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Perfectly Linear α,ω-Hydroxy-Terminated Polyethylene with Near-Ideal Crystallinity.
No full textA novel 1,5-(bis-borinane)pentane (1,5-BBP) has been developed for polyhomologation (C1 polymerization), enabling the synthesis of well-defined α,ω-hydroxy polymethylene (PM) with controlled molar masses and narrow polydispersity at elevated temperatures. The structural integrity and complete difunctionality of the PM were confirmed by 1H NMR, 1 1B NMR, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), and SEC analyses. Achieving perfectly linear polyethylene (PE), an analog to PM, without branching remains a longstanding synthetic challenge, as even trace defects disrupt lamellar packing and reduce crystallinity. We address this limitation through the introduction of a monomer purification strategy for dimethyl sulfoxonium methylide in C1 polymerization that, for the first time, reduces residual branching to 1 3C NMR. The resulting nascent PM exhibits exceptional properties, including enthalpies of fusion up to 290 J·g-1, melting temperatures of 138 °C-143.15 °C, and crystallinity values of 93.8%-99.1% (DSC) and 92.0%-95.9% (WAXS). Solid-state 2D 1H-1 3C cross-polarization magic angle spinningwide-line separation (CP-MAS WISE) NMR spectra further confirm predominantly crystalline domains with minimal amorphous content. This study demonstrates that precise control over initiator design, monomer purity, and reaction conditions enables α,ω-hydroxy-terminated PM with crystallinity approaching the theoretical limits.King Abdullah University of Science and Technology (KAUST) support is gratefully acknowledged. The authors thank Dr. Edy Abou-hamad for his assistance with the solid-state NMR experiments, and Dr. Yaping Zhang for her assistance with the WAXS experiments from the KAUST Imaging and Characterization Core Lab
Stratospheric Grid: A Wireless Power Transfer Enabled HAP Network with Integrated Generation-Grid-Load-Storage Functions
No full textConventional high-altitude platforms (HAPs) face challenges in achieving continuous all-weather operation due to intermittent photovoltaic power generation, limited energy storage capacity, and high mission loads resulting from functional integration. To address this fundamental issue, we propose a stratospheric energy grid in which wireless power transfer (WPT) interconnections constitute the grid layer, while HAPs operate as dynamically reconfigurable integrated generation-grid-load-storage (IGGLS) nodes that harvest, buffer, consume, and peer-to-peer transfer energy for constellation-level balancing and resilience. In this system, each HAP node can flexibly switch among energy source, load, and storage roles according to its energy status and mission requirements, enabling energy exchange and spatiotemporal optimization within the stratosphere. Through cooperative scheduling, the stratospheric grid not only enables surplus-to-deficit energy support among HAPs but also extends upward to satellites and downward to the terrestrial grid and communication infrastructure, forming a heterogeneous, WPT-mediated interconnection. As an IGGLS ecosystem, it exploits peer-to-peer energy logistics, spatiotemporal smoothing of intermittency, cross-domain backup via the terrestrial grid, and service-aware dispatch, thereby boosting overall energy utilization and operational resilience. The proposed approach is validated through case studies, and we delineate an agenda of feasible research directions
Mangrove-Derived Endophytic Bacteria Enhance Growth, Yield, and Stress Resilience in Rice
No full textGlobal climate change increasingly challenges agriculture with flooding and salinity. Among strategies to enhance crop resilience to these stresses, we tested several endophytic bacterial strains from mangroves, which are permanently exposed to flooding and high salinity. We show several strains that can enhance flooding and salinity tolerance in Arabidopsis and rice plants. Two strains and their combination massively enhanced the growth and yield of Oryza sativa cv. Nipponbare under both soil and hydroponic growth conditions with and without salt treatment. The bacteria-induced transcriptome changes in O. sativa roots, particularly related to ABA-signaling and lignin and suberin deposition in root tissues, explain the altered responses of colonized rice plants to hypoxic and saline stress conditions. Importantly, bacterially colonized rice plants exhibited enhanced yield and improved grain quality. These results show that microbes can be a powerful tool for enhancing the yield and resilience of rice to hypoxic and saline stress conditions.This work was supported by KAUST funding BAS/1/1062-01-01 to H.H. as a part of the DARWIN21 desert initiative (http://www.darwin21.org) accessed on 1 January 2024
FlashDP: Private Training Large Language Models with Efficient DP-SGD
