Search NASA⌕ Search

SEARCH · Search NASA

Results for “next”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

Evaluation and optimization of flow boiling frictional pressure drop correlations using the data from traditional and next-generation refrigerants in a micro-fin tube

This study presents an experimental evaluation and optimization of flow boiling frictional pressure drop correlations for conventional and next-generation refrigerants in a horizontal micro-fin tube, with particular emphasis on the newly emerging refrigerant blends R-454C and R-455A, for which pressure-drop data in enhanced tubes remain limited. Experiments were conducted with R-410A, R-454C, R-455A, R-134a, R-1234yf, and R-1234ze(E) in a copper micro-fin tube with an inner diameter of 8.468 mm, over mass fluxes ranging from 100 to 300 kg/(m²·s) depending on the refrigerant, and evaporation temperatures of 7, 12, and 14 °C. Frictional pressure gradients were determined from measured total pressure drops after subtracting acceleration pressure drop, and the resulting database was used to assess four existing models: Kuo and Wang (1996), Cavallini et al. (1997), Goto et al. (2001), and Diani et al. (2014). The measured frictional pressure gradient increased with vapor quality and mass flux for all refrigerants and increased further at lower evaporation temperatures, with the overall trend strongly related to liquid viscosity. Among the four correlations, the Goto et al. (2001) model provided the best overall agreement with the measured data before optimization. To further improve prediction accuracy, the Kuo and Wang (1996) and Goto et al. (2001) models were optimized using the complete experimental database. After optimization, both models reduced the overall mean absolute deviation to below 15%, while the optimized Goto et al. (2001) model maintained the best and most consistent overall performance. The results provide new pressure-drop data for next-generation refrigerants and demonstrate that parameter optimization can significantly enhance the applicability of existing micro-fin-tube correlations.

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗

Atomic Precision Processing of Two-Dimensional Materials for Next-Generation Microelectronics

The growth of the information era economy is driving the pursuit of advanced materials for microelectronics, spurred by exploration into “Beyond CMOS” and “More than Moore” paradigms. Atomically thin 2D materials, such as transition metal dichalcogenides (TMDCs), show great potential for next-generation microelectronics due to their properties and defect engineering capabilities. This perspective delves into atomic precision processing (APP) techniques like atomic layer deposition (ALD), epitaxy, atomic layer etching (ALE), and atomic precision advanced manufacturing (APAM) for the fabrication and modification of 2D materials, essential for future semiconductor devices. Additive APP methods like ALD and epitaxy provide precise control over composition, crystallinity, and thickness at the atomic scale, facilitating high-performance device integration. Subtractive APP techniques, such as ALE, focus on atomic-scale etching control for 2D material functionality and manufacturing. In APAM, modification techniques aim at atomic-scale defect control, offering tailored device functions and improved performance. Achieving optimal performance and energy efficiency in 2D material-based microelectronics requires a comprehensive approach encompassing fundamental understanding, process modeling, and high-throughput metrology. Finally, the outlook for APP in 2D materials is promising, with ongoing developments poised to impact manufacturing and fundamental materials science. Integration with advanced metrology and codesign frameworks will accelerate the realization of next-generation microelectronics enabled by 2D materials.

36 MATERIALS SCIENCE↗

Recent progress and future prospects of atomic layer deposition to prepare/modify solid-state electrolytes and interfaces between electrodes for next-generation lithium batteries

Lithium ion batteries (LIBs) are encouraging electrochemical devices with remarkable properties including a high energy/power density, fast charging capability, and low self-discharge rate. Further increase in energy density as well as safe usage is needed for next-generation LIBs in electric transportation vehicles. Solid-state electrolytes (SSEs) are very promising for high-performance LIBs since they enable improved safety along with increased energy density compared to flammable liquid organic electrolytes. However, utilizing SSEs with a Li metal anode is very challenging due to the possibility of undesired side reactions and the formation of an unstable solid-electrolyte interphase. Therefore, it is critical to enhance the stability of SSEs against the Li anode. One feasible approach is to form a thin and conductive interlayer between the Li anode and solid-state electrolyte. Atomic layer deposition (ALD) is a unique technique for conformal coating of complex 3D structures with finely controlled film thickness (at the atomic scale). ALD coating on the surface of SSEs can be adopted for engineering solid-electrolyte interfaces with desired attributes and improved stability. In this review paper, we have discussed recent progress in implementing the ALD technique for depositing thin layers on various SSE configurations including lithium phosphorus oxynitride (LiPON), garnets, oxides, perovskites, sulphides, Li 3 BO 3 –Li 2 CO 3 (LBCO), and sodium super ionic conductors (NASICON). We have also highlighted the major areas for future research and development in the field. We believe that this review will be very helpful for directing future research on implementing ALD for synthesizing stable and high-performance SSEs with an engineered solid-electrolyte interface for next-generation electrochemical devices (e.g., Li-ion batteries, supercapacitors, and flow batteries).

