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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Evolution of Mass Spectrometers for High m / z Biological Ion Formation, Transmission, Analysis and Detection: A Personal Perspective

Mass spectrometry (MS) has become an essential tool in virtually all academic, pharmaceutical, and biopharmaceutical analytical laboratories. The specialized and bespoke area of MS research and application of high m / z ion (> m / z 6000 and high mass, >150 kDa) formation, transmission, analysis, and detection is a relatively new area of focus for MS that has seen dramatic acceleration in interest over the last two decades. Herein we delve into this exciting aspect of MS, discussing how MS instrumentation has been refined and evolved for native-MS analysis. We cover the early groundbreaking experiments showing high m / z ion formation, transmission, and preservation of protein structure in the gas phase. Additionally, we discuss specific instrument optimizations and modifications that have advanced high m / z ion generation, transmission, analysis, and detection, contributing to the research area known as gas-phase structural biology. Native-MS sample introduction methods, emerging technologies, and future perspectives are also examined. Finally, we share personal opinions, observations, and experiences that are new to the community or previously unpublished.

collisions↗
DOE OSTI2024

Reconfigurable spin current transmission and magnon–magnon coupling in hybrid ferrimagnetic insulators

Coherent spin waves possess immense potential in wave-based information computation, storage, and transmission with high fidelity and ultra-low energy consumption. However, despite their seminal importance for magnonic devices, there is a paucity of both structural prototypes and theoretical frameworks that regulate the spin current transmission and magnon hybridization mediated by coherent spin waves. Here, we demonstrate reconfigurable coherent spin current transmission, as well as magnon–magnon coupling, in a hybrid ferrimagnetic heterostructure comprising epitaxial Gd 3 Fe 5 O 12 and Y 3 Fe 5 O 12 insulators. By adjusting the compensated moment in Gd 3 Fe 5 O 12 , magnon–magnon coupling was achieved and engineered with pronounced anticrossings between two Kittel modes, accompanied by divergent dissipative coupling approaching the magnetic compensation temperature of Gd 3 Fe 5 O 12 (T M,GdIG ), which were modeled by coherent spin pumping. Remarkably, we further identified, both experimentally and theoretically, a drastic variation in the coherent spin wave-mediated spin current across T M,GdIG , which manifested as a strong dependence on the relative alignment of magnetic moments. Our findings provide significant fundamental insight into the reconfiguration of coherent spin waves and offer a new route towards constructing artificial magnonic architectures.

42 ENGINEERING↗
DOE OSTI2025

Ferroelectrically switched valley-dependent transmission in SnTe-PbTe-SnTe monolayer lateral heterostructures

A special class of valleytronic two-dimensional (2D) semiconductors possesses carrier pockets (i.e., valleys) along certain directions in the first Brillouin zone, which can be applied as a new degree of freedom for information storage and processing. Here we show that members of this family that are ferroelectric allow the location of these valleys to be switched by rotating the ferroelectric polarization. This makes possible the control of electronic state transmission probability through an energy barrier by ferroelectrically switching the polarization direction, thereby creating or eliminating valley matching in reciprocal space. We apply molecular beam epitaxy to grow lateral sandwich heterostructures with monolayer-thick ferroelectric SnTe separated by nanometer-wide paraelectric PbTe as the barriers. Using scanning tunneling microscopy, we show that the transmission probability of the 2D hole states at the valence band maximum of SnTe monolayer strongly relies on the relative orientation between the polarization directions of the two SnTe electrodes. The transmission can be switched from a suppressed state to a permitted state by rotating the ferroelectric polarization of one SnTe electrode by 90 degrees. Our work demonstrates the electric-field-control of valley locations and its potential for tunnel junction valleytronic devices.

electronic devices↗
DOE OSTI2023

Structural and immunological differences in Plasmodium falciparum sexual stage transmission-blocking vaccines comprised of Pfs25-EPA nanoparticles

