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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Building Performance Standards and Energy Code Alignment - Technical Brief

Building energy codes focus on building design, construction and renovation and have significantly increased building efficiency since the first national energy code was published in 1975. Most jurisdictions have energy codes based on ANSI/ASHRAE/IES Standard 90.1 (hereto referred to as Standard 90.1) and the International Energy Conservation Code (IECC). Compliance options available in these model energy codes include a prescriptive path, whole building performance paths – including IECC Total Building Performance (TBP), Standard 90.1 Energy Cost Budget (ECB) method and Performance Rating Method (PRM) – and system performance paths for envelope and heating, ventilation, and air-conditioning systems. Building performance standard (BPS) policies are an emerging policy tool used by jurisdictions to reduce the operational energy use or greenhouse gas (GHG) emissions of the existing commercial building stock. BPS policies vary widely between jurisdictions and are tailored to each location’s climate and energy goals. Intuitively, projects that met a recent edition of the energy code should comply with the BPS targets. However, some new buildings may struggle with meeting the BPS for the following reasons: 1. Energy codes focus on the design of the building and its projected ability to perform efficiently, while BPS compliance is dependent on the actual ongoing performance of the building, considering variables like occupancy, operation, and maintenance. 2. There are significant differences in the methodologies used to determine BPS compliance versus code compliance, including how each handles compliance metrics, handling of building amenities, and renewable energy generation. 3. The prescriptive compliance path in the energy code is based on performance of individual building components, as opposed to the performance compliance path which accounts for holistic building design strategies and interdependent building systems. This can result in a significant variability in post-occupancy performance for buildings built using the prescriptive path. Designs on the lower end of the permitted efficiency range may struggle with meeting the BPS.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

The interpenetration polymer network in a cement paste–waterborne epoxy system

The formation of the interpenetrating polymer network (IPN) structure within the cement-polymer system has been revealed by experiments from 2 dimensional to 3-dimensional scales. However, the microstructure design and performance prediction of IPN as a function of specific C-S-H/polymer components or ingredients' parameters e.g. water to cement ratios (w/c), polymer to cement ratios (p/c), monomer components, degree of polymerization (DP), etc. is by far not available. Here we developed a mesoscale model for IPN visualization based on the Flory-Huggins interaction theory which was applied to cement science for the first time. All the ingredients in the micro-structure were considered as soluble beads with rational sizes based on their properties obtained by molecular dynamic methods. The interaction parameters of each bead were then determined based on their element ratios and chemical backbones. The model was validated with the waterborne epoxy-cement material (WECM) in which a novel waterborne epoxy resin (WEP) was prepared and impregnated. The verification results on the 2D-3D scale show that the developed model predicts the WECM's IPN structures by rule and line concerning DP, w/c, and p/c in the mixture. The C-S-H beads were progressively scaled in size which alters the C-S-H texture to have completely different dissolution characteristics. Beads of diameter ~6 Å are more unstable and soluble which enable them to form a continuous phase in water or a composite structure with WEP. In contrast, beads with diameters larger than 10 Å have different properties with stronger nucleation effects. The results also suggest the impregnation content of WEP in cement-based material should be limited to 10% vol. to prevent the polymer IPN from decomposing into discrete clusters. The application of Flory-Huggins theory in cement-based composites demonstrates great potential in performance prediction and microstructure design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Rubik’s Cube Topology Based Particle Swarm Algorithm for Bilevel Building Energy Transaction

Following the rapid growth of distributed energy resources (e.g. renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as, reducing power loss, stabilizing the main power grid, etc. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. In addition, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush-Kuhn-Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubiks Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubiks Cube topology based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology based PSO and its scalability on larger scale applications.

Feng, Xiaochun↗
DOE OSTI2021

Evaluation of Structural Lattices for a Davis Gun Earth Penetrator Impact Experiment

The advanced materials team investigated the use of additively manufactured metallic lattice structures for mitigating impact response in a Davis gun earth penetrator impact experiment. High-fidelity finite element models were developed and validated with quasistatic experiments. These models were then used to simulate the response of such lattices when subjected to the acceleration loads expected in the Davis gun experiment. Results reveal how the impact mitigation performance of lattices can change drastically at a certain relative density. Based on these observations, an experiment deck was designed to probe the response of lattices with different relative densities during the Davis gun phase 2 shots. The expected performance of these lattices is predicted before testing based on simulation results. The results of the Davis gun phase 2 shots are expected to provide data which will be used to assess the predictive capability of the finite element simulations in such a complex impact environment.

