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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Transformer system

A flexible transformer system includes conductive windings extending around a magnetic core of a transformer phase and impedance-varying windings extending around the magnetic core of the transformer phase. The conductive windings and the impedance-varying windings are configured to conduct electric current around the magnetic core of the transformer phase. The system includes an impedance switch coupled with the impedance-varying windings and with the conductive windings. The impedance switch is configured to change an impedance of the system by changing which impedance-varying winding of the impedance-varying windings is conductively coupled with the conductive windings and which impedance-varying winding of the impedance-varying windings is disconnected from the conductive windings.

Premerlani, William James↗
DOE OSTI2021

DISTRIBUTION TRANSFORMER ASSET MONITORING ON THE GRID EDGE USING SMART SENSOR DATA

As new loads such as rooftop photovoltaics, electric vehicles and other distributed energy resources become commonplace on the distribution grid, the stress on already aging assets begins to escalate. This increased loading and changing dynamics can exacerbate failure rates. While traditional monitoring efforts focus on transmission and generation assets, utilities are now beginning to pay close attention to distribution assets in order to increase reliability indices and reduce cost from unexpected outages. This research develops low-cost and scalable methods to monitoring the health of a critical distribution grid asset: the service transformer. Existing methods in literature are either invasive and thus difficult to implement or require the device to be tested offline in an expensive lab setting. Data from the ubiquitous smart meter as well as a novel Bluetooth based transformer monitor are leveraged to automatically notify the utility of deteriorating or damaged transformers. Voltage, temperature, and vibration are some of the signals measured and analyzed by the proposed algorithms to predict transformer failures. Furthermore, these algorithms are designed to keep the implementation and processing costs low by taking advantage of edge computing where possible.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Optimizing Insulation Design for Transformers in Medium Voltage Power Conversion Systems

Medium-frequency transformers (MFTs) play a crucial role in medium-voltage (MV) solidstate transformer (SST) systems, particularly in extreme fast charging applications. Achieving partial discharge (PD)-free operation while maintaining high power density is a significant challenge due to the high electric field (E-field) stresses inherent in MV applications. This dissertation focuses on the insulation design and optimization of MFTs used in both the main power electronics circuits and auxiliary power supplies. The study begins with an overview of insulation testing methodologies, including high potential tests, basic insulation level tests, and PD tests, which are critical for evaluating MFT insulation reliability. Given the importance of PD-free operation for long-term reliability, particular emphasis is placed on understanding PD mechanisms, including void, corona, and surface discharge, and their mitigation strategies. A high voltage isolated auxiliary power supply is then introduced, utilizing a gapped transformer encapsulated in silicone gel. This design achieves PD-free insulation up to 18 kV RMS while maintaining low coupling capacitance to minimize common-mode current. The proposed solution ensures reliable operation in MV environments and offers a scalable approach for auxiliary power in cascaded SST architectures. To improve MFT insulation in main power conversion circuits, a novel structure is developed using polypropylene sheets and potting compounds to create a void-free air gap, effectively mitigating E-field intensity. A prototype transformer with this insulation structure is built and achieves PD-free operation up to 30 kV RMS. This design is experimentally validated in a resonant converter operating at 46 kW, demonstrating its feasibility for MV SST applications. Further optimization is implemented to enhance MFT performance for dual-active-bridge(DAB) converters by integrating a semiconductive shielding layer within the insulation structure. This shielding layer improves the magnetic coupling coefficient while effectively confining the E-field within high insulation materials, thereby reducing eddy current losses. The optimized MFT achieves PD-free operation at 12.6 kV RMS and is successfully tested in a DAB converter operating at 43 kW, which meets the insulation requirements for a 13.2 kV SST system. This dissertation advances MFT insulation design by introducing and experimentally validating novel approaches that improve high voltage insulation while optimizing magnetic coupling and manufacturability. The proposed insulation structures enable PD-free operation while minimizing insulation material usage and simplifying assembly, making them ideal for high power, high voltage applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Temporal sequence transformer to advance long-term streamflow prediction

Accurate streamflow prediction is crucial for understanding climate change impacts on water resources and for effective management of extreme hydrological events. While Long Short-Term Memory (LSTM) networks have been the dominant data-driven approach for streamflow forecasting, recent advancements in transformer architectures for time series tasks have shown promise in outperforming traditional LSTM models. This study introduces a transformer-based model that integrates historical streamflow data with climatic variables to enhance streamflow prediction accuracy. We evaluated our transformer model against a benchmark LSTM across five diverse basins in the United States. Results demonstrate that the transformer architecture consistently outperforms the LSTM model across all evaluation metrics, highlighting its potential as a more effective tool for hydrological forecasting. This research contributes to the ongoing development of advanced AI techniques for improved water resource management and climate change adaptation strategies.