Development of a malaria vaccine that blocks transmission of different parasite stages to humans and mosquitoes is considered critical for elimination efforts. A vaccine using Pfs25, a protein on the surface of zygotes and ookinetes, is under investigation as a transmission-blocking vaccine (TBV) that would interrupt parasite passage from mosquitoes to humans. The most extensively studied Pfs25 TBVs use Pichia pastoris-produced recombinant forms of Pfs25, chemically conjugated to a recombinant carrier protein, ExoProtein A (EPA). The recombinant form of Pfs25 first used in humans was identified as Pfs25H, which contained a total of 14 heterologous amino acid residues located at the amino- and carboxyl-termini including a His6 affinity tag. A second recombinant Pfs25, identified as Pfs25M, was produced to remove the heterologous amino acid residues and conjugated to EPA (Pfs25M-EPA). Here, monomeric Pfs25M was characterized biochemically and biophysically for identity, purity, and integrity including protein structure to assess its comparability with Pfs25H. Although the biological activities of Pfs25H and Pfs25M, whether generated by monomeric forms or conjugated nanoparticles, appeared similar, fine-mapping studies with two transmission-blocking monoclonal antibodies detected structural and immunological differences. In addition, evaluation of antisera generated against conjugated Pfs25H or Pfs25M nanoparticles in nonhuman primates identified polyclonal IgG that recognized these structural differences.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Non-reciprocal transmission of microwave acoustic waves in nonlinear parity–time symmetric resonators

Acoustic waves are versatile on-chip information carriers that can be used in applications such as microwave filters and transducers. Nonreciprocal devices, in which the transmission of waves is non-symmetric between two ports, are desirable for the manipulation and routing of phonons, but building acoustic non-reciprocal devices is difficult because acoustic systems typically have a linear response. Here, we report non-reciprocal transmission of microwave surface acoustic waves using a nonlinear parity–time symmetric system based on two coupled acoustic resonators in a lithium niobate platform. Furthermore, owing to the strong piezoelectricity of lithium niobate, we can tune the gain, loss and nonlinearity of the system using electric circuitry. Our approach can achieve 10 dB of non-reciprocal transmission for surface acoustic waves at a frequency of 200 MHz, and we use it to demonstrate a one-way circulation of acoustic waves in cascading non-reciprocal devices.

42 ENGINEERING↗
DOE OSTI2024

Slitless spectrophotometry with forward modelling: Principles and application to measuring atmospheric transmission

Context.In the next decade, many optical surveys will aim to answer the question of the nature of dark energy by measuring its equation-of-state parameter at the per mill level. This requires trusting the photometric calibration of the survey with a precision never reached so far on many sources of systematic uncertainties. The measurement of the on-site atmospheric transmission for each exposure, or for each season or for the full survey on average, can help reach the per mill precision for the magnitudes. Aims.This work aims at proving the ability to use slitless spectroscopy for standard-star spectrophotometry and its use to monitor on-site atmospheric transmission as needed, for example, by theVera C. RubinObservatory Legacy Survey of Space and Time supernova cosmology program. We fully deal with the case of a disperser in the filter wheel, which is the configuration chosen in theRubinAuxiliary Telescope. Methods.The theoretical basis of slitless spectrophotometry is at the heart of our forward-model approach to extract spectroscopic information from slitless data. We developed a publicly available software calledSpectractor, which implements each ingredient of the model and finally performs a fit of a spectrogram model directly on image data to obtain the spectrum. Results.We show through simulations that our model allows us to understand the structure of spectrophotometric exposures. We also demonstrate its use on real data by solving specific issues and illustrating that our procedure allows the improvement of the model describing the data. Finally, we discuss how this approach can be used to directly extract atmospheric transmission parameters from the data and thus provide the base for on-site atmosphere monitoring. We show the efficiency of the procedure in simulations and test it on the limited available data set.

Astronomy & Astrophysics↗
DOE OSTI2023

Neutron Capture and Transmission Measurements of 54 Fe at the RPI LINAC

54 Fe radiative capture cross section and transmission measurements were conducted at the Rensselaer Polytechnic Institute (RPI) Gaerttner Linear Accelerator (LINAC) Center using an enriched 54 Fe sample in the keV energy region. 54 Fe is a constituent of natural iron, which is present in a large variety of nuclear grade materials. Therefore, it is important to have an accurate understanding of the cross sections of 54 Fe, which can be measured experimentally. In the time-of-flight measurements conducted at the LINAC, an array of four C 6 D 6 detectors surrounded the sample and radiative capture data were collected using a digital data acquisition system. Additionally, a Li-glass detector was used to collect transmission data using an analog data acquisition system. The radiative capture yield of the 54 Fe measurements were normalized to saturated resonances observed in Au and Ta to obtain an absolute capture yield. The preliminary capture yield and preliminary transmission obtained can be compared to evaluations and existing experimental data. Some disagreements were observed in prominent d-wave capture resonances observed in 54 Fe in the low-keV neutron energy region. Both sets of experimental data along with pre-existing datasets will greatly enhance RPI’s ability to perform resonance evaluation for 54 Fe up to roughly 1 MeV.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Low power on-chip data transmission for wafer-scale monolithic active pixel sensors

