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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

X-ray Ptychography Imaging of Human Chromosomes After Low-dose Irradiation

Abstract Studies of the structural and functional role of chromosomes in cytogenetics have spanned more than 10 decades. In this work, we take advantage of the coherent X-rays available at the latest synchrotron sources to extract the individual masses of all 46 chromosomes of metaphase human B and T cells using hard X-ray ptychography. We have produced ‘X-ray karyotypes’ of both heavy metal–stained and unstained spreads to determine the gain or loss of genetic material upon low-level X-ray irradiation doses due to radiation damage. The experiments were performed at the I-13 beamline, Diamond Light Source, Didcot, UK, using the phase-sensitive X-ray ptychography method.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Effect of stoichiometry and hydration level on water domain size and transport in poly(aryl piperidinium) alkaline anion-exchange membranes

Alkaline water electrolysis holds promise in decarbonizing the global economy by enabling renewable hydrogen production with non-precious group metal catalysts. Anion exchange membranes are an important component of alkaline water electrolyzers and would ideally be durable while allowing for high hydroxide conductivity. The poly(aryl piperidinium) (PAP) class of polymers has attracted recent interest due to their good mechanical robustness and high ionic conductivity. Here, in this work, we perform atomistic molecular dynamics (MD) simulations of several PAP polymers at experimentally relevant hydration levels and polymer ion exchange capacities (IECs) to gain nanoscale insight into their properties and to help elucidate the trade-offs that result from tuning the IECs through the polymer stoichiometry. Our MD-predicted macroscopic polymer properties were found to be in good agreement with experimentally available polymer swelling ratios, water-occupied volumes, X-ray scattering, and ionic conductivities. The models show that for hydration levels greater than 8H 2 O per cation a single water cluster will form that percolates through the system. The growth in water cluster size results in large polymer swelling, the creation of larger channels with widths of 7 Å or larger, and nanophase separation between the hydrophilic domains and the polymer with characteristic length scales of approximately 20–30 Å. The experimentally observed lack of a strong X-ray scattering peak at low wavevectors can be explained by a cancellation between the polymer-polymer/water-water and polymer-water correlations and not a loss in nanophase separation. The overlap in coordination environments of the hydroxide oxygen and polymer nitrogen atoms implies that vehicular diffusion between cationic groups could play a role in hydroxide transport. The polymers' hydroxide and water diffusion constants increase by approximately an order of magnitude between hydration levels of 8 and 20H 2 O per cation. However, there are diminishing returns in hydroxide diffusion constant once the IEC exceeds 2.4 meq/g.

08 HYDROGEN↗
DOE OSTI2026

Machine Learning Calibration of Groundwater Table Depth in ELM: Impact on Land Surface Hydrology and Land‐Atmosphere Fluxes

Accurate representation of groundwater table depth (GWTD) is crucial for simulating hydrological cycling in Earth system models (ESM). Nevertheless, there is a notable gap in the literature regarding the validation of GWTD simulations in ESMs and their subsequent impact on downstream hydrological components. This study explores the calibration of parameterization of global GWTD using machine learning within the Energy Exascale Earth System Model (E3SM) Land Model (ELM). Despite achieving significant gains in simulating GWTD through calibration, offline ELM simulations unexpectedly show that these improvements do not translate to substantial enhancements in model performance for other key hydrological variables, including soil moisture (SM), runoff, groundwater contribution to runoff or base flow index (BFI), and evapotranspiration and its partitioning. The performance in SM and runoff was even degraded in some regions, while BFI was mostly overestimated. Although there is significant improvement in GWTD within the critical range of 1–5 m, where groundwater traditionally influences land surface energy fluxes, these improvements occurred mostly in humid areas where the impact of GWTD on surface processes is minimal. Although the impacts of model calibration are generally small in offline ELM simulations, coupled land-atmosphere simulations exhibit much stronger responses to GWTD calibration, highlighting the role of land-atmosphere feedbacks in Earth system modeling. These findings underscore the need for integrated calibration strategies that simultaneously optimize multiple hydrological variables. However, if a single-variable approach is necessary, it is crucial to establish clear priorities for calibration, identifying the most critical variables that have the greatest impact on overall model performance.

