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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A predictive strain-gradient model with no undetermined constants or length scales

A general meso–scale (GM) crystal plasticity (CP) model was developed that accounts for lower-order (strain hardening) and higher-order (internal stress) effects of geometrically necessary dislocations (GNDs). It is predictive: no arbitrary parameters or length scales were invoked and no ad hoc numerical techniques were employed. It uses general stress field equations for GND content and a novel harmonization technique to enforce consistency of elastic long-range singular defect fields with applied elastic-plastic fields. The model facilitates implementation in commercial finite element programs without requiring special elements, special boundary conditions, or access to element shape functions. GM simulations confirmed, with improved accuracy, previously published predictions of the Hall-Petch effect, Bauschinger effect, and anelasticity. Previously unpredicted phenomena were also predicted: anelasticity and hysteresis for single Ta crystals and strain-hardening stagnation. The internal stresses (higher-order effect) dominate at large length scales, while at small length scales, the GND density hardening (lower-order effect) dominates. As a result, GM predicts that strain heterogeneity and consequent GND internal stresses are important factors in anelasticity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

What Can We Learn from US National Transmission Studies?

Multiple US regions have announced new electricity transmission plans, are actively revisiting the future role of transmission, and could benefit from findings from recent national-scale transmission studies. A review of seven national studies shows that significant transmission expansion is cost-optimal for serving new demand, integrating additional resources, and supporting grid reliability. A majority of the reviewed scenarios, which span a range of policy and technology assumptions, include at least a doubling of the transmission system by 2050. The national studies find substantial net system cost savings from transmission expansion and high benefit-cost ratios for transmission investments. The results are derived through multi-value, nationally coordinated, co-optimized, multi-scenario modeling, which is an approach that could yield lower-cost pathways compared to current industry planning practices.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Energy-water interdependencies across the three major United States electric grids: A multi-sectoral analysis

As water availability and timing of delivery fluctuates and the US electric grid sees rapid transformation and reconfiguration under decarbonization and resource adequacy strategies, there is a critical need for information and data that supports understanding the water-energy interdependency landscape. The United States currently lacks comprehensive data, informative visualizations, and analysis of energy-water interdependencies at scales necessary to support resource and operational decision-making. This article provides US electricity interconnection-level Sankey diagrams that show the relative reliance of water and energy across various economic sectors. A deeper analysis is additionally provided at the county level to illustrate trends and potential opportunities related to resiliency and efficiency in multi-sectoral water and energy flow distributions and intensities. We find that the electricity interconnections in the US vary dramatically in their water and energy interdependencies across applications and economic sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Nanotwin stability in alloyed copper under ambient and cryo-temperature dependent deformation states

Nanometer size grains, solid solution strengthening, low temperatures, and a high density of nanotwins can provide significant strengthening to a material. Nevertheless, under loading the microstructure may evolve altering the effect of grain size, twin density, etc. on this strengthening. In some cases, these effects can be coupled as in detwinning, which is a mechanism for cryogenic grain growth. Here, in this work, a series of copper nanotwinned columnar grains are solid solution alloyed with aluminum and subject to ambient and cryogenic (–196 °C) environments during mechanical indentation, with the influence of alloying on the detwinning evolution studied. Under indentation, at a lower aluminum solute content (2 at.%), the columnar grains bent corresponding to a loss of twins. At a higher aluminum solute content (8 at.%), the grains shear and retain the nanotwins. Atomistic-scale simulations reveal an increase in the incoherent twin boundary velocity with decreasing temperature, but this boundary velocity is reduced with increasing alloy solute content. The coupling of solid solution strengthening and nanotwin stabilization is then used to explain the microstructural stability as a function of indentation at different temperature conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Valuing wind as a distributed energy resource: A literature review

As more distributed energy resources are deployed on electric grid systems across the world, it is important to identify, characterize, and quantify the value elements of different types of distributed energy resources so that policymakers, developers, and utilities can make informed energy deployment decisions. This paper focuses on the value of wind energy as a distributed energy resource (i.e., “distributed wind”). Because of a lack of distributed wind-specific valuation studies, in this review we document the current state of distributed energy resource valuation, analyze a wide array of distributed energy resource valuation metastudies, and identify several value elements for which we recommend developing more robust and standardized calculation methodologies for their potential inclusion in distributed wind valuation. These value elements are ancillary services and locational, resilience, reliability, and resource diversity benefits. Furthermore, this work lays the foundation for a future comprehensive framework for distributed wind valuation studies.