Here, this paper details the implementation of the digital pulse shaping subsystem within the Backbone Transmission Line Encoding (BTLE) driver, a low-power, long-distance on-chip data transmission solution designed in a 65 nm CMOS process. Digital pulse shaping is critical for minimizing inter-symbol interference (ISI) caused by bandwidth limitations of on-chip interconnects, especially in wafer-scale monolithic active pixel sensors (MAPS). A duobinary encoder coupled with a parallelized polyphase finite impulse response (FIR) filter is used for efficient shaping of the transmitted signal spectrum. This reconfigurable architecture achieves reliable 160 Mb/s data transfer over a 10 cm on-chip link, as validated by simulations demonstrating low power consumption (FoM 37.3 fJ/bit/mm of transmission line length) and effective ISI mitigation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Endogenous Interface Pricing for Consistent Transmission–Distribution Co-Optimization With Discrete Distribution Controls

This paper proposes an endogenous interface pricing model for day-ahead transmission–distribution co-optimization that co-determines the interface locational marginal price (LMP) and the transmission–distribution exchange, ensuring price–dispatch consistency while optimally scheduling discrete distribution controls. The formulation couples a DC optimal power flow (OPF) with a branch-flow AC OPF that schedules distributed energy resources (DERs), tap-changer settings, capacitor banks (CBs), and multi-period energy storage systems (ESSs) under feeder voltage and current limits, and is solved as a mixed-integer second-order cone program (MISOCP). In a T14–D33 system, coordinated device scheduling recovers about 90% of the distribution-to-transmission export achievable in a reference case that ignores distribution network (DN) limits, while satisfying a 1.05 p.u. voltage upper bound. In a T39–D34/D37/D123 system, a sequential decoupled benchmark produces interface LMP distortions up to 12.5% and a 7.28% mismatch in net export energy, whereas the proposed model removes these distortions and the associated settlement mismatches. Second-order cone (SOC) relaxation gaps remain below $10^{-3}$ in all cases.

Noh, Seung-Gil↗
DOE OSTI2022

Semi-Supervised Disaggregation of Load Profiles at Transmission Buses with Significant Behind-the-Meter Solar Generations

It is of imperative interests for regional transmission organizations (RTOs) to effectively extract daily load profiles at transmission buses, which remains a gap in existing technology paradigm. This digest proposes an explicit yet efficient linear estimator, to disaggregate metered load profiles at buses with significant behind-the-meter (BTM) solar generations in a data driven manner. The proposed estimator is based on utility zonal load profiles and proxy solar irradiance profiles, which in reality is the aggregated waveform at each transmission bus and equivalent to the mix of summed load profiles minus actual BTM solar generation. To overcome technical challenges in the lack of “ground truth” and validate the performance of supervised learning algorithms, we propose semi-supervised mechanisms with parameter tuning, and leverage the unique characteristics of zero-crossing points in BTM solar peaking behaviors.

machine leaning, behind-the-meter, power grid anal↗
DOE OSTI2024

Data-Driven Invertible Neural Surrogates of Atmospheric Transmission

We present Data-Driven Invertible Neural Surrogates of Atmospheric transmission, or DINSAT. DINSAT is a novel framework for inferring an atmospheric transmission profile from a spectral scene. This framework leverages a lightweight, physics-based simulator that is automatically tuned -- by virtue of autodifferentiation and differentiable programming -- to construct a surrogate atmospheric profile to model the observed data. The framework has utility in (i) performing atmospheric correction, (ii) recasting spectral data between various modalities (e.g. radiance and reflectance at the surface and at the sensor), and (iii) inferring atmospheric transmission profiles, such as absorbing bands and their relative magnitudes. We demonstrate the utility of these methods by performing a canonical atmospheric correction task for the purposes of further analysis - in this case, target detection within a scene.

