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Atomistic insights into catalytic role of platinum-graphene nanostructures in decomposition of high-energy-density fuels
No full textTo advance the cooling performance critical for hypersonic vehicles, high-energy-density fuels have emerged as promising candidates, with platinum-graphene (Pt@FGS) nanocatalysts demonstrating significant potential for enhancing their regenerative cooling efficiency. However, the underlying catalytic mechanisms of these nanocatalysts, particularly their influence on reaction pathways and carbonization processes, remain insufficiently understood. This study employs a ReaxFF-based hybrid simulation approach to investigate the effects of Pt@FGS nanocatalysts on the decomposition of exo-tetrahydrodicyclopentadiene (exo-THDCPD) across a broad temperature range (900-2000 K). The Pt@FGS nanocatalysts were modeled as a partially oxidized graphene structure with six platinum atoms anchored at defect sites. ReaxFF molecular dynamics (MD) simulations were performed to capture real-time pyrolysis pathways and nanocatalyst-fuel interactions at the atomic scale. To extend the timescale and observe low-temperature pyrolysis relevant to experimental conditions, the collective variabledriven hyperdynamics (CVHD) method was employed. Nudged elastic band (NEB) calculations quantified key bond dissociation energy barriers, providing insight into catalytic dehydrogenation mechanisms. The MD results revealed that Pt@FGS nanocatalysts reduce the activation energy by approximately 33 % compared to neat fuel, significantly enhancing fuel conversion rates by up to a factor of four through catalytic dehydrogenation. Heat sink capacity improvements were observed at lower temperature ranges, attributed to nanocatalyst-promoted dehydrogenation, as confirmed by NEB analysis. The CVHD approach enabled pyrolysis simulations under experimentally relevant conditions, yielding activation energies and product distributions consistent with those obtained from high-temperature MD simulations. Interestingly, additional MD simulations demonstrated Pt@FGS nanocatalysts can delay carbonization onset effectively suppressing the formation of carbon deposits. By combining MD, CVHD, and NEB analyses, we elucidated the reaction mechanisms of exo-THDCPD decomposition over Pt@FGS nanocatalysts. The results demonstrate at the atomistic scale that Pt suppresses coke formation by interacting with intermediates and hindering aromatic ring closure, providing insights into the design of fueldispersible catalysts for regenerative fuel cooling.
Fe-N4@Graphene Single-Atom Catalyst-Based Nanozyme against Influenza A Virus
No full textRecent COVID-19 pandemic has raised an urgent need for effective strategies to combat viruses that can pose serious health threats to the entire human race. Incorporating antipathogenic functions into everyday objects and personal protective equipment has become increasingly important, motivating the development of general-purpose antiviral materials. Single-atom catalysts, known for superior catalytic performance and maximized atomic utilization, have been explored in various research fields, including artificial nanozymes for bioapplications. We present reduced graphene oxide (rGO)-supported Fe-N-4 single-atom catalyst-based nanozyme (Fe-N-rGO) capable of achieving 99.99% viral deactivation against influenza A virus, outperforming bulk and nanoscale counterparts. The antiviral mechanism is attributed to the strong adsorption of hemagglutinin on the viral surface, leading to protein denaturation along with the potential generation of reactive oxygen species. Additionally, Fe-N-rGO with 1 wt %(Fe) can be uniformly coated onto arbitrary substrates, well-maintaining the strong antiviral performance.
Directional control of near-field energy transfer enabled by ultra-thin carbon nanotube films
No full textSingle-walled carbon nanotube films (CNFs), as ultra-thin and transdimensional material platforms, exhibit anisotropic electromagnetic modes in wave vector space, offering potential for directional control of energy transfer. In this work, we construct a heat exchange system consisting of nanoparticles (NPs) and a semi-enclosed cavity composed of two single-walled CNFs, and systematically investigate how to control the directionality of energy transfer through CNFs. We find that due to the excitation of cavity modes, the radiative heat transfer (RHT) between NPs in the presence of the semi-enclosed cavity is more than twice that of a single-layer CNF, and significantly higher than that of other cases. Also, through the study of the chiral index and the separation spacing between nanotubes, we find that RHT can be greatly regulated by rotating CNFs. When the rotation angles of the two CNFs are 16.5 degrees and 163.5 degrees, respectively, the enhancement ratio of RHT can surpass four orders of magnitude. In addition, a multi-terminal radiative thermal router for energy splitting is proposed based on CNFs. By rotating CNFs, the RHT between the heat source and different receiving terminals can be directionally controlled. When the angular misalignment is fixed at 147 degrees, the thermal router can achieve a splitting ratio of 86% and the total RHT is higher than that of other cases. These findings may provide practical solutions for directional control of contactless energy transfer between thermal elements in functional thermal devices.
Advances in Software Engineering Research for Systems-of-Systems and Software Ecosystems
No full textFor more than a decade, software engineering for systems-of-systems (SoS) and software ecosystems (SECO) has been largely investigated in order to cope with complexity in software-intensive systems. SoS research addresses several aspects related to software system architecture comprising a set of constituent systems that relate to each other to perform missions. As such, SoS have key characteristics such as operational and managerial independence, distribution, emergent behavior, and evolutionary development. Full interoperability and dynamic architecture become critical challenges in this context. On the hand, SECO research refers to modeling and analysis of a socio-technical network of actors and artifacts formed on top of common technological platforms, in which business factors directly influence software maintenance and evolution. Software sustainability and diversity as well as quality attributes that affect the SECO platform health represent challenges in the field. From the long-running, successful series of the International Workshop on Software Engineering for systems-of-systems and Software Ecosystems (SESoS), co-located with the IEEE/ACM International Conference on Software Engineering (ICSE), we present this special issue on the topics in the Journal of Software: Evolution and Process from SESoS 2023 in Melbourne, Australia. Four articles were accepted and published in this special issue, covering a longitudinal analysis of SoS research, as well as strategic patterns, services, and trust in SECO. These articles provide researchers and practitioners with advances in the state of the art and point out opportunities for further research.
