Optimal Structure Research Articles

Experimental investigation of the cooling effect of topology-optimized structure on photovoltaic wall

Nowadays, photovoltaic walls have been widely used, which will generate heat behind the PV panel and cause overheating, making the lower efficiency of the PV panel and higher temperature of the exterior wall. Topology optimization structures have been explored in many fields for heat dissipation, but few are applied in heat dissipation of the PV wall systems. The purpose of this paper is to experimentally investigate the effect of topological optimized structure of the copper sheet on electricity generation efficiency of the PV panel and cooling effect of the exterior wall. The topology optimization method is used to numerically find the optimal geometric configuration of high thermal conductivity material of copper sheet on the back of the photovoltaic panel. And the topology-optimized copper sheet is fabricated by 3D printing and experimented with four different cases. The experimental results show that under natural convection, compared with the reference photovoltaic wall, the largest reduction of temperature of the photovoltaic panel (ΔTpv) and the largest output power increment rate (ΔE/E) of the photovoltaic wall with topology-optimized copper in the 5 test days are 2.7℃and 1.30 % respectively, and the largest reduction of temperature of the exterior wall (ΔTw) is 1.6℃. Under forced convection, the temperature reduction (ΔTpv) and the increment of output power (ΔE) of the photovoltaic panel and the temperature reduction of the exterior wall (ΔTw) increase significantly under wind speed of 1 m/s compared with natural convection. But when the wind speed is increased from 1.5 m/s to 2 m/s, the increment is less obvious. Therefore, the optimal wind speed in the air gap of the photovoltaic wall with topology-optimized copper is 1 ∼ 1.5 m/s. At last, based on the results of our previous study, the optimal-constructed photovoltaic wall in hot summer and cold winter area is discussed. The results of this research can provide some technical guidance for engineering application of the photovoltaic panel integrated with walls in similar climate regions.

Discovery of potent HIV-1 NNRTIs by CuAAC click-chemistry-based miniaturized synthesis, rapid screening and structure optimization

In addressing the urgent need for novel HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs) to combat drug resistance, we employed CuAAC click chemistry to construct a diverse 312-member diarylpyrimidine (DAPY) derivative library. This rapid synthesis approach facilitated the identification of A6N36, demonstrating exceptional HIV-1 RT inhibitory activity. Moreover, it was demonstrated with EC50 values of 1.8–8.7 nM for mutant strains L100I, K103 N, Y181C, and E138K, being equipotent or superior to that of ETR. However, A6N36's efficacy was compromised against specific resistant strains (Y188L, F227L + V106A and RES056), highlighting a need for further optimization. Through scaffold hopping, we optimized this lead to develop 10c, which exhibited broad-spectrum activity with EC50 values ranging from 3.2 to 57.5 nM and superior water solubility. Molecular docking underscored the key interactions of 10c within the NNIBP. Our findings present 10c as a promising NNRTI lead, illustrating the power of click chemistry and rational design in combatting HIV-1 resistance.

Tile roof inspired structure optimization on radial wood to fabricate oil-water separation function

Cross wood was usually selected to fabricate oil-water separation function. However, the cross wood is easy to be deformed after chemical delignification. Therefore, structure optimization via drilling holes on radial wood along with nano Cu(OH)2/CuCl modification overcame the bottleneck defect of dimensional instability, and simultaneously fabricated oil-water separation function. The oil absorption capacity of modified wood increases with the number and depth of drilled holes, reaching a maximum of 3.7 g/g toward dichloromethane. The modified radial wood demonstrated exceptional filtration effectiveness toward dichloromethane/chloroform-water mixtures and exhibited superior photocatalytic degradation capabilities against methylene blue, malachite green, and direct blue 151 dyes. Additionally, the modified radial wood displayed favorable recycle ability for both oil-water separation and photocatalytic degradation. Thus, a facile, cost-effective and environmental friendly strategy proposed in this work has potential to enhance the practical application of wood based oil-water separation materials.

