Microscopic and elemental analysis of temperature-induced changes in sulfur/silicon nitride stack-passivated Si surface
Not Available
Mouri, Tasnim Kamal↗
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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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COCOA: A compact Compton camera for astrophysical observation of MeV-scale gamma rays
COCOA (COmpact COmpton cAmera) is a next-generation gamma-ray telescope designed for astrophysical observations in the MeV energy range. The detector comprises a scatterer volume employing the LiquidO detection technology and an array of scintillating crystals acting as absorber. Surrounding plastic scintillator panels serve as a veto system for charged particles. The detector's compact, scalable design enables flexible deployment on microsatellites or high-altitude balloons. Gamma rays at MeV energies have not been well explored historically (the so-called "MeV gap") and COCOA has the potential to improve the sensitivity in this energy band.
79 ASTRONOMY AND ASTROPHYSICS↗
Atmospheric pion, kaon, and muon fluxes for sub-orbital experiments
Cosmic rays interacting with the Earth's atmosphere generate extensive air showers, which produce Cherenkov, fluorescence and radio emissions. These emissions are key signatures for detection by ground-based, sub-orbital, and satellite-based telescopes aiming to study high energy cosmic ray and neutrino events. However, detectors operating at ground and balloon altitudes are also exposed to a background of atmospheric charged particles, primarily pions, kaons, and muons, that can mimic or obscure the signals from astrophysical sources. In this work, we use coupled cascade equations to calculate the atmospheric pion, kaon and muon fluxes reaching detectors at various altitudes. Our analysis focuses on energies above 10 GeV, where the influence of the Earth's magnetic field on particle trajectories is minimal. We provide angular and energy-resolved flux estimates and discuss their relevance as background for extensive air shower detection. Furthermore, our results are potentially relevant for interpreting data from current and future balloon-borne experiments such as EUSO-SPB2 and for refining trigger and veto strategies in Cherenkov and fluorescence telescopes.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Cellulose-MOFs hybrid materials: Chemistry and mechanism of applications in biomedical - A review
Rising costs and performance limits of modern biomedical materials motivate the search for advanced, biocompatible alternatives. Cellulose-based metal-organic frameworks (cellulose-MOFs) emerge as distinctive hybrids combining renewable polymer chemistry with tunable porous architectures, enabling uncommon structure–function relationships. Their large surface area, controllable pore size, adaptable functional groups, and efficient host–guest interactions underpin diverse biomedical functions. Till now, no comprehensive, application-focused review has systematically summarized cellulose-MOFs synthesis for biomedical applications. This review critically analyzes cellulose-MOFs, emphasizing mechanistic links between chemistry, synthesis routes, interfacial interactions, and biomedical performance, rather than cataloging applications alone. Antibacterial action, targeted drug delivery, and sensing/biosensing are discussed through comparative insights. The article identifies unresolved challenges and proposes future research pathways to rationally design next-generation cellulose-MOFs systems, guiding researchers and clinicians alike.
Biomedical↗
Scalable thin graphene oxide membranes enabled by polydopamine gutter layer
Two-dimensional (2D) nanosheets have been widely used to fabricate thin-film composite membranes for dye desalination. However, they often need to be thick to mitigate the defects resulting from their random stacking and rough support surface. Herein, bio-adhesive polydopamine (PDA) is used as a gutter layer to prepare graphene oxide (GO)-based membranes by improving the adhesion between the GO and porous support and providing a smooth surface to form thin, highly selective layers. For example, the PDA priming reduces the GO layer thickness by 57 %, from 447 to 190 nm, while achieving similar dye desalination properties. The effect of the dopamine concentration, exposure time, and GO layer thickness on the membrane structure and desalination performance are thoroughly investigated using various techniques, such as scanning electron microscopy (SEM), x-ray photoelectron spectroscopy (XPS), and x-ray diffraction (XRD). The PDA gutter layer is also applied for hollow fiber membranes, achieving water permeance of 79 L m -2 h −1 bar−1 and rejection of ∼99 % for Direct red 80. The membranes were challenged by simulated dye/salt mixtures to elucidate the complicated effect of the compositions on the desalination performance. Furthermore, this study unveils a new avenue to improve separation performance and large-scale manufacturability of 2D material-based membranes.
