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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Potential energy savings benefits and limitations of radiative cooling coatings for U.S. residential buildings

We report radiative coatings are a promising strategy to implement passive cooling that provides an eco-friendly pathway to achieve energy efficiency in buildings. This study investigates the benefits and limitations of implementing radiative coatings on the building envelope, particularly the roof, of residential buildings in the United States. The analysis compares the performance of an ideal radiative coating with broadband surface properties to a realistic radiative coating with diffuse and semitransparent properties. To enhance the net energy efficiency of buildings, we carried out a comprehensive parametric analysis comprising key radiation surface properties to maximize cooling energy savings while minimizing heating energy penalties. A countrywide assessment for 68 locations across the United States showed that net energy savings are a strong function of the climatic and atmospheric conditions. Broadly, southern locations showed high overall energy savings whereas northern locations exhibited high overall energy penalties. Locations in International Energy Conservation Code (IECC) climate zones 1A, 2A, and 2B showed a net annual energy savings above 5%, whereas locations in IECC climate zones 5B, 6B, and 7 showed a net annual energy penalty greater than 3%. The hot and dry climate of Phoenix, Arizona, showed the highest overall energy savings of 426 kWh (6.2%). Additionally, the mathematical correlation reveals that the net energy savings of a location is positive only when its average cooling degree days is greater than 5.5 or its average heating degree days is less than 10.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Uncertain quantum computing futures and potential energy and physical resource impacts at scale

Considerable attention has recently focused on the vast energy and water demands of supercomputing, namely large-scale data centers that underpin artificial intelligence (AI), one of the great disruptors of contemporary society. Looking ahead some years from now, quantum computing is poised to disrupt established computing paradigms once again. Scientists and engineers are now working intensely to bring this century-old dream of physicists to fruition. Yet, as quantum computers begin to be integrated with classical supercomputing architectures, the implications for energy and physical resource use also need to be understood, especially how they compare to today’s AI data centers. These impacts have not yet been quantified by the research community – a notable gap in the literature, even if commercial-scale deployment of Quantum-Accelerated Computing Infrastructure (QuACI) is not expected for a few more years. This study is the first to conduct such an assessment. Using publicly available information from academic sources and private industry, we characterize multiple configurations of superconducting qubit-based, fault-tolerant quantum computers (FTQC) that could plausibly be deployed at scale in the 2030s and into the 2040s. By parameterizing these FTQC systems at a process level, we conduct a prospective scenario analysis to quantify their energy and physical resource needs. While these estimates are uncertain, given the current state of quantum technologies and their unknown future trajectories, important insights can already be drawn. One key finding is that while the electricity needs for a fleet of FTQCs are within the bounds of previous modeling studies that have explored high electricity demand futures, the needs for certain physical resources, namely water and helium-3, could pose bottlenecks to QuACI scale-up.

Computing↗
DOE OSTI2023

Automated Reaction Kinetics of Gas-Phase Organic Species over Multiwell Potential Energy Surfaces

Automation of rate-coefficient calculations for gas-phase organic species became possible in recent years and has transformed how we explore these complicated systems computationally. Kinetics workflow tools bring rigor and speed and eliminate a large fraction of manual labor and related error sources. In this paper we give an overview of this quickly evolving field and illustrate, through five detailed examples, the capabilities of our own automated tool, KinBot. Here we bring examples from combustion and atmospheric chemistry of C-, H-, O-, and N-atom-containing species that are relevant to molecular weight growth and autoxidation processes. The examples shed light on the capabilities of automation and also highlight particular challenges associated with the various chemical systems that need to be addressed in future work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