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With the increasing severity of climate change, Carbon Capture, Utilization, and Storage (CCUS) technology has become essential for reducing atmospheric CO2. Marine carbon sequestration, which stores CO2 in seabed geological structures, offers advantages such as large storage capacity and high stability. Cryogenic hoses are critical for the ship-to-ship transfer of liquid CO2 from transportation vessels to offshore carbon sequestration platforms, but their design methods and mechanical analysis remain inadequately understood. This study reviews existing cryogenic hose designs, including reinforced corrugated hoses, vacuum-insulated hoses, and composite hoses, to assess their suitability for liquid CO2 transfer. Based on CO2’s physicochemical properties, a conceptual composite hose structure is proposed, featuring a double-spring-supported internal composite hose, thermal insulation layer, and outer sheath. Practical recommendations for material selection, corrosion prevention, and monitoring strategies are provided to improve flexibility, pressure resistance, and thermal insulation, enabling reliable long-distance tandem transfer. A mechanical analysis framework is developed to evaluate structural performance under conditions including mechanical loads, thermal stress, and dynamic responses. This manuscript includes an introduction to the background, the methodology for data collection, a review of existing designs, an analysis of CO2 characteristics, the proposed design methods, the mechanical analysis framework, a discussion of challenges, and the conclusions.

Fiber-reinforced flexible pipes are subjected to large axial tension loads in deep-water applications, which may result in the excessive deformation of the pipes. Owing to the anisotropy of the composite materials, accurately describing the tensile behavior of these pipes is difficult. Theoretical, numerical, and experimental methods are employed in this study to investigate the mechanical characteristics of a glass fiber-reinforced unbonded flexible pipe under axial tensile loads. Based on the load–strain relationship of each pipe layer, analytical equations considering the effect of anisotropy and radial deformation are first proposed to calculate the axial tensile stiffness of the pipe. A detailed numerical model is established to simulate the tensile behavior of the pipe. A prototype test is performed on a 4500 mm long sample using a tensile testing machine. The leading roles of outer tensile reinforcement layers in axial tensile capacity are illustrated by the strain energy of the pipe layers obtained by the numerical model. Subsequently, a comparison analysis of the mean fiber direction strains of the selected sections are performed between numerical and experimental results, which validates the numerical model. Additionally, the stress distributions of different pipe layers are discussed based on the results of the numerical analysis. Finally, the comparison of axial tensile stiffness results validates the accuracy of the analytical model considering radial deformation. This study proposes effective theoretical and numerical models to predict the tensile behavior of a fiber-reinforced flexible pipe, which provides useful references for the design and structural analysis of these pipes.

Accurate and rapid thermal load identification based on limited measurement points is crucial for spacecraft on-orbit monitoring. This study proposes a stepwise identification method based on deep learning for identifying structural thermal loads that efficiently map the local responses and overall thermal load of a box structure. To determine the location and magnitude of the thermal load accurately, the proposed method segments a structure into several subregions and applies a cascade of deep learning models to gradually reduce the solution domain. The generalization ability of the model is significantly enhanced by the inclusion of boundary conditions in the deep learning models. In this study, a large simulated dataset was generated by varying the load application position and intensity for each sample. The input variables encompass a small set of structural displacements, while the outputs include parameters related to the thermal load, such as the position and magnitude of the load. Ablation experiments are conducted to validate the effectiveness of this approach. The results show that this method reduces the identification error of the thermal load parameters by more than 45% compared with a single deep learning network. The proposed method holds promise for optimizing the design and analysis of spacecraft structures, contributing to improved performance and reliability in future space missions.

With the increasing severity of climate change, Carbon Capture, Utilization, and Storage (CCUS) technology has become essential for reducing atmospheric CO[sub.2]. Marine carbon sequestration, which stores CO[sub.2] in seabed geological structures, offers advantages such as large storage capacity and high stability. Cryogenic hoses are critical for the ship-to-ship transfer of liquid CO[sub.2] from transportation vessels to offshore carbon sequestration platforms, but their design methods and mechanical analysis remain inadequately understood. This study reviews existing cryogenic hose designs, including reinforced corrugated hoses, vacuum-insulated hoses, and composite hoses, to assess their suitability for liquid CO[sub.2] transfer. Based on CO[sub.2]’s physicochemical properties, a conceptual composite hose structure is proposed, featuring a double-spring-supported internal composite hose, thermal insulation layer, and outer sheath. Practical recommendations for material selection, corrosion prevention, and monitoring strategies are provided to improve flexibility, pressure resistance, and thermal insulation, enabling reliable long-distance tandem transfer. A mechanical analysis framework is developed to evaluate structural performance under conditions including mechanical loads, thermal stress, and dynamic responses. This manuscript includes an introduction to the background, the methodology for data collection, a review of existing designs, an analysis of CO[sub.2] characteristics, the proposed design methods, the mechanical analysis framework, a discussion of challenges, and the conclusions.

