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At least 433 records · Page 24

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DOE OSTI2022

Widespread transposon co-option in the Caenorhabditis germline regulatory network

The movement of selfish DNA elements can lead to widespread genomic alterations with potential to create novel functions. We show that transposon expansions in Caenorhabditis nematodes led to extensive rewiring of germline transcriptional regulation. We find that about one-third of Caenorhabditis elegans germline-specific promoters have been co-opted from two related miniature inverted repeat transposable elements (TEs), CERP2 and CELE2. These promoters are regulated by HIM-17, a THAP domain–containing transcription factor related to a transposase. Expansion of CERP2 occurred before radiation of the Caenorhabditis genus, as did fixation of mutations in HIM-17 through positive selection, whereas CELE2 expanded only in C. elegans. Through comparative analyses in Caenorhabditis briggsae, we find not only evolutionary conservation of most CERP2 co-opted promoters but also a substantial fraction that are species-specific. Our work reveals the emergence and evolutionary conservation of a novel transcriptional network driven by TE co-option with a major impact on regulatory evolution.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Exploration of Rayleigh-Taylor seeding mechanisms in laser- and pulsed-power-driven inertial fusion

The ubiquitous Rayleigh-Taylor instability (RTI) has been observed in fluids and plasmas in a wide range of parameter regimes from astrophysical to laboratory plasmas. In high-energy-density (HED) laboratory plasmas, such as laser-driven inertial confinement fusion (ICF) plasmas, the RTI can have a detrimental impact on achieving fusion ignition through the generation of hydrodynamic mix. Hence, an understanding of the seeding mechanisms that produce the RTI and identifying ways to mitigate hydrodynamic mix is of critical importance. Appropriately aligned magnetic fields have been known to stabilize short-wavelength RTI. A number of numerical and experimental studies have demonstrated the benefits of using imposed magnetic fields in laser-driven ICF to achieve higher ion temeratures, higher neutron yields, and a relaxation of the ignition criteria. This work addresses seeding mechanisms in laser-driven implosions to understand critical early-stage physics that ultimately leads to substantial growth of the RTI along with mechanisms for mitigation of this growth. Surface perturbations due to machining tolerances and single-feature seeds (for example due to fill tubes) can produce substantial RTI growth in the ignition-relevant high-convergence ratio targets for laser- driven ICF implosions. RTI growth from single-feature seeding in laser-based implosions has the potential to be mitigated through appropriately aligned externally applied magnetic fields and the goal of this work has been to quantify that numerically and experimentally. Resistive-magnetohydrodynamic (MHD) simu- lations are used to study the seeding and evolution of the RTI leveraging previous support from the DOE HEDLP program. Furthermore, experimental data has been obtained and applied towards code validation of unmagnetized and magnetized evolution of single-feature seeded RTI growth.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Ionomer Optimization for Water Uptake and Swelling in Anion Exchange Membrane Electrolyzer: Hydrogen Evolution Electrode

Green hydrogen produced through anion exchange membrane water electrolysis is a promising, low-cost chemical storage solution for intermittent renewable energy sources. Low-temperature electrolysis using anion exchange membranes (AEM) combines the benefits of established water electrolysis technologies based on alkaline electrolysis and proton exchange membrane electrolysis. The anion conductive ionomers (ACI) used in the AEM electrolyzer (AEMEL) electrodes has been investigated. The ACI serves two primary purposes: (i) facilitate hydroxide conduction between the catalyst and bulk electrolyte and (ii) bind the catalyst to the porous transport layer and membrane. High ion exchange capacity (IEC) ACIs are desired, however, high IEC can cause excessive water uptake (WU) and detrimental ACI swelling. Proper water management is a key factor in obtaining maximum performance in AEM-based devices. In this study, a series of poly(norbornene)-based ACIs were synthesized and deployed in hydrogen evolving AEMEL cathode electrodes. A balance between ionic conductivity, WU and ionomer swelling was achieved in the ACI by varying the IEC and degree of polymer cross-linking. It was found that higher IEC ACIs with light crosslinking are preferred in the HER electrode. Furthermore, such a configuration fine-tuned the WU and ionomer swelling to achieve optimum cell performance and reduce cell operating voltages.

