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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Dataset for Blueprinting Electrified Transit System Implementation

This dataset contains the figures and tabulated results generated from a system-level optimization study of transit fleet electrification planning. The dataset does not include executable modeling code required to reproduce the optimization. The dataset includes results for optimized charging infrastructure deployment by location and power level and service block assignments by fuel type, battery capacity selections, and distributed energy resource sizing. It also contains aggregated financial results, capital expenditures, operating cost summaries, net present cost comparisons across scenarios, and quantified air quality impacts. Results are structured to reflect multiple planning scenarios, including heuristic electrification plans, system-optimized configurations, and sensitivity cases with alternative objective weightings. The modeling was developed using publicly available General Transit Feed Specification data from Omnitrans and standardized modeling assumptions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Enhancing the EVI-X National Framework to Address Emerging Energy Questions

This project advances the state-of-the-art in infrastructure analysis to better inform deployment strategies. It enhances NLR's EVI-X Suite, a set of tools supporting national network planning, local site design, and financial evaluation. These capabilities will position DOE to provide timely analysis and inform the strategic buildout of the national charging network. EVI-X development is closely coordinated with other DOE-funded efforts to ensure consistent, integrated use of key inputs and outputs, including EV adoption scenarios from NLR's TEMPO model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Layer-by-Layer-Processed Organic Solar Cells with 18.02% Efficiency Enabled by Regulating the Aggregation of Bottom Polymers

The fabrication of organic solar cells (OSCs) by a layer-by-layer (LBL) method has attracted growing attention in recent years. As already known, the pre-aggregates of conjugated polymers in solution have a profound impact on their microstructure morphology in films. Herein, by simply controlling the solution temperature and annealing processes, the pre-aggregation behavior of D18 polymer in solution can be fine-tuned and the microstructure of D18 bottom layer is well manipulated. The optimized D18 bottom layer can effectively regulate L8-BO upper-layer-forming suitable networks for efficient charge transportation. In addition, a vertical phase separation with a special D/D:A/A structure (P-i-N-type component distribution) is also formed. As a result, compared to the 16.43% power conversion efficiency (PCE) of the bulk heterojunction devices, such control enables bilayer OSC devices based on the polymer D18 and L8-BO to deliver an enhanced PCE of 18.02% with simultaneously improved short-circuit current density, open-circuit voltage, and fill factor. Importantly, it is also demonstrated in these results that the LBL deposition process utilizing the pre-aggregation of polymer and its fiber-network-forming ability is a very promising approach to improve charge dynamics, suppress carrier recombination, and fabricate highly efficient OSCs.

14 SOLAR ENERGY↗
DOE OSTI2024

T-Type Modular DC Circuit Breaker (T-Breaker) for Future DC Networks

The developed T-Type Modular DC Circuit Breaker (T-Breaker) technology offers an all-in-one solution to challenges in DC networks. This includes swift fault detection and protection, power transient stability, and power quality improvement, achieved through the utilization of wide bandgap (WBG) power semiconductors and energy storage devices. The T-Breaker not only facilitates rapid fault current detection and interruption but also implements fault current limiting through active insertion of storage devices or by operating WBG devices in the saturation region. Additionally, with the assistance of energy storage devices, potential overvoltage issues on power devices induced by control signal misalignment can be mitigated. The T-Breaker can be regulated to perform shunt current injection/absorption using the vertical arm and series voltage insertion via the horizontal arm, thereby enhancing DC system stability during voltage or load power fluctuation transients. The OSU team and Raytheon team actively worked together on designing, fabricating, assembling, and testing of two T-Breaker prototypes. The first prototype is rated at 1 kV, 500 A with half-bridge (unipolar) structure to validate the T-Breaker concept. The second prototype is rated at 20 kV, 50 A with full-bridge (bipolar) topology which can reach an efficiency of 99.977%, realize a power density of 60.2 MW/m3, and eliminate the 500-A fault current with a fault response time of around 20 µs. The prototypes show great feasibility of adopting this technology in multiple applications including electrified aircraft, super charging stations, data centers, etc.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Enhancing Distribution Grid Resilience Through Model Predictive Controller Enabled Prioritized Load Restoration Strategy

