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DOE OSTI2020

Renewable Ammonia as An Energy Fuel for Ocean Exploration and Transportation

Renewable power generated from wave energy has faced technological and cost barriers to entry into utility-scale electricity markets. As an alternative, the production of chemical fuels, such as ammonia (NH3) which has high energy density (11.5 MJ/L) and facile storage properties, may open wave energy to new markets including ocean exploration and transportation. The electrochemical method has been studied to synthesize NH3 from air and water at ambient conditions. Based on some recent work on the electrochemical synthesis of NH3, it is possible to achieve an overall conversion efficiency of 10% from wave energy to NH3 through an electrochemical reaction between air and water. If all the recoverable wave energy in the United States (1170 TWh/yr) is used to produce renewable NH3 fuel replacing hydrocarbon fuels, this can help reduce over 300 million tons of CO2 emission every year. Several potential application scenarios at sea have been proposed for renewable NH3 fuel including production and storage for marine shipping and seasonal energy storage for Arctic exploration. Liquefied NH3 has much higher energy density, both gravimetric and volumetric, than a variety of batteries but the energy efficiency of NH3 is lower than modern batteries such as Li-ion. The Levelized cost of storing NH3 prepared using electric energy is less than $0.2/kWh and the storage time can exceed 10,000 hours which indicates that NH3 can be a promising energy storage solution to make use of abundant wave energy. However, there are some safety and environmental concerns involved in the usage of NH3 at sea. The challenges in the electrochemical catalyst for the NH3 synthesis and how molecular simulation may help to screen electrocatalyst with high efficiency and selectivity were also briefly discussed.

Liu, Jian↗

DOE OSTI2023

Exploring the impacts of unprecedented climate extremes on forest ecosystems: hypotheses to guide modeling and experimental studies

Abstract. Climatic extreme events are expected to occur more frequently in the future, increasing the likelihood of unprecedented climate extremes (UCEs) or record-breaking events. UCEs, such as extreme heatwaves and droughts, substantially affect ecosystem stability and carbon cycling by increasing plant mortality and delaying ecosystem recovery. Quantitative knowledge of such effects is limited due to the paucity of experiments focusing on extreme climatic events beyond the range of historical experience. Here, we present a road map of how dynamic vegetation demographic models (VDMs) can be used to investigate hypotheses surrounding ecosystem responses to one type of UCE: unprecedented droughts. As a result of nonlinear ecosystem responses to UCEs that are qualitatively different from responses to milder extremes, we consider both biomass loss and recovery rates over time by reporting a time-integrated carbon loss as a result of UCE, relative to the absence of drought. Additionally, we explore how unprecedented droughts in combination with increasing atmospheric CO2 and/or temperature may affect ecosystem stability and carbon cycling. We explored these questions using simulations of pre-drought and post-drought conditions at well-studied forest sites using well-tested models (ED2 and LPJ-GUESS). The severity and patterns of biomass losses differed substantially between models. For example, biomass loss could be sensitive to either drought duration or drought intensity depending on the model approach. This is due to the models having different, but also plausible, representations of processes and interactions, highlighting the complicated variability of UCE impacts that still need to be narrowed down in models. Elevated atmospheric CO2 concentrations (eCO2) alone did not completely buffer the ecosystems from carbon losses during UCEs in the majority of our simulations. Our findings highlight the consequences of differences in process formulations and uncertainties in models, most notably related to availability in plant carbohydrate storage and the diversity of plant hydraulic schemes, in projecting potential ecosystem responses to UCEs. We provide a summary of the current state and role of many model processes that give way to different underlying hypotheses of plant responses to UCEs, reflecting knowledge gaps which in future studies could be tested with targeted field experiments and an iterative modeling–experimental conceptual framework.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

National Geothermal Data System: Transforming the Discovery, Access, and Analytics of Data for Geothermal Exploration