Hyperspectral Anomaly Detection With Enhanced Spectral Graph Transformer Network
No full textHyperspectral imaging (HSI) plays a pivotal role across diverse sectors-including agriculture, environmental monitoring, and defense-by capturing rich spectral information that enables fine-grained material discrimination. Despite its advantages, the inherently high dimensionality and complexity of hyperspectral data present substantial challenges for reliable anomaly detection. Conventional approaches often fall short when confronted with subtle or context-dependent anomalies, underscoring the need for more advanced methodologies. In this study, we propose the Enhanced Spectral Graph Transformer Network (ESGTN), a novel framework that synergistically combines graph-based modeling, transformer architectures, and hyperbolic space embedding to improve the accuracy and efficiency of spectral anomaly detection. By representing HSIs as graphs, ESGTN effectively models both spatial and spectral relationships. The transformer component, equipped with self-attention mechanisms, adaptively emphasizes salient features, while the incorporation of hyperbolic embeddings provides a compact and distortion-minimized representation of the data's hierarchical structure. Extensive experiments conducted on multiple benchmark hyperspectral datasets demonstrate that ESGTN consistently outperforms existing state-of-the-art methods, achieving superior precision, recall, and computational efficiency. These findings highlight the model's robustness and practical applicability across a range of real-world scenarios. Moreover, this work contributes to the growing body of research at the intersection of deep learning and hyperspectral imaging, offering a scalable path forward for tackling the complex analytical demands inherent to high-dimensional remote sensing data.
Wireless, battery-free multi-axial sensor for augmented reality-assisted monitoring at skin interfaces
No full textDemand for augmented reality (AR) technology in the healthcare industry has gradually increased due to its immersive and interactive environment, which enhances the medical staff's intuitive interpretation of sensing data during surgery, rehabilitation, diagnosis, education, and therapy. However, current skin-mountable, wearable sensors integrated with AR platforms mainly focus on Human-Machine Interface (HMI) for interactive experiences. Furthermore, most wearable sensors currently used in conjunction with AR systems are rigid and cumbersome, which hampers their application to the skin interfaces of patients for personalized healthcare. Herein, we developed a wireless, battery-free multi-axial sensor with a thin and small form factor and integrated it with the AR system to visualize sensing data (e.g., pressure, shear stress, and temperature) from the subjects. The overall system demonstrated efficacy in preventing pressure injuries, monitoring posture to prevent disc herniation, and intuitive AR monitoring of physical parameters for subjects sitting in wheelchairs and lying in bed.
p21-Activated Kinase 4 and Ischemic Acute Kidney Injury in Mice and Humans
No full textKey Pointsp21-activated kinase 4 (PAK4) phosphorylates and inactivates GSH peroxidase 3 in the kidney after ischemia-reperfusion.Mice lacking PAK4 or treated with PAK4 proteolysis-targeting chimera were protected from kidney damage caused by ischemia-reperfusion injury.PAK4 expression in kidney tissues post-transplant inversely correlated with kidney function.BackgroundAKI after ischemia-reperfusion remains a substantial perioperative challenge lacking effective treatment. p21-activated kinase 4 (PAK4), a downstream effector of Rho GTPase, has been explored in hepatic ischemia-reperfusion injury, but its role in renal ischemia-reperfusion is unknown.MethodsWild-type and proximal tubule-specific Pak4 knockout mice underwent 25 minutes of ischemia followed by 24 hours of reperfusion injury. Primary tubular cells and human kidney-2 cells were exposed to hypoxia-reoxygenation injury to investigate the in vitro effect of PAK4. Selective degradation of PAK4 was employed using proteolysis-targeting chimera (PROTAC) to ameliorate AKI.ResultsPost-ischemia-reperfusion, the expression of PAK4 was upregulated through hypoxia-inducible factor 1 alpha in mouse kidneys. Deletion of PAK4 in proximal tubule cells, but not in myeloid cells, significantly mitigated ischemia-reperfusion-induced AKI, as evidenced by decreased levels of BUN, creatinine, tubular necrosis, apoptosis, macrophage infiltration, and lipid accumulation compared with control mice. Further investigation revealed that PAK4 phosphorylated GSH peroxidase 3 (GPx3) at T47, leading to its proteasomal degradation. In addition, pretreatment of mice with the PAK4 PROTAC preserved GPx3 and enhanced fatty acid beta-oxidation, thereby protecting against AKI. In kidney tissues from people with a kidney transplant, elevated levels of PAK4 protein and phosphorylation of GPx3 at T47 were observed.ConclusionsRenal tubular PAK4 contributes to tissue damage during ischemia-reperfusion injury, whereas PAK4 PROTAC mitigates ischemia-reperfusion injury by reducing oxidative stress and promoting fatty acid beta-oxidation.