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Abstract Metal-organic network-forming glasses are an emerging type of material capable of combining the modular design and high porosity of metal-organic frameworks and the high processability and optical transparency of glasses. However, a generalizable strategy for achieving both high porosity and high glass-forming ability in modularly designed metal-organic networks has yet to be developed. Herein, we develop a series of aluminum alkoxide glasses and monoliths by linking aluminum-oxo clusters with alcohol linkers. A bulky monodentate alcohol modulator is introduced during synthesis and act as both network plasticizer and pore template, which can be removed by the subsequent solvent exchange to give gas accessible pores. Glasses synthesized with the modulator template exhibit well-defined glass transitions in their as-synthesized form and high surface areas up to 500 m2/g after activation, making them among the most porous glassy materials. The aluminum alkoxide glasses also have optical transparency and fluorescent properties, and their structures are elucidated by pair-distribution functions, spectroscopic and compositional analysis. These findings could significantly expand the library of microporous metal-organic network-forming glasses and enable their future applications.

Abstract Installing different chemical entities onto crystalline frameworks with well-defined spatial distributions represents a viable approach to achieve ordered and complex synthetic materials. Herein, a covalent organic framework (COF-305) is constructed from tetrakis(4-aminophenyl)methane and 2,3-dimethoxyterephthalaldehyde, which has the largest unit cell and asymmetric unit among known COFs. The ordered complexity of COF-305 is embodied by nine different stereoisomers of its constituents showing specific sequences on topologically equivalent sites, which can be attributed to its building blocks deviating from their intrinsically preferred simple packing geometries in their molecular crystals to adapt to the framework formation. The insight provided by COF-305 supplements the principle of covalent reticular design from the perspective of non-covalent interactions and opens opportunities for pursuing complex chemical sequences in molecular frameworks.

As an infrastructure, the railway stations' roof and platform canopy have considerable space potential for deploying photovoltaic power generation systems. In order to study the feasibility of installing PV systems in railway stations, this paper analyzes the PV potential and techno-economic characteristics of China's high-grade railroad stations by combining a three-dimensional digital earth system (LSV) and PV plant calculation methods. The results show that the total installed PV capacity of Chinese high-grade railway stations, which are mainly used for passenger transportation, can reach 820 MW, and the total annual PV power generation capacity can reach 1111GWh. The self-sufficiency rate of each station is affected by the scale of the station building, the number of canopies on the passenger platform and the architectural design factors. The smaller the scale of the station building, the larger the area of the platform canopy, the smaller the overlap between the station building and the station canopy, the easier the railway station to achieve self-sustaining. The payback period is the time it takes for the total return on PV power generation to equal the investment in PV construction. 63% of the stations can realize full payback of their investment within 4–7 years under the operation strategy of full self-consumption of power generation. In addition the photovoltaic systems in railroad stations can generate considerable ecological benefits, reducing carbon dioxide emissions by 820,000 tons per year, which is about the carbon emissions of 304,000 cars in one year.

Well-defined metal–organic framework (MOF)@polymer core–shell composite particles with polyamide, polyurea, and polythiourea as the shell layer have been constructed for the first time using non-solvent-induced surface-aimed polymerization. This surface polymerization method utilizes non-solvent-induced phase separation to concentrate and direct monomers onto MOF particle surfaces, thus completing the coating process in less than 5 min. The generalizability of this method has been demonstrated with different MOFs. Coating MOF particles with any of the three polymers can effectively improve the stability of the MOF in harsh chemical environments. When used for heavy metal removal, polythiourea-coated composite particles (MOF@HDA-PDTC) exhibited a drastically improved Hg(II) removal rate and full utilization of the thione groups for Hg(II) binding compared to their neat polymer counterparts. This highlights the unique benefit of this core–shell architecture for the optimization of diffusion.

Abstract The enolimine-ketoenamine tautomerism has been utilised to construct 2D covalent organic frameworks (COFs) with a higher level of chemical robustness and superior photoelectronic activity. However, it remains challenging to fully control the tautomeric states and correlate their tautomeric structure-photoelectronic properties due to the mobile equilibrium of proton transfer between two other atoms. We show that symmetry-asymmetry tautomerisation from diiminol to iminol/cis-ketoenamine can be stabilised and switched in a crystalline, porous, and dynamic 3D COF (dynaCOF-301) through concerted structural transformation and host-guest interactions upon removal and adaptive inclusion of various guest molecules. Specifically, the tautomeric dynaCOF-301 is constructed by linking the hydroquinone with a tetrahedral building block through imine linkages to form 7-fold interwoven diamondoid networks with 1D channels. Reversible framework deformation and ordering-disordering transition are determined from solvated to activated and hydrated phases, accompanied by solvatochromic and hydrochromic effects useful for rapid, steady, and visual naked-eye chemosensing.