Compendium of Papers from the 38th Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California February 11-13, 2013 The National Geothermal Data System (NGDS) is a distributed, interoperable network of data collected from state geological surveys across all fifty states and the nation’s leading academic geothermal centers. The system serves as a platform for sharing consistent, reliable, geothermal-relevant technical data with users of all types, while supplying tools relevant for their work. As aggregated data supports new scientific findings, this content-rich linked data ultimately broadens the pool of knowledge available to promote discovery and development of commercial-scale geothermal energy production. Most of the up-front risks associated with geothermal development stem from exploration and characterization of subsurface resources. Wider access to distributed data will, therefore, result in lower costs for geothermal development. NGDS is on track to become fully operational by 2014 and will provide a platform for custom applications for accessing geothermal relevant data in the U.S. and abroad. It is being built on the U.S. Geoscience Information Network (USGIN) data integration framework to promote interoperability across the Earth sciences community. The basic structure of the NGDS employs state-of-the art informatics to advance geothermal knowledge. The following four papers comprising this Open-File Report are a compendium of presentations, from the 38th Annual Workshop on Geothermal Reservoir Engineering, taking place February 11-13, 2013 at Stanford University, Stanford, California. “NGDS Geothermal Data Domain: Assessment of Geothermal Community Data Needs,” outlines the efforts of a set of nationwide data providers to supply data for the NGDS. In particular, data acquisition, delivery, and methodology are discussed. The paper addresses the various types of data and metadata required and why simple links to existing data are insufficient for promoting geothermal exploration. Authors of this paper are Arlene Anderson, US DOE Geothermal Technologies Office, David Blackwell, Southern Methodist University (SMU), Cathy Chickering (SMU), Toni Boyd, Oregon Institute of Technology’s GeoHeat Center, Roland Horne, Stanford University, Matthew MacKenzie, Uberity, Joe Moore, University of Utah, Duane Nickull, Uberity, Stephen Richard, Arizona Geological Survey, and Lisa Shevenell, University of Nevada, Reno. “NGDS User Centered Design: Meeting the Needs of the Geothermal Community,” discusses the user- centered design approach taken in the development of a user interface solution for the NGDS. The development process is research based, highly collaborative, and incorporates state-of-the-art practices to ensure a quality user interface for the widest and greatest utility. Authors of this paper are Harold Blackman, Boise State University, Suzanne Boyd, Anthro-Tech, Kim Patten, Arizona Geological Survey, and Sam Zheng, Siemens Corporate Research. “Fueling Innovation and Adoption by Sharing Data on the DOE Geothermal Data Repository Node on the National Geothermal Data System,” describes the motivation behind the development of the Geothermal Data Repository (GDR) and its role in the NGDS. This includes the benefits of using the GDR to share geothermal data of all types and DOE’s data submission process. Authors of this paper are Jon Weers, National Renewable Energy Laboratory and Arlene Anderson, US DOE Geothermal Technologies Office. Finally, “Developing the NGDS Adoption of CKAN for Domestic & International Data Deployment,” provides an overview of the “Node-In-A-Box” software package designed to provide data consumers with a highly functional interface to access the system, and to ease the burden on data providers who wish to publish data in the system. It is important to note that this software package constitutes a reference implementation and that the NGDS architecture is based on open standards, which means other server software can make resources available, and other client applications can utilize NGDS data. Authors of this paper are Ryan Clark, Arizona Geological Survey (AZGS), Christoph Kuhmuench, Siemens Corporate Research, and Stephen Richard, AZGS.

15 GEOTHERMAL ENERGY↗

DOE OSTI2014

Exploring growth kinetics of carbon nanotube arrays by in situ optical diagnostics and modeling

Simple kinetic models of carbon nanotube growth have been able to successfully link together many experimental parameters involved in the growth of carbon nanotubes for practical applications including the prediction of growth rates, terminal lengths, number of walls, activation energies, and their dependences on the growth environment. The implications of recent experiments utilizing in situ monitoring of carbon nanotube growth on our past kinetic model are first reviewed. Then, sub-second pulsed feedstock gas introduction is discussed to explore the nucleation and initial growth of carbon nanotubes in the context of the kinetic model. Moreover, kinetic effects in "pulsed CVD" - using repeated pulsed gas introduction to stop and restart nanotube growth - are explored to understand renucleation, the origin of alignment in nanotube arrays, and incremental growth. Time-resolved reflectivity of the surface is used to remotely understand the kinetics of nucleation and the coordinated growth of arrays. This approach demonstrates that continuous vertically aligned single wall carbon nanotubes can be grown incrementally by pulsed CVD, and that the first exposure of fresh catalyst to feedstock gas is critical to nanotubes site density required for coordinated growth. Aligned nanotube arrays (as short as 60 nm) are shown to nucleate and grow within single, sub-second gas pulses. The multiple-pulse growth experiments (> 100 pulses) show that a high fraction of nanotubes renucleate on subsequent gas pulses.