Singh, Ruhaan [Farragut High School]↗
DOE OSTI2025

Spatially Aware Linear Transformer (SAL-T) for Particle Jet Tagging

Transformers are very effective in capturing both global and local correlations within high-energy particle collisions, but they present deployment challenges in high-data-throughput environments, such as the CERN LHC. The quadratic complexity of transformer models demands substantial resources and increases latency during inference. In order to address these issues, we introduce the Spatially Aware Linear Transformer (SAL-T), a physics-inspired enhancement of the linformer architecture that maintains linear attention. Our method incorporates spatially aware partitioning of particles based on kinematic features, thereby computing attention between regions of physical significance. Additionally, we employ convolutional layers to capture local correlations, informed by insights from jet physics. In addition to outperforming the standard linformer in jet classification tasks, SAL-T also achieves classification results comparable to full-attention transformers, while using considerably fewer resources with lower latency during inference. Experiments on a generic point cloud classification dataset (ModelNet10) further confirm this trend. Our code is available at https://github.com/aaronw5/SAL-T4HEP.

Wang, Aaron [Illinois U., Chicago] (ORCID:00000003↗
DOE OSTI2020

Friction stir gradient alloying: A high-throughput method to explore the influence of V in enabling HCP to BCC transformation in a γ-FCC dominated high entropy alloy

The compositional possibilities in high entropy alloys (HEAs) is very vast and effective strategies are needed to establish potential alloy chemistries. In this study, friction stir gradient alloying (FSGA), a recently-introduced high-throughput (HT) technique incorporating compositional and microstructural gradients, was used to explore the possibility of introducing a bcc transformation domain in γ-fcc dominated TRIP HEA Fe 38.5 Mn 20 Cr 15 Co 20 Si 5 Cu 1.5 (at.%) by vanadium addition. FSGA has accelerated the process of attaining the composition-microstructure library and the results suggest that vanadium addition of ~1 at.% results in nucleation of α-bcc. Additionally, this is the first observation of ε-hcp to α-bcc transformation in a TRIP HEA and supports the Olson-Cohen model of martensitic transformation (γ-fcc → ε-hcp → α-bcc). ε-hcp is nucleated with a pyramidal orientation by the formation of planar faults on the {111} close-packed planes of γ-fcc, and α-bcc is nucleated in the vicinity of ε-hcp along the {111} γ-fcc trace. There are indications for the formation of basal orientated ε-hcp from intersecting ε-hcp planes orientated for the pyramidal slip. Thus, the study shows the nucleation and growth of the α-bcc phase attributed to the dual effects of chemistry and strain and potential co-existence of all the three phases.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Irradiation-induced shift in the thermodynamic stability of phases and the self-healing effect in transformative high entropy alloys

Here, this work investigated Fe 40 Mn 20 Cr 15 Co 20 Si 5 high entropy alloy (CS-HEA), which exhibits transformation induced plasticity (TRIP) from γ-fcc → ε-hcp, as a probable candidate for nuclear applications. CS-HEA is an extensively-explored, low stacking fault energy alloy with superior strength, ductility, fatigue resistance, and corrosion resistance. This study delved into the effect of irradiation on the shift in thermodynamic stability of the phases and thus radiation tolerance. The evolution of phases, lattice parameters, and transformation volume, V γ→ε , were evaluated from X-ray diffraction experiments along with the mechanical response from nanoindentation. The alloy exhibited a recently-proposed novel self-healing mechanism possible due to the TRIP effect to minimize irradiation damage by restraining the γ-fcc → ε-hcp transformation via thermal aid; this self-healing mechanism was confirmed by transmission electron microscopy. The results were corroborated by a negative change in V γ→ε and a low |V γ→ε |, which is an important criterion for recovery of parent γ-fcc phase. Thus, this alloy was deemed a good radiation-tolerant candidate for nuclear application.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Multiport Control with Partial Power Processing in Solid-State Transformer for PV, Storage, and Fast-Charging Electric Vehicle Integration

