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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Single crystal purification reduces trace impurities in halide perovskite precursors, alters perovskite thin film performance, and improves phase stability

Impurities present in commercially available halide perovskite precursors are known to affect photovoltaic performance. Here, we employ bulk single crystal growth of FAPbI 3 using solvent orthogonality induced crystallization (SONIC) to remove a broad set of extrinsic impurities from commercially available halide perovskite precursors, as verified by detailed chemical analysis. Following SONIC purification, FAPbI 3 films made from PbI 2 of originally low purity (99%) and high purity (99.99%) show improved phase purity and stability under light and heat relative to films made from raw precursors or precursors purified via retrograde powder crystallization (RPC) in 2-methoxyethanol, a method commonly utilized in recent reports of the highest-efficiency perovskite solar cells. In conclusion, single-crystal purification of precursors improves film stability under operational stressors, and the large enhancements in material purity provide a cleaner slate for improved isolation of compositional and additive effects on perovskite phase stability.

14 SOLAR ENERGY↗
DOE OSTI2015

Structure and spectroscopic properties of neutral and cationic tetratomic [C,H,N,Zn] isomers: A theoretical study

The structure and spectroscopic parameters of the most relevant [C,H,N,Zn] isomers have been studied employing high-level quantum chemical methods. For each isomer, we provide predictions for their molecular structure, thermodynamic stabilities as well as vibrational and rotational spectroscopic parameters which could eventually help in their experimental detection. In addition, we have carried out a detailed study of the bonding situations by means of a topological analysis of the electron density in the framework of the Bader’s quantum theory of atoms in molecules. The analysis of the relative stabilities and spectroscopic parameters suggests two linear isomers of the neutral [C,H,N,Zn] composition, namely, cyanidehydridezinc HZnCN ({sup 1}Σ) and hydrideisocyanidezinc HZnNC ({sup 1}Σ), as possible candidates for experimental detections. For the cationic [C,H,N,Zn]{sup +} composition, the most stable isomers are the ion-molecule complexes arising from the direct interaction of the zinc cation with either the nitrogen or carbon atom of either hydrogen cyanide or hydrogen isocyanide, namely, HCNZn{sup +} ({sup 2}Σ) and HCNZn{sup +} ({sup 2}Σ)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Production of micron-sized polymer particles for additive manufacturing by melt emulsification

Melt emulsification is an advanced top-down approach that permits to produce spherical particles and thus widens the availability of polymer feed materials for additive manufacturing. In the process the polymer is molten in a continuous phase and droplet breakup is realized in a rotor-stator-device. The stabilization of the newly formed surfaces is quite challenging. Therefore, a new method to identify an appropriate emulsifier by measuring the interfacial tension between the polymer and continuous phase using a high pressure / high temperature cell is presented. The obtained powders are characterized by scanning electron microscopy (SEM) and by a Zimmermann tensile strength tester to determine the powder flowability. The processability of the polymer powders for additive manufacturing is investigated and demonstrated by building single layers by laser beam melting.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Electron-field instability: Excitation of electron plasma waves by an electric field

Electric fields are commonplace in plasmas and affect transport by driving currents and, in some cases, instabilities. The necessary condition for instability in collisionless plasmas is commonly understood to be described by the Penrose criterion, which quantifies a sufficient relative drift between different populations of particles that must be present for wave amplification via inverse Landau damping. For example, electric fields generate drifts between electrons and ions that can excite the ion-acoustic instability. Here, we use particle-in-cell simulations and linear stability analysis to show that the electric field can drive a fundamentally different type of kinetic instability, named the electron-field instability. This instability excites electron plasma waves with wavelengths ≳30λ De , has a growth rate that is proportional to the electric field strength, and does not require a relative drift between electrons and ions. The Penrose criterion does not apply when accounting for the electric field. Furthermore, the large value of the observed frequency, near the electron plasma frequency, further distinguishes it from the standard ion-acoustic instability, which oscillates near the ion plasma frequency. The ubiquity of macroscopic electric fields in quasineutral plasmas suggests that this instability is possible in a host of systems, including low-temperature and space plasmas. In fact, damping from neutral collisions in such systems is often not enough to completely damp the instability, adding to the robustness of the instability across plasma conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

High pressure melt line of nickel using a generalized embedded atomic method potential