08 HYDROGEN↗

DOE OSTI2024

Identification and time evolution of thionyl chloride (SOCl 2 ) radiolysis products

In this study, innovative solutions are needed to reduce the amount of high-level waste generated by used nuclear fuel recycling strategies to support the widespread adoption of sustainable nuclear fission energy technologies. To this end, a new sulfur chloride-based process has been developed to recycle zirconium alloy-based materials, which make up a significant fraction of high-level radioactive waste. To support the continued development of this process, we present new data on the potential reaction pathways over time of the products arising from the gamma and electron beam radiolysis of neat thionyl chloride (SOCl 2 ). Interrogation of the gamma irradiated liquid by Raman spectroscopy provided more conclusive identification of the SOCl 2 degradation products, specifically sulfur dichloride (SCl 2 ), molecular chlorine (Cl 2 ), sulfur dioxide (SO 2 ), and sulfuryl chloride (SO 2 Cl 2 ). In comparison, the high dose rate (~10 7 Gy s -1 ) electron beam irradiations formed significantly more degradation products. For both cobalt-60 gamma and electron beam irradiations, the observed degradation products were found to evolve as a function of time post-irradiation via the same reaction pathways, with indication of a solvent regeneration mechanism. These findings are fortuitous for process development, as such a mechanism would be beneficial for process longevity and cost effectiveness.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2025

Geothermal Collegiate Competition: Evolution and Impact

In 2010, the U.S. Department of Energy (DOE) announced the launch of its inaugural National Geothermal Student Competition. The competition was open to all colleges, universities, and other post-secondary institutions in the United States, and was labeled as the first-ever to address geothermal education. The GeoVision, published in 2019 by the Geothermal Technologies Office (GTO), stated that improving geothermal energy education and outreach is critical in reducing risks and costs of geothermal technology deployment. The key actions included improving public education and outreach about geothermal energy and providing resources intended to attract and inform a skilled geothermal workforce. Student competitions in particular have the ability to increase awareness of renewable energy fields by engaging multi-disciplinary students in compelling design challenges to prepare them for careers in renewable energy. GTO, in partnership with an administration team at the National Renewable Energy Laboratory (NREL), currently supports the Geothermal Collegiate Competition (GCC), with the main objective of advancing and cultivating collegiate student knowledge and career interest in geothermal energy. The administrating team works toward growing the number of students and collegiate institutions engaged, as well as diversifying the scope of the student design challenges. The main intentions of this publication are documenting the competition’s evolution, setting a baseline for future GCC impact analysis and serving as a guide to other students’ competition design committees looking for ideas to capture and increase the interest of students in collegiate competitions.

Geothermal Collegiate Competition↗

DOE OSTI2025

Editorial: Functionalization of porous materials for sustainable energy applications

Global energy demands are shifting toward a more sustainable future, with the goal of achieving carbon neutrality by 2050. Emerging technologies are driving this transition. The industry, academia, government, non-profit organizations, and the broader community are collaboratively working to reduce greenhouse gas (GHG) emissions and address climate change to ensure a sustainable future. According to the International Energy Agency, in 2022, the production, transportation, and processing of oil and gas resulted in 5.1 billion tons of CO 2 -equivalent emissions, representing nearly 15% of all energy-related GHG emissions. Moreover, the end-use of oil and gas accounted for an additional 40% of emissions. The IEA’s Net Zero Emissions by 2050 Scenario calls for immediate, collective action from the industry, transportation and other stakeholders to mitigate these emissions. In this effort, the development of energy materials will play a critical role in reducing emissions. Among these, porous materials offer an innovative solution, leveraging their high surface area, adjustable pore sizes, and chemical versatility to address these pressing challenges effectively. By carefully designing their nanostructures, the architecture and properties of these materials can be tailored for specific applications. Key factors such as chemical composition, particle size, pore distribution, and surface area optimization enhance the reactivity and energy conversion efficiency. Additionally, pre- and post-functionalization processes can introduce targeted chemical properties, further improving their performance. This Research Topic explores recent advancements in energy and materials science through four scholarly papers, showcasing innovative solutions for sustainable energy technologies while providing valuable insights into the unique properties and structure of porous materials (Figure 1). Li et al. present their work on highly defective NiFeV layered triple hydroxides, highlighting enhanced electrocatalytic activity and stability for oxygen evolution reactions (OER). Kovalskii et al. contribute a mini-review on hydrogen storage using hexagonal boron nitride (h-BN) and BN-based materials, offering an insightful overview of these promising materials. Chava et al. discuss their recent achievements in ceramic electrolytes used for improvement of performance of solid-state batteries. Lastly, Li et al. review the properties of porous materials with a focus on shrinkage behavior during the drying process, shedding light on key considerations for material design.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Facile Solvent-Free Synthesis of Manganese Nickel-Layered Double Hydroxide for Sustainable Water-Splitting Applications