36 MATERIALS SCIENCE↗
DOE OSTI2021

UiO-66 Metal–Organic Framework as an Anode for a Potassium-Ion Battery: Quantum Mechanical Analysis

The natural abundance of potassium in the earth’s crust is 1000 times higher than that of lithium, so energy technologies built on potassium are more sustainable. Potassium-ion batteries have attracted considerable attention because of their relatively low cost and high operating potential, but questions remain about the best anode material for such batteries. Here, in this paper, we report first-principles computations based on density functional theory to investigate the performance of the UiO-66 metal–organic framework as an anode material for potassium-ion batteries; the goal is to provide a fundamental understanding of metal–organic framework (MOF)-based electrodes to guide the design and development of high-performance potassium-ion batteries. Our study includes the stability and electronic properties of potassiated structures and the mechanisms of potassium intercalation and diffusion in the framework. The results indicate that UiO-66 has a maximum specific capacity of 644 mAh/g as the anode of a potassium-ion battery. During potassiation, we observe charge transfer from potassium to carbon or oxygen of UiO-66 near the intercalated K. During K diffusion, the K migrates along the UiO-66 framework with a maximal migration energy barrier of 0.377 eV in the optimal pathway, which is much lower than the barriers for Li and Na diffusion in UiO-66. The diffusion coefficient of K in the anode is several orders of magnitude larger than those of Li and Na. This favors potassium ions over lithium ions or sodium ions when UiO-66 is the anode.

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

High-throughput design of high-performance lightweight high-entropy alloys

Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further improves the accuracy of the thermodynamic database of the discovered alloy system. This study shows that integrating high-throughput screening, multiscale modeling, and experimental validation proves to be efficient and useful in accelerating the discovery of advanced precipitation-strengthened structural materials tuned by the high-entropy alloy concept.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Broadband coplanar-waveguide-based impedance-transformed Josephson parametric amplifier

Quantum-limited Josephson parametric amplifiers play a pivotal role in advancing the field of circuit quantum electrodynamics by enabling the fast and high-fidelity measurement of weak microwave signals. Therefore, it is necessary to develop robust parametric amplifiers with low noise, broad bandwidth, and reduced design complexity for microwave detection. However, current broadband parametric amplifiers either have degraded noise performance or rely on complex designs. Here, we present a device based on the broadband impedance-transformed Josephson parametric amplifier that integrates a hornlike coplanar waveguide transmission line, which significantly decreases the design and fabrication complexity while keeping comparable performance. The device shows an instantaneous bandwidth of 700 (200) MHz for 15 (20) dB gain with an average input saturation power of − 110 dBm and near quantum-limited added noise. The operating frequency can be tuned over 1.4 GHz using an external flux bias. We further demonstrate the negligible backaction from our device on a transmon qubit. The amplification performance and simplicity of our device promise its wide adaptation in quantum metrology, quantum communication, and quantum information processing. Published by the American Physical Society 2024

Qing, Bingcheng (ORCID:0000000345227017)↗
DOE OSTI2021

Lactone Backbone Density in Rigid Electron-Deficient Semiconducting Polymers Enabling High n-type Organic Thermoelectric Performance

We report three lactone-based rigid semiconducting polymers were designed to overcome major limitations in the development of n-type organic thermoelectrics, namely electrical conductivity and air stability. Experimental and theoretical investigations demonstrated that increasing the lactone group density by increasing the benzene content from 0% benzene (P-0), to 50% (P-50), and 75% (P-75) resulted in progressively larger electron affinities (up to 4.37 eV), suggesting a more favorable doping process, when employing (N-DMBI) as the dopant. Larger polaron delocalization was also evident, due to the more planarized conformation, which is proposed to lead to a lower hopping energy barrier. As a consequence, the electrical conductivity increased by three orders of magnitude, to achieve values of up to 12 S/cm and Power factors of 13.2 μWm -1 K -2 were thereby enabled. These findings present new insights into material design guidelines for the future development of air stable n-type organic thermoelectrics.

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

Chemometric optimisation of pressurised liquid extraction for the determination of alliin and S‐allyl‐cysteine in giant garlic ( Allium ampeloprasum L.) by liquid chromatography tandem mass spectrometry