A total of 87 new monoclinic silicon allotropes are systematically scanned by a random strategy combined with group and graph theory and high-throughput calculations. The new allotropes include 13 with a direct or quasi-direct band gap and 12 with metallic characteristics, and the rest are indirect band gap semiconductors. More than 30 of these novel monoclinic Si allotropes show bulk moduli greater than or equal to 80 GPa, and three of them show even greater bulk moduli than diamond Si. Only two of the new Si allotropes show a greater shear modulus than diamond Si. The crystal structures, stability (elastic constants, phonon spectra), mechanical properties, electronic properties, effective carrier masses and optical properties of all 87 Si monoclinic allotropes are studied in detail. The electron effective masses ml of five of the new allotropes are smaller than that of diamond Si. All of these novel monoclinic Si allotropes show strong absorption in the visible spectral region. Taken together with their electronic band gap structures, this makes them promising materials for photovoltaic applications. These investigations greatly enrich the current knowledge of the structure and electronic properties of silicon allotropes.

Accurately classifying targets and clutter plots is crucial in radar data processing. It is beneficial for filtering out a large amount of clutters and improving the track initiation speed and tracking accuracy of real targets. However, in practical applications, this problem becomes difficult due to complex electromagnetic environments such as cloud and rain clutter, sea clutter, and strong ground clutter. This has led to poor performance of some commonly used radar plot classification algorithms. In order to solve this problem and further improve classification accuracy, the radar plot classification algorithm based on evidence adaptive updating (RPC-EAU) is proposed in this paper. Firstly, the multi-dimensional recognition features of radar plots used for classification are established. Secondly, the construction and combination of mass functions based on feature sample distribution are designed. Then, a confidence network classifier containing an uncertain class was designed, and an iterative update strategy for it was provided. Finally, several experiments based on synthetic and real radar plots were presented. The results show that RPC-EAU can effectively improve the radar plot classification performance, achieving a classification accuracy of about 0.96 and a clutter removal rate of 0.95. Compared with some traditional radar pattern recognition algorithms, it can improve by 1 to 10 percentage points. The target loss rate of RPC-EAU is also the lowest, only about 0.02, which is about one third to one half of the comparison algorithms. In addition, RPC-EAU avoids clustering all radar points in each update, greatly saving the computational time. The proposed algorithm has the characteristics of high classification accuracy, low target loss rate, and less computational time. Therefore, it is suitable for radar data processing with high timeliness requirements and multiple radar plots.

Organic macrocycles and cages have been well-developed as porous solids for gas detection but balancing adaptability and robustness in these materials remains challenging. Here, the authors report a dynamic 3D covalent organic framework that can undergo concerted and adaptive structural transitions upon adsorption of gas and vapours.

The grinding surface mechanical property is important for its working life span, which is determined by the microstructure distribution. To improve the machining mechanical performance, the greenly grinding generated heat is utilized to generate the coating layer without extra liquid. However, the coating layer microstructure composite is difficult to predict due to the non-steady grinding temperature. A digital complicated microstructure transformation (DCM) model is established and coupled with the transient grinding heat based on the validated improved finite difference method. The austenization, the ferrite reverted transformation, the cementite precipitation, the bainite transformation and the martensite transformation are all considered and automatically distinguished according to the grinding coating CCT. The analytic results indicate that the larger grinding depth mainly increases the bainite content, which can be restricted by improving the feeding rate, and the quicker feeding rate can increase the martensite content by three times. Combined with the measurement of corresponding representative mechanical performances (hardness and the residual stress), the achieved model is verified as an effective tool to realize the microstructure prediction. The research brings about a novelty macro mechanical property control of the grinding coating layer and is significant for achieving higher mechanical performance in surface strengthening manufacturing components.

Metal-organic frameworks (MOFs) are promising nanoporous materials with diverse applications. Traditional material discovery based on intensive manual experiments has certain limitations on efficiency and effectiveness when faced with nearly infinite material space. The current situation offers an opportunity for high-throughput (HT) and machine learning (ML) approaches, including computational and experimental methods, as they have greatly improved the efficiency of MOF screening and discovery and have the capacity to deal with the enormous growth of data. In this review, we discuss the research progress in HT computation and experiments and their effect on MOF screening and discovery. We also highlight how ML-based approaches and the integration of HT methods with ML algorithms accelerate MOF design. In addition, we provide our insights on the future capability of data-driven techniques for MOF discovery, despite facing some knowledge gaps as an obstacle.