In this study, thermal-fluid-solid coupled simulations on the gas-phase pre-cooling operation of the corrugated cryogenic hoses were performed. Attention was focused on the temporal evolution and spatial distribution of transient thermal stress in the hose structure caused by convective heat transfer of the cooling medium, Liquefied Natural Gas Boil-Off Gas (BOG). The effects of different corrugated hose parameters, i.e., boundary conditions, hose lengths, BOG inlet flow rates, and corrugation shapes (C-type and U-type), on the transient thermal stress behavior were thoroughly assessed. The thermal stress developed at different locations of the corrugated hoses with these parameters is found to be governed by two major factors: the boundary constraint and local temperature gradient. The objective of this study is to offer practical insights for the structural strength design of corrugated cryogenic hoses and effective pre-cooling strategies, aiming to mitigate structural safety risks caused by excessive thermal stress.

Triggered by the pioneering research on graphene, the family of two-dimensional layered materials (2DLMs) has been investigated for more than a decade, and appealing functionalities have been demonstrated. However, there are still challenges inhibiting high-quality growth and circuit-level integration, and results from previous studies are still far from complying with industrial standards. Here, we overcome these challenges by utilizing machine-learning (ML) algorithms to evaluate key process parameters that impact the electrical characteristics of MoS 2 top-gated field-effect transistors (FETs). The wafer-scale fabrication processes are then guided by ML combined with grid searching to co-optimize device performance, including mobility, threshold voltage and subthreshold swing. A 62-level SPICE modeling was implemented for MoS 2 FETs and further used to construct functional digital, analog, and photodetection circuits. Finally, we present wafer-scale test FET arrays and a 4-bit full adder employing industry-standard design flows and processes. Taken together, these results experimentally validate the application potential of ML-assisted fabrication optimization for beyond-silicon electronic materials. Here, the authors demonstrate the application of machine learning to optimize the device fabrication process for wafer-scale 2D semiconductors, and eventually fabricate digital, analog, and optoelectrical circuits.

Perceiving incoming environmental information is critical for optimizing plant growth and development. Multiple B-box proteins (BBXs) play essential roles in light-dependent developmental processes in plants. However, whether BBXs function as a signal integrator between light and temperature in tomato plants remains elusive. In this study, 31 SlBBX genes were identified from the newly released tomato ( Solanum lycopersicum ) genome sequences and were clustered into five subgroups. Gene structure and protein motif analyses showed relatively high conservation of closely clustered SlBBX genes within each subgroup; however, genome mapping analysis indicated the uneven distribution of the SlBBX genes on tomato chromosomes. Promoter cis -regulatory elements prediction and gene expression indicated that SlBBX genes were highly responsive to light, hormones, and stress conditions. Reverse genetic approaches revealed that disruption of SlBBX7, SlBBX9 , and SlBBX20 largely suppressed the cold tolerance of tomato plants. Furthermore, the impairment of SlBBX7, SlBBX9 , and SlBBX20 suppressed the photosynthetic response immediately after cold stress. Due to the impairment of non-photochemical quenching (NPQ), the excess photon energy and electron flow excited by low temperature were not consumed in SlBBX7-, SlBBX9- , and SlBBX20- silenced plants, leading to the over reduction of electron carriers and damage of the photosystem. Our study emphasized the positive roles of light signaling transcription factors SlBBXs in cold tolerance in tomato plants, which may improve the current understanding of how plants integrate light and temperature signals to adapt to adverse environments.