Effective resilience improvement strategies enable the power grid to cope with disruptive extreme events. Most power grid outages are caused by disruptions in distribution grids. Motivated by the urgent need for power system resilience research, this paper proposes a priority-weighted optimal load restoration technique to enhance the resilience of distribution grids against extreme events. The proposed technique is based on smart distribution technology and framed as sequential multi-step decision process (MDP) and mixed integer linear program (MILP). It is formulated as optimal control problem with a model predictive control (MPC) approach. We applied the devised MILP-MPC-based load restoration technique to a simplified single-bus version of the IEEE 13-bus distribution system with integrated distributed energy resources (DERs) such as wind turbine, photovoitaic array, microturbine, and energy storage device. The technique executes a reducing and rolling horizon optimization in each control step in real-time using the forecasted information of the renewables, the fuel status of the microturbine and the state of charge of the energy storage device. We consider an extreme event which triggered outage of the upstream utility grid and caused islanded operation of the distribution grid. We demonstrated the effectiveness of the proposed MPC approach in restoring the distribution grid loads based on their priority during the main grid outage-caused islanded operation.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Enhancing Distribution Grid Resilience Through Model Predictive Controller Enabled Prioritized Load Restoration Strategy: Preprint

Effective resilience improvement strategies enable the power grid to cope with disruptive extreme events. Most power grid outages are caused by disruptions in distribution grids. Motivated by the urgent need for power system resilience research, this paper proposes a priority-weighted optimal load restoration technique to enhance the resilience of distribution grids against extreme events. The proposed technique is based on smart distribution technology and framed as sequential multi-step decision process (MDP) and mixed integer linear program (MILP). It is formulated as optimal control problem with a model predictive control (MPC) approach. We applied the devised MILP-MPC-based load restoration technique to a simplified single-bus version of the IEEE 13-bus distribution system with integrated distributed energy resources (DERs) such as wind turbine, photovoltaic array, microturbine, and energy storage device. The technique executes a reducing and rolling horizon optimization in each control step in real-time using the forecasted information of the renewables, the fuel status of the microturbine and the state of charge of the energy storage device. We consider an extreme event which triggered outage of the upstream utility grid and caused islanded operation of the distribution grid. We demonstrated the effectiveness of the proposed MPC approach in restoring the distribution grid loads based on their priority during the main grid outage-caused islanded operation.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Enhancing Distribution Grid Resilience Through Model Predictive Controller Enabled Prioritized Load Restoration Strategy

Effective resilience improvement strategies enable the power grid to cope with disruptive extreme events. Most power grid outages are caused by disruptions in distribution grids. Motivated by the urgent need for power system resilience research, this paper proposes a priority-weighted optimal load restoration technique to enhance the resilience of distribution grids against extreme events. The proposed technique is based on smart distribution technology and framed as sequential multi-step decision process (MDP) and mixed integer linear program (MILP). It is formulated as optimal control problem with a model predictive control (MPC) approach. We applied the devised MILP-MPC-based load restoration technique to a simplified single-bus version of the IEEE 13-bus distribution system with integrated distributed energy resources (DERs) such as wind turbine, photovoltaic array, microturbine, and energy storage device. The technique executes a reducing and rolling horizon optimization in each control step in real-time using the forecasted information of the renewables, the fuel status of the microturbine and the state of charge of the energy storage device. We consider an extreme event which triggered outage of the upstream utility grid and caused islanded operation of the distribution grid. We demonstrated the effectiveness of the proposed MPC approach in restoring the distribution grid loads based on their priority during the main grid outage-caused islanded operation.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

Scaled Implementation of Smart Charge Management for Electric Vehicles

Smart charge management (SCM) has become a critical strategy for mitigating potential grid impacts and reducing electricity costs for all customers. This study will evaluate the economics of implementing light-duty EV SCM at scale across the United States. This work will enhance distribution system analysis by estimating SCM implementation costs, exploring viable business cases, and developing a framework for national-level applications. The primary methodology involves leveraging detailed grid modeling from a specific service territory and using spatial extrapolation techniques to generalize findings to other regions. The analysis will develop key metrics to quantify the costs and benefits of SCM, including implementation costs relative to strategy and scale, the cost of distribution system upgrades with and without SCM, and the percentage of peak-load reduction. The objective is to produce a comprehensive report and a parameterized framework that enables utilities to self-assess the value of SCM in their own service territories. This will support the development of cost-effective charging strategies, accelerate the energization of new EV chargers, and facilitate the seamless integration of EVs into the nation's power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Concept Study of Robotic Camera-Based Foreign Object Detection for EV Wireless Charging