Screw transmission structure based triboelectric–electromagnetic hybridized generator for efficiently harvesting energy from a single mechanical stimulation

Among various electromechanical conversion technologies, the triboelectric-electromagnetic hybrid generator (TEHG) stands out with its capacity to operate across a wider frequency range. Nevertheless, extracting more electricity from a single mechanical stimulation remains a significant challenge. In this work, we propose a screw transmission structure based TEHG (ST-TEHG) that converts the contact-separation motion into continuous rotation. This transformation enables the device to produce multiple pulse outputs in both compression and rebound processes. Specifically, the threaded barrel is designed to rotate continuously under the action of the pressing lever. Excess energy is stored as elastic potential energy in the tower spring, which then initiates the threaded barrel’s reverse rotation upon the release of external force. Through systematical optimization of the screw transmission structure and device’s performances, ST-TEHG achieves an energy utilization efficiency that is 70.86 times than the device with conventional contact-separation mode in an operating cycle. The developed ST-TEHG demonstrates promising applications in smart factories for indoor conditions monitoring, such as temperature and humidity, assembly line monitoring, and hazardous zones warning. This screw transmission structure sets a precedent for highly efficient mechanical energy harvesting, propelling the practical advancement of hybrid generators.

Carrying Capacity of Water Environment and the Associated Optimization of Socioeconomic Structure of Yangzong Lake Basin, China

Yangzong Lake is the third largest deep-water plateau lake in Yunnan, China. Rapid socioeconomic development of the basin has resulted in pollution of water environment. This study aimed to identify the carrying capacity of water environment and to conduct the associated optimization of socioeconomic development. The results of this study showed that: (1) The carrying capacities of tributary rivers were small in relation to that of the lake. The maximum allowable annual loads of chemical oxygen demand (COD), ammonia nitrogen (NH3-N), and total phosphorus (TP) into the main rivers of the basin were 449.37, 24.73, and 5.38 tons, respectively. (2) Under the planning scenario, COD and NH3-N loads remain the primary constraints on economic and social development in the watershed. (3) In further optimizing the structure of the plantation industry, focusing on strengthening the collection and treatment capacity of rural domestic sewage, the watershed can achieve high-quality development of the tourism industry. The tourism output value in 2025 and 2035 can carry up to 20.28 billion CNY (growth rate: around 15.44%) and 76.80 billion CNY (growth rate: around 14.64%), respectively. This study can provide basic support for the future economic and social development of the watershed for decision-makers.

Control of extractive distillation processes with preconcentration for the separation of ternary azeotropic mixture ethyl acetate-ethanol–water in the face of multiple feed disturbances

The integration of preconcentration and solvent recovery functions is one of the effective ways to save energy consumption of extractive distillation processes for separating ternary azeotropic mixtures with a high content of one composition. However, the integration of various functions inevitably increases the difficulty of constructing robust control structures. In this paper, different proportion-integration (PI) control structures are investigated for the four-column extractive distillation with preconcentration process, while different PI and PI with model prediction controller (MPC) hybrid control structures are proposed for the three-column extractive distillation with integrated distillation column (TCED-IDC) process to deal with feed disturbances via taking the separation of ternary azeotropic mixture ethyl acetate-ethanol–water as a case study. The control structures are tested via introducing multiple feed disturbances including one feed flowrates disturbance and three feed compositions disturbances. The dynamic test comparison results show that the integration of preconcentration and solvent recovery functions causes a larger transient deviation in terms of dynamic responses of the individual optimal control structures. In addition, the integral of squared error of the TCED-IDC process are reduced by about 22 times after introducing the MPC in the face of feed disturbances.

Heteroatom-Doped Defects Anchoring Nano-Pt for High-Stability and Low-Humidity Proton Exchange Membrane Fuel Cell.

To meet the ever-increasing demand of proton exchange membrane fuel cell (PEMFC), it is necessary to carry out structure optimization for low-cost and high-stability oxygen reduction reaction (ORR) catalysts. Herein, a zeolitic imidazolate framework (ZIF)-derived carbon material with a mass of heteroatoms and defects is developed and serves as advanced support for nano-Pt-based ORR catalysts. This unique structure enhances the interaction between nano-Pt and support, leading to higher ORR intrinsic activity. During fuel cell applications, it demonstrates impressive water-retaining capacity and electrochemical stability. Under H2-O2 supply without cathode humidification, this catalyst achieves high mass activity of 0.475 A mgPt -1, with only 7.4% attenuation in maximum power density after 20 000 cycles of accelerated durability test, highlighting its remarkable potential for fuel cell applications. Physicochemical characterization and theoretical simulation reveal the crucial anchoring effect of heteroatom-doped defects to nano-Pt, providing valuable insights for further ORR catalyst design and PEMFC applications.