Fang, Yilin [Pacific Northwest National Laboratory↗
DOE OSTI2022

Identifying Modular Construction Worker Tasks Using Computer Vision

Modular construction is increasingly being seen as an attractive method for delivering building projects due to advantages in safety, quality, and lead-time. Despite these benefits, this method still relies heavily on human labor, which causes variability in factory assembly-line performance that can erode performance benefits of modular construction. Continuous improvement methods can alleviate some of these issues, but they also require continuous monitoring of human workers' performance. Due to limitations of manual time study and automated sensor-based monitoring methods, recently computer vision-based methods have gained momentum in identifying the activities of construction workers from the videos of onsite construction. Therefore, this paper explores the use of computer vision-based human activity recognition techniques to identify and classify worker activities in modular construction videos. Computer vision-based tracking method has been used to track the human workers in each frame, and Resnet-50 network has been used to classify the activity of tracked workers. Evaluation of this framework has achieved higher than 90% accuracy and recall in testing.

computer vision↗
DOE OSTI2020

Improved Fireset Acceptance Using Established Evaluation Measurements

As new insight is gained into the relationship between firesets and detonators, tighter control of the circuit parameters is desired to maintain consistent and optimum system performance. An analysis of the established acceptance method reveals that it has insufficient precision to guarantee a uniform population of units. While the production has been historically very uniform, the uniformity has been primarily due to the quality and consistency of the manufacturing process rather than to the stringency of the acceptance criteria. The established method of evaluating and accepting firesets for the stockpile has been to discharge the units into a representative load and to record the output current waveform. Three characteristics of the output waveform (Peak Current, Rise Time, and Pulse Width) are then analyzed and an acceptance window is applied directly to these measurements. The purpose of this paper is to introduce a new approach that incorporates these same established measurements. However, instead of applying acceptance criteria to the three measurements directly, rather these measurements are used to evaluate the circuit values of capacitance, inductance and resistance to provide a more stringent and uniform acceptance criteria.

42 ENGINEERING↗
DOE OSTI2023

Increased power gains from wake steering control using preview wind direction information

Abstract. Yaw controllers typically rely on measurements taken at the wind turbine, resulting in a slow reaction to wind direction changes and subsequent power losses due to misalignments. Delayed yaw action is especially problematic in wake steering operation because it can result in power losses when the yaw misalignment angle deviates from the intended one due to a changing wind direction. This study explores the use of preview wind direction information for wake steering control in a two-turbine setup with a wind speed in the partial load range. For these conditions and a simple yaw controller, results from an engineering model identify an optimum preview time of 90 s. These results are validated by forcing wind direction changes in a large-eddy simulation model. For a set of six simulations with large wind direction changes, the average power gain from wake steering increases from only 0.44 % to 1.32 %. For a second set of six simulations with smaller wind direction changes, the average power gain from wake steering increases from 1.24 % to 1.85 %. Low-frequency fluctuations are shown to have a larger impact on the performance of wake steering and the effectiveness of preview control, in particular, than high-frequency fluctuations. From these results, it is concluded that the benefit of preview wind direction control for wake steering is substantial, making it a topic worth pursuing in future work.

17 WIND ENERGY↗
DOE OSTI2020

Passive bias temperature compensation circuit module

A passive bias temperature compensation module for silicon photomultiplier, avalanche photodiodes and similar photodetectors that possess a moderately linear temperature coefficient of gain and that may be compensated by varying an applied bias voltage. The module includes an electrical circuit and a method for determining component values to provide a constant voltage source to stabilize the gain of one or more photodetector devices. A temperature sensor in the module is held in close thermal contact with the photodetector and a filter capacitor is electrically close to the photodetector. The module is based on the concept of temperature sensitive voltage division which is applicable to situations in which large numbers of photodetectors must be gain-compensated for temperature variations over a wide range while maintaining excellent gain matching. The passive bias temperature compensation method enables multiple photodetectors to share a single constant voltage supply without loss of matching performance.

42 ENGINEERING↗
DOE OSTI2022

Transforming U.S. Particle Physics Education: A Snowmass 2021 Study

The pursuit of knowledge in particle physics requires constant learning. As new tools become available, new theories are developed, and physicists search for new answers with ever-evolving methods. However, it is the case that formal educational systems serve as the primary training grounds for particle physicists. Graduate school (and undergraduate school to a lesser extent) is where researchers learn most of the technical skills required for research, develop scientific problem-solving abilities, learn how to establish themselves in their field, and begin developing their career. It is unfortunate, then, that the skills gained by physicists during their formal education are often mismatched with the skills actually required for a successful career in physics. We performed a survey of the U.S. particle physics community to determine the missing elements of graduate and undergraduate education and to gauge how to bridge these gaps. In this contributed paper, part of the 2021-22 Snowmass Community Planning Exercise, we report the results of this survey. We also recommend several specific community actions to improve the quality of particle physics education; the "community" here refers to physics departments, national labs, professional societies, funding agencies, and individual physicists.