The quest for efficient and sustainable water-splitting electrocatalysts has led to the development of a novel bifunctional material, manganese nickel-layered double hydroxide (MnNi-LDH), which demonstrates promising performance for both the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Although manganese-based materials are less explored than other transition metals, they offer significant potential owing to their widespread availability, affordability, and customizable electronic characteristics. MnNi-LDH exhibits a nanosheet morphology and a layered structure, which collectively provide numerous accessible active sites and facilitate efficient charge transfer and mass transport. Characterization using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy, and transmission electron microscopy reveals the structural and compositional properties of MnNi-LDH. The oxidation states of Mn and Ni, as determined by XPS, play a crucial role in improving the catalytic activity. Notably, MnNi-LDH demonstrates low overpotentials of 187 mV for OER and 225 mV for HER at 10 mA/cm 2 current density comparable to conventional catalysts. Long-term stability tests show minimal degradation in cell performance over 50 h, with a current density drop of only 0.6153% per hour for the OER and 0.37% per hour for the HER. Further, these findings highlight the potential of MnNi-LDH as a promising and environmentally friendly bifunctional electrocatalyst for water splitting, contributing to the advancement of renewable energy sources.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Advances in Machine and Deep Learning for Modeling and Real-time Detection of Multi-Messenger Sources

We live in momentous times. The science community is empowered with an arsenal of cosmic messengers to study the universe in unprecedented detail. Gravitational waves, electromagnetic waves, neutrinos, and cosmic rays cover a wide range of wavelengths and timescales. Combining and processing these datasets that vary in volume, speed, and dimensionality requires new modes of instrument coordination, funding, and international collaboration with a specialized human and technological infrastructure. In tandem with the advent of large-scale scientific facilities, the last decade has experienced an unprecedented transformation in computing and signal-processing algorithms. The combination of graphics processing units, deep learning, and the availability of open source, high-quality datasets has powered the rise of artificial intelligence. This digital revolution now powers a multibillion dollar industry, with far-reaching implications in technology and society. In this chapter, we describe pioneering efforts to adapt artificial intelligence algorithms to address computational grand challenges in multi-messenger astrophysics. We review the rapid evolution of these disruptive algorithms, from the first class of algorithms introduced in early 2017 to the sophisticated algorithms that now incorporate domain expertise in their architectural design and optimization schemes. We discuss the importance of scientific visualization and extreme-scale computing in reducing time-to-insight and obtaining new knowledge from the interplay between models and data.

Artificial Intelligence↗

DOE OSTI2022

Trait drift in microalgae and applications for strain improvement

Microalgae are increasingly used to generate a wide range of commercial products, and there is growing evidence that microalgae-based products can be produced sustainably. However, industrial production of microalgal biomass is not as developed as other biomanufacturing platform technologies. In addition, results of bench-scale research often fail to translate to large-scale or mass production systems. This disconnect may result from trait drift and evolution occurring, through time, in response to unique drivers in each environment, such as cultivation regimes, weather, and pests. Moreover, outdoor and indoor cultivation of microalgae has the potential to impose negative selection pressures, which makes the maintenance of desired traits a challenge. In this context, this review sheds the light on our current understanding of trait drift and evolution in microalgae. Here, we delineate the basics of phenotype plasticity and evolution, with a focus on how microalgae respond under various conditions. In addition, we review techniques that exploit phenotypic plasticity and evolution for strain improvement in view of industrial commercial applications, highlighting associated advantages and shortcomings. Finally, we suggest future research directions and recommendations to overcome unwanted trait drift and evolution in microalgae cultivation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