As the second most abundant metal in the Earth's core, nickel plays an important role in determining the structure and temperature of the Earth's core. Yet, the melt line of Ni at pressures corresponding to the Earth's core has not been explored in the literature. Many previous experimental and simulation efforts have reported the melting point of Ni at pressures below 100 GPa, but there exist large discrepancies, most of which have persisted due to various experimental and simulation bottlenecks in handling extreme pressure and temperature conditions. We adopted the generalized embedded atom method, which overcomes the limitations of existing interatomic potentials, to probe phase stability and phase boundaries of Ni at pressures between 50 and 500 GPa. Further, the potential was validated by comparing the cold curves, phonon dispersion curves, and enthalpies of fusion with ab initio density functional theory calculations. Our analysis shows that face centered cubic (FCC) is stable, and the hexagonal close packed (HCP) and body centered cubic (BCC) phases are metastable close to the melt line. Melting temperatures at different pressures were obtained from two-phase co-existence simulations and take the following functional form: $T$ m = $1969.23+19.15P-0.012P$ 2 . In contrast to iron, differences between the melting points of the stable and metastable phases of Ni are less than 250 K at 300 GPa, and the difference in melting points of the metastable BCC and HCP phases changes sign at 500 GPa, which implies that the phase transition mechanisms during solidification can be very complex.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A high-throughput and data-driven computational framework for novel quantum materials

Two-dimensional layered materials, such as transition metal dichalcogenides (TMDs), possess an intrinsic van der Waals gap at the layer interface, allowing for remarkable tunability of the optoelectronic features via external intercalation of foreign guests such as atoms, ions, or molecules. Herein, we introduce a high-throughput, data-driven computational framework for the design of novel quantum materials derived from intercalating planar conjugated organic molecules into bilayer transition metal dichalcogenides and dioxides. By combining first-principles methods, material informatics, and machine learning, we characterize the energetic and mechanical stability of this new class of materials and identify the fifty (50) most stable hybrid materials from a vast configurational space comprising ∼105 materials, employing intercalation energy as the screening criterion.

Kastuar, Srihari M. (ORCID:0000000279001561)↗
DOE OSTI2020

Algorithm-Based Fault Tolerance for Convolutional Neural Networks

Convolutional neural networks (CNNs) are becoming more and more important for solving challenging and critical problems in many fields. CNN inference applications have been deployed in safety-critical systems, which may suffer from soft errors caused by high-energy particles, high temperature, or abnormal voltage. Of critical importance is ensuring the stability of the CNN inference process against soft errors. Traditional fault tolerance methods are not suitable for CNN inference because error-correcting code is unable to protect computational components, instruction duplication techniques incur high overhead, and existing algorithm-based fault tolerance (ABFT) techniques cannot protect all convolution implementations. In this paper, we focus on how to protect the CNN inference process against soft errors as efficiently as possible, with the following three contributions. (1) We propose several systematic ABFT schemes based on checksum techniques and analyze their fault protection ability and runtime thoroughly. Unlike traditional ABFT based on matrix-matrix multiplication, our schemes support any convolution implementations. (2) We design a novel workflow integrating all the proposed schemes to obtain a high detection/correction ability with limited total runtime overhead. (3) We perform our evaluation using ImageNet with well-known CNN models including AlexNet, VGG-19, ResNet-18, and YOLOv2. Here, experimental results demonstrate that our implementation can handle soft errors with very limited runtime overhead (4%~8% in both error-free and error-injected situations).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Incorporating Elevation in Traffic-Vehicle CO-Simulation: Issues, Impacts, and Solutions

Traffic-vehicle co-simulation couples microscopic traffic simulation with full-body vehicle dynamics to assess system-level impacts on mobility, energy, and safety with greater realism. Incorporating elevation is critical for accurately modeling vehicle behavior and energy use, especially for gradient-sensitive vehicles such as electric and heavy-duty trucks. However, raw elevation data often contain noise, discontinuities, and inconsistencies. While such issues may be negligible in traditional traffic simulations, they significantly affect traffic-vehicle co-simulations where vehicle dynamics are sensitive to road grade variations. This paper investigates the impact of unprocessed elevation data on vehicle behavior and energy consumption using a 42-mile simulation along Interstate 81. We propose an elevation processing workflow that can mitigate the effects stem from elevation data issues, improving the realism and stability of traffic-vehicle co-simulation. Results show that the method effectively removes noise and abrupt elevation transitions while preserving roadway geometry.