Numerical investigation on the effect of area ratio on an adjustable ejector for heat pump dryer based on dynamic mesh

Adjustable ejector is considered as a promising device to recover the expansion work and enhance the performances of refrigeration or heat pump system. To investigate the impacts of area ratio (AR) of mixing chamber throat to nozzle throat, a dynamic mesh based numerical model of an adjustable ejector for the heat pump dryer was established. The area of nozzle throat could be modified by adjusting the position of needle. The movement of needle was simulated by using the dynamic mesh method. The effects of the nozzle throat area and the mixing chamber throat area on the ejector performances were investigated. Further, the optimal values of dimensionless parameter AR under the different structure parameters of ejector were estimated. The numerical model was validated by the experimental results, and the k-ε standard turbulence model was proved to predict the ejector performances well. The numerical results indicated the optimal AR to obtain the maximum entrainment ratio of ejector ranged from 2.65 to 4.87 at the given working condition. Among the structure parameters of ejector, the length of constant-area mixing section has the greatest influence on the optimal AR. These numerical results provided the guidance for structure optimization of adjustable ejectors in heat pump dryer.

Can the resource and environmental dilemma due to water-energy-carbon constraints be solved in the process of new urbanization?

The rapid development of basin resource-based cities (BRCs) in developing countries have led to severe resource and environmental problems centered on the “water-energy-carbon” (WEC) nexus. Based on their spatiotemporal evolution, WEC constraints are evaluated via a multidimensional coupling coordination degree (CCD) mode. Resource-environmental efficiency (REE) under these constraints is measured via the superefficiency SBM model. The path of resource and environmental improvement via new urbanization (NU) is discussed based on the spatial econometric model. Water resource consumption in the BRCs decreased by 12.22 %, but energy consumption and carbon emissions increased by 20.1 % and 70.05 %, respectively, and the CCD of the WEC nexus showed a “highly coordinated - seriously imbalanced” change. Therefore, the REE increase of 44.03 % was unsustainable. NU improved REE and reduced water resource consumption but did not reduce energy consumption or carbon emission, and there is significant regional variability. Scientific and technological innovation, economic agglomeration and land structure diversity contributed to the resource-environmental improvement effects of NU, but optimized industrial structures and environmental governance had masking effects. The policy implication is that during NU, efficiency gains must be combined with policies to promote industrial structure optimization and environmental governance and thus achieve sustainable urban development.

Enhanced De/hydrogenation Kinetics and Cycle Stability of Mg/MgH2 by the MnOx-Coated Ti2CTx Catalyst with Optimized Ti-H Bond Stability.

MXene based catalysts can significantly enhance hydrogenation and dehydrogenation (de/hydrogenation) kinetics of Mg/MgH2, but they suffer from uncontrollable catalysts-hydrogen bond strength and structural instability. Here, we propose Tx density control of MXene-based catalysts and MnOx coating as a promising solution. The MnOx@Ti2CTx-catalyzed Mg/MgH2 can release 5.97 wt % H2 at 300 °C in 3 min and 5.60 wt % H2 at 240 °C in 15 min with an activation energy of 75.57 kJ·mol-1. In addition, the samples showed excellent de/hydrogenation-cycle stability, and the degradation of hydrogen storage capacity is negligible even after 100 cycles. DFT calculations combined with XPS analysis showed that the Tx defect on the surface of the MnOx@Ti2CTx catalyst could optimize the strength of the Ti-H bond, accelerating both hydrogen dissociation and diffusion processes. The catalyst's surface properties were protected by the MnOx coating, achieving high chemical and catalytic stability. These findings offer a strategy for surface structure optimization and protection of MXene-based catalysts, realizing controllable catalyst-hydrogen bond strength.