36 MATERIALS SCIENCE↗

New opportunities at the next-generation neutrino experiments I: BSM neutrino physics and dark matter

The combination of the high intensity proton beam facilities and massive detectors for precision measurements of neutrino oscillation parameters including the charge-parity violating (CPV) phase will open the door to help make beyond the standard model (BSM) physics reachable even in low energy regimes in the accelerator-based experiments. Large-mass detectors with highly precise tracking and energy measurements, excellent timing resolution, and low energy thresholds will enable the searches for BSM phenomena from cosmogenic origin, as well. Therefore, it is also conceivable that BSM topics in the next-generation neutrino experiments could be the dominant physics topics in the foreseeable future, as the precision of the neutrino oscillation parameter and CPV measurements continue to improve. This paper reviews the current landscape of BSM theory in neutrino experiments in two selected areas of the BSM topics-dark matter and neutrino related BSM-and summarizes the current results from existing neutrino experiments to set benchmarks for both theory and experiment. This paper then provides a review of upcoming neutrino experiments throughout the next 10 to 15 year time scale and their capabilities to set the foundation for potential reach in BSM physics in the two aforementioned themes. An important outcome of this paper is to ensure theoretical and simulation tools exist to carry out studies of these new areas of physics, from the first day of the experiments, such as Deep Underground Neutrino Experiment in the U.S. and Hyper-Kamiokande Experiment in Japan.

dark sector↗

SNEWS 2.0: a next-generation supernova early warning system for multi-messenger astronomy

The next core-collapse supernova in the Milky Way or its satellites will represent a once-in-a-generation opportunity to obtain detailed information about the explosion of a star and provide significant scientific insight for a variety of fields because of the extreme conditions found within. Supernovae in our galaxy are not only rare on a human timescale but also happen at unscheduled times, so it is crucial to be ready and use all available instruments to capture all possible information from the event. The first indication of a potential stellar explosion will be the arrival of a bright burst of neutrinos. Its observation by multiple detectors worldwide can provide an early warning for the subsequent electromagnetic fireworks, as well as signal to other detectors with significant backgrounds so they can store their recent data. The supernova early warning system (SNEWS) has been operating as a simple coincidence between neutrino experiments in automated mode since 2005. In the current era of multi-messenger astronomy there are new opportunities for SNEWS to optimize sensitivity to science from the next galactic supernova beyond the simple early alert. This document is the product of a workshop in June 2019 towards design of SNEWS 2.0, an upgraded SNEWS with enhanced capabilities exploiting the unique advantages of prompt neutrino detection to maximize the science gained from such a valuable event.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Scenario adaptive disruption prediction study for next generation burning-plasma tokamaks

Next generation High Performance (HP) tokamaks risk damage from unmitigated disruptions at high current and power. Achieving reliable disruption prediction for a device's HP operation based on its Low Performance (LP) data is a key to its success. In this letter, through explorative data analysis and dedicated numerical experiments on multiple existing tokamaks, we demonstrate how the operational regimes of tokamaks can affect the power of a trained disruption predictor. First, our results suggest data-driven disruption predictors trained on abundant LP discharges work poorly on the HP regime of the same tokamak, which is a consequence of the distinct distributions of the tightly correlated signals related to disruptions in these two regimes. Second, we find that matching operational parameters among tokamaks strongly improves cross-machine accuracy which implies our model learns from the underlying scalings of dimensionless physics parameters like q 95 , β p and confirms the importance of these parameters in disruption physics and cross machine domain matching from the data-driven perspective. Finally, our results show in the absence of HP data from the target devices, the best predictivity of the HP regime for the target machine can be achieved by combining LP data from the target with HP data from other machines. Furthermore, these results provide a possible disruption predictor development strategy for next generation tokamaks, such as ITER and SPARC, and highlight the importance of developing baseline scenario discharges of future tokamaks on existing machines to collect more relevant disruptive data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Validation of the VUV-reflective coating for next-generation liquid xenon detectors