Wireless charging of an electric vehicle (EV) is an emerging charging technology promising convenient, autonomous, and highly efficient EV charging without requiring heavy gauge cables. However, due to the strong electromagnetic field created by this process that surrounds the wireless charger, the presence of foreign objects can detrimentally interact with it, thus affecting wireless power transfer (WPT) performance or leading to harmful and unwanted safety risks. This paper presents the results for a concept study on a robotic camera-based foreign object detection (FOD) system, as a supplement to the industry-existing overlapped FOD coil array method, for EV wireless charging. A Raspberry PI 4 control board and compatible Raspberry PI Camera Module 2 are used to implement camera-based object detection. The FOD program was developed using a state-of-the-art deep learning object detection model with the OpenCV and Pytorch library and is compatible with camera module hardware. A dry-run test with Raspberry PI and a camera module was conducted and the preliminary FOD function was verified. The feasibility assessment is also validated by comparing the performance of five existing state-of-the-art deep learning object detection models for vehicles, animals, persons, and metals subsets, respectively. Satisfactory performance on the benchmark datasets is observed by the tests, but further improvements are needed in future work when detecting small-sized metallic objects. A programable robotic car is also under development as ongoing work for carrying the Raspberry PI and camera module while moving for the maintenance process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Stochastic generation of electrolyzer anode catalyst layers

Here, we introduce a stochastic methodology to reproduce the complex pore structure observed in commercial iridium catalyst layers. This method preserves the α pore (pores smaller than 250 nm) and β pore (pores greater than or equal to 250 nm) regions of the catalyst layer. The morphology of the generated materials was validated by comparing the pore size distributions of generated materials against those obtained from commercial materials imaged using x-ray nano computed tomography. We further demonstrate that the pore size distributions of the generated materials are statistically indistinguishable from the imaged catalyst layers, indicating that the stochastic methodology is capable of accurately reproducing catalyst layer morphology. Pore network modelling was conducted on the generated catalyst materials to simulate single-phase permeability, electrical conductivity, and ionic conductivity, and these properties were found to be within experimentally measured ranges for electrolyzer catalyst layers. Additionally, simulations were performed on the generated materials with varying ionomer and iridium catalyst loadings. As the ionomer loading is added, proton conductivity increases exponentially, which demonstrates the importance of optimizing ionomer loading, considering that these effects will be exacerbated in the hydration and temperature conditions of operating electrolyzers. The stochastic material generation method presented in this work is a powerful tool for the development of novel low loading catalyst layers, where the effect of various structural parameters on electrolyzer performance characteristics can be explored.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Imaging hole-density inhomogeneity in arsenic-doped CdTe thin films by scanning capacitance microscopy

We report nanometer-scale hole-density imaging in As-doped CdTe films by scanning capacitance microscopy (SCM). The hole-density profiling is validated by contrasting a CdTe cross-section sample made by molecular-beam epitaxy with systematically increased As doping in a staircase pattern over the range of 10 15 -10 18 /cm 3 within a single film. In polycrystalline films, the carrier distribution is significantly nonuniform, with inhomogeneity ranging from several hundred nm to several um and hole density varying by one order of magnitude (low 10^16 to low 10 17 /cm 3 ). This nonuniformity is distributed randomly, independent of the grain structure and grain boundaries (GBs). Kelvin probe force microscopy (KPFM) maps the surface potential and is correlated to cathodoluminescence (CL) and SCM by imaging over identical areas. Higher potential and lower CL intensity are found on GBs but not by SCM contrast; this indicates positive GB charging and recombination, but not GB-specific hole-density changes. The overall KPFM potential image is in rough agreement with the SCM carrier distribution and indicates band-edge potential fluctuations. Nonuniform carrier concentration, potential fluctuations, and defect recombination can all cause voltage and performance loss in As-doped CdTe solar technology.

14 SOLAR ENERGY↗
DOE OSTI2025

Novel artificial neural network model for instantaneous power losses and operational efficiency mapping of MW-scale vanadium redox flow battery for improved technoeconomic analysis