Abstract Introduction Giant garlic is a functional food that contains different kinds of bioactive molecules with beneficial effects on chronic noncommunicable diseases like diabetes and cardiovascular conditions. Considering biosynthesis pathways, abundance, and biological activity, alliin and S‐allyl‐cysteine were used as chemical markers of organosulphur compounds present in giant garlic. Objective To establish a chemometric optimisation of pressurised liquid extraction for the determination of alliin and S‐allyl‐cysteine in giant garlic by liquid chromatography tandem mass spectrometry (LC–MS/MS). Methodology Samples were blanched (ca. 90°C for 10 min) to inactivate alliinase and γ‐glutamyl transpeptidase enzymes and then freeze‐dried. Chemometric optimisation was performed via response surface methodology based on central composite design (CCD). Organosulphur compound yields were determined applying a validated LC–MS/MS method in multiple reaction monitoring (MRM) mode using the following transitions: for alliin m/z 178 → 74 and for S‐allyl‐cysteine m/z 162 → 41. Results According to CCD results, under constant conditions of pressure (1500 psi) and time (20 min), the optimal conditions for pressurised liquid extraction of alliin and S‐allyl‐cysteine were 70.75 and 68.97% v/v of ethanol in extraction solvent and 76.45 and 98.88°C as extraction temperature, respectively. Multiple response optimisation for the simultaneous extraction of both organosulphur compounds was established via desirability function. Under these conditions, 2.70 ± 0.27 mg g −1 dry weight (DW) of alliin and 2.79 ± 0.22 mg g −1 DW of S‐allyl‐cysteine were extracted. Conclusions These results clearly demonstrated that pressurised liquid extraction is an efficient green technique to extract bioactive organosulphur compounds from giant garlic. Extraction yields were significantly ( p < 0.05) higher than those obtained with conventional ultra‐turrax extraction.

Peterssen‐Fonseca, Darlene↗
DOE OSTI2021

Understanding and design of spin-driven thermoelectrics

While progress in thermoelectric materials based on the engineering of electronic and phononic characteristics is reaching a plateau, the addition of the spin degree of freedom has the potential to open a new landscape for alternative thermoelectric materials. Here, we present the concepts, current understanding, and guidelines for designing spin-driven thermoelectrics. We show that the interplay between the spin and heat currents in entropy transport via charge carriers can offer a path to enhance the electronic thermopower. The classical antiferromagnetic semiconductor manganese telluride (MnTe) is chosen as the case study due to its significant spin-mediated thermoelectric properties. We show that, although the spin-disorder scattering reduces the carrier mobility in magnetic materials, spin entropy, magnon, and paramagnon carrier drags can dominate and significantly enhance the thermoelectric power factor, and hence zT. Finally, several guidelines are drawn based on the current understanding for designing high-performance spin-driven thermoelectric materials.

42 ENGINEERING↗
DOE OSTI2023

Modular Solar-to-Fuel Electrolysis at Low Cell Potentials Enabled by Glycerol Electrooxidation and a Bipolar Membrane Separator

Solar fuel generation through water electrolysis or electrochemical CO 2 reduction is thermodynamically limited when paired with the oxygen evolution reaction (OER). The glycerol electrooxidation reaction (GEOR) is an alternative anodic reaction with lower anodic electrochemical potential that utilizes a renewable coproduct produced during biodiesel synthesis. We show that GEOR on a Au-Pt-Bi ternary metal electrocatalyst in a model alkaline crude glycerol solution can provide significant cell potential reductions even when paired to reduction reactions in seawater and acidic catholytes via a bipolar membrane (BPM). We showed that the combination of GEOR electrooxidation and a BPM separator lowers the total cell potential by 1 V at an electrolysis current of 10.0 mA cm -2 versus to an anode performing OER when paired with hydrogen evolution and CO 2 reduction cathodes. The observed voltage reduction was steady for periods of up to 80 hours, with minimal glycerol crossover observed through the membrane. Furthermore, these results motivate new, high-performance cell designs for photoelectrochemical solar fuels integrated systems based on glycerol electrooxidation.

25 ENERGY STORAGE↗
DOE OSTI2024

Predicting Adhesion Energies of Metal Nanoparticles to Support Surfaces, Which Determines Metal Chemical Potential versus Particle Size and Thus Catalyst Performance

Improved catalysts and electrocatalysts composed of transition metal nanoparticles dispersed on high-area supports are essential for energy and environmental technologies. The chemical potential of the metal atoms in these supported nanoparticles is an important descriptor that correlates with both their catalytic activity and deactivation rate. This descriptor (μ M ) is predictably determined by the particle size and the adhesion energy per unit area at the metal/support interface (E adh ). We show here that the adhesion energies for different metals on a given support scale linearly with a simple property of the metal: for oxides, it is proportional to the metal oxophilicity, and for the carbon support, it increases linearly with metal carbophilicity (both divided by the area per metal atom). Furthermore, these relationships allow predicting E adh for other metal/support combinations, thus allowing estimation of μ M versus particle size and thereby better structure-based predictions of catalysts’ performance, which can aid in designing improved catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