Abstract Coating detector materials with films highly reflective in the vacuum ultraviolet region improves sensitivity of the next-generation rare-event detectors that use liquid xenon. In this work, we investigate the MgF 2 -Al-MgF 2 coating designed to achieve high reflectance at 175 nm, the mean wavelength of liquid xenon (LXe) scintillation. The coating was applied to an unpolished, passivated copper substrate mimicking a realistic detector component of the proposed nEXO experiment, as well as to two unpassivated substrates with “high” and “average” levels of polishing. After confirming the composition and morphology of the thin-film coating using TEM and EDS, the samples underwent reflectance measurements in LXe and gaseous nitrogen (GN2). Measurements in LXe exposed the coated samples to -100°C for several hours. No peeling of the coatings was observed after several thermal cycles. Polishing is found to strongly correlate with the measured specular reflectance (R spec ). In particular, 5.8(5)% specular spike reflectance in LXe was measured for the realistic sample at 20° of incidence, while the values for similar angles of incidence on the high and average polish samples are 62.3(1.3)% and 27.4(7)%, respectively. At large angles (66°–75°), theR spec in LXe for the three samples increases to 23(5)%, 80(8)%, and 84(18)%, respectively. The R spec at around 45° was measured in both GN2 and LXe for average polish sample and shows a reasonable agreement. Importantly, the total reflectance of the samples is comparable and estimated to be 92(8)%, 85(8)%, and 83(8)% in GN2 for the realistic, average, and high polish samples, respectively. This is considered satisfactory for the next-generation LXe experiments that could benefit from using reflective films, such as nEXO and DARWIN, thus validating the design of the coating.

Instruments & Instrumentation↗

NGPINT V3: a containerized orchestration Python software for discovery of next-generation protein–protein interactions

Abstract Summary Batch yeast two-hybrid (Y2H) assays, leveraged with next-generation sequencing, have afforded successful innovations for the analysis of protein–protein interactions. NGPINT is a Conda-based software designed to process the millions of raw sequencing reads resulting from Y2H–next-generation interaction screens. Over time, increasing compatibility and dependency issues have prevented clean NGPINT installation and operation. A system-wide update was essential to continue effective use with its companion software, Y2H-SCORES. We present NGPINT V3, a containerized implementation built with both Singularity and Docker, allowing accessibility across virtually any operating system and computing environment. Availability and implementation This update includes streamlined dependencies and container images hosted on Sylabs (https://cloud.sylabs.io/library/schuyler/ngpint/ngpint) and Dockerhub (https://hub.docker.com/r/schuylerds/ngpint), facilitating easier adoption and integration into high-throughput and cloud-computing workflows. Full instructions and software can be also found in the GitHub repository https://github.com/Wiselab2/NGPINT_V3 and Zenodo https://doi.org/10.5281/zenodo.15256036.

Biochemistry & Molecular Biology↗

Two-Step Procedure to Detect Cosmological Gravitational Wave Backgrounds with Next-Generation Terrestrial Gravitational-Wave Detectors

Cosmological gravitational-wave backgrounds are an exciting science target for next-generation ground-based detectors, as they encode invaluable information about the primordial Universe. However, any such background is expected to be obscured by the astrophysical foreground from compact-binary coalescences. We propose a novel framework to detect a cosmological gravitational-wave background in the presence of binary black holes and binary neutron star signals with next-generation ground-based detectors, including Cosmic Explorer and the Einstein Telescope. Our procedure involves first removing all the individually resolved binary black hole signals by notching them out in the time-frequency domain. Then, we perform joint Bayesian inference on the individually resolved binary neutron star signals, the unresolved binary neutron star foreground, and the cosmological background. For a flat cosmological background, we find that we can claim detection at 5⁢𝜎 level when Ω ref ≥ 2.7 × 10 −12 /$\sqrt{𝑇_{obs}/yr}$, where 𝑇 obs is the observation time (in years), which is within a factor of ≲ 2 from the sensitivity reached in the absence of these astrophysical foregrounds.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Demonstration of the neutron tracking capability of NEXT array in time-of-flight measurements to improve energy resolution