When radar receives target echoes to form plots, it is inevitably affected by clutter, which brings a lot of imprecise and uncertain information to target recognition. Traditional radar plot recognition algorithms often have poor performance in dealing with imprecise and uncertain information. To solve this problem, a radar plot recognition algorithm based on adaptive evidence classification (RPREC) is proposed in this paper. The RPREC can be considered as the evidence classification version under the belief functions. First, the recognition framework based on the belief functions for target, clutter, and uncertainty is created, and a deep neural network model classifier that can give the class of radar plots is also designed. Secondly, according to the classification results of each iteration round, the decision pieces of evidence are constructed and fused. Before being fused, evidence will be corrected based on the distribution of radar plots. Finally, based on the global fusion results, the class labels of all radar plots are updated, and the classifier is retrained and updated so as to iterate until all the class labels of radar plots are no longer changed. The performance of the RPREC is verified and analyzed based on the real radar plot datasets by comparison with other related methods.

This paper presents an in- depth investigation of the silicon substrate characteristics based on frequency-dependent parameters in the through-silicon via (TSV)-based 3-D ICs. It is the first time to define the frequency bands accurately on the ground of a quantitative standard of calibration to represent different characteristics of the silicon substrate. Moreover, by converting the conventional model of a TSV pair into an RC parallel circuit, a simplified model is established which makes the analysis of the silicon substrate concise associated with the frequency variation. To further reveal the influence of silicon substrate on the signal transmission between adjacent TSVs, relevant impedance parameters of the silicon substrate are converted into the impedance ( $Z$ ) matrix for parametric modeling, which is validated by 3D full-wave simulations. This work contributes a systematic examination of the silicon substrate characteristics with the variation of frequency, and provides significant guidance for parametric analysis and modeling in TSV-based 3-D ICs.

It has been a hot research topic at home and abroad to sense the vibration, strain and temperature by communication optical fibers, so as to monitor and position the threat events along the pipeline, but how to realize the fusion and application of the sensed data is still in the exploration stage. Based on the principle of optical fiber sensing, the joint monitoring method for vibration, strain and temperature of optical cables accompanying the pipeline was proposed. Vibration data can be used for length alignment and third-party activity monitoring, the strain data for lateral displacement monitoring and temperature data for leakage monitoring and other abnormal operation analysis. The multi-dimensional monitoring data are subjected to joint analysis and interactive verification after spatial length alignment and time alignment, so that the false alarm rate can be further reduced. The fusion and application of 3 kinds of sensed data could realize the sensing of pipeline state under complex conditions and provide technical support for safe operation of pipelines.

The optical response of inorganic two-dimensional semiconductors is dominated by Wannier-Mott excitons, but molecular systems can host localised Frenkel excitons. Here, the authors report strong optical response in a class of monolayer molecular J-aggregates due to the coherent Coulomb interaction between localised Frenkel excitons.

To solve the problem of difficult hazelnut harvesting in mountainous areas of Liaoning, China, a small pneumatic hazelnut harvesting machine was designed, which can realize negative pressure when picking up hazelnut mixtures and positive pressure when cleaning impurities. The key structure and parameters of the harvesting machine were determined by constructing a mechanical model of the whole machine and combining theoretical analysis and operational requirements. To explore the harvesting machine scavenging performance, Liaoning hazelnut No. 3 with a moisture content of 7.47% was used as the experimental object. Firstly, the terminal velocity of hazelnuts and fallen leaves was measured using a material suspension velocity test bench. Secondly, the gas–solid two-phase flow theory was applied comprehensively, and the motion state, particle distribution, and air flow field distribution of hazelnuts from the inlet to the outlet of the pneumatic conveying device were simulated and analyzed using the coupling of computational flow fluid dynamics method (CFD) and discrete element method (DEM) to evaluate the cleaning performance from the perspective of the net fruit rate of hazelnuts in the cleaning box. Finally, a Box–Behnken design experiment was conducted with the sieve plate angle, the distance of the sieve plate, and the air flow velocity as factors and the net fruit rate of hazelnuts as indicators to explore the influence of the three factors on the net fruit rate of hazelnuts. The parameter optimization module of Design-Expert software was used to obtain the optimal combination of parameters for the factors. The experimental results show that the test factors affecting the test index are the following: the air flow rate, the angle of the screen plate, and the distance of the screen plate. The best combination of parameters was an air flow velocity of 14.1 m∙s−1, a sieve plate angle of 55.7°, and a distance of the sieve plate of 33.2 mm. The net fruit rate of hazelnuts was 95.12%. The clearing performance was stable and can guarantee the requirements of hazelnut harvester operation, which provides a certain theoretical basis for the design of a nut harvester.