Puretzky, Alexander A↗

DOE OSTI2014

Operations of a Radioisotope-based Propulsion System Enabling CubeSat Exploration of the Outer Planets

Exploration to the outer planets is an ongoing endeavor but in the current economical environment, cost reduction is the forefront of all concern. The success of small satellites such as CubeSats launched to Near-Earth Orbit has lead to examine their potential use to achieve cheaper science for deep space applications. However, to achieve lower cost missions; hardware, launch and operations costs must be minimized. Additionally, as we push towards smaller exploration beds with relative limited power sources, allowing for adequate communication back to Earth is imperative. Researchers at the Center for Space Nuclear Research are developing the potential of utilizing an advanced, radioisotope-based system. This system will be capable of providing both the propulsion power needed to reach the destination and the additional requirements needed to maintain communication while at location. Presented here are a basic trajectory analysis, communication link budget and concept of operations of a dual-mode (thermal and electric) radioisotope-based propulsion system, for a proposed mission to Enceladus (Saturnian icy moon) using a 6U CubeSat payload. The radioisotope system being proposed will be the integration of three sub-systems working together to achieve the overall mission. At the core of the system, stored thermal energy from radioisotope decay is transferred to a passing propellant to achieve high thrust – useful for quick orbital maneuvering. An auxiliary closed-loop Brayton cycle can be operated in parallel to the thrusting mode to provide short bursts of high power for high data-rate communications back to Earth. Additionally, a thermal photovoltaic (TPV) energy conversion system will use radiation heat losses from the core. This in turn can provide the electrical energy needed to utilize the efficiency of ion propulsion to achieve quick interplanetary transit times. The intelligent operation to handle all functions of this system under optimized conditions adds to the complexity of the mission architecture.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2014

Exploration Drilling and Technology Demonstration At Fort Bliss

The Tularosa-Hueco basin in south-central New Mexico has long been known as an extensional area of high heat flow. Much of the basin is within the Fort Bliss military reservation, which is an exceptionally high value customer for power independent of the regional electric grid and for direct use energy in building climate control. A series of slim holes drilled in the 1990s established the existence of a thermal anomaly but not its practical value. This study began in 2009 with a demonstration of new exploration drilling technology. The subsequent phases reported here delivered a useful well, comparative exploration data sets and encouragement for further development. A production-size well, RMI56-5, was sited after extensive study of archival and newly collected data in 2010-2011. Most of 2012 was taken up with getting state and Federal authorities to agree on a lead agency for permitting purposes, getting a drilling permit and redesigning the drilling program to suit available equipment. In 2013 we drilled, logged and tested a 924 m well on the McGregor Range at Fort Bliss using a reverse circulation rig. Rig tests demonstrated commercial permeability and the well has a 7-inch slotted liner for use either in production or injection. An August 2013 survey of the completed well showed a temperature of 90 C with no reversal, the highest such temperature in the vicinity. The well’s proximity to demand suggests a potentially valuable resource for direct use heat and emergency power generation. The drilling produced cuttings of excellent size and quality. These were subjected to traditional analyses (thin sections, XRD) and to the QEMScan™ for comparison. QEMScan™ technology includes algorithms for determining such properties of rocks as density, mineralogy, heavy/light atoms, and porosity to be compared with direct measurements of the cuttings. In addition to a complete cuttings set, conventional and resistivity image logs were obtained in the open hole before the well was cased.