Dye desalination↗
Controllable oxygen vacancy defect engineering of BiVO 4 porous structures for room temperature NH 3 detection
Controlling structural features of sensing material while judiciously introducing vacancy defect states for revamping the electronic properties of the sample to obtain its superior gas sensing performance, is quite rare. Herein, we report for the first time, the room temperature (RT) ammonia (NH 3 ) detection of peanut-like porous bismuth vanadate (BiVO 4 ) with a stable monoclinic phase. The developed BiVO 4 possess abundant oxygen vacancies and porosity by virtue of calcinations (400–800 ℃). BiVO 4 calcined at 400 ℃ exhibits high selectivity towards NH 3 with a maximum response of 1421 @ 270 ppm at RT, which is 2.5 fold enhanced compared to without calcined BiVO 4 (response of 547 @ 270 ppm NH 3 ). The oxygen defective BiVO 4 appeared highly durable and stable even under high humid conditions (∼60 %). Besides, the porosity of BiVO 4 not only enhances the specific surface area (19.8 m 2 /g) but also results in fast diffusion of NH 3 molecules, leading to a reduction in the decay time (34 s for 90 ppm NH 3 ). The density functional theory (DFT) uncovers that the oxygen vacancy formation in BiVO 4 augments the NH 3 sensing capabilities by enhancing the adsorption energy of NH 3 . This work provides insight into the sensing mechanism of increased response caused by defect engineering and porosity, which will be favourable for fabricating high-performance NH 3 sensors at RT.
DFT analysis↗
Synergistically combining peracetic acid and reduced graphene oxide membranes to degrade trace organic contaminants
The removal of trace organic contaminants is a critical step for the reuse of municipal and industrial wastewater. Herein, we demonstrate a catalytic membrane platform synergistically integrating reduced graphene oxide (rGO) membranes and peracetic acid (PAA) oxidation, using a dye of methylene blue (MB) and a pesticide of 2,4-dichlorophenoxyacetic acid (2,4-D) as model contaminants. In a crossflow system with rGO membrane and 25 ppm PAA, the degradation rates of MB and 2,4-D were 22 and 0.12 g h −1 per g rGO, with an initial concentration of 10 and 1.1 ppm, respectively. The degradation time profile of MB and 2,4-D follows a pseudo-first-order model, and the degradation rate constant increases with increasing initial PAA doses. Here, the rGO membranes also exhibited good stability over a 1-month test for 2,4-D degradation. In addition to the nanofiltration performance of the rGO membrane, the integrated PAA-rGO membrane process shows great potential to degrade various organic contaminants without the need to separate and recover the metal-free catalyst in downstream treatment.
2,4-D↗
Stable yet hydrophilic graphene oxide nanomembranes by zwitterionic reduction for dye desalination
Holey graphene oxide (HGO) nanosheets have emerged as a promising membrane platform for dye desalination, and they must be reduced to enhance hydrophobicity and stability for long-term underwater operation, which usually decreases water and salt permeance. Herein, we develop a facile method to stabilize HGO nanosheets while retaining their hydrophilicity by reducing them with sulfobetaine amine (SBAm, a superhydrophilic zwitterion), achieving high water and salt permeance and a high salt/dye separation factor. Specifically, HGO nanosheets react with SBAm via an amine-epoxide reaction, rendering reduced HGO nanosheets containing superhydrophilic zwitterions. The effects of in-plane pores, zwitterion content, and layer thickness on the membrane chemistry, structure, and salt/dye separation properties of the SBAm-reduced HGOs (SHGOs) are thoroughly examined. The membrane achieves a Na 2 SO 4 /Direct red separation factor of up to 850, surpassing the state-of-the-art GO membranes. Moreover, hollow fiber membrane modules based on SHGOs are fabricated and exhibit stable performance in multi-cycle tests over 100 h of operation with mixed dye-salt solutions, demonstrating the scalability of our approach and its potential for practical applications.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Atomic-resolution imaging as a mechanistic tool for studying single-site heterogeneous catalysis
Heterogeneous catalysts dominate the chemical industry but typically feature diverse, incompletely defined active sites. Thus, describing structure-activity relationships, unlike homogeneous catalysts, remains challenging. In contrast, molecularly defined single-site heterogeneous catalysts (SSHCs), using appropriate tools, are poised to address these challenges and provide new avenues for catalysis research and development. The present study explores eco-friendly H 2 production mediated by discrete MoO 2 sites supported on carbon nanohorns (CNHs) and active for alcohol dehydrogenation. While informative, detailed ensemble EXAFS/XANES/XPS, kinetic measurements, and DFT analysis alone cannot provide a full molecular picture of the reaction pathway. Here, using single-molecule atomic-resolution time-resolved electron microscopy (SMART-EM), we propose the identification of four key catalytic intermediates anchored to CNHs and uncover a new reaction pathway involving alkoxide/hemiacetal equilibration and acetal oligomerization. Furthermore, these intermediates are inferred through a combination of theory and SMART-EM, showcasing the potential of SMART-EM as a complementary tool for exploring mechanistic hypotheses in catalysis.