LHC physics dataset for unsupervised New Physics detection at 40 MHz

In the particle detectors at the Large Hadron Collider, hundreds of millions of proton-proton collisions are produced every second. If one could store the whole data stream produced in these collisions, tens of terabytes of data would be written to disk every second. The general-purpose experiments ATLAS and CMS reduce this overwhelming data volume to a sustainable level, by deciding in real-time whether each collision event should be kept for further analysis or be discarded. We introduce a dataset of proton collision events that emulates a typical data stream collected by such a real-time processing system, pre-filtered by requiring the presence of at least one electron or muon. This dataset could be used to develop novel event selection strategies and assess their sensitivity to new phenomena. In particular, we intend to stimulate a community-based effort towards the design of novel algorithms for performing unsupervised new physics detection, customized to fit the bandwidth, latency and computational resource constraints of the real-time event selection system of a typical particle detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Robust deep learning–based protein sequence design using ProteinMPNN

Although deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here, we describe a deep learning–based protein sequence design method, ProteinMPNN, that has outstanding performance in both in silico and experimental tests. On native protein backbones, ProteinMPNN has a sequence recovery of 52.4% compared with 32.9% for Rosetta. The amino acid sequence at different positions can be coupled between single or multiple chains, enabling application to a wide range of current protein design challenges. We demonstrate the broad utility and high accuracy of ProteinMPNN using x-ray crystallography, cryo–electron microscopy, and functional studies by rescuing previously failed designs, which were made using Rosetta or AlphaFold, of protein monomers, cyclic homo-oligomers, tetrahedral nanoparticles, and target-binding proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

IER 296 Experiment- Thermal Feasibility Analysis [Slides]

This set of slides summarizes progress, highlights, and issues related to the LANL design engineering effort for the IER 296 critical experiment. The experiment configuration described in Section 5.1.1 of CED-1 IRSN Preliminary Design for Thermal/Epithermal Experiments with MOX FUEL (TEX-MOX) is re-examined in a finite element analysis model using design geometry utilized in the Chlorine Worth Study (CWS) Experiments. Preliminary results and design considerations are presented. Additional analysis has been performed based on comments from the collaborative virtual meeting on 12JAN2023. Specifically, the fuel cladding and gas gap have been included in the thermal analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

High-Temperature Heat Pump Model Documentation and Case Studies

High temperature heat pumps (HTHPs) have the potential to serve two valuable functions in the U.S. industry. First, by valorizing and elevating waste heat streams, HTHPs can improve industrial energy efficiency. Second, by electrifying process heat generation, HTHPs can replace combustion technologies with less carbon-intensive sources of energy and reduce industrial greenhouse gas emissions. In certain applications, the combination of increased efficiency, cost savings, and emissions reduction makes HTHPs a promising component of strategies for industrial electrification and clean energy transition. Researchers at NREL have developed a HTHP model. This model has both a physics-based performance estimation component and an economic evaluation component designed to demonstrate the potential economic competitiveness of HTHPs. This document has three main sections. First, an overview of HTHPs is provided as a literature review of relevant information to provide the reader with state-of-the-art information. Second, a description of the HTHP model is provided along with detailed instructions about how to use the model. Third, case studies are provided to showcase the deployment of the HTHP model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Tough Errors are no Match (TEAM): Optimizing the Quantum Compiler for Noise Resilience

This project builds toward a comprehensive error-mitigating toolkit that makes quantum programming more robust and adaptive to the noisy, resource-limited nature of today’s quantum hardware. To that end, it integrates established error-mitigation methods — such as zero-noise extrapolation and dynamical decoupling — directly into compiler infrastructures. These techniques will be packaged as modules that can automatically adjust and combine based on performance analysis, enabling compilers to explore large design spaces and produce optimized, low-noise quantum programs with minimal manual intervention. In parallel, this project also explores new approaches to analog quantum programming or quantum simulation, and has developed the programming language SimuQ which treats quantum Hamiltonian evolution as the central object.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Q-VR: System-Level Design for Future Mobile Collaborative Virtual Reality

High Quality Mobile Virtual Reality (VR) is what the incoming graphics technology era demands: users around the world, regardless of their hardware and network conditions, can all enjoy the immersive virtual experience. However, the state-of-the-art software-based mobile VR designs cannot fully satisfy the realtime performance requirements due to the highly interactive nature of user's actions and complex environmental constraints during VR execution. Inspired by the unique human visual system effects and the strong correlation between VR motion features and realtime hardware-level information, we propose Q-VR, a novel dynamic collaborative rendering solution via software-hardware co-design for enabling future low-latency high-quality mobile VR. At software-level, Q-VR provides flexible high-level tuning interface to reduce network latency while maintaining user perception. At hardware-level, Q-VR accommodates a wide spectrum of hardware and network conditions across users by effectively leveraging the computing capability of the increasingly powerful VR hardware. Extensive evaluation on real-world games demonstrates that Q-VR can achieve an average end-to-end performance speedup of 3.4x (up to 6.7x) over the traditional local rendering design in commercial VR devices, and a 4.1x frame rate improvement over the state-of-the-art static collaborative rendering.

Xie, Chenhao↗