This article proposes a multiport control method to enable partial power processing (PPP) in a medium-voltage (MV) multiport solid-state transformer (SST). MV multiport SSTs are promising in integrating low-voltage DC sources or loads such as solar photovoltaic, energy storage, and electric vehicles into smart grids without bulky line-frequency transformers. Compared to voltage-source SST, current-source (CS) SST features single-stage isolated bidirectional AC/AC, AC/DC, or DC/DC conversion using an inductive DC link. For a multiport CS SST, it is revealed in this article that the PPP capability can be enabled through the proposed control without extra hardware, different from the case of voltage-source converters where special hardware architecture is required for the PPP. With the PPP, most power exchange between LV ports is processed by only a fraction of the entire conversion stage, leading to reduced DC-link current, volume, loss, and improved efficiency. The proposed multiport PPP control scheme is analyzed to verify the advantages across a wide voltage and power range against conventional full power processing (FPP) multiport control, using the soft-switching solid-state transformer (S4T) with reduced conduction loss as an example. Comparative experimental results based on a SiC three-port S4T prototype verify the effectiveness of the proposed PPP scheme against the FPP scheme under both steady state and dynamic conditions. Here, the DC-link current reduction is measured to be more than 36%. Significantly, the proposed multiport PPP control scheme is generic and applicable to any hard-switching or soft-switching CS SSTs without extra hardware.

14 SOLAR ENERGY↗
DOE OSTI2024

Data and scripts associated with “Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds” (v2)

This data package is associated with the publication “Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds” submitted to Biogeochemistry by Ryan et al., 2024 (DOI: https://doi.org/10.1007/s10533-024-01169-5). This study aims to investigate fundamental and transferable drivers of dissolved organic matter (DOM) diversity across five nested watersheds within the contiguous United States. DOM diversity was explored using ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The samples and the unprocessed FTICR-MS data used in this study are publicly available on the Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) data repository (see DOIs below). The data for the Willamette, Gunnison, Connecticut, and Deschutes basins were collected as part of a collaboration between the Watershed Rules of Life (WROL) project and Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS). The data for the Yakima River basin (YRB) was collected by the PNNL River Corridor SFA. The raw, unprocessed FTICR-MS data with additional (meta)data can be found at doi:10.15485/1895159 for WROL samples and doi:10.15485/1898912 for YRB samples. This data package contains the processed data used in the associated manuscript. This package also contains ancillary geospatial, hydrological, and geochemical information that supports the interpretation of the FTICR-MS data within Ryan et al., 2024. This data package is associated with the GitHub repository found at https://github.com/WHONDRS-Hub/rcsfa-RC4-WROL-YRB_DOM_Diversity. This data package was originally published August 2024. It was updated January 2025 (modified files). See the change history in the readme more details. At the directory level, the data package is comprised of three folders: (1) data, (2) output, and (3) src; and five additional files including the data dictionary (file ending in "_dd.csv”) and file-level metadata (file ending in “_flmd.csv”). The “src” folder contains the scripts used to process the FTICR data, conduct the analyses, and produce the manuscript figures. The inputs for these scripts are in the “data” folder and the returned outputs in the “output” folder. Inputs include temporal and spatial metadata associated with the sampling efforts, processed FTICR data, and total and normalized putative biochemical transformations per sample. Outputs include cleaned and combined data presented as tables, descriptive statistics, and plots. The file-level metadata file lists all files contained in this data package and descriptions for each. The data dictionary describes the units and definitions for each tabular data column or row header.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Toward Complete Transformation of Sodium Polysulfides by Regulating the Second-Shell Coordinating Environment of Atomically Dispersed Fe

