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25 records · Page 2

Photo-Swing CO2 Capture Using a Branched Polyethylenimine As Sorbents and TiN Light Absorber

Using branched polyethylenimine as the sorbent material for dilute CO2 capture, a photo-swing method is demonstrated in an industrially relevant support architecture using titanium nitride (TiN) nanosized light absorbers coupled with low-power LEDs with irradiances up to 420 mW cm-2. The photo-swing desorption process is applied to dry and humid streams of 400 ppm CO2 diluted in N2. Consistent with known sorption mechanisms for aminopolymers, humid CO2 streams increased the CO2 uptake, in our case by ~30%. The photo-swing CO2 capture desorbed ~83% and ~100% CO2 compared to thermally-driven desorption over the same period for a dry and humid CO2 stream, respectively. The photo-swing CO2 capture exhibits robust performance over >90 cycles without significant signs of photo(thermal) induced sorbent degradation. This work lays the groundwork for photo-swing DAC technology as a scalable, energy-efficient solution for CO2 capture, well-suited for modular systems in remote locations utilizing intermittent renewable energy sources.

36 MATERIALS SCIENCE

Magnetically Arrested Circumbinary Accretion Flows

Abstract Binary systems with comparable masses and a surrounding accretion disk can accrete gas through spiral accretion streams penetrating the central cavity formed by tidal interactions. Using three-dimensional Newtonian magnetohydrodynamics simulations, we investigate the possibility of a magnetically arrested accretion flow through the cavity. Rather than solely continuously feeding the binary through spiral accretion streams, the accretion is regulated by the strong magnetic field inside the cavity. Transport of mass and angular momentum onto the binary then proceeds largely periodically in magnetic flux eruption episodes. The ejected flux tubes carry angular momentum outward and away from the binary, inject hot plasma into the disk, and can launch flares. This likely intermittent scenario could have potential implications for the emission signatures of supermassive black hole binaries and shed light onto the role magnetic fields play in the binary’s orbital evolution.

Astronomy & Astrophysics

On Alfvénic turbulence of solar wind streams observed by Solar Orbiter during March 2022 perihelion and their source regions

It has been recently accepted that the standard classification of the solar wind solely according to flow speed is outdated, and particular interest has been devoted to the study of the origin and evolution of so-called Alfvénic slow solar wind streams and to what extent such streams resemble or differ from fast wind. In March 2022, Solar Orbiter completed its first nominal phase perihelion passage. During this interval, it observed several Alfvénic streams, allowing for characterization of fluctuations in three slow wind intervals (AS1-AS3) and comparison with a fast wind stream (F) at almost the same heliocentric distance. This work makes use of Solar Orbiter plasma parameters from the Solar Wind Analyzer (SWA) and magnetic field measurements from the magnetometer (MAG). The magnetic connectivity to the solar sources of selected solar wind intervals was reconstructed using a ballistic extrapolation based on measured solar wind speed down to the (spherical) source surface at 2.5 R s below which a potential field extrapolation was used to map back to the Sun. The source regions were identified using SDO/AIA observations. A spectral analysis of in situ measured magnetic field and velocity fluctuations was performed to characterize correlations, Alfvénicity, normalized cross-helicity, and residual energy in the frequency domain as well as intermittency of the fluctuations and spectral energy transfer rate estimated via mixed third-order moments. A machine learning technique was used to separate proton core, proton beam, and alpha particles and to study v − b correlations for the different ion populations in order to evaluate the role played by each population in determining the Alfvénic content of solar wind fluctuations. The comparison between fast wind and Alfvénic slow wind intervals highlights the differences between the two solar wind regimes: The fast wind is characterized by larger amplitude fluctuations, and magnetic and velocity fluctuations are closer to equipartition of energy. In fact the Alfvénic slow wind streams appear to be on a spectrum of wind types, with AS1, originating from open field lines neighboring active regions and displaying similarities with the fast wind in terms of fluctuation amplitude and turbulence characteristics, but not with respect to the alpha particles and proton beams. The other two slow streams differed both in their sources as well as plasma characteristics, with AS2 coming from the expansion of a narrow coronal hole corridor and AS3 from a region straddling a pseudostreamer. The latter displayed the coldest and highest density but the slowest stream with the smallest fluctuation amplitude and greatest magnetic energy excess. It also showed the largest scatter in proton beam speeds and the greatest difference in speed between proton beam and alpha particles. This study shows how the old fast–slow solar wind dichotomy, already called into question by the observations of slower Alfvénic solar wind streams, should further be refined, as the Alfvénic slow wind, originating in different solar wind regions, show significant differences in density, temperature, and proton and alpha-particle properties in the inner heliosphere. The observations presented here provide the starting point for a better understanding of the origin and evolution of different solar wind streams as well as the evolving turbulence contained within.

magnetohydrodynamics (MHD)

Imputation of urban environmental sensor data using gated attention bidirectional long short-term memory (GA-BiLSTM): methods, performance, and implications

Urban environmental monitoring networks frequently encounter significant data gaps due to sensor malfunctions, environmental disturbances, and communication failures. Reliable approaches to address these gaps are essential for ensuring the continuity and quality of environmental data streams. In this study, we developed a gated attention bidirectional long short-term memory (GA-BiLSTM) model to impute missing data in a dense urban monitoring network. Using observations from the CROCUS network in Chicago, we evaluated GA-BiLSTM against widely used approaches (XGBoost and K-nearest neighbors) under scenarios of both short-term intermittent gaps and prolonged outages. GA-BiLSTM consistently outperformed comparative methods, particularly during extended outages of up to ten days, demonstrating its ability to capture spatiotemporal dependencies across sensor nodes. Beyond performance metrics, feature importance and spatial network analyses highlighted the unexpected but critical predictive role of peripheral rural nodes, underlining their strategic value for maintaining robust urban monitoring systems. These results emphasize that advanced imputation methods can substantially improve the reliability of environmental monitoring networks and support more resilient data infrastructures for urban sustainability.

