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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Role of silicon-graphite homogeneity as promoted by low molecular weight dispersants

This study explores low molecular weight polymers with the same chemical repeat structure as high molecular weight poly acrylic acid (PAA) and lithium poly acrylic acid (LiPAA) binders which act as a dispersant to improve the silicon-graphite electrode performance. The electrodes which utilize LiPAA as a dispersant perform, on average, the best with respect to the maximum capacity (compared to theoretical), rate performance, and capacity retention with time. These electrodes also have the poorest dispersion of binder, indicating that the poor binder dispersion is essential to electrode performance. In contrast, this study shows that electrodes formulated using PAA had good dispersion and performs the worst in cycling. Finally, this work demonstrates that the binder is not uniformly distributed in the electrode, but rather resides in local regions. Overall, the results indicate these regions accommodate volume expansion during cycling.

25 ENERGY STORAGE↗
DOE OSTI2026

The Evolving Role of Demand Charges in Retail Electricity Rates

Retail electricity demand charges refer to a type of retail rate that is based on a metric of kilowatt (kW) demand rather than kilowatt-hour (kWh) energy usage. Demand charges are widely used in the commercial and industrial (C&I) electricity sectors to recover significant portions of utility revenue and are also used in residential rates in a modest but growing number of locations. This paper explores the historical context of and motivations for demand charges, describes their implementation and impacts in today's context, and uses a variety of opinions collected from relevant parties through semi-structured interviews to inform how demand charges align with four widely accepted rate design principles. This project is funded by the Department of Energy's Office of Electricity, which is interested in conducting research to understand the current state of affairs related to demand charges and how the future U.S. electricity grid will help to define retail rates.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Functional protein mining with conformal guarantees

Molecular structure prediction and homology detection offer promising paths to discovering protein function and evolutionary relationships. However, current approaches lack statistical reliability assurances, limiting their practical utility for selecting proteins for further experimental and in-silico characterization. To address this challenge, we introduce a statistically principled approach to protein search leveraging principles from conformal prediction, offering a framework that ensures statistical guarantees with user-specified risk and provides calibrated probabilities (rather than raw ML scores) for any protein search model. Our method (1) lets users select many biologically-relevant loss metrics (i.e. false discovery rate) and assigns reliable functional probabilities for annotating genes of unknown function; (2) achieves state-of-the-art performance in enzyme classification without training new models; and (3) robustly and rapidly pre-filters proteins for computationally intensive structural alignment algorithms. Our framework enhances the reliability of protein homology detection and enables the discovery of uncharacterized proteins with likely desirable functional properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Predicting structural material degradation in advanced nuclear reactors with ion irradiation

Swelling associated with the formation and growth of cavities is among the most damaging of radiation-induced degradation modes for structural materials in advanced nuclear reactor concepts. Ion irradiation has emerged as the only practical option to rapidly assess swelling in candidate materials. For decades, researchers have tried to simulate the harsh environment in a nuclear reactor in the laboratory at an accelerated rate. Here we present the first case in which swelling in a candidate alloy irradiated ~ 2 years in a nuclear reactor was replicated using dual ion irradiation in ~ 1 day with precise control over damage rate, helium injection rate, and temperature and utilize physical models to predict the effects of radiation in reactors. The capability to predict and replicate the complex processes surrounding cavity nucleation and growth across many decades of radiation dose rate highlights the potential of accelerated radiation damage experiments. More importantly, it demonstrates the capability to predict the swelling evolution and the possibility to predict other features of the irradiated microstructure evolution that control material property degradation required to accelerate the development of new, radiation-tolerant materials.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Reactive phosphine combinatorial co-sputtering of cation disordered ZnGeP2 films