Xu, Guanhao [ORNL] (ORCID:0000000214326357)↗
DOE OSTI2022

A scalable solid-state nanoporous network with atomic-level interaction design for carbon dioxide capture

Carbon capture and sequestration reduces carbon dioxide emissions and is critical in accomplishing carbon neutrality targets. Here, we demonstrate new sustainable, solid-state, polyamine-appended, cyanuric acid–stabilized melamine nanoporous networks (MNNs) via dynamic combinatorial chemistry (DCC) at the kilogram scale toward effective and high-capacity carbon dioxide capture. Polyamine-appended MNNs reaction mechanisms with carbon dioxide were elucidated with double-level DCC where two-dimensional heteronuclear chemical shift correlation nuclear magnetic resonance spectroscopy was performed to demonstrate the interatomic interactions. We distinguished ammonium carbamate pairs and a mix of ammonium carbamate and carbamic acid during carbon dioxide chemisorption. The coordination of polyamine and cyanuric acid modification endows MNNs with high adsorption capacity (1.82 millimoles per gram at 1 bar), fast adsorption time (less than 1 minute), low price, and extraordinary stability to cycling by flue gas. This work creates a general industrialization method toward carbon dioxide capture via DCC atomic-level design strategies.

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

FCET Solid Oxide Fuel Cell Testing and Development: CRADA 526 [Abstract only]

The purpose of the proposed project is for PNNL to test the performance of prototype solid oxide fuel cells (SOFCs) created by FCET. Such testing will provide FCET with independent performance data that can be communicated to potential clients and/or investors. Additionally, PNNL will collaborate with FCET on design changes to improve fuel cell performance. Intellectual property developed in this way will benefit FCET with improved products to market, and PNNL through royalty revenue. The key technology held by FCET is a process to deposit extremely thin layers of oxide materials, from 10-50 nm in thickness. The range of possible materials that can be deposited with their method is broad, but this project will focus on the yttria-stabilized zirconia (YSZ) electrolytes for SOFCs. Thin, gas tight YSZ membranes have been a long-sought target in SOFC research. The thinner the YSZ, the lower the cell resistance, and the higher performance of the cell (or the lower the operating temperature). 10-50 nm would be a major step change in YSZ thickness from the state of the art. PNNL can team with FCET on future R&D projects and push this technology forward to improve energy efficiency and reduce carbon emissions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2017

Aqueous lithium air batteries

Aqueous Li/Air secondary battery cells are configurable to achieve high energy density and prolonged cycle life. The cells include a protected a lithium metal or alloy anode and an aqueous catholyte in a cathode compartment. The aqueous catholyte comprises an evaporative-loss resistant and/or polyprotic active compound or active agent that partakes in the discharge reaction and effectuates cathode capacity for discharge in the acidic region. This leads to improved performance including one or more of increased specific energy, improved stability on open circuit, and prolonged cycle life, as well as various methods, including a method of operating an aqueous Li/Air cell to simultaneously achieve improved energy density and prolonged cycle life.

25 ENERGY STORAGE↗
DOE OSTI2022

Dynamic Phasor Modeling of Three Phase Voltage Source Inverters

With the increase in the development and implementation of distributed energy resources, application of parallel connected inverters is increasing and as a result having accurate modeling and simulation tools that can help in the design, analysis and stability assessment of the grid is of great importance. Development of fundamental methods that can achieve accurate, reliable, and computationally efficient results can be very beneficial. Application of Dynamic phasor (DP) modeling method has been limited to study of limited harmonics and small combination of interconnected converters due to the complexity associated with developing models that describe larger systems. In this paper, application of DP modeling method is expanded to model any number of parallel connected three phase voltage source inverter (VSI) with inclusion of a wider harmonic content including fundamental, subharmonics, inter-harmonics, switching frequency and their sidebands. Results achieved from this modeling method is compared with conventional average model as well as detailed switching model and the effect of inclusion of wider harmonic content on accuracy of DP modeling method is demonstrated.