Precise neutron-energy measurements are required to probe the nuclear structure effects of neutron-rich nuclei, where β-delayed neutron emission becomes a dominant decay mode. The Neutron dEtector with Xn Tracking (NEXT) array has been designed and constructed to measure β-delayed neutrons with better energy resolution. The new design localizes the neutron interaction position by optically segmenting the detector along the direction of the neutron flight path, reducing the associated uncertainties in the neutron time-of-flight measurements. This significantly improves the energy resolution without losing the necessary detection efficiency. The proof-of-principle and efficiency measurements showed promising results. Herein, this article details the implementation of the neutron tracking capability of NEXT array in time-of-flight measurements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Detectability of QCD phase transitions in binary neutron star mergers: Bayesian inference with the next generation gravitational wave detectors

We study the detectability of postmerger QCD phase transitions in neutron star binaries with next-generation gravitational-wave detectors Cosmic Explorer and Einstein Telescope. We perform numerical relativity simulations of neutron star mergers with equations of state that include a quark deconfinement phase transition through either a Gibbs or Maxwell construction. These are followed by Bayesian parameter estimation of the associated gravitational-wave signals using the nrpmw waveform model, with priors inferred from the analysis of the inspiral signal. We assess the ability of the model to measure the postmerger peak frequency $f$$^{peak}_{2}$ and identify aspects that should be improved in the model. We show that, even at postmerger signal to noise ratios as low as 10, the model can distinguish (at the 90% level) $f$$^{peak}_{2}$ between binaries with and without a phase transition in most cases. Phase-transition induced deviations in the $f$$^{peak}_{2}$ from the predictions of equation-of-state insensitive relations can also be detected if they exceed 1.6⁢σ. Our results suggest that next-generation gravitational wave detectors can measure phase transition effects in binary neutron star mergers. Furthermore, unless the phase transition is “strong,” disentangling it from other hadronic physics uncertainties will require significant theory improvements.

79 ASTRONOMY AND ASTROPHYSICS↗

Two-mirror resonator for next-generation Compton gamma-ray source

The next-generation Compton gamma-ray sources (CGSs) based on storage rings require a high-power, well-focused laser beam as a photon driver, which can be realized using a Fabry-Perot cavity (FPC). In this work, we reexamine the behavior and performance of a two-mirror, nearly concentric resonator by introducing a new figure of merit representing the cavity’s proximity to instability. This figure of merit is used to analyze various aspects of the cavity design, including misalignment, beam coupling limitations, and beam size scaling. We then examine several factors affecting the gamma-ray flux, such as the interaction area, crossing angle for collision, frequency matching between the electron and laser beams, and intrabeam scattering effects. Using an example CGS, we demonstrate how to make improved design choices for a two-mirror resonator to enhance the gamma-ray beam flux. This work shows that simple two-mirror Fabry-Perot cavities are well suited as the laser driver for the next-generation storage ring-based CGS, while offering superior advantages in gamma-ray beam polarization control compared to more complex four-mirror, nonplanar resonators.

Delooze, Will↗

Observational Data for Next-Generation Climate Model Evaluation: Requirements, Considerations, and Best Practices

Climate model simulations are an important source of information about our planet’s climate system and also enable informed decision-making under different future scenarios. As a new archive of results from the next generation of climate models is anticipated to become available with the Coupled Model Intercomparison Project phase 7 (CMIP7), the need to develop efficient and robust methods to evaluate models is paramount. Observations are an integral part of model evaluation, providing a means to quantify and understand the degree to which climate models can faithfully reproduce Earth system processes. Such analysis is critical for constraining climate projections, identifying areas of focus for model development, and assisting analysts in deciphering the utility of models for specific applications. Observations of Earth system come from a diversity of sources, span different space–time domains, and are produced by different communities, and each dataset features different data structures and formats, metadata standards, and its own unique uncertainties. Uncertainties in an observational dataset may stem from gaps in temporal and spatial coverage, instrumentation errors, or assumptions in retrieval and processing methods. How then does one ensure that observational data are ready for use and utilized in the most appropriate way for robust, rapid, and routine climate model evaluation? The CMIP7 Model Benchmarking Task Team with input from the broader climate modeling, model evaluation, and observational data communities present a vision and considerations for best practices toward the optimal and appropriate use of observational data to support next-generation climate model evaluation.

Climate models↗

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