Koch, James V.↗
DOE OSTI2024

Transmission Data-Driven User-Defined Model for Inverter-based and Conventional Power Plants

Recent events in Odessa [1], [2] have shed light on the complexities of integrating large Inverter-Based Resource (IBR) plants with the transmission system, prompting NERC to stress continuous performance monitoring by transmission operators. Challenges such as plant control updates, IBR model revisions, Phase-locked loop loss of synchronism, and protection events have been identified, underscoring the need for enhanced monitoring protocols by regulatory bodies. The recent FERC 901 order underscores the importance of accurate data exchange regarding IBRs for reliability studies. However, limited access to IBR plant-related data hampers effective decision-making for transmission operators (TOP). This paper proposes a method for constructing data-driven User-Defined dynamic Models (UDM) for power plants for validating multiple-event data using field measurements from interconnection bus locations. The problem is formulated as a power plant model identification problem and a multi-task learning approach under partial input observability assumptions is proposed in this work. This approach aims to predict aggregated responses of conventional and IBR power plants during various dynamic physical events which is useful for planning studies under diverse disturbance conditions. Ultimately, this methodology emphasizes the importance of plant visibility to operators in addressing power system challenges, facilitating improved planning and operational studies.

Mahapatra, Kaveri [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2024

Technical Impacts of Light-Duty and Heavy-Duty Transportation Electrification on a Coordinated Transmission and Distribution System

In this study, we propose a strategy to model the required spatiotemporal charging demand from light-duty (LD) and medium- and heavy-duty (MHD) electric vehicles (EVs) using actual transportation data by mapping the demand for the required EV charging to a realistic and coordinated distribution and transmission electric grid at the predicted times of the day to study their impact on the power system in a variety of load, weather, and EV penetration scenarios. This work is the first study that includes the actual weather data and transportation data with realistic and coordinated distribution and transmission grid data in a large industry-scale level study. The main goal of this study is to identify possible issues and required upgrades in the electric grid, caused by an increase in EV integration. The transmission case study is a large grid with 6717 buses over a Texas footprint, and the distribution grid is over Houston, a city in Texas, covering over three million customers. The resulting overloads and voltage violations experienced in the system are discussed, and required planning upgrades to avoid these issues are suggested.

AC optimal power flow (AC-OPF)↗
DOE OSTI2026

Dynamic Transmission Line Switching Amid Wildfire-Prone Weather Under Decision-Dependent Uncertainty

During dry and windy seasons, environmental conditions significantly increase the risk of wildfires, exposing power grids to disruptions caused by transmission line failures. Wildfire propagation exacerbates grid vulnerability, potentially leading to prolonged power outages. To address this challenge, we propose a multistage optimization model that dynamically adjusts transmission grid topology in response to wildfire propagation, aiming to develop an optimal response policy. By accounting for decision-dependent uncertainty, where line survival probabilities depend on usage, we employ distributionally robust optimization to model uncertainty in line survival distributions. We adapt the stochastic nested decomposition algorithm and derive a deterministic upper bound for its finite convergence. To enhance computational efficiency, we exploit the Lagrangian dual problem structure for a faster generation of Lagrangian cuts. Using realistic data from the California transmission grid, we demonstrate the superior performance of dynamic response policies against two-stage alternatives through a comprehensive case study. In addition, after solving the multistage formulation, we construct easy-to-implement policies that significantly reduce computational burden while maintaining good performance in real-time deployment. History: Accepted by Russell Bent, Area Editor for Network Optimization: Algorithms and Applications. Funding: This work was supported by the U.S. Department of Energy, Office of Electricity [Grant DE-AC02-05CH11231]. The work of R. Jiang was supported in part by the U.S. National Science Foundation, Division of Electrical, Communications and Cyber Systems [Grant ECCS-1845980] and the U.S. Air Force Office of Scientific Research [Grant FA9550-23-1-0323]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2025.1210 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2025.1210 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Estrada-Garcia, Juan-Alberto↗
DOE OSTI2023

Quantification of early nonpharmaceutical interventions aimed at slowing transmission of Coronavirus Disease 2019 in the Navajo Nation and surrounding states (Arizona, Colorado, New Mexico, and Utah)