Optimization of composite cylinder subjected to hydrostatic pressure using customized evolutionary algorithm

The structure for optimization is a composite cylinder subjected to hydrostatic pressure. The customization is in the method of incorporating the balanced laminate constraint using a while loop which not only improves buckling resistance but also drastically reduces the computation time. The formulation of the objective function is carried out in a novel way. The third customization is in considering geometric variables along with layup in optimization to arrive at the most optimal configuration. The results suggest a significant increase in buckling load ranging from 61.3% to 92.2% and a reduction by about 76.3% in time required for optimization.

Optimal truss design with MOHO: A multi-objective optimization perspective.

This research article presents the Multi-Objective Hippopotamus Optimizer (MOHO), a unique approach that excels in tackling complex structural optimization problems. The Hippopotamus Optimizer (HO) is a novel approach in meta-heuristic methodology that draws inspiration from the natural behaviour of hippos. The HO is built upon a trinary-phase model that incorporates mathematical representations of crucial aspects of Hippo's behaviour, including their movements in aquatic environments, defense mechanisms against predators, and avoidance strategies. This conceptual framework forms the basis for developing the multi-objective (MO) variant MOHO, which was applied to optimize five well-known truss structures. Balancing safety precautions and size constraints concerning stresses on individual sections and constituent parts, these problems also involved competing objectives, such as reducing the weight of the structure and the maximum nodal displacement. The findings of six popular optimization methods were used to compare the results. Four industry-standard performance measures were used for this comparison and qualitative examination of the finest Pareto-front plots generated by each algorithm. The average values obtained by the Friedman rank test and comparison analysis unequivocally showed that MOHO outperformed other methods in resolving significant structure optimization problems quickly. In addition to finding and preserving more Pareto-optimal sets, the recommended algorithm produced excellent convergence and variance in the objective and decision fields. MOHO demonstrated its potential for navigating competing objectives through diversity analysis. Additionally, the swarm plots effectively visualize MOHO's solution distribution of MOHO across iterations, highlighting its superior convergence behaviour. Consequently, MOHO exhibits promise as a valuable method for tackling complex multi-objective structure optimization issues.

Automated model order reduction for building thermal load prediction using smart thermostats data

This paper presents a methodology to automatically determine the structure of sufficiently accurate grey-box models for model predictive control, energy efficiency and flexibility applications in buildings. The methodology is based on model reduction and system identification techniques, with a path that enhances data pre-processing, a multistage order reduction, and parameter estimation. The model structure is determined with a cascade approach that either neglects, keeps, or aggregates thermal zones by using discrete and continuous frequency domain techniques. Once the optimal structure is identified, the parameters are calibrated with the measured data from smart thermostats, using the model predictive control relevant identification method. The methodology is applied to a monitored house located in Québec, Canada. The developed algorithm identifies adjacent zones, even when the building layout is unknown, by studying indoor temperature fluctuations. The results concerning the model creation suggest that, for this specific building, the aggregation by floor is the most efficient way for creating reduced order thermal models, limiting uncertainty due to thermal zone interaction. This methodology provides control-oriented models that accurately predict response up to 24-h ahead with Root Mean Square Error less than 0.5 °C and acceptable Fitness Function values for the minimum number of selected parameters. Finally, several scenarios demonstrate the insights gained from using grey-box building thermal models for design, control, and retrofitting applications.

Can the digital economy facilitate the optimization of industrial structure in resource-based cities?

With the continuous development of economy, resource-based cities in China are in urgent need of transforming and upgrading their industrial structures. This article utilizes panel data of 114 resource-based cities from 2011 to 2021 to explore the impact and mechanism of digital economy on optimizing and upgrading industrial structure. The findings, demonstrating a nonlinear relationship, reveal that digital economy promotes the advancement of the industrial structure in resource-based regions significantly. Technological innovation and financial development serve as the intermediary channel of facilitating the advancement of industrial structure in digital economy through intermediary effect analysis. Moreover, in terms of regional heterogeneity, digital economy is more effective in assisting inland resource-based cities in achieving advanced industrial structure compared to coastal areas in China.