Data imputation

Monitoring river flow status using low-cost wildlife camera and image segmentation artificial intelligence

Continuous measurement and monitoring of surface water coverage in non-perennial streams are essential for understanding the exchange fluxes between surface and subsurface waters under both inundated and non-inundated conditions. In this study, a wildlife camera photo-based framework was developed to monitor small stream water inundation, depth, discharge, and velocity. Two advanced machine learning models, YOLOv8 and Mask2Former, were utilized to efficiently analyze images captured by wildlife cameras. The accuracy of the framework was validated against on-site depth measurements at six sites in the Yakima River Basin, along with the gage height, discharge, and velocity data from four USGS sites. This approach facilitates long-term, continuous monitoring and quantification of river intermittency and water availability with high precision and low cost, thereby advancing river ecosystem research and management.

machine learning

Cloud-Based Demonstration of the Eastern Interconnection Situational Awareness Monitoring System (ESAMS)

This report describes a cloud-based implementation and field demonstration of the Eastern Interconnection Situational Awareness and Monitoring System (ESAMS). ESAMS was developed to support the detection and source localization of forced oscillations using synchrophasor measurements from tie-lines connecting areas served by different reliability coordinators (RCs), so that RCs could better coordinate their response to wide-area events. A previous effort had identified deployment barriers associated with hosting shared situational awareness tools at a single RC. To address these barriers, ESAMS was migrated to Amazon Web Services and evaluated in a six-month field demonstration. ISO New England (ISO-NE) and PJM streamed data to the platform using AWS Direct Connect and a site-to-site VPN, respectively. The resulting multi-utility measurement footprint enabled regional source localization across major portions of the U.S. Eastern Interconnection and supported routine identification of oscillation events. During the final three months of the trial, 24 events above 2 MW/MVAR were detected. The largest detected oscillation approached a 25 MW peak-to-peak amplitude, and the longest persisted intermittently for more than 11 hours. The demonstration also assessed operational considerations—including data transfer volumes, end-to-end latency, and cloud computing costs—and found that network and compute requirements were modest relative to typical cloud capabilities while providing performance comparable to prior on-premises deployments. Overall, the results indicate that cloud hosting can provide a practical path to shared interconnection-wide oscillation monitoring. The cloud ESAMS demonstration establishes a foundation for broader utility participation and for building future wide-area analytics that leverage measurements across organizational boundaries.

Follum, James D.

Experimental Characterization of High-Surface Area Thermal Energy Storage

There is growing interest in energy storage technologies due to the expansion of renewable energy sources that are inherently intermittent and the increasing frequency of extreme weather events that disturb the power grid. Power consumption in buildings makes up approximately 76% of all electricity usage on the grid and is primarily used for thermal applications such as space conditioning, hot water, and cooking. This makes thermal energy storage (TES) an ideal solution for many of these applications. Many TES technologies rely on latent energy storage, which utilizes the melting/solidification of phase change materials (PCM) to store energy. Typically, TES designs suffer from low power density due to their low inherent thermal conductivity. This limitation makes the deployment of TES in active applications difficult as the ease of access to energy is essential for effective use. Common routes for improving power density include high thermal conductivity additives or extended features such as fins that increase cost. This study presents an alternative approach to improving performance through increasing the overall surface area to volume ratio of the device, to increase the available area for convection to occur between the working fluid and PCM. In the study a commercial PCM was selected with a transition temperature ideal for space heating applications. The heat exchanger design utilizes a unique application of triply periodic minimal surfaces (TPMS) for macro-encapsulation of the PCM. The use of TPMS for heat exchangers has been growing in interest due to their high-surface area to volume ratios, which were previously unmanufacturable until the development of additive manufacturing. A modular system was designed and manufactured with a stereolithography resin printing system that is then backfilled with PCM. An experiment test set-up is designed to test the charge and discharge performance of the thermal storage using a conditioned air stream. The pressure drop of the design is tested across a variety of flow rates. When compared to existing experimental data within literature, there is excellent agreement based on the Reynolds number at similar hydraulic diameters. Several inlet temperatures are tested at consistent temperature differences from the phase change temperature for both charging and discharging. Additionally, the volumetric flow rate is varied for each temperature set point. It was found that increasing flow rate had diminishing returns in reducing the overall charge time of the TES. The temperature delta from the melting temperature was the primary contributor to the change in average heat flux with limited variation in average heat transfer rate between charging and discharging at similar inlet temperatures and flow rates. The TPMS heat exchanger design has a high air-side pressure drop but it provides high heat transfer rates. This helps maintain a high outlet temperature during discharge, which is important to thermal comfort applications. The design, manufacturing, and experimental characterization of the TES device will be presented as part of this study.

25 ENERGY STORAGE