During an early period of the Coronavirus Disease 2019 (COVID-19) pandemic, the Navajo Nation, much like New York City, experienced a relatively high rate of disease transmission. Yet, between January and October 2020, it experienced only a single period of growth in new COVID-19 cases, which ended when cases peaked in May 2020. The daily number of new cases slowly decayed in the summer of 2020 until late September 2020. In contrast, the surrounding states of Arizona, Colorado, New Mexico, and Utah all experienced at least two periods of growth in the same time frame, with second surges beginning in late May to early June. Here, we investigated these differences in disease transmission dynamics with the objective of quantifying the contributions of non-pharmaceutical interventions (NPIs) (e.g., behaviors that limit disease transmission). We considered a compartmental model accounting for distinct periods of NPIs to analyze the epidemic in each of the five regions. We used Bayesian inference to estimate region-specific model parameters from regional surveillance data (daily reports of new COVID-19 cases) and to quantify uncertainty in parameter estimates and model predictions. Our results suggest that NPIs in the Navajo Nation were sustained over the period of interest, whereas in the surrounding states, NPIs were relaxed, which allowed for subsequent surges in cases. Our region-specific model parameterizations allow us to quantify the impacts of NPIs on disease incidence in the regions of interest.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Age-specific case data reveal varying dengue transmission intensity in US states and territories

Dengue viruses (DENV) are endemic in the US territories of Puerto Rico, American Samoa, and the US Virgin Islands, with focal outbreaks also reported in the states of Florida and Hawaii. However, little is known about the intensity of dengue virus transmission over time and how dengue viruses have shaped the level of immunity in these populations, despite the importance of understanding how and why levels of immunity against dengue may change over time. These changes need to be considered when responding to future outbreaks and enacting dengue management strategies, such as guiding vaccine deployment. We used catalytic models fitted to case surveillance data stratified by age from the ArboNET national arboviral surveillance system to reconstruct the history of recent dengue virus transmission in Puerto Rico, American Samoa, US Virgin Islands, Florida, Hawaii, and Guam. We estimated average annual transmission intensity (i.e., force of infection) of DENV between 2010 and 2019 and the level of seroprevalence by age group in each population. We compared models and found that assuming all reported cases are secondary infections generally fit the surveillance data better than assuming all cases are primary infections. Using the secondary case model, we found that force of infection was highly heterogeneous between jurisdictions and over time within jurisdictions, ranging from 0.00008 (95% CrI: 0.00002–0.0004) in Florida to 0.08 (95% CrI: 0.044–0.14) in American Samoa during the 2010–2019 period. For early 2020, we estimated that seropositivity in 10 year-olds ranged from 0.09% (0.02%–0.54%) in Florida to 56.3% (43.7%–69.3%) in American Samoa. In the absence of serological data, age-specific case notification data collected through routine surveillance combined with mathematical modeling are powerful tools to monitor arbovirus circulation, estimate the level of population immunity, and design dengue management strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don’t yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A Compton transmission polarimeter for DC and SRF electron photo-injectors

The production of high-current and intense spin polarized electron beams is of great importance in electron-based facilities. Tests are planned to produce such beams in 2023 using GaAs-based photocathodes installed in the Brookhaven National Lab RHIC Coherent electron Cooling superconducting radiofrequency (SRF) photogun [1]. A fast and efficient electron polarimeter operating in the MeV energy range is required to measure the beam spin polarization. While Mott polarimeters provide larger measured asymmetries, a Compton Transmission polarimeter is well suited in the few MeV energy range. In this work, we report on a relatively compact and cost-effective Compton transmission polarimeter which has been built and calibrated at Jefferson Lab (JLab). First, we present the design of the polarimeter radiator, polarized target analyzing magnet, BGO detector assembly and data acquisition system. Next, results of a two-week commissioning study performed at the JLab Upgraded Injector Test Facility will be described. Here, a well-known polarized electron beam produced from a bulk GaAs photocathode in a dc high-voltage photogun was first measured in a 180 keV Mott scattering polarimeter, then used to characterize and calibrate the Compton transmission polarimeter as a function of the polarized target magnetization and beam properties. Finally, we report an effective analyzing power of the Compton polarimeter and compare experimental results with those produced via Geant4 simulations.

Blume, G.↗