A novel data-driven, machine-learning-based method for modeling the instantaneous power losses of a distribution-sited 2 MW/8MWh vanadium redox flow battery (VRFB), a grid-scale electrochemical storage technology, is introduced and compared against benchmark empirical modeling approaches, including symmetric and asymmetric models, as well as a recent convex hull modeling approach. The novel loss modeling method introduces several advantages over the benchmark models and over simplistic efficiency estimates, the most significant of which is that the model can accurately reflect the stepwise and non-linear parasitic losses associated with the duty cycles of mechanical auxiliary systems like pump motor drives and blower fans. Residuals of the models are compared; the proposed data driven model features significantly improved accuracy over the benchmark models. The model's coefficient of determination is also improved relative to that of the benchmark models. Furthermore, a novel method for visualization of operational efficiency of the grid-scale storage technology is introduced. To demonstrate the benefits of the novel data-driven method for modeling the VRFB, the benchmark models and the proposed models are embedded into an Open DSS distribution network model to study two applications of the grid-scale electrical storage system: load leveling for grid support and energy arbitrage. This article demonstrates that the accuracy of the instantaneous power loss model significantly impacts the understanding of the state of charge of the VRFB. In turn, the accuracy of the efficiency modeling of the VRFB impacts the understanding of the potential economic value and technical benefits to the distribution network operators. In conclusion, the presented power loss modeling approach is, therefore, highly relevant for utility-stakeholders, battery asset owners, system engineers, system designers, and financial planners interested in evaluating or optimizing the operation of grid-scale VRFBs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Mechanical Solutions Scan Report

Power lines, poles, and towers are the backbone of the United States (U.S.) electric-power grid. These transmission and distribution networks route electricity from generator to loads. The characteristics of these routes are rapidly changing -- trending towards decentralized renewable generation, electric heating, vehicle charging, and large data-center loads. Coupled with aging infrastructure and the increased frequency of extreme weather events, there is concern about the future reliability and transmission capacity of conductors and adjacent components. This scan report seeks to provide an overview of mechanical solutions to challenges caused by extreme weather events associated with components of transmission and distribution infrastructure, including conductor heat sag, ice accumulation, wind, and wildfire. Many options could increase transmission capacity or reliability, and these are at various stages of technological readiness. Some have only been lab tested, while some have been widely deployed in the U.S. or overseas for decades. The solution categories and providers featured in this report are intended to be comprehensive at the time of publication and to serve as a reference for decision-makers concerned about transmission and distribution reliability. There are two other categories of large, complex solutions, which are not covered in this report: replacing existing conductors with advanced conductors and implementing digital grid enhancing technologies. A separate scan report titled “Advanced Conductor Scan Report,” which discusses advanced carbon-core conductors, was published by the Idaho National Laboratory (INL) in 2023. Information on digital technologies, such as dynamic line ratings, power-flow controllers, and other power electronics and communications-based devices, can be found on the Grid- Enhancing Technologies landing page. Mechanical grid-enhancing technologies, or solutions covered in this report, often do not require full equipment replacement and do not rely on digital components. Mechanical technologies are overlooked because they may be older, simpler, or seemingly “more obvious” than digital or carbon-core technologies. However, it is wise to consider mechanical solutions in a thorough evaluation of grid enhancing technology solutions.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A method for modeling battery-temperature-aware EV power profiles utilizing Next-Gen Profile data

With the expected increase in the number of electric vehicles (EVs) on the road in the coming years, it is important that analysis tools are capable of modeling and predicting the expected load on the power grid due to both individual EV charging sessions as well as large populations of vehicles. To do this accurately, the power profile of an EV charge session must be accurately modeled, including for scenarios where the temperature is above or below the ideal, and also take into account the nuances of manufacturer charging preferences. This paper introduces a method that utilizes the data in the Next-Gen Profile (NGP) data collection project to build a model of EV charging that takes into account the variations in charging power that occur due to off-nominal battery temperature and manufacturer preferences that limit power due to cold temperatures or high battery state-of-charge.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Programmable Cryogenic Memory in a Ge/GeSi Heterostructure

Programmable memory components that operate optimally at cryogenic temperatures are essential for cryogenic computing architectures that seek to implement computing-in-memory. In this work, we demonstrate highly programmable memory in a Ge/GeSi heterostructure field-effect transistor (HFET). To operate, the HFET is gated to introduce positive carriers within the Ge quantum well, creating a high-conductance state. We show that this device can be set to a low-conductance state by sweeping a negative bias on the device drain, and reset it to its high-conductance state by sweeping a more positive bias on the device gate, thereby creating memory. We then determine that the device can be programmed within a 103 range of conductances using either the SET or the RESET operation. We propose that memory is achieved through charge trapping as carriers tunnel out of the quantum well, and that altering the density and spatial distribution of carriers modulates the device conductance. This mechanism exhibits endurance over 1000 cycles at temperatures ≤ 25 K, suggesting that the carrier traps are located at the oxide-semiconductor interface. As a first demonstration of programmable conductance in a Ge/GeSi HFET, this work highlights the potential of group-IV HFETs to perform as analog cryogenic memory components.