17 WIND ENERGY↗
DOE OSTI2020

Insights into grain boundary energy structure-property relationships by examining computed [100] disorientation axis grain boundaries in Nickel

A study of 346 computed [100] disorientation axis grain boundaries provides insight into grain boundary energy structure-property relationships. The grain boundaries come from 6 coincidence site lattice misorientations at regularly spaced disorientation angles, and cover the full range of boundary plane orientations. The computed energy has clear trends in disorientation angle and boundary plane orientation. Here, the data are used to reexamine the 'special' attribute frequently applied to low Σ coincidence site lattice misorientations and low-angle boundaries and to assess the accuracy of a face-centered cubic grain boundary energy function.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Low-Temperature Direct Oxidation of Propane to Propylene Oxide Using Supported Subnanometer Cu Clusters

Propylene oxide, a key commodity of the chemical industry for a wide range of consumer products, is synthesized through sequential propane dehydrogenation and epoxidation reactions. However, the lack of a direct catalytic route from propane to propylene oxide reduces efficiency and represents a major challenge for catalysis science. Herein, we report the discovery of a highly active and selective catalyst, made of alumina-supported subnanometer copper clusters, which can directly convert propane to propylene oxide at temperatures as low as 150 °C. Moreover, at higher temperatures, on the same catalysts, the selectivity is switched to propylene. Accompanying theoretical calculations indicate that partially oxidized and/or hydroxylated clusters have low activation energies for both propane dehydrogenation and propylene epoxidation pathways, enabling direct conversion with very high selectivity for propylene oxide. The discovery of a low-temperature catalyst that can convert propane directly to propylene oxide provides an important opportunity for the development of energy-efficient and economic catalysts for this industrially critical process. Similarly, when operating at higher temperatures, these catalysts are posed as potent oxidative dehydrogenation catalysts.

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

Impact of Nanoparticle Size and Surface Chemistry on Peptoid Self-Assembly

Self-assembled organic nanomaterials can be generated by bottom-up assembly pathways where the structure is controlled by the organic sequence and altered using pH, temperature, and solvation. In contrast, self-assembled structures based on inorganic nanoparticles typically rely on physical packing and drying effects to achieve uniform superlattices. By combining these two chemistries to access inorganic–organic nanostructures, we aim to understand the key factors that govern the assembly pathway and structural outcomes in hybrid systems. In this work, we outline two assembly regimes between quantum dots (QDs) and reversibly binding peptoids. These regimes can be accessed by changing the solubility and size of the hybrid (peptoid-QD) monomer unit. The hybrid monomers are prepared via ligand exchange and assembled, and the resulting assemblies are studied using ex-situ transmission electron microscopy as a function of assembly time. In aqueous conditions, QDs were found to stabilize certain morphologies of peptoid intermediates and generate a final product consisting of multilayers of small peptoid sheets linked by QDs. The QDs were also seen to facilitate or inhibit assembly in organic solvents based on the relative hydrophobicity of the surface ligands, which ultimately dictated the solubility of the hybrid monomer unit. Increasing the size of the QDs led to large hybrid sheets with regions of highly ordered square-packed QDs. A second, smaller QD species can also be integrated to create binary hybrid lattices. Furthermore, these results create a set of design principles for controlling the structure and structural evolution of hybrid peptoid-QD assemblies and contribute to the predictive synthesis of complex hybrid matter.

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

A classical equation that accounts for observations of non-Arrhenius and cryogenic grain boundary migration

Observations of microstructural coarsening at cryogenic temperatures, as well as numerous simulations of grain boundary motion that show faster migration at low temperature than at high temperature, have been troubling because they do not follow the expected Arrhenius behavior. This work demonstrates that classical equations, that are not simplified, account for all these oddities and demonstrate that non-Arrhenius behavior can emerge from thermally activated processes. According to this classical model, this occurs when the intrinsic barrier energies of the processes become small, allowing activation at cryogenic temperatures. Additional thermal energy then allows the low energy process to proceed in reverse, so increasing temperature only serves to frustrate the forward motion. This classical form is shown to reconcile and describe a variety of diverse grain boundary migration observations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Feature engineering descriptors, transforms, and machine learning for grain boundaries and variable-sized atom clusters

Abstract Obtaining microscopic structure-property relationships for grain boundaries is challenging due to their complex atomic structures. Recent efforts use machine learning to derive these relationships, but the way the atomic grain boundary structure is represented can have a significant impact on the predictions. Key steps for property prediction common to grain boundaries and other variable-sized atom clustered structures include: (1) describing the atomic structure as a feature matrix, (2) transforming the variable-sized feature matrix to a fixed length common to all structures, and (3) applying a machine learning algorithm to predict properties from the transformed matrices. We examine how these steps and different combinations of engineered features impact the accuracy of grain boundary energy predictions using a database of over 7000 grain boundaries. Additionally, we assess how different engineered features support interpretability, offering insights into the physics of the structure-property relationships.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effect of a redox-mediating ligand shell on photocatalysis by CdS quantum dots