In-Operando Study of Shape Retention and Microstructure Development in a Hydrolyzing Sol–Gel Ink during 3D-Printing

3D printing of amorphous and crystalline ceramics is of paramount importance for the fabrication of a wide range of devices with applications across different technology fields. Printed ceramics are remarkably enabled by the sol-gel synthesis method in conjunction with continuous filament direct ink writing. During printing, multiple processes contribute to the evolution of inks including shape retention, chemical conversion, solidification, and microstructure formation. Traditionally, depending on the ink composition and printing environment, several mechanisms have been associated with the shape retention and solidification of 3D printed structures: gelation, rapid solvent evaporation, energy-driven phase transformation, and chemical-driven phase transformation. Understanding the fundamental differences between these mechanisms becomes key since they strongly influence the spatiotemporal evolution of the materials, as the out-of-equilibrium processes inherent to the extrusion, relaxation, and solidification of printed materials have significant effects on the materials properties. Herein, we investigate the shape retention mechanism and the hydrolysis-induced material conversion and microstructure formation during the 3D printing of a water reactive sol-gel ink that transforms into titanium dioxide-based ceramic. This study aims at identifying characteristic mechanisms associated with the material transformation, establishing connections between the microstructure development and the timescales associated with solidification under operando 3D-printing conditions. The investigation of this material's out-of-equilibrium pathways under processing conditions is enabled by time-resolved coherent X-ray scattering, providing simultaneous access to temporospatially resolved microstructural and dynamics information. Furthermore, we explore X-ray speckle tracking as a tool to resolve deformations of the microstructure in a printed filament associated with the deposition of consecutive filaments. Through this work, we aim at providing a fundamental understanding of the relationships behind these transformative processes in 3D printing and their timescales as the basis for achieving unprecedented control over printed materials microstructure.

36 MATERIALS SCIENCE↗

DOE OSTI2023

White Paper On Nuclear Structure Reactions and Astrophysics

In preparation for the 2023 NSAC Long Range Plan (LRP), the DNP Town Meeting on Nuclear Structure, Reactions, and Astrophysics was held at Argonne National Laboratory (ANL) on Nov 14-16, 2022. The town meeting brought together 578 members of the low-energy nuclear science community, including 216 in-person attendees and 362 remote participants coming from US national laboratories, a wide range of US universities and other research institutions and universities abroad. Participants met in five topic-oriented and seven cross-cutting and intersecting working groups to discuss progress since the 2015 LRP and identify compelling science opportunities and the resources needed to realize them. These considerations were used during the Town Meeting to determine a set of resolutions outlining the highest priorities for our subfield. The full text of the resolutions endorsed by unanimous consent by the low-energy nuclear science community at the Town Meeting is presented at the end of this executive summary. The reports from all working groups that met during the Town Meeting are included as Secs. 1 to 11 of this Whitepaper. The intellectual challenges for nuclear structure, reactions and astrophysics can be captured in the following questions: What is the nature of the nuclear force that binds protons and neutrons into stable nuclei and rare isotopes, and how do the rich phenomena of nuclear structure and reactions emerge? How do single-nucleon, cluster, and collective degrees of freedom coexist and evolve with increasing proton-neutron imbalance and excitation energies? What are the limits of nuclear existence, and what features arise near and beyond these limits? What are the astrophysical origins of the elements and how did the associated chemical evolution proceed? How do stars evolve, and what nuclear signatures do they leave behind? What is the nature of neutron stars and dense matter? How can the knowledge and technological progress provided by nuclear science best be used to benefit society?

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Adaptive Neuro Fuzzy Inference System for Cyber-Intrusion Detection in a Smart Grid

The evolution of the power grid has brought increasing deployment of advance metering infrastructure, penetration of intelligent electronic devices, and integration of physical power system components with information and communications technologies. With the fast-expanding connectivity, cyber vulnerabilities arise due to the use of internet-based communication systems. These systems are targets of cyber-intrusions which attempt to disturb the normal power system functions. Traditional intrusion detection algorithms have been developed without an explicit model of the cyber components. In this paper, an algorithm to detect false data injections in the power system is proposed considering both cyber and physical models of the power system. The algorithm is based on an Adaptive Neuro Fuzzy Inference System (ANFIS) which collects information from state variables of the cyber-physical system to meet the performance requirements of the grid. Simulations of the proposed approach using the IEEE 13-bus test system validate the effectiveness of this artificial intelligence-based algorithm.