15 GEOTHERMAL ENERGY↗

DOE OSTI2015

EAGLE: 'EAGLE'Is an' Algorithmic Graph Library for Exploration

The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. Today there is no tools to conduct "graph mining" on RDF standard data sets. We address that need through implementation of popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, degree distribution, diversity degree, PageRank, etc.). We implement these algorithms as SPARQL queries, wrapped within Python scripts and call our software tool as EAGLE. In RDF style, EAGLE stands for "EAGLE 'Is an' algorithmic graph library for exploration. EAGLE is like 'MATLAB' for 'Linked Data.'

Source record↗

DOE OSTI2014

Plenario: An Open Data Discovery and Exploration Platform for Urban Science

The past decade has seen the widespread release of open data concerning city services, conditions, and activities by government bodies and public institutions of all sizes. Hundreds of open data portals now host thousands of datasets of many different types. These new data sources represent enormous po- tential for improved understanding of urban dynamics and processes—and, ultimately, for more livable, efficient, and prosperous communities. However, those who seek to realize this potential quickly discover that discovering and applying those data relevant to any particular question can be extraordinarily dif- ficult, due to decentralized storage, heterogeneous formats, and poor documentation. In this context, we introduce Plenario, a platform designed to automating time-consuming tasks associated with the discovery, exploration, and application of open city data—and, in so doing, reduce barriers to data use for researchers, policymakers, service providers, journalists, and members of the general public. Key innovations include a geospatial data warehouse that allows data from many sources to be registered into a common spatial and temporal frame; simple and intuitive interfaces that permit rapid discovery and exploration of data subsets pertaining to a particular area and time, regardless of type and source; easy export of such data subsets for further analysis; a user-configurable data ingest framework for automated importing and periodic updating of new datasets into the data warehouse; cloud hosting for elastic scaling and rapid creation of new Plenario instances; and an open source implementation to enable community contributions. We describe here the architecture and implementation of the Plenario platform, discuss lessons learned from its use by several communities, and outline plans for future work.

Catlett, Charlie↗

DOE OSTI2017

The Renewable Energy Data Explorer: Mapping Our Renewable Energy Future

The Renewable Energy (RE) Data Explorer, developed by the National Renewable Energy Laboratory, is an innovative web-based platform that allows users to visualize and analyze renewable energy potential. The RE Data Explorer informs prospecting, integrated planning, and policymaking to enable low emission development.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Collaborative Exploration of Scientific Datasets Using Immersive and Statistical Visualization: Preprint

We discuss the value of collaborative, immersive visualization for the exploration of scientific datasets and review techniques and tools that have been developed and deployed at the National Renewable Energy Laboratory (NREL). We believe that collaborative visualizations linking statistical interfaces and graphics on laptops and high-performance computing (HPC) with 3D visualizations on immersive displays (head-mounted displays and large-scale immersive environments) enable scientific workflows that further rapid exploration of large, high-dimensional datasets by teams of analysts. We present a framework, PlottyVR, that blends statistical tools, general-purpose programming environments, and simulation with 3D visualizations. To contextualize this framework, we propose a categorization and loose taxonomy of collaborative visualization and analysis techniques. Finally, we describe how scientists and engineers have adopted this framework to investigate large, complex datasets.

collaborative visualization↗

DOE OSTI2021

Exploring QCD Factorization at Moderate Energy Scales

Asymptotic freedom in QCD facilitates the use of partonic degrees of freedom over short distances, but physical processes are sensitive to a wide range of scales. Thus, it is necessary in QCD calculations to utilize a factorization scheme to separate a process into perturbative and non-perturbative factors. This separation relies on an assumption that one energy scale is infinitely larger than the other scales involved in the process. However, much experimental research in areas such as nucleon structure and quark-hadron duality occur at more moderate energy scales where that basic assumption may not be true but perturbative calculations should still be useful. Thus, an exploration of the limits of factorization at more moderate energy scales is needed. This dissertation examines various aspects of factorization at these energy scales first by applying the necessary approximations to a simple model where exact calculations are possible and so the effects of these approximations can be quantified. This is followed by examining areas where corrections are known to be needed. First is an exploration of target mass corrections (TMCs) in the case of deep inelastic scattering (DIS), including a discussion of what large corrections imply about the target structure. Second, is a general examination of PDFs and FFs at moderate scales. Third, I will discuss how this fits into the long-term effort to study the transition between small transverse momentum (generated non-perturbatively) and large transverse momentum (generated in the hard process)