Room temperature sodium-sulfur (RT Na-S) batteries are highly competitive as potential energy storage devices. Nevertheless, their actually achieved reversible capacities are far below the theoretical value due to incomplete transformation of polysulfides. Herein, atomically dispersed Fe-N/S active center by regulating the second-shell coordinating environment of Fe single atom is proposed. The Fe-N4S2 coordination structure with enhanced local electronic concentration around the Fermi level is revealed via synchrotron radiation X-ray absorption spectroscopy (XAS) and theoretical calculations, which can not only significantly promote the transformation kinetics of polysulfides, but induce uniform Na deposition for dendrite-free Na anode. Here as a result, the obtained S cathode delivers a high initial reversible capacity of 1590 mAh g-1, nearly the theoretical value. Here this work opens up a new avenue to facilitate the complete transformation of polysulfides for RT Na-S batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

Toward Complete Transformation of Sodium Polysulfides by Regulating the Second–Shell Coordinating Environment of Atomically Dispersed Fe

Room temperature sodium-sulfur (RT Na-S) batteries are highly competitive as potential energy storage devices. Nevertheless, their actually achieved reversible capacities are far below the theoretical value due to incomplete transformation of polysulfides. Herein, atomically dispersed Fe-N/S active center by regulating the second-shell coordinating environment of Fe single atom is proposed. The Fe–N 4 S 2 coordination structure with enhanced local electronic concentration around the Fermi level is revealed via synchrotron radiation X-ray absorption spectroscopy (XAS) and theoretical calculations, which can not only significantly promote the transformation kinetics of polysulfides, but induce uniform Na deposition for dendrite-free Na anode. As a result, the obtained S cathode delivers a high initial reversible capacity of 1590 mAh g –1 , nearly the theoretical value. Finally, this work opens up a new avenue to facilitate the complete transformation of polysulfides for RT Na-S batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

Controlling the Phase Transformation of Alumina for Enhanced Stability and Catalytic Properties

Current transition alumina catalysts require the presence of significant amounts of toxic, environmentally deleterious dopants for their stabilization. Herein, we report a simple and novel strategy to engineer transition aluminas to withstand aging temperatures up to 1200 °C without inducing the transformation to low-surface-area α-Al 2 O 3 and without requiring dopants. By judiciously optimizing the abundance of dominant facets and the interparticle distance, we can control the temperature of the phase transformation from θ-Al 2 O 3 to α-Al 2 O 3 and the specific surface sites on the latter. These specific surface sites provide favorable interactions with supported metal catalysts, leading to improved metal dispersion and greatly enhanced catalytic activity for hydrocarbon oxidation. Further, the results presented herein not only provide molecular-level insights into the critical factors causing deactivation and phase transformation of aluminas but also pave the way for the development of catalysts with improved activity for catalytic hydrocarbon oxidation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Hybrid Quantum–Classical Graph Transformers for Efficient Sentiment Analysis

Quantum Machine Learning (QML) offers a promising paradigm that leverages quantum computing principles to develop efficient and expressive models for learning from complex and structured data. Recent advances in natural language processing (NLP) and artificial intelligence (AI) have demonstrated capabilities in understanding, generating, and reasoning over linguistic and multimodal information. In this work, we present the Quantum Graph Transformer (QGT), a hybrid quantum–classical architecture that extends graph transformer capabilities through quantum self-attention. The QGT models variable-length sentences as token graphs, where both the embedding encoding and the self-attention mechanisms are implemented using parameterized quantum circuits (PQCs), enabling efficient contextual learning with significantly fewer trainable parameters. We train QGT using both fully connected and 𝑘 -nearest-neighbor graph structures and evaluate it on five benchmark sentiment-classification datasets. Experimental results show that QGT consistently achieves higher or comparable accuracy to existing quantum NLP models and outperforms a Classical Graph Transformer (CGT) baseline with identical architecture, achieving 29.4 × fewer parameters while requiring 3–5 × fewer samples to reach comparable performance. These findings highlight the potential of graph-based quantum models as scalable and data-efficient architectures for natural language understanding.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Mechanistic Transformation of CuI Nanoparticles Into Oxidation‐Resistant 2D Copper Nanoplates