Adaptive Neuro Fuzzy Inference System (ANFIS), cyb↗

DOE OSTI2023

Measuring Sustainability of PV in Energy Transition: Mass, Energy, and Circularity

Energy transition to a carbon-free energy system is crucial for global decarbonization and underpins circular economy (CE) goals. Photovoltaic (PV) technology is required for energy transition, but manufacturing and circular pathways can be material, energy, and carbon-intensive. Therefore, we need a prioritization of sustainability strategies for PV evolution. In this study, we compare sustainable PV module designs in terms of their entailed mass, energy, circularity, and carbon impacts to achieve Energy Transition. Results will support decision-makers through data-backed scenario and tradeoff analyses offering prioritization of sustainable PV module designs and CE pathways for meeting Energy Transition goals.

carbon↗

DOE OSTI2025

Stable Metal–Organic Electrocatalysts for Anion-Exchange Membrane Water Electrolyzers by Defect Engineering

Developing efficient and durable catalysts for the alkaline oxygen evolution reaction (OER) is vital to achieving practical anion-exchange membrane water electrolyzers (AEMWE) for green hydrogen production. In this work, we break the activity-stability trade-off of electrocatalysis by defect engineering of Ni-based metal-organic electrocatalysts (Ni-benzene dicarboxylate; Ni-BDC) through coordinating ferrocenecarboxylates (Fc) to the metal sites. Experimental results collectively reveal that the defect MOF (Ni-BDC:Fc_5:1) exhibits a high OER turnover frequency of 0.75 O 2 s -1 at 300 mV overpotential. Operando Raman spectroscopy and isotope-labelling electrochemical mass spectrometry measurements indicate the structure of Ni-BDC:Fc_5:1 is also more stable in service than that of pure Ni-BDC. The high activity and stability could be attributed to the moderate defects (i.e., unsaturated Ni sites) in the structure that not only increase the intrinsic activity and stability of the local active environment by inhibiting lattice oxygen exchange, but also electrochemically activates the bulk of the catalysts by creating a porous network that facilitates internal H 2 O/OH - conduction with enhanced electronic conduction. Accordingly, an AEMWE employing Ni-BDC:Fc_5:1 as the OER catalyst delivers an industrial-level current density of 1 A cm -2 at 1.73 V cell and can be steadily operated for more than 120 hours.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Operando X-Ray Diffraction During High Temperature Electrolysis

This work presents the design, development, and deployment of an operando X-ray diffraction (XRD) system for high-temperature electrolysis (HTE), enabling real-time characterization of solid oxide electrolysis cells (SOECs) under true operational conditions. The integration of an HTE test stand within a synchrotron radiation environment, mimicking the conditions of a laboratory setup, aims to enhance our understanding of the degradation processes affecting the performance and longevity of SOECs. Utilizing a custom furnace and a high precision motor stack assembly at the Stanford Synchrotron Radiation Lightsource (SSRL), the system revealed unparalleled insights into the structural evolution of SOEC components through various operational stages, including initial heat ramp, cell reduction, fuel ramp, and wet electrolysis. Initial results demonstrate the significant impact of the initial heating and cooling on secondary phase formation within the SOEC, highlighting the utility of operando XRD for developing more efficient and durable hydrogen production technologies.

08 HYDROGEN↗

DOE OSTI2024

Sensor response and radiation damage effects for 3D pixels in the ATLAS IBL Detector

Pixel sensors in 3D technology equip the outer ends of the staves of the Insertable B Layer (IBL), the innermost layer of the ATLAS Pixel Detector, which was installed before the start of LHC Run 2 in 2015. 3D pixel sensors are expected to exhibit more tolerance to radiation damage and are the technology of choice for the innermost layer in the ATLAS tracker upgrade for the HL-LHC programme. While the LHC has delivered an integrated luminosity of ≃ 235 fb -1 since the start of Run 2, the 3D sensors have received a non-ionising energy deposition corresponding to a fluence of ≃ 8.5 × 10 14 1 MeV neutron-equivalent cm -2 averaged over the sensor area. This paper presents results of measurements of the 3D pixel sensors' response during Run 2 and the first two years of Run 3, with predictions of its evolution until the end of Run 3 in 2025. Data are compared with radiation damage simulations, based on detailed maps of the electric field in the Si substrate, at various fluence levels and bias voltage values. These results illustrate the potential of 3D technology for pixel applications in high-radiation