The past and future dynamics of ecological resilience and its spatial response analysis to natural and anthropogenic factors in Southwest China with typical Karst

With the global land use/land cover (LULC) and climate change, the ecological resilience (ER) in typical Karst areas has become the focus of attention. Its future development trend and its spatial response to natural and anthropogenic factors are crucial for understanding the changes of ecologically fragile areas to human behavior. However, there is still a lack of relevant quantitative research. The study systematically analyzed the characteristics of LULC changes in Southwest China with typical Karst over the past 20 years. Drawing on the landscape ecology research paradigm, a potential-elasticity-stability ER assessment model was constructed. Revealing the characteristics and heterogeneity of the spatial distribution, annual evolution, and development trend of ER in the past and under different scenarios of shared socioeconomic pathways and representative concentration pathways (SSP-RCP) in the future. In addition, the spatial econometric model was utilized to reveal the spatial effect response mechanism of ER, and adaptive development strategies were proposed to promote the sustainable development of Southwest China. The study found that : (1) In the past 20 years, the LULC in Southwest China showed an accelerated change trend, the ER decreased declined in general, and there was significant spatial heterogeneity, showing the spatial distribution pattern of “west is larger than east, south is larger than north, and reduction in the west was slower than that in the east.” (2) Under the same SSP scenario, with the increase of RCP emission concentration, the area of the lowest-resilience increased significantly, and the area of the highest-resilience decreased. (3) The woodland was the largest contributor to ER per unit area in the Southwest China, and grassland was the main LULC type, which had a prominent impact on the ER of the study area. (4) The average precipitation and the normalized difference vegetation index (NDVI) were significant natural drivers of ER in the study area, and the economic growth, innovation, and optimization of industrial structure contributed to the ER of Southwest China. Overall, the integration of quantitative assessment and multi-scenario-based modeling not only provides new perspectives for understanding the pattern of change and response mechanisms, but also provides valuable references for other typical Karst regions around the world to achieve sustainable development.

VEGFD signaling balances stability and activity-dependent structural plasticity of dendrites

Mature neurons have stable dendritic architecture, which is essential for the nervous system to operate correctly. The ability to undergo structural plasticity, required to support adaptive processes like memory formation, is still present in mature neurons. It is unclear what molecular and cellular processes control this delicate balance between dendritic structural plasticity and stabilization. Failures in the preservation of optimal dendrite structure due to atrophy or maladaptive plasticity result in abnormal connectivity and are associated with various neurological diseases. Vascular endothelial growth factor D (VEGFD) is critical for the maintenance of mature dendritic trees. Here, we describe how VEGFD affects the neuronal cytoskeleton and demonstrate that VEGFD exerts its effects on dendrite stabilization by influencing the actin cortex and reducing microtubule dynamics. Further, we found that during synaptic activity-induced structural plasticity VEGFD is downregulated. Our findings revealed that VEGFD, acting on its cognate receptor VEGFR3, opposes structural changes by negatively regulating dendrite growth in cultured hippocampal neurons and in vivo in the adult mouse hippocampus with consequences on memory formation. A phosphoproteomic screening identified several regulatory proteins of the cytoskeleton modulated by VEGFD. Among the actin cortex-associated proteins, we found that VEGFD induces dephosphorylation of ezrin at tyrosine 478 via activation of the striatal-enriched protein tyrosine phosphatase (STEP). Activity-triggered structural plasticity of dendrites was impaired by expression of a phospho-deficient mutant ezrin in vitro and in vivo. Thus, VEGFD governs the equilibrium between stabilization and plasticity of dendrites by acting as a molecular brake of structural remodeling.