Bitter, O.↗
DOE OSTI2024

Two-Step Hyperparameter Optimization Method: Accelerating Hyperparameter Search by Using a Fraction of a Training Dataset

Abstract Hyperparameter optimization (HPO) is an important step in machine learning (ML) model development, but common practices are archaic—primarily relying on manual or grid searches. This is partly because adopting advanced HPO algorithms introduces added complexity to the workflow, leading to longer computation times. This poses a notable challenge to ML applications, as suboptimal hyperparameter selections curtail the potential of ML model performance, ultimately obstructing the full exploitation of ML techniques. In this article, we present a two-step HPO method as a strategic solution to curbing computational demands and wait times, gleaned from practical experiences in applied ML parameterization work. The initial phase involves a preliminary evaluation of hyperparameters on a small subset of the training dataset, followed by a reevaluation of the top-performing candidate models postretraining with the entire training dataset. This two-step HPO method is universally applicable across HPO search algorithms, and we argue it has attractive efficiency gains. As a case study, we present our recent application of the two-step HPO method to the development of neural network emulators for aerosol activation. Although our primary use case is a data-rich limit with many millions of samples, we also find that using up to 0.0025% of the data—a few thousand samples—in the initial step is sufficient to find optimal hyperparameter configurations from much more extensive sampling, achieving up to 135× speedup. The benefits of this method materialize through an assessment of hyperparameters and model performance, revealing the minimal model complexity required to achieve the best performance. The assortment of top-performing models harvested from the HPO process allows us to choose a high-performing model with a low inference cost for efficient use in global climate models (GCMs).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Integration of full divertor detachment with improved core confinement for tokamak fusion plasmas

Divertor detachment offers a promising solution to the challenge of plasma-wall interactions for steady-state operation of fusion reactors. Here, we demonstrate the excellent compatibility of actively controlled full divertor detachment with a high-performance (β N ~ 3, H 98 ~ 1.5) core plasma, using high-β p (poloidal beta, β p > 2) scenario characterized by a sustained core internal transport barrier (ITB) and a modest edge transport barrier (ETB) in DIII-D tokamak. The high-β p high-confinement scenario facilitates divertor detachment which, in turn, promotes the development of an even stronger ITB at large radius with a weaker ETB. This self-organized synergy between ITB and ETB, leads to a net gain in energy confinement, in contrast to the net confinement loss caused by divertor detachment in standard H-modes. These results show the potential of integrating excellent core plasma performance with an efficient divertor solution, an essential step towards steady-state operation of reactor-grade plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

ChemComp: Compiling and Computing with Chemical Reaction Networks

The exponential growth in computing demands driven by scientific computing, data analytics, and artificial intelligence is pushing conventional CMOS-based high-performance computing systems to their physical and energy efficiency limits. As we approach the era of post-exascale computing, disruptive approaches are necessary to overcome these barriers and achieve substantial gains in energy efficiency. Analog and hybrid digital-analog computing systems have emerged as promising alternatives, offering the potential for orders-of-magnitude improvements in efficiency. Among these, biochemical computing stands out as a novel paradigm capable of leveraging the natural efficiency of chemical reactions, which have shown promise in solving optimization problems by converging to steady states. By scaling up reaction networks or reaction vessel sizes, biochemical systems present an opportunity to meet the high-performance demands of modern computing tasks. Despite their promise, significant theoretical and practical challenges remain, particularly in formulating and mapping computational problems to chemical reaction networks (CRNs) and designing viable biochemical computing devices. This paper addresses these challenges by introducing new ideas to ChemComp, a compilation and emulation framework for chemical computation. This work describes the mechanisms through which solutions to ordinary differential equations (ODEs) that can be represented as CRN systems can be achieved. Furthermore, we explain the design principles of an ODE dialect implemented as a multi-level intermediate representation (MLIR) compiler extension that will be coupled with existing infrastructure. We demonstrate the potential of our framework through a case study emulating a simplified chemical reservoir computing device. This work establishes foundational tools and methodologies necessary to harness the computational power of chemistry, paving the way for the development of energy-efficient, high-performance computing systems tailored to contemporary and future computational needs.