The discovery of new materials by coupling high-throughput synthesis with computational screening is being increasingly adopted. However, thus far, phosphides have been largely overlooked for both computational screening and high-throughput synthesis. In this paper, we report on the use of a high-throughput synthesis technique, reactive combinatorial co-sputtering with PH 3 , to deposit ZnGeP 2 thin films. We grew amorphous films over a wide range of compositions and found an upper limit in growth temperature determined by Zn and P volatility. We found that depositing in a Ge-limited regime could be utilized to slow the growth rate to compensate for the desorption of the Zn and P. Crystalline films were achieved by depositing films at higher temperatures in this Ge-limited regime with a reduced deposition rate. X-ray diffraction revealed that the films had crystallized in the zinc blende, cation-disordered structure. The crystalline films exhibited optical absorption energy threshold values ranging from 0.8 to 1.3 eV. Increased Ge content was found in films that exhibited a decreased absorption onset energy. Native defect calculations were used to gain an understanding of the off-stoichiometry seen in these films. This work provides the first high-throughput investigation of ZnGeP 2 , demonstrating the ability to grow amorphous and cation disordered ZnGeP 2 over a wide range of compositions with varying optical properties.

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

Laser-driven, ion-scale magnetospheres in laboratory plasmas. I. Experimental platform and first results

We report magnetospheres are a ubiquitous feature of magnetized bodies embedded in a plasma flow. While large planetary magnetospheres have been studied for decades by spacecraft, ion-scale “mini” magnetospheres can provide a unique environment to study kinetic-scale, collisionless plasma physics in the laboratory to help validate models of larger systems. In this work, we present preliminary experiments of ion-scale magnetospheres performed on a unique high-repetition-rate platform developed for the Large Plasma Device at the University of California, Los Angeles. The experiments utilize a high-repetition-rate laser to drive a fast plasma flow into a pulsed dipole magnetic field embedded in a uniform magnetized background plasma. 2D maps of the magnetic field with high spatial and temporal resolution are measured with magnetic flux probes to examine the evolution of magnetosphere and current density structures for a range of dipole and upstream parameters. The results are further compared to 2D particle-in-cell simulations to identify key observational signatures of the kinetic-scale structures and dynamics of the laser-driven plasma. We find that distinct 2D kinetic-scale magnetopause and diamagnetic current structures are formed at higher dipole moments, and their locations are consistent with predictions based on pressure balances and energy conservation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Improved cycle stability and high-rate capability of LiNbO 3 -coated Li 3 VO 4 as anode material for lithium-ion battery

Lithium vanadate (Li 3 VO 4 ) has garnered considerable attention as an alternative negative electrode material for non-aqueous lithium-ion batteries due to its high capacity, energy efficiency, and stable discharge voltage. Nonetheless, the Li 3 VO 4 material displays a low rate capability, attributed mainly to its poor intrinsic electronic conductivity. Here, in this study, we report the synthesis of lithium niobate LiNbO 3 -coated Li 3 VO 4 (LVO@LNO) using a one-pot sol-gel method. The resulting LVO@LNO demonstrates a high reversible capacity of approximately 530 mAh/g, which is more than double that of free Li 3 VO 4 . To explore the effect of the LNO coating process on the morphological and structural properties, Raman, XRD, operando XRD, XPS, SEM and HTEM analyses were conducted. To explain the enhancement of electronic conductivity in our modified material after a LiNbO 3 coating, we conducted an Ex-Situ electrochemical impedance (EIS) and Density Functional Theory (DFT) computational study. Additionally, we designed a full cell utilizing a 1 wt% LNO-coated LVO anode and NMC-811 cathode. The cell yielded an output voltage of approximately 2.8 V with a high initial specific capacity of 350 mAh/g versus to the anode, at 1C with a capacity retention of 85 % after 100 cycles.

25 ENERGY STORAGE↗
DOE OSTI2025

Impacts of PV Module Connector Failures on Cost and Performance of Utility Scale Photovoltaic Systems

