (cm/hr) from both inner and outer probes, and Sage Node identifiers so the data can be mapped to related variables such as air quality and wind speed that were collected on the Sage nodes. All timestamps are in local Chicago time (CDT/CST). Quality control flags are provided using a 3-bit binary system indicating physical range violations (< -10 or > 60 cm/hr), step spikes (absolute difference > 36 cm/hr), and stuck sensor conditions (> 10 consecutive identical values). These are raw data, not corrected for wood anatomy or species-specific characteristics. Data is provided in comma separated (CSV) format. This dataset is part of a larger collection of CROCUS environmental monitoring data, including linked datasets from Air Quality Transmitter (AQT) sensors, Weather Transmitter (WXT) sensors, and Multi-Function Research LoRaWAN (MFR) Nodes. DOIs for the supporting data are provided as part of this data package.

Chicago↗
DOE OSTI2023

Topics and Considerations for Developing State Geothermal Regulations

The intent of this document is to provide guidance to states for developing geothermal regulations that would be inclusive of all geothermal technologies (e.g., conventional and non-conventional power production and direct-use applications) with applicability in all states. As part of this project, the NREL project team reviewed and catalogued existing state and federal geothermal regulations, compiled best practices from geothermal and other extractive industries, and established a Geothermal Regulatory Stakeholder Working Group (SWG) to advise and review the geothermal regulatory guidance. The SWG met approximately monthly over the course of one year to review and discuss specific topics as relevant to this geothermal regulatory guidance. This report is broken into five main sections, which were identified in coordination with the SWG as the main topics for inclusion. Within these sections, a list of considerations within each category were identified and, in some cases, relevant examples from existing state and federal geothermal regulations are included to further illustrate the proposed considerations. This report includes the following topics: geothermal resource definition; leasing process; exploration approval process; drilling/wellfield development approval process; and underground injection control process.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Two-point Correlation Function Studies for the Milky Way: Discovery of Spatial Clustering from Disk Excitations and Substructure

We introduce a two-particle correlation function (2PCF) for the Milky Way, constructed to probe spatial correlations in the orthogonal directions of the stellar disk in the Galactic cylindrical coordinates of R, ϕ, and z. We use this new tool to probe the structure and dynamics of the Galaxy using the carefully selected set of solar neighborhood stars (d ≲ 3 kpc) from Gaia Data Release 2 that we previously employed for studies of axial symmetry breaking in stellar number counts. We make additional, extensive tests, comparing to reference numerical simulations, to ensure our control over possibly confounding systematic effects. Supposing either axial or north–south symmetry, we divide this data set into two nominally symmetric sectors and construct the 2PCF, in the manner of the Landy–Szalay estimator, from the Gaia data. In so doing, working well away from the midplane region in which the spiral arms appear, we have discovered distinct symmetry-breaking patterns in the 2PCF in its orthogonal directions, thus establishing the existence of correlations in stellar number counts alone at subkiloparsec length scales for the very first time. In particular, we observe extensive wavelike structures of amplitude greatly in excess of what we would estimate if the system were in a steady state. We study the variations in these patterns across the Galactic disk, and with increasing ∣z∣, and we show how our results complement other observations of non-steady-state effects near the Sun, such as vertical asymmetries in stellar number counts and the Gaia snail.

79 ASTRONOMY AND ASTROPHYSICS↗