Moffat, Eric↗

DOE OSTI2021

Collaborative Exploration of Scientific Datasets Using Immersive and Statistical Visualization

collaborative visualization↗

DOE OSTI2021

Enabling Long-range Exploration in Minimization of Multimodal Functions

We consider the problem of minimizing multi-modal loss functions with a large number of local optima. Since the local gradient points to the direction of the steepest slope in an infinitesimal neighborhood, an optimizer guided by the local gradient is often trapped in a local minimum. To address this issue, we develop a novel nonlocal gradient to skip small local minima by capturing major structures of the loss’s landscape in black-box optimization. The nonlocal gradient is defined by a directional Gaussian smoothing (DGS) approach. The key idea of DGS is to conducts 1D long-range exploration with a large smoothing radius along d orthogonal directions in Rd, each of which defines a nonlocal directional derivative as a 1D integral. Such long-range exploration enables the nonlocal gradient to skip small local minima. The d directional derivatives are then assembled to form the nonlocal gradient. We use the Gauss-Hermite quadrature rule to approximate the d 1D integrals to obtain an accurate estimator. The superior performance of our method is demonstrated in three sets of examples, including benchmark functions for global optimization, and two real-world scientific problems.

Zhang, Jiaxin↗

DOE OSTI2017

Geothermal Exploration of Mount Baker Hot Springs Through Ground-Based Magnetic and Gravity Surveys

The Washington State Division of Geology and Earth Resources (WDGER), together with the USGS, Altarock Energy Inc., Colorado College, Temple University, Innovate Geothermal Ltd., University of British Columbia, and Western Washington University(WWU), conducted phase two of a geothermal play fairway exploration at three plays (Mount Baker, Mount St. Helens seismic zone, and Wind River valley) along the Washington Cascade Range. The Mount Baker (MB) play is an ideal location for further investigation as a potential geothermal resource due to the presence of thermal features, young volcanic centers, existing geothermal leases, accessibility, and its proximity to existing transmission lines at the Baker Lake Dam. The goal of phase II exploration at all three plays is to collect geologic and geophysical data to help constrain spatial changes in subsurface lithology and structures that may be associated with the geothermal systems. Furthermore, this paper discusses the geothermal potential of the southeast flank of Mount Baker, WA by interpreting newly collected ground-based gravity and magnetic data. The Mount Baker play was surveyed from July-September, 2016 by the USGS, WDGER, and WWU. Results of a detailed magnetic and gravity surveys of the region surrounding the Baker hot springs, the primary surface expression of the hydrothermal system, are presented here. Gravity data were collected at 495 stations in the study area amounting to an area of roughly 150 square km. Approximately 93 km of line magnetometer data were collected within the study area, over a dozen magnetic susceptibility measurements were taken at 50 locations and about 50 hand samples were collected for density measurements. Preliminary data and modeling suggest pronounced magnetic anomalies trending NE/SW, generally in line with previously mapped lineaments identified in LiDAR. We present a series of preliminary two-dimensional forward models of the gravity and magnetic data as well as a 3D inversion model of magnetic susceptibility and interpret these models in terms of the structural controls influencing the Baker hot springs and hydrothermal system.

Geophysics↗

DOE OSTI2023

Exploring the Potential of Factory Installed Solar + Storage for Homebuilding

In recent years, an increasing number of grid disruptions due to intense weather events, natural disasters, and high peak loads resulted in increased interest in energy-resilient homes. Solar + storage (S+S) as an energy resiliency solution can provide continuity, onsite generation, and backup power during critical events. This project explored factory-installed solar plus storage (FISS) to overcome first cost and installation barriers and bring this resiliency solution to scale for single-family affordable and market-rate homebuyers. Guided by the principles of Lean manufacturing, the team explored how factories building high-performance zero energy modular homes can incorporate S+S into their existing construction system while improving quality and productivity and reducing the costs of the resilient energy system.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗

DOE OSTI2023

Exploration of Parameters That Affect High Field Q-Slope

The onset of high field Q-slope (HFQS) around 25 MV/m prevents cavities in electropolished (EP) condition from reaching high quality factors at high gradients due to the precipitation of niobium hydrides during cooldown. These hydrides are non-superconducting at 2 K, and contribute to losses such as Q disease and HFQS. We are interested in exploring the parameters that affect the behavior of HFQS. We study a high RRR cavity that received an 800 C by 3 hour bake and EP treatment to observe HFQS. First, we explore the effect of trapped magnetic flux. The cavity is tested after cooling slowly through Tc while applying various levels of ambient field. We observe the onset of the HFQS and correlate this behavior with the amount of trapped flux. Next, we investigate the effect of the size/concentration of hydrides. The cavity is tested after holding the temperature at 100 K for 12 hours during the cooldown to promote the growth of hydrides. We can correlate the behavior of the HF QS with the increased hydride concentration. Our results will help further the understanding of the mechanism of HFQS.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Beyond Human Vision: Exploring Materials with Machine Intelligence

Machine intelligence has the potential to revolutionize materials science, enabling autonomous synthesis, self-driving characterization, and accelerated modeling. However, despite the promise, successful implementation of these methods in day-to-day research remains a challenge. This talk will delve into the reasons behind this, exploring how truly intelligent experiments are hindered by opaque experiment control, a lack of domain-specific models, and human-centric design. Through a focus on the characterization of next-generation microelectronics and energy storage materials, I will share insights from both successful and failed attempts to implement machine intelligence. We will then explore the next steps necessary to unlock the full potential of machine intelligence in materials science, creating a future where intelligent systems work seamlessly alongside researchers to drive innovation and discovery.

artificial intelligence↗

DOE OSTI2024

Hot Springs and Geysers: Exploring Historical and Modern Impacts of Geothermal Energy Production on Associated Natural Surface Systems and Standardizing Management Practices

Surface thermal features, most notably hot springs and geysers are increasingly being recognized for their importance to ecosystems, indigenous cultures, and in some cases agriculture, recreation, and tourism. Geothermal project development poses a potential risk to these natural features but current regulatory requirements for assessing and managing these risks during exploration, permitting and monitoring are somewhat inconsistent and unpredictable across different geothermal fields. This has resulted in uncertainty and increases in exploration risk for geothermal energy developers that have led to costly project delays, cancellations, or hesitation to commit. Varying regulatory requirements may also influence public perception, fostering confusion, distrust and ultimately opposition to geothermal projects, further contributing to project delays or cancellations. At a time when there is an increasing urgency for reliable baseload clean energy, geothermal is a net-zero, renewable solution that additionally provides access to more equitable and environmentally just clean power. Continued integration of geothermal energy into the national energy roadmap can be facilitated through consistent and predictable permitting, providing regulators the framework they need, developers a clear path forward, and transparency that the public deserves. This project, currently in its beginning phases, seeks to address this important issue by providing a technical basis from which to build a preliminary protocol for assessing and managing potential impacts from new or existing geothermal energy projects to surface thermal features and their associated ecosystems. Development of this preliminary protocol will be informed by (1) a literature review of well-documented case studies in the western U.S. and New Zealand to understand the range of conditions that exemplify geothermal-surface thermal systems; (2) development of generic illustrative conceptual-numerical models to quantify, understand, and predict the first-order controls (e.g., pressure and permeability) on surface flows; and (3) additional independent and scientifically rigorous evaluations of geothermal-surface thermal system case studies from the Basin and Range Province that incorporate publicly available data as well as data provided by industry through data-sharing agreements. Learning from the successes of the process used to develop the Induced Seismicity Management Protocol (ISMP), we ultimately aim to use these initial efforts as a springboard for establishing a surface thermal feature management working group that will work collaboratively to finalize the protocol as well as co-create recommended best practices for implementation. We envision that the working group will primarily be composed of representatives from regulatory entities, government agencies, Tribes, academia, national laboratories, and industry, and will include early and regular engagement with community organizations and environmental groups. This will help ensure broad acceptance and implementation of the protocol, which will facilitate a more consistent, predictable, and standardized regulatory process, and help to ensure that geothermal energy continues to provide a reliable source of clean energy, and a pathway to achieving greater energy equity in the U.S.

Best Practices↗