No full textAs large language models (LLMs) increasingly underpin technological advancements, the privacy of their training data emerges as a critical concern. Differential Privacy (DP) serves as a rigorous mechanism to protect this data, yet its integration via Differentially Private Stochastic Gradient Descent (DP-SGD) introduces substantial challenges, primarily due to the complexities of per-sample gradient clipping. Current explicit methods, such as Opacus, necessitate extensive storage for per-sample gradients, significantly inflating memory requirements. Conversely, implicit methods like GhostClip reduce storage needs by recalculating gradients multiple times, which leads to inefficiencies due to redundant computations. This paper introduces FlashDP, an innovative cache-friendly per-layer DP-SGD that consolidates necessary operations into a single task, calculating gradients only once in a fused manner. This approach not only diminishes memory movement by up to \textbf{50\%} but also cuts down redundant computations by \textbf{20\%}, compared to previous methods. Consequently, FlashDP does not increase memory demands and achieves a \textbf{90\%} throughput compared to the Non-DP method on a four-A100 system during the pre-training of the Llama-13B model, while maintaining parity with standard per-layer clipped DP-SGD in terms of accuracy. These advancements establish FlashDP as a pivotal development for efficient and privacy-preserving training of LLMs. FlashDP's code has been open-sourced in https://github.com/kaustpradalab/flashdp
Performance Evaluation of TVWS LTE-Based Wireless Broadband Technology in Suburban Non-Line-of-Sight Environments
No full textMany rural and suburban areas still lack broadband Internet access due to economic, technological and geographic challenges. In this paper, we examine the performance of TVWS wireless technology for providing Internet service through practical deployment in a suburban area of the King Abdullah University of Science and Technology (KAUST). We conduct outdoor measurements to measure the various performance metrics, including the received signal strength (RSS), signal-to-interference-plus-noise ratio (SINR), and data rate. In addition, the collected data are used to evaluate and compare the measured pathloss with some widely used pathloss models
Advancing Cryogenic Carbon Capture: Design of Liquid and Solid CO2 Onboard Storage Systems
No full textThe escalating climate crisis, driven by rising CO2 emissions, requires urgent decarbonization efforts. Carbon capture, utilization, and storage (CCUS) offers a promising pathway to limit global temperature rise to below 2 C. Among emerging technologies, cryogenic carbon capture (CCC) stands out due to its energy efficiency compared to conventional solvent-based processes. This thesis advances CCC technology in two key areas. First, an onboard storage and liquefaction system for the KAUST CCC rig was designed. A pressure vessel was designed to store liquid CO2 at 65 bar and 25 C, and two liquefaction strategies were evaluated through thermodynamic modeling using MATLAB and Aspen Plus. A closed-loop external refrigeration system outperformed an open-loop expansion cycle, achieving a lower specific energy consumption of 126.6 kJ/kg CO2. Second, the feasibility of enabling solid CCC was explored through experimental investigations of mechanical frost removal from cold surfaces. A mechanical scraping system was built and demonstrated using water frost, offering proof-of-concept results. These findings establish a foundation for extending CCC technologies to mobile and space-limited applications, particularly for the maritime industry
BOLT: Boost Large Vision-Language Model Without Training for Long-form Video Understanding
No full textLarge video-language models (VLMs) have demonstrated promising progress in various video understanding tasks. However, their effectiveness in long-form video analysis is constrained by limited context windows. Traditional approaches, such as uniform frame sampling, often inevitably allocate resources to irrelevant content, diminishing their effectiveness in real-world scenarios. In this paper, we introduce BOLT, a method to BOost Large VLMs without additional Training through a comprehensive study of frame selection strategies. First, to enable a more realistic evaluation of VLMs in long-form video understanding, we propose a multi-source retrieval evaluation setting. Our findings reveal that uniform sampling performs poorly in noisy contexts, underscoring the importance of selecting the right frames. Second, we explore several frame selection strategies based on query-frame similarity and analyze their effectiveness at inference time. Our results show that inverse transform sampling yields the most significant performance improvement, increasing accuracy on the Video-MME benchmark from 53.8% to 56.1% and MLVU benchmark from 58.9% to 63.4%. Our code is available at https://github.com/sming256/BOLT.This work is supported by the KAUST Center of Excellence for Generative AI under award number 5940. The computational resources are provided by
IBEX, which is managed by the Supercomputing Core Laboratory at KAUST
A Digitization Framework for Belt Rotation Monitoring in Pipe Conveyor Applications