Bohm Agostini, Nicolas↗
DOE OSTI2020

Adaptive model tuning studies for non-invasive diagnostics and feedback control of plasma wakefield acceleration at FACET-II

Beam-driven plasma wakefield acceleration (PWFA) achieves the same energy gain in a single meter, for which conventional accelerators require several kilometers, however much work is still required to match the beam quality of conventional accelerators. The PWFA processes to be studied at the FACET-II facility will utilize extremely short (down to a few fs) high energy (10 GeV), high charge (few nC) electron and eventually positron bunches. The PWFA process is extremely sensitive to the detailed longitudinal current profiles of these bunches and it would be of great benefit to have precise measurement and control of these profiles. We present an adaptive model tuning technique for FACET-II to adaptively tune online models based on real time accelerator and beam data to continuously provide a non-invasive diagnostic which predicts the longitudinal phase space (LPS) of extremely short and highly compressed electron beams, which otherwise require destructive X-band transverse deflecting cavity (XTCAV)-based measurements. Based on simulation studies, our method has the potential for: (1). The development of a non-invasive longitudinal phase space diagnostic by adaptively tuning models based on non-invasive measurements such as energy spread spectra which could be recorded at all of the bunch compressors in the facility. (2). Utilize these diagnostic to perform model-independent feedback-based to achieve desired longitudinal phase space distributions. (3). Utilize the model-independent feedback approach to maximize energy gain while minimizing emittance growth and energy gain variance of the PWFA process by tuning accelerator parameters, while monitoring what longitudinal phase space the algorithm has found, information that will be useful for further analytical and simulation studies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

A lightweight method for evaluating in situ workflow efficiency

Performance evaluation is crucial to understanding the behavior of scientific workflows. In this study, we target an emerging type of workflow, called in situ workflows. These workflows tightly couple components such as simulation and analysis to improve overall workflow performance. To understand the tradeoffs of various configurable parameters for coupling these heterogeneous tasks, namely simulation stride, and component placement, separately monitoring each component is insufficient to gain insights into the entire workflow behavior. Through an analysis of the state-of-the-art research, we propose a lightweight metric, derived from a defined in situ step, for assessing resource usage efficiency of an in situ workflow execution. By applying this metric to a synthetic workflow, which is parameterized to emulate behaviors of a molecular dynamics simulation, we explore two possible scenarios (Idle Simulation and Idle Analyzer) for the characterization of in situ workflow execution. In addition to preliminary results from a recently published study [11], we further exploit the proposed metric to evaluate a practical in situ workflow with a real molecular dynamics application, i.e., GROMACS. Here, experimental results show that the in transit placement (analytics on dedicated nodes) sustains a higher frequency for performing in situ analysis compared to the helper-core configuration (analytics co-allocated with simulation).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Advanced defrosting techniques in air source heat pumps: A review of vapor injection, thermal energy storage, and experimental frost accumulation data

Electrification is a critical step for reducing greenhouse gas emissions from heating. Air source heat pumps (ASHPs) are a promising alternative to fossil fuel-based systems due to their high coefficients of performance (COP), dual heating and cooling capability, and lower carbon footprint. However, for ASHPs to achieve widespread adoption, they must operate reliably across all climates, including cold regions. Additionally, defrosting techniques should be energy efficient and minimally disruptive to indoor comfort. Vapor injection (VI) technology can address the high-pressure and high-temperature lift challenges encountered in low ambient conditions. More recently, in addition to enhancing heating performance, VI has also been shown to improve the speed and efficiency of reverse cycle defrosting. Likewise, thermal energy storage (TES) has steadily gained attention for its ability to serve as an auxiliary heat source during both normal operation and defrosting. This review analyzes the benefits and limitations of VI- and TES-assisted defrosting approaches. While both technologies show strong potential individually, no studies to date have explored their combined use in ASHP systems. Additionally, to support continued development of defrosting strategies, both in modeling and experimental work, it is critical to establish frost accumulation data under a range of operating conditions. By compiling the available data from the literature, this paper also highlights the limited availability of such experimental data and the wide variation in frosting and defrosting durations and termination criteria, which are often influenced by system design and test setups.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

A numerical study of the spectral radiative properties of packed bed with mixed bauxite and silica spheres

Bauxite and silica particles have gained increasing attention for applications in the field of concentrated solar power. In this work, a Monte Carlo ray-tracing simulation is performed to predict the radiative properties (absorptance, reflectance, and transmittance) of packed beds with mixed bauxite and silica spherical particles at wavelengths of 0.5, 2.6, 9.0, and 9.35 µm. These wavelengths are representative for the visible, near-infrared, and the mid-infrared regions that are important for solar and thermal radiation, respectively. A repeating unit-column approach is used to mathematically represent the particle bed. The effects of particle mixing ratio, volume fraction, and wavelength on the predicted radiative properties are examined. The obtained radiative properties are inputted to an inverse method to retrieve the effective absorption and scattering coefficients as well as the scattering albedo, which may be later used in a continuous-scale radiative heat transfer analysis. Furthermore, the independent scattering model is used to obtain the absorption coefficient and scattering albedo based on the absorption and scattering cross sections predicted by a Monte Carlo algorithm for a single particle. It is shown that the independent scattering model underpredicts the scattering coefficient for opaque particles but overpredicts the scattering coefficient for semitransparent particles for sufficiently high particle volume fractions. Here, the radiative properties calculated from the independent scattering model are compared to the full Monte Carlo simulation of the particle bed to examine the influence of particle mixing on dependent scattering.