Xue, Yaosuo↗
DOE OSTI2017

Geo-polymer Solidification of Intermediate Level Waste - 17078

To reduce the amount of hydrogen generated due to water radiolysis in stored intermediate-level waste, geo-polymer solidification, followed by drying, was studied. From the viewpoints of high thermal stability and low processing cost, geo-polymer solidification is an excellent method for conditioning intermediate level waste. In this study, in order to determine if radioactive waste could be treated using geo-polymer solidification, tests were conducted by using a simulated slurry generated from contaminated water treatment. The uniaxial compressive strength of the geo-polymer solidified waste containing 50 wt.% of the slurry was more than 10 MPa. To reduce the amount of hydrogen generated, the geo-polymer-solidified waste was dehydrated, and the water content of the remaining solid was less than 1 wt.%. Moreover, the value of the uniaxial compressive strength of dehydrated geo-polymer-solidified waste was similar to that of the untreated one. The volume reduction rate of the slurry solidification was obtained at the applicability limit. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

A Comparison of Machine Learning Methods for Frequency Nadir Estimation in Power Systems: Preprint

An increasing penetration level of inverter-based renewable energy resources changes the inertia of power systems, posing challenges for maintaining the desired system frequency stability. An accurate frequency nadir estimation is crucial for power system operators to prepare preventive actions against large frequency excursions. In this paper, five machine learning methods - linear regression, gradient boosting, support vector regression, an artificial neural network, and XGBoost - are applied to two different sets of preprocess data for the prediction of the frequency nadir in the Western Electricity Coordinating Council 240-bus system with high renewable penetration levels. The training and testing data sets are collected by extensive generation scheduling simulations on the Multi-timescale Integrated Dynamic and Scheduling (MIDAS) toolbox. Numerical results show that all five machine learning methods can achieve high performance accuracy for power system nadir frequency estimation. Among them, the gradient boosting and the XGBoost are clear winners by providing the best prediction accuracy.

data driven↗
DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗
DOE OSTI2016

Damage-plasticity model of the host rock in a nuclear waste repository

The paper describes damage-plasticity model for the modelling of the host rock environment of a nuclear waste repository. Radioactive Waste Repository Authority in Czech Republic assumes the repository to be in a granite rock mass which exhibit anisotropic behaviour where the strength in tension is lower than in compression. In order to describe this phenomenon, the damage-plasticity model is formulated with the help of the Drucker-Prager yield criterion which can be set to capture the compression behaviour while the tensile stress states is described with the help of scalar isotropic damage model. The concept of damage-plasticity model was implemented in the SIFEL finite element code and consequently, the code was used for the simulation of the Äspö Pillar Stability Experiment (APSE) which was performed in order to determine yielding strength under various conditions in similar granite rocks as in Czech Republic. The results from the performed analysis are presented and discussed in the paper.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

A benchmark photoelectron spectroscopic and theoretical study of the electronic stability of [B12H12]2-

We report a joint benchmark study on the electronic stability of closo-dodecaborate [B12H12]2- employing negative ion photoelectron spectroscopy and high level electronic structure methods. The photoelectron spectra of [B12H12]2-, measured at 266, 193 and 157 nm, yield the Adiabatic and Vertical Detachment Energies (ADE and VDE) of this dianion at 0.93 ± 0.05 eV and 1.15 ± 0.05 eV, respectively, along with a ~ 3 eV Repulsive Coulomb Barrier (RCB) against electron detachment. Theoretical calculations at various levels of electronic structure theory confirm the high stability of this dianion. The ADE and VDE values calculated at the CCSD(T)/aug-cc-PVQZ level are 0.92, and 1.16 eV, in excellent agreement with the experimental benchmark values. The comparison between the experimental and the theoretical values obtained at different levels of theory indicate that the PBE0 density functional represents a cost-effective method of sufficient accuracy to describe the molecular properties of this dianion and associated compounds. The theoretical RCB was modelled after the electrostatic potential (ESP) and point charge method (PCM) along three different detachment pathways, viz. along the B-H bond, perpendicular to a B-B bond, and normal to a B-B-B triangle. It was found that detachment of the electron along the B-H bond is preferred, as this pathway is associated with RCBs between 2.3 eV (PCM) and 3.3 eV (ESP), values that bracket the experimental estimate of ~ 3 eV.

Apra, Edoardo↗