Long-term storage of pear fruit at low temperature can retard senescence but may result in pericarp browning. We previously reported that increasing endogenous γ-aminobutyrate (GABA) content by exogenous GABA treatment can maintain mitochondrial structure integrity, thereby alleviating pericarp browning of ‘Nanguo’ pears after cold storage. Here, we tested the effectiveness of Ca2+ treatment on pericarp browning in relation to GABA biosynthesis. Fruit browning was reduced by treatment with Ca2+ after 180 days of storage. Pericarp Ca2+ and calmodulin content in treated fruit increased, and concomitantly, endogenous GABA content, key GABA synthesis-related enzyme activity, and gene expression were upregulated. Moreover, the mitochondrial structure in the pericarp tissue was found to be well preserved. Thus, Ca2+ treatment effectively reduced pericarp browning of refrigerated ‘Nanguo’ pears owing to improvement in the GABA biosynthesis capacity in the fruit.

The blue honeysuckle is a rich source of bioactive compounds. In this study, we obtained a polyphenol-rich blue honeysuckle extract (BHE) and found that cyanidin 3-glucoside and chlorogenic acid accounted for most of its phenolic content. Administration of BHE to mice alleviated silica particle (SP)-induced lung inflammation and reduced the recruitment of macrophages to lungs. BHE also reduced the pro-inflammatory cytokine levels in the bronchoalveolar lavage fluid. In vitro study showed that BHE reduced pro-inflammatory cytokine secretion by macrophages and reduced apoptosis in macrophages. Cell signaling analysis revealed that BHE inhibited p38 and c-Jun N-terminal kinase phosphorylation and decreased the nuclear expression of nuclear factor-κB. BHE treatment also down-regulated the expression of inducible nitric oxide synthase and up-regulated two antioxidant mediators, nuclear factor (erythroid-derived 2)-like 2 and heme oxygenase-1, in macrophages. The findings demonstrated that BHE may serve as a complementary and alternative functional food to prevent SP-induced pulmonary diseases.

Based on the energy conversion equation and dynamic power model of the semi-transparent crystalline silicon photovoltaic (PV) window (ST-PVW), through an iterative coupling solution to the operating temperature of the cell, a thermal-electric coupling calculation method for the ST-PVW is provided, and, combined with experiments, the method model was verified. Based on this model, the influence of PV cell coverage rate (PVR) on the thermal performance of the ST-PVW was studied. According to the simulation results, in summer, the heat gain of the ST-PVW decreases with the increase of PVR, and in winter, the amount of heat loss increases with the increase of PVR. For the four cities of Guangzhou, Nanjing, Beijing and Harbin, when the PVR is 1, 0.60 to 0.64, 0.28 to 0.32 and 0.26 to 0.30, respectively, the annual power consumption of the air conditioner can reach the minimum, and when the PVR is 0.16 to 0.17, 0.24 to 0.25, 0.22 to 0.23 and 0.19 to 0.20, respectively, the amount of electricity generated can just offset the power consumption of the air conditioner during the day.

Low-temperature storage is the primary postharvest method employed to maintain fruit quality and commercial value. However, pitting can develop during refrigeration, especially during the shelf life. In this study, a membrane lipidomic approach was employed to analyze the potential relationship between pitting and membrane lipid metabolism during post-cold-storage shelf life. We also determined the changes in ultrastructure and water distribution by low-field nuclear magnetic resonance (LF-NMR) and assessed the permeability of membrane, membrane lipid peroxidation, proline and malondialdehyde contents, and the activity and gene expression of phospholipase D and lipoxygenase, which are involved in membrane lipid metabolism. The results indicated that the changes in blueberry phospholipids during storage could be caused by cold stress. Furthermore, dehydration is a manifestation of chilling injury. Finally, the significant increase in electrolyte leakage, content of malondialdehyde and proline, and activity of phospholipase D and lipoxygenase in chilled blueberry also indicated that membrane lipid metabolism plays an important role in cold stress response.

Dynamic 3D covalent organic frameworks (COFs) have shown concerted structural transformation and adaptive gas adsorption due to the conformational diversity of organic linkers. However, the isolation and observation of COF rotamers constitute undergoing challenges due to their comparable free energy and subtle rotational energy barrier. Here, we report the atomic-level observation and structural evolution of COF rotamers by cryo-3D electron diffraction and synchrotron powder X-ray diffraction. Specifically, we optimize the crystallinity and morphology of COF-320 to manifest its coherent dynamic responses upon adaptive inclusion of guest molecules. We observe a significant crystal expansion of 29 vol% upon hydration and a giant swelling with volume change up to 78 vol% upon solvation. We record the structural evolution from a non-porous contracted phase to two narrow-pore intermediate phases and the fully opened expanded phase using n-butane as a stabilizing probe at ambient conditions. We uncover the rotational freedom of biphenylene giving rise to significant conformational changes on the diimine motifs from synclinal to syn-periplanar and anticlinal rotamers. We illustrate the 10-fold increment of pore volumes and 100% enhancement of methane uptake capacity of COF-320 at 100 bar and 298 K. The present findings shed light on the design of smarter organic porous materials to maximize host-guest interaction and boost gas uptake capacity through progressive structural transformation. [ABSTRACT FROM AUTHOR]