Structural Modules Research Articles

Optimization and evaluation of tuned inerter-based dampers for mitigating coupled responses of offshore wind turbines

To achieve lightweight vibration control in offshore wind turbines (OWTs), this study proposes the utilization of two types of tuned inerter-based dampers (TIBDs), namely, the tuned viscous mass damper (TVMD) and tuned inerter damper (TID), to mitigate the coupled responses of an OWT induced by wind and wave loads. First, a multi-degree-of-freedom (MDOF) lumped mass model is established to represent an OWT equipped with a TIBD. Then, a novel structural control module for TIBDs is developed and seamlessly integrated into the modular numerical analysis code OpenFAST. This enables fully coupled aero-hydro-servo-elastic simulations of the OWT-TIBD system. Using the established MDOF model, a TIBD parameter optimization design method is proposed to minimize the peak of the non-dimensional displacement frequency response function. Additionally, a parametric study is performed to investigate the effect of inertance and span height on the control performance. Finally, the performance of the TIBD in attenuating both fatigue and extreme loads is evaluated through nonlinear fully coupled time-domain simulations using OpenFAST and compared to traditional tuned mass dampers (TMDs). The results showed that a lightweight and small damper displacement TIBD is capable of effectively dampening OWT vibrations, yielding a better mitigation effect than that provided by a bulky TMD. Overall, the reduced installation requirements and the commendable control efficiency of a TIBD highlight its potential as a promising candidate for passive control devices in OWT applications.

The Influence of Pressure on the Electronic and Elastic Characteristics of GaP Nanocrystals using Density Functional Theory

The electronic structural and mechanical properties of III-V Gallium Phosphide (GaP) nano-crystals zinc-blende stable (ZB) phase under pressure dependence have been studied via the model of the density functional theory (DFT) in combination with the large unit cell (LUC) approach at (8, 16, 54 & 64) atoms. The exchanges and correlations (XC) energy has been defined in all approaches through generalized gradient approximations of the Perdew-Burke-Ernzerhof (GGA-PBE), and determination of GaP characteristics in the case where the pressure has been increased from 0GPa to ±50GPa. Elastic parameters like elastic constants (C11, C12 & C44), Kleinmann parameter (ξ), Zener anisotropic factor (A), shear modulus (G), Young's modulus (E), Poisson’s ratio (v), Bulk modules (B) of GaP-ZB structure have been calculated and showed systematic variation with a pressure increase. Our calculations show that Bulk modules and sound speed increase with an increase in the number of core atoms. In this systematic approach, it has been found that the B/G ratio is 1.58 for this compound and it exhibits a negative Cauchy pressure, classifying GaP as brittle. The results were discovered to be consistent with other theoretical as well as experimental results. The present study directly relates to the latest experimental works on the III-phosphide compounds. The current results provide information and direction for further investigation into the fundamentals and potential applications of gallium phosphate (GaP) nanocrystals. In addition, we attempted to compare the results of the investigation with some similar types of compounds that are already documented in the literature. We believe that our study will have a significant impact on both the field of research and contemporary technology based on semi-conducting materials.

Cascade contour-enhanced panoptic segmentation for robotic vision perception

Panoptic segmentation plays a crucial role in enabling robots to comprehend their surroundings, providing fine-grained scene understanding information for robots' intelligent tasks. Although existing methods have made some progress, they are prone to fail in areas with weak textures, small objects, etc. Inspired by biological vision research, we propose a cascaded contour-enhanced panoptic segmentation network called CCPSNet, attempting to enhance the discriminability of instances through structural knowledge. To acquire the scene structure, a cascade contour detection stream is designed, which extracts comprehensive scene contours using channel regulation structural perception module and coarse-to-fine cascade strategy. Furthermore, the contour-guided multi-scale feature enhancement stream is developed to boost the discrimination ability for small objects and weak textures. The stream integrates contour information and multi-scale context features through structural-aware feature modulation module and inverse aggregation technique. Experimental results show that our method improves accuracy on the Cityscapes (61.2 PQ) and COCO (43.5 PQ) datasets while also demonstrating robustness in challenging simulated real-world complex scenarios faced by robots, such as dirty cameras and rainy conditions. The proposed network promises to help the robot perceive the real scene. In future work, an unsupervised training strategy for the network could be explored to reduce the training cost.