cryogenic memory↗
DOE OSTI2026

Humins-Derived Hard Carbon as a Low-Cost Material for Sodium-Ion Battery Anodes

The growing demand for sodium-ion batteries (SIBs) in grid storage underscores the need for electrode materials that balance performance and cost, including sustainable and robust carbon sources. The equitable and abundant distribution of materials for SIBs, along with their superior low-temperature performance, safety, and fast-charging capability, further distinguishes them from lithium-ion batteries (LIBs). Hard carbon (HC) is the state-of-the-art anode for SIBs, but current commercial HC production is localized mostly to one region of the world, raising concerns about supply chain vulnerability, critical material dependency, and environmental aspects. Here, the first demonstration of humins, an abundant biorefinery byproduct, as a precursor for HC anodes for sodium-ion storage is reported. Humins were carbonized at 1100 degrees C-1300 degrees C, and the resulting materials were subjected to comprehensive materials and electrochemical characterization. Among the temperatures studied, humins-derived hard carbon synthesized at 1200 degrees C delivers an initial reversible capacity 270mA h g-1 , with stable cycling performance up to 500 cycles and excellent rate capability, representing the optimal performance. This study establishes humins as a promising and low-cost carbon source that provides a route to mitigate supply chain risks and valorizes an underutilized biorefinery waste stream for high-performance SIB anodes.

25 ENERGY STORAGE↗
DOE OSTI2022

A nuclear-hydrogen hybrid energy system with large-scale storage: A study in optimal dispatch and economic performance in a real-world market

Here a study in optimal dispatch and economic analysis of a novel nuclear hybrid energy system (NHES) with large-scale hydrogen storage and a novel control scheme is conducted. The control scheme makes charge and discharge decisions by using the real-time electricity price relative to the historical price distribution. The pricing data is taken from the ERCOT Houston and West load zones with different price oscillations. Six case control studies with different levels of aggressiveness were chosen for each load zone for a total of 12 case studies. It is found that in a high price volatility load zone, a more aggressive control strategy maximizes revenue, while in a less oscillatory load zone, a moderate control strategy performs better. The NHES can store energy when the price is low and sell additional electricity when the price is high, as well as participate in the ancillary services market. Due to these advantages, the NHES can generate 10–40 million USD more revenue annually than a stand-alone nuclear plant. Due to higher costs, the NHES has a higher LCOE (81.36 USD/MWh) than a stand-alone plant (68.66 USD/MWh); however, the LCOE of the NHES is still comparable to other new forms of electricity generation. It is found that both the NHES and the stand-alone plant are not economical in the existing electricity market. Due to the extra revenue generated, the hybrid system has a positive annual cashflow whereas the stand-alone plant does not. It is found that the hybrid plant needs less cost subsidy than a stand-alone plant to become economical.

08 HYDROGEN↗
DOE OSTI2026

Characterization of core neutrals using passive measurements of the D α spectrum near the X -point in the DIII-D tokamak

New spectroscopic measurements of deuterium Balmer-α emission are used to infer the spatial distribution of neutral particles near the X-point in a diverted high confinement mode plasma. The charge exchange neutral spectroscopy (CENS) diagnostic—recently installed on the DIII-D tokamak—uses 15 lines of sight extending from the edge of the confined region (ρ ≈ 0.7) to the X-point in lower single-null plasmas. Each CENS line of sight is spectrally resolved around the deuterium Balmer-α wavelength (6561 Å) to measure the Doppler shift, line broadening, and intensity of Dα emission. Thermal line broadening is used to identify emission from neutrals undergoing charge-exchange (CX) with high temperature ions in the confined plasma. This spectral information allows a more accurate determination of the neutral density deeper inside the confined plasma compared to traditional filter-based diagnostics. We present two methods of analyzing CENS measurements: (1) fitting the spectrum from each view-chord separately, and (2) a tomographic method for inverting the neutral density over a 2D region of space using all CENS views collectively. The neutral density profile is found to decay exponentially in the radial direction with two scale-lengths. In the pedestal region the neutral density decays at a rate approximately equal to the local mean-free-path for CX collisions, $L_{n_\mathrm{D0}}\approx \lambda_\text{CX}$. Further inside the plasma the neutral density decays at a rate equal to the mean-free-path for ionization, $L_{n_\mathrm{D0}}\approx \lambda_\text{inz.}$. The separatrix $n_\mathrm{D0}$ value is found to be approximately $2\times10^{15}$ m−3. Based on results from the 2D inversion, the density of neutrals is found to increase along the separatrix approaching the X-point by a factor of $\approx 5\times$ over the region covered by the CENS diagnostic.

X-point neutrals↗