The reliability, cost and performance of electrical connectors are a concern in all types of electrical systems, and demands on connectors used on photovoltaic (PV) systems include that connectors maintain electrical conductivity and physical strength, endure ultraviolet sunlight and high ambient temperature, and resist moisture and chemical intrusion over a very long (>25 year) performance period. Connector failures increase operation and maintenance (O&M) costs and reduce plant production, but connector failure can also cause safety and liability problems, which are of greater concern. This work results from a three-year collaboration between Sandia National Laboratories (SNL), the Electric Power Research Institute (EPRI), and the National Renewable Energy Laboratory (NREL) and funded by the U.S. Department of Energy (DOE) Solar Energy Technology Office (SETO) under Agreements #39035 and #38531 "Connector Reliability Across the US Solar Sector." a multi-pronged investigation of PV connector health across the US (see https://energy.sandia.gov/pvconnectors/). This report presents derivation of a Techno-Economic Analysis (TEA) that models failure modes and frequencies (how often failure occurs), estimates O&M costs and lost production associated with connector failures, and then calculates the effect that PV module connectors can have on Levelized Cost of Energy (LCOE). The model is informed with initial data from quantitative assessment of failure rates, root causes and mechanisms, in-situ diagnostics and data collection, lab-based forensics, and interviews with PV connector manufacturers and plant operators. SNL conducted site inspections at multiple utility-scale sites in different climates and subjected field samples of new, used, and degraded connectors to visual and electrical characterization. EPRI conducted metallurgical analysis of the pin and sleeve conductors to study failure-induced morphological and compositional changes. There is in general a shortage of statistically valid data, but data from PVROM database maintained by SNL was sufficient to ascertain failure rates and lost production as well as provide qualitative insight in its curated maintenance records. This report details the structure of the mathematical model but the sources of data to inform the model will continue to evolve. Analysis of a 100 MW PV plant is provided as an example of the use of the model, with results indicating that connectors are responsible for Annualized O&M Costs of $\$$71,933/year; Annualized Unit O&M Costs of $\$$0.72/kW/year; that a Reserve Account of $\$$187,220 should be available to fund repairs related to connectors; that connectors add $\$$1,494,004 to the Net Present Value of the O&M Costs (project life); and that O&M related to connectors adds about $\$$0.00088/kWh to the Levelized Cost of Energy. The impact of this model is to provide a tool to make the US solar sector more robust by quantifying and monetizing the reliability risks to utility-scale PV systems posed by poorly installed, mismatched and/or poorly designed and manufactured connectors. The TEA provides a model incorporating failure statistics, O&M cost data, and lost production into a single figure of merit, informing decisions and enabling practitioners to optimize cost and performance trade-offs. Stakeholders include connector manufacturers, system designers and equipment specifiers, standards bodies, installers and O&M providers, investors and insurance underwriters. This report supports continued growth of PV predicated on assurances that properly installed and maintained PV system connectors are safe and reliable. The project team is proposing future work including accelerated testing of connectors and expanding the approach taken here to other PV system components, such as TEA for rapid shut-down devices.

14 SOLAR ENERGY↗
DOE OSTI2025

Backup power or bill savings? How electricity tariffs impact residential solar-plus-storage usage in the United States

Adoption of paired solar-plus-storage systems has accelerated in recent years, driven by both the demand for backup power and a desire to manage utility bills. Tradeoffs between those two uses can arise through the reserve setting on the battery storage system, which serves to maintain a minimum state of charge in case of a power interruption. Our paper applies an economic framework to evaluate this tradeoff in terms of changes in bill savings and customer reliability value across reserve levels, considering how those tradeoffs depend on the underlying electricity rate structure and levels. The analysis is based on a representative set of load profiles, solar profiles, tariff designs, and stochastic power interruption events across ten different regions in the United States. We find that the opportunity cost of holding storage capacity in reserve, in terms of foregone bill reductions, outweighs any gains in reliability value from mitigated power interruptions in the majority of customer situations. Higher storage reserve levels increase total customer value only in specific circumstances, such as for customers with inferior reliability (10x average interruptions), with a very high value of lost load ($50/kWh), and with tariff or interconnection rules that disallow grid charging. However, even this result is dampened when considering tariff designs with higher price differentials that increase the opportunity cost of holding storage in reserve (e.g. import/export or time-of-use rates). Allowing grid charging in tariffs essentially eliminates the necessity to hold any storage in reserve in all sensitivity cases explored.