Unconventional phase transformations reveal new crystallization mechanisms, yet direct observation of such pathways during nanoscale solution-phase synthesis remains challenging. This study uncovers an atypical growth process in which thermodynamically stable CuI nanoparticles (NPs) transform into high-energy 2D Cu plates. Using a combination of in situ transmission electron microscopy, ex situ structural analysis, and density functional theory calculations shows that the formation of structural defects induced by hexadecylamine and chloride ions facilitates the transformation by promoting surface iodine vacancies. The resulting Cu{111} nanoplates, with ultrathin thicknesses (≈4 nm) and exceptionally high aspect ratios (≈450), display enhanced oxidation resistance and long-term stability under ambient conditions. This resistance is attributed to the close-packed {111} facets, which suppress chemical oxidation even after extended exposure to air over 100 days. These findings provide new insights into non-classical crystallization pathways in metal nanomaterials and suggest a versatile approach for preparing oxidation-resistant, structurally defined Cu nanostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Direct interpolative construction of the discrete Fourier transform as a matrix product operator

The quantum Fourier transform (QFT), which can be viewed as a reindexing of the discrete Fourier transform (DFT), has been shown to be compressible as a low-rank matrix product operator (MPO) or quantized tensor train (QTT) operator. However, the original proof of this fact does not furnish a construction of the MPO with a guaranteed error bound. Meanwhile, the existing practical construction of this MPO, based on the compression of a quantum circuit, is not as efficient as possible. We present a simple closed-form construction of the QFT MPO using the interpolative decomposition, with guaranteed near-optimal compression error for a given rank. This construction can speed up the application of the QFT and the DFT, respectively, in quantum circuit simulations and QTT applications. We also connect our interpolative construction to the approximate quantum Fourier transform (AQFT) by demonstrating that the AQFT can be viewed as an MPO constructed using a different interpolation scheme.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Disorder-order transformation in Fe-50%Co fabricated via laser powder bed fusion

Fe-Co alloys are an important class of soft magnetic materials that often pose challenges in their fabrication because of the brittle B2-ordered phase. We show that laser beam powder bed fusion (PBF-LB), owing to its rapid cooling rates, offers an avenue for the fabrication of these alloys by suppressing the disorder →order phase transformation at room temperature. We use neutron diffraction to understand the phase transformations in a Fe-50%Co alloy fabricated via PBF-LB. We report that the disorder→order phase transformation in this alloy occurs concurrently via homogeneous ordering and classical nucleation and growth.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Predicting phase transformation kinetics during metal additive manufacturing using non-isothermal Johnson-Mehl-Avrami models: Application to Inconel 718 and Ti-6Al-4V

Here, a computational model was developed to predict solid-state phase transformation kinetics within mechanical parts during metal additive manufacturing processes. This model is a modified version of the Johnson-Mehl-Avrami model for non-isothermal phase transformations that can be applied to various material systems undergoing solid-state phase transformations. Using the thermal history of an additive manufacturing fabricated mechanical part, along with the necessary thermodynamic data and kinetic information as inputs, the model outputs the history of phase fraction evolution during the build process. The model was applied to an Inconel 718 part built by powder bed fusion and a Ti-6Al-4V part built by directed energy deposition. Microstructure characterization and mechanical testing were performed for the validation of the model.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Atomistic evidence of nucleation mechanism for the direct graphite-to-diamond transformation

The direct graphite-to-diamond transformation mechanism has been a subject of intense study and remains debated concerning the initial stages of the conversion, the intermediate phases, and their transformation pathways. Here, we successfully recover samples at the early conversion stage by tuning high-pressure/high-temperature conditions and reveal direct evidence supporting the nucleation-growth mechanism. Atomistic observations show that intermediate orthorhombic graphite phase mediates the growth of diamond nuclei. Furthermore, we observe that quenchable orthorhombic and rhombohedra graphite are stabilized in buckled graphite at lower temperatures. These intermediate phases are further converted into hexagonal and cubic diamond at higher temperatures following energetically favorable pathways in the order: graphite → orthorhombic graphite → hexagonal diamond, graphite → orthorhombic graphite → cubic diamond, graphite → rhombohedra graphite → cubic diamond. Furthermore, these results significantly improve our understanding of the transformation mechanism, enabling the synthesis of different high-quality forms of diamond from graphite.

Graphite-diamond phase transformation↗