36 MATERIALS SCIENCE↗
Delamination-informed lifecycle decisions: A dielectric and machine learning framework for composite sorting and recycling
Composite materials are widely used in aerospace, marine, and automotive sectors due to their high strength-to-weight ratio and durability. However, their long-term reliability can be compromised by damage accumulation. Specifically, delamination initiation serves as a precursor to structural failure, which is often difficult to detect during damage inspection. Identifying and sorting delamination initiation in samples not only increases operational safety while providing critical information for end-of-life decisions, which influences both the service life extension value and the efficiency of fiber extraction during recycling. This research addresses two challenges: (1) developing a nondestructive, ex-situ framework to sort composite materials based on damage severity, particularly delamination, and (2) understanding how damage in composites influences resin removal during pyrolysis. Both experimental work and finite element analysis were performed to predict critical stress levels that are associated with delamination onset. Based on these results, three loading levels 50 %, 75 %, and 90 % of maximum stress, were selected for controlled experiments, generating composite samples with varying extents of damage for machine learning model training. Microscopic imaging of these samples confirmed the damage progression from matrix cracking to delamination, validating the computational predictions. We explored supervised machine learning using dielectric measurements to classify damage states. Preliminary results show an artificial neural network can identify early delamination which is a potential precursor to failure, with 94.44 % accuracy on our dataset. A parallel investigation into the effect of damage severity on pyrolysis recycling showed that heavily delaminated samples required significantly less energy for comparable matrix removal than undamaged samples.
dielectric variables↗
Dynamically allocated individual pitch control for fatigue load reduction in wind turbines
Not Available
Mohsin, Kazi (ORCID:0009000686727658)↗
Trajectory optimization for temporally multi-staged batch counterflow reverse osmosis
Not Available
Das, Abhimanyu↗
A systematic review of machine learning in groundwater monitoring
With increasing concerns about water scarcity, groundwater has become crucial since this resource provides most of the freshwater needs. However, various human and natural activities often contaminate the groundwater, making it unsuitable for use. Over the years, scientists and engineers have used many methods to predict and track groundwater contamination as part of environmental monitoring. Consequently, there is an urgent need for improved methods, particularly in the face of increasing contamination. Machine learning has sometimes been used to monitor groundwater, air quality, and climate. Traditional methods must be improved due to the complexity and large amount of environmental data. This includes using hybrid models that combine traditional and new techniques. Despite the use of machine learning in many scientific areas, there is a lack of comprehensive reviews focusing on its use in environmental monitoring, especially groundwater monitoring. We aim to fill this gap by exploring machine-learning applications in groundwater monitoring. We discuss relevant methods, their limitations, and future potential. We summarize research on automating data processing and model training using groundwater sensor data. Our research underscores the transformative potential of machine learning to revolutionize long-term groundwater monitoring and contamination detection, providing valuable insights for future research and practical applications.