Electric resilience↗
DOE OSTI2020

An encoder–decoder LSTM-based EMPC framework applied to a building HVAC system

Numerous studies have demonstrated the benefit of economic model predictive control (EMPC) applied to building heating, ventilation, and air conditioning (HVAC) systems. However, the construction and training of predictive models for building HVAC systems are widely recognized as a key technological barrier preventing large-scale adoption of EMPC for buildings. In this work, an encoder–decoder long short-term memory-based EMPC framework is developed. The key advantage of the approach is that a model may be automatically generated from a list of inputs and outputs. From the definition of inputs and outputs, the constructed model may be trained and automatically embedded into the EMPC framework for real-time estimation and control. The overall end-to-end EMPC framework from model training to on-line estimation and control are described. To this end, the encoder–decoder model provides a natural framework for state estimation (encoder), which is required to provide an initial condition for the predictive model of EMPC (decoder). Closed-loop simulations using EnergyPlus are performed to demonstrate the approach. The simulated closed-loop system consists of a building zone from a multi-zone building, which is served by an air handling unit-variable air volume HVAC system. For the HVAC example considered, the trained encoder–decoder model can predict the indoor air temperature and HVAC sensible cooling rate of a building zone over a two-day horizon with high accuracy. Overall, we find that considering a time-of-use electric rate structure, the EMPC, which manipulates the zone temperature setpoint, can reduce the HVAC power consumption cost relative to keeping the zone temperature setpoint at its maximum value (i.e., minimum energy approach).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Modelling and Experimental Validation of Improved Performance of Lithium-Ion Batteries Having Thick Electrodes with Laser-Ablated Micro-Structures

For widespread adoption of electric vehicles, lithium-ion batteries (LiBs) need to achieve energy densities of >275 Wh/kg, cost less than $100/Wh, and charge to more than 80% capacity within 15 minutes. Increasing the battery electrode thicknesses is one way to increase cell energy densities while also saving on cell manufacturing cost by increasing the ratio of electrode active material to inactive material within each cell. However, increased electrode loading is often accompanied by decreased Li+-ion diffusion across the full thick electrodes. This leads to significant cell polarization that prevents full capacity utilization and accelerates cell degradation, especially at fast charging/discharging rates. The introduction of secondary pore networks in thick battery electrodes alleviates some of the trade-offs between energy and power performance. These microstructures provide low tortuosity pathways for facile Li+-ion diffusion deep into the thick electrodes, diminishing detrimental concentration gradients within the cell. Ultrafast-pulsed laser ablation is a promising method to introduce micro pores or channels in thick battery electrodes as it allows for precise control of pattern geometries, results in minimal damage to the electrode and can be introduced into existing roll-to-roll electrode manufacturing lines. Herein, the limitations of thick planer electrodes and the advanced predictive models to identify optimal electrode patterns for improved cycling performance will be presented. The impact of electrode laser patterning to create secondary pore networks also will be discussed. Materials characterization techniques (SEM-EDS, XRD) were used to explore the affect ultrafast laser ablation had on the electrode materials’ morphology and structure. The improvements in the patterned electrodes’ electrochemical cycling performances and degrees of wetting will be compared to a pristine baseline case. Finally, the discrepancies between experimentally obtained data and model predictions will be explained.

DIRECT ENERGY CONVERSION,ENERGY STORAGE↗
DOE OSTI2026

Structural and mechanistic insights into protective non-neutralizing antibodies targeting Crimean-Congo hemorrhagic fever virus nucleocapsid protein

Abstract Crimean-Congo Hemorrhagic Fever Virus (CCHFV) is a tick-borne virus endemic to Africa, Asia, and expanding regions within Europe. With mortality rates approaching 40%, rising incidence, and no currently approved countermeasures, CCHFV is recognized as a priority public health threat. CCHFV nucleocapsid protein (NP) has long been a key target for diagnostics. Recently, NP-specific humoral responses have also been correlated with protection conferred by protective vaccines candidates. Additionally, the first non-neutralizing monoclonal antibody (mAb) 9D5 demonstrated protective efficacy against CCHFV challenge, underscoring NP as a viable antiviral target. Here, nine anti-NP mAb were utilized to identify four antigenic sites on NP as well as localize these sites to the head or stalk domains. These mAb also revealed variable levels of in vivo protection, independent from whether the epitope site is located in the head or stalk regions. Additionally, three X-ray crystallography structures were obtained that included CCHFV NP from strain Afg09-2990 in complex with the most potent mAb (9D5). This, along with additional structures of two unbound NPs, revealed structural elements critical for mAb-9D5 broad-spectrum protective characteristics. These findings provide a path towards the rapid identification of broadly protective anti-NP mAb countermeasures.