No full textPipe conveyors provide an environmentally friendly alternative to open-troughed bulk solids conveyance, particularly for long or complex routing applications. However, the sustainability of this technology is compromised by unstable operations. Complex routing, operational variations, and environmental factors create uneven contact forces, triggering belt rotation. This is a critical failure mode that requires continuous monitoring throughout the conveyor’s lifecycle. Insufficient failure data represents a typical challenge for this application. This study hypothesized technological principles that constitute the minimum requirements for enabling the scaling of industrial applications of belt rotation monitoring. Enabling technologies were adopted to foster innovation, and a physical prototype was implemented to address data scarcity for this failure mode. Using a controller-responder wireless network of ESP32 Industrial Internet of Things devices, we developed a belt-independent measurement system with multiparameter capability. Key criteria for detecting unsafe operational states and a criticality-based approach for determining optimal measuring unit quantities were established. The measurement results demonstrated suitable precision for digitization objectives: overlap angle (3.3107° ± 16.7562°), pipe diameter (+13.3850 ± 7.2114 mm), and overlap length (−26.2750 ± 25.1536 mm), based on 307 samples with a latency of 350.1303 ms. The framework demonstrates potential for industrial deployment with acceptable performance for real-time monitoring.The authors sincerely thank the Graduate Program in Natural Resources Engineering of the Amazon (PRODERNA), part of the Institute of Technology (ITEC) at the Federal University of Pará (UFPA), Brazil. Additionally, appreciation is owed to the Lubrication Laboratory (LabLub), part of the Mechanical Engineering Department (DEMEC) at the State University of Maranhão (UEMA) in Brazil, and the Innovation Fabrication Lab (IFL), part of the Prototyping and Product Development Core Lab (PCL) at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia for their support
Unipolar <i>β</i>-Ga2O3 Pseudo-junction barrier Schottky diodes via Low-Cost magnesium diffusion process
No full textBeta Gallium Oxide (β-Ga2O3) Junction Barrier Schottky diodes possess excellent breakdown characteristics and efficiency, but the lack of p-type β-Ga2O3 has led to the use of alternative materials, such as NiOx, which pose challenges regarding lattice mismatch and temperature stability. This work reports a unipolar β-Ga2O3 diode enabled by the magnesium (Mg) diffusion process to create high-resistance electron-blocking regions. The Mg diffusion process developed in this work uses a room temperature compatible chemical process followed by an 800 °C annealing step, which is lower compared to already reported methods in the literature. Therefore, the proposed method is thought to reduce the device processing temperature budget and hence cost. The resulting device achieves an Ion/Ioff ratio of ∼109, a knee voltage of ∼0.9 V, and a breakdown voltage of 596 V. In addition, it demonstrates stable operation from 100 to 500 K, highlighting its suitability for electronics operating across a broad temperature range
Dependence of Lowland Water Use on Mountain Runoff Globally: Interannual Variability and Future Changes at Seasonal Scale
No full textMost of the global population lives in lowlands, where water demand is highest. Therefore, understanding the dependence of lowland regions on mountain water at a global scale is crucial as mountains provide an essential contribution to lowland water resources. Yet, interannual variability remains poorly studied in this context, although it is a key factor influencing water supply and demand. In this study, we used global simulations to contrast lowland and mountain runoff and future changes across all river basins larger than 10,000 km2 globally, focusing on seasonality and interannual variability. We also examined the contribution of mountain runoff to lowland water use, its seasonality and interannual variability and its potential future changes. Our results indicate that relative interannual runoff variability is lower in mountain regions compared to lowlands in 70% of river basins. Lowland water use exhibits considerable interannual variability with greater reliance on mountain runoff during years with low lowland runoff. By the end of the century, under the SSP5-8.5 pathway, the absolute volume of lowland water abstraction reliant on mountain runoff is projected to increase in most river basins compared to the past due to socio-economic changes. Yet, its share relative to total lowland surface water abstraction is projected to decline in many basins due to increased average lowland precipitation. Possible implications of such an increased reliance on mountain runoff include heightened water conflicts, as growing dependence on upstream mountain runoff may intensify transboundary challenges.We thank Dor Fridman for providing the global water demand scenario data. Open access publishing facilitated by Universitat Zurich, as part of the Wiley - Universitat Zurich agreement via the Consortium Of Swiss Academic Libraries