Impact of Industrial Intelligence on China’s Urban Land Green Utilization Efficiency

Against the backdrop of the fourth technological revolution, industrial intelligence (INDI) represented by industrial robots has rapidly developed. This evolution provides favorable opportunities for precise decision-making in pollution control and achieving China’s “dual carbon” goals. Previous studies have mainly discussed the economic effects of INDI from the perspective of the labor market. This study shifts its focus to examining the impact of INDI on the land green utilization efficiency (LGUE) in cities. Using the panel data of Chinese cities spanning 2009–2021, this study empirically tests the effect and transmission mechanism of INDI on LGUE. We find that urban INDI significantly enhances LGUE. In terms of its transmission mechanism, INDI drives improvements in urban LGUE through technological progress, energy structure optimization, and industrial structure upgrading. Urban infrastructure construction and financial agglomeration level can further strengthen the positive impact of INDI on LGUE. In addition, the improvement in LGUE due to INDI is more significant in non-resource-based and large-sized cities than resource-based and small and medium-sized cities. Therefore, each region should enhance the integration of intelligent technology with traditional industrial manufacturing. Doing so is essential to establish comprehensive assessment indicators that balance environmental protection and economic growth, strengthen regional information infrastructure construction, ensure steady financial flow, and support green development initiatives across regions.

Green finance and environmental pollution: Evidence from China

Green finance has emerged as a vital tool in addressing the dual imperatives of environmental protection and economic growth. This study investigates the relationship between green finance initiatives and environmental pollution in China. Drawing on urban data spanning from 2006 to 2021, we employ a comprehensive analysis to discern the impact of green finance policies on mitigating environmental degradation. Our findings highlight the pivotal role of green finance in reducing pollution through channels such as industrial structure optimization, energy mix transformation, and the promotion of green technology. Moreover, we identify specific conditions under which green finance interventions prove most effective, including regions characterized by robust digital economy development, competitive commercial banking, and stringent government environmental regulations. By shedding light on the nuanced interplay between green finance and environmental outcomes, this research underscores the importance of targeted policy measures in fostering ecological sustainability within China's evolving economic landscape.

Finite Element Analysis and Optimization of the Piezoelectric Circular Diaphragm Energy Harvester

The effectiveness of power generation of the piezoelectric energy harvester (PEH) depends on the coupling between its resonant frequency and the oscillation frequency of the vibration source. The resonant frequency of a PEH is determined by its structural design, and therefore, to improve piezoelectric energy harvester performance, the piezoelectric energy harvester must be optimally designed to achieve the resonant frequency that matches the excitation frequency of the vibration source. This paper presents the design and detailed calculation of the piezoelectric energy harvester in the form of a bimorph piezoelectric circular diaphragm (PCD) structure by finite element analysis (FEA) using the software package ANSYS. Based on analyses and calculations, the optimal structure of the piezoelectric circular diaphragm energy harvester is proposed to meet the specified resonant frequency response matching the vibration source frequency. Detailed calculations of the PEH were performed with an excitation frequency of 100 Hz. With an optimal load resistor of 10.1 kΩ, an output power of 0.287 W was generated at 100 Hz (equal to the resonant frequency of the PEH) under an amplitude of harmonic excitation of 0.1mm. In addition, the research results can be used to fabricate piezoelectric circular diaphragm energy harvester operating at a resonant frequency suitable for the available vibrations.

Characterization of o-B2N2 monolayer surface for effective sensing and detection of toxic nitrogen oxides

Using density functional theory (DFT), researchers examined how the o-B2N2 monolayer interacts with toxic gases such as NO2 and NO. They investigated various aspects of the adsorption system, including its state density, differential charge density, optimal structure, and other features. The analysis revealed that the o-B2N2 monolayer remained stable throughout the adsorption process. The researchers also examined additional properties of the adsorption process, including work function, sensitivity, response time, recovery time, and energy gap to gain a deeper comprehension of adsorption features of NO2 and NO gases. The findings indicate that the o-B2N2 monolayer exhibits a shorter recovery time at higher temperatures, suggesting improved performance. Furthermore, the monolayer demonstrates higher sensitivity and a greater variation in the work function, indicating its superior adsorption capabilities. The findings suggest that the o-B2N2 monolayer has potential with great promise as an adsorbent for toxic gases like NO2 and NO. This has practical implications for applications such as air purification and environmental protection. Our findings demonstrate that the o-B2N2 monolayer serves as an effective gas sensor at room temperature, exhibiting both high sensitivity and selectivity in detecting NO2 and NO gases. Moreover, it can be reused multiple times for gas detection purposes.