AI/ML↗
Elevated-Mn ChemCam targets illuminating Mn redox cycling and diagenesis in the Bradbury Rise, Gale Crater, Mars
Manganese plays a crucial role as a paleo-environmental and geological indicator due to its sensitivity to redox potential and pH variations in the environment. On Earth, the association between the rise of atmospheric oxygen during the Great Oxidation Event and the presence of Mn in the sedimentary rock record underscores its significance. Here, in this study, we reexamined ChemCam targets from the first 600 sols of the Mars Science Laboratory mission, focusing on identifying instances of above-average Mn within these targets. These elevated-Mn targets were categorized into distinct geologic classes, revealing a pattern linking heightened Mn levels with diagenetically altered materials, such as calcium-sulfate veins and concretions, as well as clay minerals within the same targets, indicating a compelling relationship between Mn enrichment and diagenetic processes. High concentrations of Mn were observed in chemically altered targets, suggesting the occurrence of multiple fluid events: the first to alter the material and the second to deposit Mn. The observed patterns suggest multiple diagenetic events and redox cycling that facilitated the deposition and transport of Mn subsequent to the initial dissolution of basaltic materials. This research sheds light on the complexity of martian diagenetic processes and their implications for the planet’s environmental evolution.
58 GEOSCIENCES↗
Modeling and Verification of Lumped-Parameter, Multibody Structural Dynamics for Offshore Wind Turbines
This paper presents the modeling and verification of multibody structural dynamics for offshore wind turbines. The flexible tower and support structure of a monopile-based offshore wind turbine are modeled using an acausal, lumped-parameter, multibody approach that incorporates structural flexibility, soil-structure interaction, and hydrodynamic models. Simulation results are benchmarked against alternative modeling approaches, demonstrating the model's ability to accurately capture both static and dynamic behaviors under various wind and wave conditions while maintaining computational efficiency. This work provides a valuable tool for analyzing key structural characteristics of wind turbines, including eigenfrequencies, mode shapes, damping, and internal forces.
17 WIND ENERGY↗
The development of grain resolved stress fields around notch tips in soft-textured zirconium polycrystals: A three-dimensional synchrotron X-ray diffraction study
Not Available
Louca, Karim (ORCID:0000000279142663)↗
Inhibition of dimeric SARS-CoV-2 Mpro displays positive cooperativity and a mixture of covalent and non-covalent binding
Not provided.
Science & Technology - Other Topics↗
Reactive flash sintering and characterization of bulk high entropy nitrides
Over the past decade, numerous high-entropy ceramics have been synthesized, often displaying attractive properties. However, the study on facile preparation of bulk high entropy nitrides (HEN) are limited, despite its broad potential applications. This research demonstrates for the first time rapid fabrication (within ∼6 min) of bulk high-entropy nitrides, especially (Al 0.17 Nb 0.17 Ta 0.17 Ti 0.32 Zr 0.17 )N, from binary nitride powder mixtures using a highly efficient reactive flash sintering (RFS) technique. X-ray diffraction (XRD) shows the HENs from RFS are near single-phase solid solutions with a rock salt crystal structure, while in situ synchrotron study carried out during RFS captured in real time the formation of HEN, which was preserved upon cooling, suggesting thermodynamic stability of the HEN phase, even up to extreme pressure (∼35.6 GPa). Microscopic analyses using SEM, STEM, and EDS reveal decent uniformity for HEN with no obvious segregation of elements, even to submicron scale. Some properties of the obtained bulk HENs are consistent with expectations. For example, their hardness and bulk modulus are close to estimates based on rule-of-mixture (ROM) values from the constituent binary nitrides. Meanwhile, some other measured properties seem to show surprises. For example, the fracture toughness for the HENs (e.g., 7.81 ± 1.40 MPa•m 1/2 or higher) turns out to be more than double of the expected ROM estimates. The significantly improved fracture toughness is attributed to the observed nano-layered structure of the HENs, despite the HEN’s cubic crystal structure and high hardness. In addition, the oxidation resistance shows improvement up till ∼800°C, possibly due to Ta doping that suppress oxygen vacancy formation in the oxide shell, while the 5-metal HEN of (Al 0.17 Nb 0.17 Ta 0.17 Ti 0.32 Zr 0.17 )N displays superconductivity (T c of ∼5–7 K from magnetism and resistivity measurements, slightly lower than ROM estimate), despite insulating property of starting AlN. Furthermore, future study combining experimental investigation using larger samples to confirm the observed increase in fracture toughness and oxidation resistance, theoretical modeling at different length scale, and more detailed structural/chemical characterization, especially at the atomic scale, are all needed to fully understand the inter-relationships between composition, processing, structure, and novel properties for these HENs and the development of related new materials for different applications.
Flash sintering↗