Moresco, Vanessa↗
DOE OSTI2025

Initial Design of SABRE Fueled Molten Salt Experiment Irradiation Vehicle

Molten Salt Reactors (MSRs) are emerging as promising advanced reactor technologies, utilizing molten salts for both fuel and primary cooling. These reactors may offer advantages such as passive safety, enhanced economic viability, and efficient waste reprocessing while operating at high temperatures and low pressures, which leads to increased system efficiency and reduced mechanical stress on containment structures. However, challenges arise from the complex chemistry and high corrosion rates of fueled molten salts, alongside the volatility of certain fission products during irradiation. The accumulation of these fission products can alter the fuel salt chemistry, affecting corrosion potential and radioactive source terms. Therefore, understanding these phenomena under neutron irradiation is essential for future MSR designs. The SABRE (Salt and Actinide Burnup in a Reactor Environment) experiment, currently in conceptual design at Idaho National Laboratory (INL), aims to investigate these challenges by conducting a drop-in capsule experiment in the Advanced Test Reactor (ATR). The primary objectives include achieving a minimum burnup of 2 GWd/MTU and characterizing fission products while studying corrosion behavior in molten salt systems. This innovative experiment will leverage recent advancements in ATR capabilities, allowing for the safe irradiation of molten salts, thereby advancing the understanding and qualification of MSR technology for future nuclear power generation.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Understanding Your Utility Bills: Natural Gas

As a fossil fuel NG is a colorless and odorless gas in its natural state and is one of the cleanest burning hydrocarbons. The factors that contribute to the popularity of natural gas in the US manufacturing sector include ease of availability, clean burning properties, market deregulation, and increased domestic production. Analyzing natural gas (NG) bills can sometimes pose unique problems. Learning to read your utility bills and understand why your utility charges different fees is critical in maximizing your cost savings through energy efficiency. A key to creating a baseline is collecting and analyzing natural gas utility data. Historical data from NG bills can identify trends and help to find the baseline usage for a manufacturing operation. This guide intends to help Better Plant Program partners in understanding natural gas bills and analyzing usage to reduce costs. The guide focuses on natural gas production and transportation, understanding key charges on bills, different rate structures, and saving opportunities. A fictitious worked out example in the final section demonstrates how readers could go about analyzing natural gas bills.

03 NATURAL GAS↗
DOE OSTI2024

Unraveling the Pyrolytic Behavior and Kinetics of Single Polymers and Plastic-Rich Municipal Solid Waste Using Thermal Analysis

Pyrolysis is a highly promising thermochemical recycling technology for converting heterogenous plastic waste into sustainable fuels in a single step. Therefore, understanding the pyrolysis mechanism is essential for enabling rational reactor design and enhancing efficient recycling techniques. In this study, the thermal degradation behaviors and corresponding kinetics of pure polymers (PE, PP, and PET) and plastic-rich MSW were examined using simultaneous thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). Experiments were carried out in the temperature range of 30-800°C with variable heating rates from 5°C/min to 20°C/min in an ultra-high purity Argon atmosphere. Our results indicated that the plastic pyrolysis was an endothermic process, with varying decomposition temperature ranges depending on their structure and composition. Various iso-conversional model-free methods (Friedman, Flynn-Wall-Ozawa, Starink, and Kissinger-Akahira-Sunose) were utilized to determine the apparent activation energy of the plastic degradation, which increased in the following order: PET (214 kJ/mol), PP (218 kJ/mol), PE (245 kJ/mol), and MSW (249 kJ/mol). Finally, Criado’s master plots were employed to identify the best-fitting reaction model and the pre-exponential factor was subsequently determined.