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Modeling and Analysis of Wind Turbine Wake Vortex Evolution Due to Time-Constant Spatial Variations in Atmospheric Flow

Modern utility-scale wind turbines are evolving toward larger, lighter, and more flexible designs to meet the growing demand for renewable energy while minimizing logistical costs. However, these advancements in lightweight design result in heightened aeroelastic sensitivity, leading to complex interactions which affect the rotor’s capacity to withstand aerodynamic loading and the cascading effects that manifest in the wake’s vortex-structure evolution under variable atmospheric conditions. In this paper, we analyze the influence of stream-wise fluctuating atmospheric flow conditions on wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs’ Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex–wake interactions for a range of conditions with spatially variant atmospheric flow. CODEF solutions for turbine operation in wind conditions featuring only one parameter fluctuation are compared to wind conditions with several wind parameter variations in combination. By isolating individual inflow variations and comparing them to multi-parameter scenarios, we determine the contributions of each atmospheric factor to rotor dynamics, wake evolution, and downstream wind farm interactions. The purpose of this paper is to analyze the effects of spatial variations in atmospheric flow on the topological evolution of wind turbine vortex wakes, which constitutes a gap in the current understanding of wind turbine wake dynamics. The insights gained from this study are particularly valuable for the development of wind farm control strategies aimed at mitigating the adverse effects of wake interactions, enhancing energy capture, and improving the overall stability of wind farm operations. With these insights, we aim to contribute to the development of modeling and simulation tools to optimize utility-scale wind power plants operating in diverse atmospheric environments.

Farrell, Alayna (ORCID:000000023555720X)↗

DOE OSTI2020

Electrification Futures Study Flexible Load Profiles

This data set includes hourly profiles for flexible load developed for the Electrification Futures Study (EFS). The load profiles represent projected end-use electricity demand that is assumed to be flexible (i.e., can be shifted throughout a day) for various scenarios of flexibility (Base, Enhanced), electrification (Reference, Medium, High), and technology advancement (Slow, Moderate, Rapid), and were developed as inputs into the ReEDS model. The quantity of flexible load is estimated using assumptions on the level of flexibility and customer participation within each subsector modeled in the EFS. Detailed assumptions and modeling implementation will be documented in ongoing EFS analyses. Flexible load profiles are provided for a subset of years (2018, 2020, 2024, 2030, 2040, 2050) and are aggregated to the state and sector level. Total electricity load profiles can be found in a related EFS data set (https://dx.doi.org/10.7799/1593122). NOTE: Due to the file size, Mac users may experience issues decompressing the zip files using the Mac Archive Utility. In those cases, decompressing using the command line is recommended. - Mai, Trieu, Paige Jadun, Jeffrey Logan, Colin McMillan, Matteo Muratori, Daniel Steinberg, Laura Vimmerstedt, Ryan Jones, Benjamin Haley, and Brent Nelson. 2018. Electrification Futures Study: Scenarios of Electric Technology Adoption and Power Consumption for the United States. National Renewable Energy Laboratory. NREL/TP-6A20-71500. https://doi.org/10.2172/1459351. - Murphy, Caitlin, Trieu Mai, Yinong Sun, Paige Jadun, Matteo Muratori, Brent Nelson, Ryan Jones. Forthcoming. Electrification Futures Study: Scenarios of Power System Evolution and Infrastructure Development for the United States. National Renewable Energy Laboratory. - Sun, Yinong, Paige Jadun, Brent Nelson, Matteo Muratori, Caitlin Murphy, Jeffrey Logan, and Trieu Mai. Forthcoming. Electrification Futures Study: Methodological Approaches for Assessing Long-Term Power System Impacts of End-Use Electrification. National Renewable Energy Laboratory.

buildings↗