• Plants have evolved sophisticated regulatory networks to cope with dynamically changing light and temperature environments during day–night and seasonal cycles. However, the integration mechanisms of light and low temperature remain largely unclear. • Here, we show that low red : far-red ratio (LR : FR) induces FAR-RED ELONGATED HYPOCOTYL3 (SlFHY3) transcription under cold stress in tomato (Solanum lycopersicum). Reverse genetic approaches revealed that knocking out SlFHY3 decreases myo-inositol accumulation and increases cold susceptibility, whereas overexpressing SlFHY3 induces myo-inositol accumulation and enhances cold tolerance in tomato plants. • SlFHY3 physically interacts with ELONGATED HYPOCOTYL5 (SlHY5) to promote the transcriptional activity of SlHY5 on MYO-INOSITOL-1-PHOSPHATE SYNTHASE 3 (SlMIPS3) and induce myo-inositol accumulation in tomato plants under cold stress. Disruption of SlHY5 and SlMIPS3 largely suppresses the cold tolerance of SlFHY3-overexpressing plants and myo-inositol accumulation in tomato. Furthermore, silencing of SlMIPS3 drastically reduces myo-inositol accumulation and compromises LR : FR-induced cold tolerance in tomato. • Together, our results reveal a crucial role of SlFHY3 in LR : FR-induced cold tolerance in tomato and unravel a novel regulatory mechanism whereby plants integrate dynamic environmental light signals and internal cues (inositol biosynthesis) to induce and control cold tolerance in tomato plants.

Plants experience low ambient temperature and low red to far-red ratios (L-R/FR) of light due to vegetative shading and longer twilight durations in cool seasons. Low temperature induce photoinhibition through inactivation of the photosynthetic apparatus, however, the role of light quality on photoprotection during cold stress remains poorly understood. Here, we report that L-R/FR significantly prevents the overreduction of the entire intersystem electron transfer chain and the limitation of photosystem I (PSI) acceptor side, eventually alleviating the cold-induced photoinhibition. During cold stress, L-R/FR activated cyclic electron flow (CEF), enhanced protonation of PSII subunit S (PsbS) and de-epoxidation state of the xanthophyll cycle, and promoted energy-dependent quenching (qE) component of non-photochemical quenching (NPQ), enzyme activity of Foyer-Halliwell-Asada cycle and D1 proteins accumulation. However, L-R/FR –induced photoprotection pathways were compromised in tomato PROTON GRADIENT REGULATION5 ( PGR5 ) and PGR5-LIKE PHOTOSYNTHETIC PHENOTYPE1A ( PGRL1A ) co-silenced plants and NADH DEHYDROGENASE-LIKE COMPLEX M ( NDHM ) -silenced plants during cold stress. Our results demonstrate that both PGR5/PGRL1- and NDH-dependent CEF mediate L-R/FR –induced cold tolerance by enhancing the thermal dissipation and the repair of photodamaged PSII, thereby mitigating the overreduction of electron carriers and the accumulation of reactive oxygen species. The study indicates that there is an anterograde link between photoreception and photoprotection in tomato plants during cold stress.

Anthocyanins in maize ( Zea mays L. ) kernels determine the plant’s color and can enhance its resistance. Selenium (Se) significantly impacts plant growth, development, and secondary metabolic regulation. However, the molecular mechanisms by which Se regulates anthocyanin synthesis in waxy corn remain unclear. This study employed integrated transcriptomic and metabolomic analyses to investigate the mechanisms through which selenium influences anthocyanin synthesis in yellow and purple waxy corn. The results showed that maize varieties with higher anthocyanin content had higher selenium enrichment capacity in their kernels. Under selenium stress, HN2025 exhibited 1,904 more differentially expressed genes (DEGs) and 140 more differential metabolites compared to HN5. The expression levels of anthocyanin synthesis-related genes and transcription factors such as phenylalanine ammonia-lyase, flavonoid 3-hydroxylase (F3H), dihydroflavonol reductase (DFR), chalcone synthase (CHS), cinnamate-4-hydroxylase (C4H), anthocyanin 5,3-O-glucosyltransferases, and anthocyanidin reductase, MYB, and bHLH were strongly induced in HN2025. Metabolomic analysis revealed significant enrichment in anthocyanin biosynthesis, flavonoid and flavonol biosynthesis, glutathione metabolism, phenylalanine biosynthesis, and phenylalanine metabolism under selenium treatment. Three up-regulated PAL genes and one C4H gene were significantly enriched with DAMs in phenylalanine metabolism, phenylpropanoid biosynthesis, flavonoid biosynthesis, and anthocyanin biosynthesis, resulting in significant differences between HN5 and HN2025 in selenium-induced anthocyanin metabolism-related pathways. These findings provide a theoretical basis for understanding the effects of selenium on the molecular regulatory mechanisms of anthocyanin biosynthesis in maize kernels.