Bashir, Muhammad Aamir↗
DOE OSTI2026

Estimating the impact of tariff-driven behind-the-meter storage operation on distribution grid investments

Increasing growth of distributed solar photovoltaics (PV) and electric vehicles (EV) can strain local distribution networks and require costly upgrades. Distributed battery storage, often deployed alongside PV, can be used to mitigate those costs, depending on how batteries are operated. This study evaluates the potential deferral value of distributed battery storage across a range of tariff structures, focusing on the rate structures most commonly available to residential customers today and related variants. Deferrals are evaluated with a least-cost distribution grid expansion optimization model to identify requirements on line reconductoring, transformer upgrades, and voltage regulator installations under each tariff. Results show that TOU rates and net billing tariffs can yield meaningful deferral value, depending on specific tariff structure features. Under the best performing tariff structure tested, storage produced a median annualized deferral value of $7.18 per kW of storage capacity ( kW S ) across all feeders in the sample, though deferral values were considerably larger for feeders with peak loads that coincide with utility system peak, i.e., timing of TOU peak period. In contrast, under an unrestricted TOU design with no restrictions on grid charging or discharging, the median deferral value was $0/ kW S illustrating the critical importance of tariff structure details.

Rodriguez-Garcia, Luis↗
DOE OSTI2023

Electron scattering and neutrino physics

Abstract A thorough understanding of neutrino–nucleus scattering physics is crucial for the successful execution of the entire US neutrino physics program. Neutrino–nucleus interaction constitutes one of the biggest systematic uncertainties in neutrino experiments—both at intermediate energies affecting long-baseline deep underground neutrino experiment, as well as at low energies affecting coherent scattering neutrino program—and could well be the difference between achieving or missing discovery level precision. To this end, electron–nucleus scattering experiments provide vital information to test, assess and validate different nuclear models and event generators intended to test, assess and validate different nuclear models and event generators intended to be used in neutrino experiments. Similarly, for the low-energy neutrino program revolving around the coherent elastic neutrino–nucleus scattering (CEvNS) physics at stopped pion sources, such as at ORNL, the main source of uncertainty in the evaluation of the CEvNS cross section is driven by the underlying nuclear structure, embedded in the weak form factor, of the target nucleus. To this end, parity-violating electron scattering (PVES) experiments, utilizing polarized electron beams, provide vital model-independent information in determining weak form factors. This information is vital in achieving a percent level precision needed to disentangle new physics signals from the standard model expected CEvNS rate. In this white paper, we highlight connections between electron- and neutrino–nucleus scattering physics at energies ranging from 10 s of MeV to a few GeV, review the status of ongoing and planned electron scattering experiments, identify gaps, and lay out a path forward that benefits the neutrino community. We also highlight the systemic challenges with respect to the divide between the nuclear and high-energy physics communities and funding that presents additional hurdles in mobilizing these connections to the benefit of neutrino programs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Classifying and analyzing small-angle scattering data using weighted k nearest neighbors machine learning techniques

A consistent challenge for both new and expert practitioners of small-angle scattering (SAS) lies in determining how to analyze the data, given the limited information content of said data and the large number of models that can be employed. Machine learning (ML) methods are powerful tools for classifying data that have found diverse applications in many fields of science. Here, ML methods are applied to the problem of classifying SAS data for the most appropriate model to use for data analysis. The approach employed is built around the method of weighted k nearest neighbors (wKNN), and utilizes a subset of the models implemented in the SasView package (https://www.sasview.org/) for generating a well defined set of training and testing data. The prediction rate of the wKNN method implemented here using a subset of SasView models is reasonably good for many of the models, but has difficulty with others, notably those based on spherical structures. A novel expansion of the wKNN method was also developed, which uses Gaussian processes to produce local surrogate models for the classification, and this significantly improves the classification accuracy. Further, by integrating a stochastic gradient descent method during post-processing, it is possible to leverage the local surrogate model both to classify the SAS data with high accuracy and to predict the structural parameters that best describe the data. The linking of data classification and model fitting has the potential to facilitate the translation of measured data into results for both novice and expert practitioners of SAS.

97 MATHEMATICS AND COMPUTING↗