Semiconductor quantum dots (QDs) are efficient organic photoredox catalysts due to their high extinction coefficients and easily tunable band edge potentials. Despite the majority of the surface being covered by ligands, our understanding of the effect of the ligand shell on organic photocatalysis is limited to steric effects. We hypothesize that we can increase the activity of QD photocatalysts by designing a ligand shell with targeted electronic properties, namely, redox-mediating ligands. Herein, we functionalize our QDs with hole-mediating ferrocene (Fc) derivative ligands and perform a reaction where the slow step is hole transfer from QD to substrate. Surprisingly, we find that a hole-shuttling Fc inhibits catalysis, but confers much greater stability to the catalyst by preventing a build-up of destructive holes. We also find that dynamically bound Fc ligands can promote catalysis by surface exchange and creation of a more permeable ligand shell. Finally, we find that trapping the electron on a ligand dramatically increases the rate of reaction. Furthermore, these results have major implications for understanding the rate-limiting processes for charge transfer from QDs and the role of the ligand shell in modulating it.

Chemistry↗
DOE OSTI2022

Modeling the evolution of the US opioid crisis for national policy development

The opioid crisis remains one of the greatest public health challenges in the United States. The crisis is complex, with long delays and feedbacks between policy actions and their effects, which creates a risk of unintended consequences and complicates policy decision-making. We present SOURCE (Simulation of Opioid Use, Response, Consequences, and Effects), an operationally detailed national-level model of the opioid crisis, intended to enhance understanding of the crisis and guide policy decisions. Drawing on multiple data sources, SOURCE replicates how risks of opioid misuse initiation and overdose have evolved over time in response to behavioral and other changes and suggests how those risks may evolve in the future, providing a basis for projecting and analyzing potential policy impacts and solutions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Parallel simulation via SPPARKS of on-lattice kinetic and Metropolis Monte Carlo models for materials processing

Abstract SPPARKS is an open-source parallel simulation code for developing and running various kinds of on-lattice Monte Carlo models at the atomic or meso scales. It can be used to study the properties of solid-state materials as well as model their dynamic evolution during processing. The modular nature of the code allows new models and diagnostic computations to be added without modification to its core functionality, including its parallel algorithms. A variety of models for microstructural evolution (grain growth), solid-state diffusion, thin film deposition, and additive manufacturing (AM) processes are included in the code. SPPARKS can also be used to implement grid-based algorithms such as phase field or cellular automata models, to run either in tandem with a Monte Carlo method or independently. For very large systems such as AM applications, the Stitch I/O library is included, which enables only a small portion of a huge system to be resident in memory. In this paper we describe SPPARKS and its parallel algorithms and performance, explain how new Monte Carlo models can be added, and highlight a variety of applications which have been developed within the code.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Blockchain-Based Man-in-the-Middle (MITM) Attack Detection for Photovoltaic Systems

Cybersecurity of photovoltaic (PV) systems entails a much larger scope than just encryption and firewall of communications. For instance, integrity of data in transit between inverters and a cloud server can be compromised by authorized third-party, devices, and internal network within security perimeter (i.e., man-in-the-middle (MITM) attack). To address this challenge, this paper proposes a blockchain-based MITM attack detection method for a PV system. A breakthrough method includes screening network data, network intrusion detection, and hash comparison of in-transit data using distributed ledgers. Furthermore, the proposed method is implemented in Internet-of-Thing (IoT) security modules as clients of a blockchain network and validated by experiments.

blockchain↗
DOE OSTI2021

A Review of Cyber-Physical Security for Photovoltaic Systems

In this paper, the challenges and a future vision of the cyber-physical security of photovoltaic (PV) systems are discussed from a firmware, network, PV converter controls, and grid security perspective. The vulnerabilities of PV systems are investigated under a variety of cyber-attacks, ranging from data integrity attacks to software-based attacks. A success rate metric is designed to evaluate the impact and facilitate decision making. Model-based and data-driven methods for threat detection and mitigation are summarized. In addition, the blockchain technology that addresses cyber-attacks in software and cyber networks is described. Simulation and experimental results that show the impact of cyber-attacks at the converter (device) and grid (system) levels are presented. Finally, potential research opportunities are discussed for next-generation, cyber-secure power electronics systems. These opportunities include multi-scale controllability, self-/event-triggering control, artificial intelligence/machine learning, hot patching, and online security. As of today, this study will be one of the few comprehensive studies in this emerging and fast-growing area.

14 SOLAR ENERGY↗
DOE OSTI2023

Integrated Resource and System Plannning Based on Energy Costs and Emission Analysis for a Sustainable Future

Efficient integration of renewable energy sources (RES) - such as wind, solar, geothermal, tidal, and wave - into the electric power grids can help improve energy security and contribute toward a sustainable energy future. To date, however, electric power grids are critically dependent on conventional sources, such as fossil fuels. Given the increasing penetration of RES and dynamic loads, there is a need to thoroughly reanalyze the performance of power grids in terms of cost, efficiency, and energy security. This paper presents a comprehensive analysis in terms of energy costs and emissions estimates of dynamic power grids incorporating various power-generating sources.

distributed energy resources↗