42 ENGINEERING↗
DOE OSTI2025

Creation of Self-Semi-Interpenetrating Network Structures in PIM-1 Membranes for Enhanced Physical Aging Resistance

A series of self-semi-interpenetrating network (ssIPN) thin films based on PIM-1 structure were developed by end-cross-linking telechelic PIM-1 oligomers end-capped with curable carboxylic acid groups to form model networks, which are penetrated by linear high-molecular-weight PIM-1 chains. ssIPN films with systematically varied network content ranging from 10 to 30 wt % were comprehensively examined on their microstructure and gas permeation properties. Fresh PIM-1 ssIPN films exhibited gas separation performances close to those of as-cast linear PIM-1, where the films closely followed the upper bound trade-off line, gaining as much selectivity as they lose gas permeability as the network content increases. This indicates that gas permeability is largely preserved despite cross-linking. Wide-angle X-ray scattering supported this observation, with peaks shifting toward lower d-spacing as oligomer content increased, suggesting tighter chain packing with higher cross-linkable oligomer loading. In physical aging studies over two months, all ssIPN films outperform linear PIM-1 for H 2 /CH 4 and O 2 /N 2 separations. Notably, the PIM-1 ssIPN with 10 wt % network content showed the best physical aging resistance, with negligible permeability loss even after one month. Finally, these findings highlight a promising macromolecular strategy for enhancing the physical aging resistance of microporous polymer membranes for gas separation.

PIM-1↗
DOE OSTI2020

A native oxide high-κ gate dielectric for two-dimensional electronics

Silicon-based transistors are approaching their physical limits and thus new high-mobility semiconductors are sought to replace silicon in the microelectronics industry. Both bulk materials (such as silicon-germanium and III–V semiconductors) and low-dimensional nanomaterials (such as one-dimensional carbon nanotubes and two-dimensional transition metal dichalcogenides) have been explored, but, unlike silicon, which uses silicon dioxide (SiO 2 ) as its gate dielectric, these materials suffer from the absence of a high-quality native oxide as a dielectric counterpart. This can lead to compatibility problems in practical devices. Here, we show that an atomically thin gate dielectric of bismuth selenite (Bi 2 SeO 5 ) can be conformally formed via layer-by-layer oxidization of an underlying high-mobility two-dimensional semiconductor, Bi 2 O 2 Se. Using this native oxide dielectric, high-performance Bi 2 O 2 Se field-effect transistors can be created, as well as inverter circuits that exhibit a large voltage gain (as high as 150). The high dielectric constant (~21) of Bi 2 SeO 5 allows its equivalent oxide thickness to be reduced to 0.9 nm while maintaining a gate leakage lower than thermal SiO 2 . The Bi 2 SeO 5 can also be selectively etched away by a wet chemical method that leaves the mobility of the underlying Bi 2 O 2 Se semiconductor almost unchanged.

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

High throughput exploration of the oxidation landscape in high entropy alloys

We report high entropy alloys (HEAs) have gained interest for structural applications in extreme environments. With a potentially vast chemical and phase space, there are significant opportunities to discover superior performing alloys. Crucial for most high-temperature applications is understanding and mitigating the oxidation behavior of these chemically complex alloys. Most experimental and computational HEA studies have focused on a limited set of compositions and only a fraction these compositions have been characterized for oxidation. We present a high-throughput framework that utilizes density-functional theory (DFT) in concert with a combined machine-learning model and grand-canonical linear programming for assessing phase stability, phase-fraction, chemical activity and high-temperature survivability of arbitrary HEAs. This framework considers temperature dependent contributions to the Gibbs energy of the competing phases arising from short-range order and vibrational entropy. We demonstrate the effectiveness of the framework by assessing the thermodynamic stability, oxidation behavior, chemical activity, and phase decomposition of body-centered cubic Mo-W-Ta-Ti-Zr refractory HEAs. A total of 51 compositions were analyzed and ranked in order of their survivability based on the Pareto-front analysis. Oxidation was performed at 1373 K on fours samples in air showing the difference in oxidation behavior determined experimentally through scale thickness and their mass changes. The insights on oxidation behavior presented in this work will enable the fast assessment of technologically useful HEAs needed for future structural application in extreme conditions

36 MATERIALS SCIENCE↗