Heron: Visualizing and Controlling Chemical Reaction Explorations and Networks.

Automated and high-throughput quantum chemical investigations into chemical processes have become feasible in great detail and broad scope. This results in an increase in complexity of the tasks and in the amount of generated data. An efficient and intuitive way for an operator to interact with these data and to steer virtual experiments is required. Here, we introduce Heron, a graphical user interface that allows for advanced human-machine interactions with quantum chemical exploration campaigns into molecular structure and reactivity. Heron offers access to interactive and automated explorations of chemical reactions with standard electronic structure modules, haptic force feedback, microkinetic modeling, and refinement of data by automated correlated calculations including black-box complete active space calculations. It is tailored to the exploration and analysis of vast chemical reaction networks. We show how interoperable modules enable advanced workflows and pave the way for routine low-entrance-barrier access to advanced modeling techniques.

Genomics and evolutionary analysis of Chlorella variabilis-infecting viruses demarcate criteria for defining species of giant viruses.

Chloroviruses exhibit a close relationship with their hosts with the phenotypic aspect of their ability to form lytic plaques having primarily guided the taxonomy. However, with the isolation of viruses that are only able to complete their replication cycle in one strain of Chlorella variabilis, systematic challenges emerged. In this study, we described the genomic features of 53 new chlorovirus isolates and used them to elucidate part of the evolutionary history and taxonomy of this clade. Our analysis revealed new chloroviruses with the largest genomes to date (>400 kbp) and indicated that four genomic features are statistically different in the viruses that only infect the Syngen 2-3 strain of C. variabilis (OSy viruses). We found large regions of dissimilarity in the genomes of viruses PBCV-1 and OSy-NE5 when compared with the other genomes. These regions contained genes related to the interaction with the host cell machinery and viral capsid proteins, which provided insights into the evolution of the replicative and structural modules in these giant viruses. Phylogenetic analysis using hallmark genes of Nucleocytoviricota revealed that OSy-viruses evolved from the NC64A-viruses, possibly emerging as a result of the strict relationship with their hosts. Merging phylogenetics and nucleotide identity analyses, we propose strategies to demarcate viral species, resulting in seven new species of chloroviruses. Collectively, our results show how genomic data can be used as lines of evidence to demarcate viral species. Using the chloroviruses as a case study, we expect that similar initiatives will emerge using the basis exhibited here.IMPORTANCEChloroviruses are a group of giant viruses with long dsDNA genomes that infect different species of Chlorella-like green algae. They are host-specific, and some isolates can only replicate within a single strain of Chlorella variabilis. The genomics of these viruses is still poorly explored, and the characterization of new isolates provides important data on their genetic diversity and evolution. In this work, we describe 53 new chlorovirus genomes, including many isolated from alkaline lakes for the first time. Through comparative genomics and molecular phylogeny, we provide evidence of genomic gigantism in chloroviruses and show that a subset of viruses became highly specific for their hosts at a particular point in evolutionary history. We propose criteria to demarcate species of chloroviruses, paving the way for an update in the taxonomy of other groups of viruses. This study is a new and important piece in the complex puzzle of giant algal viruses.

High-entropy spinel oxide: Synthesis and photo-responsivity of Mn0.68Cr0.8Rh0.64Co0.87O4

Recently, there has been extensive research on modulating band structures using MnCr2O4, which has gained significant attention as a photocatalyst. However, due to thermodynamic constraints, conventional modulation of band structures using two compositions poses challenges. Therefore, we utilized a high-entropy approach to easily modulate band structures by forming multi-composition systems (three-composition oxides or higher). The spinel structure of Mn0.68Cr0.8Rh0.64Co0.87O4 produced via electrospinning enabled the fabrication of nano fibers with an average diameter of 160 nm at a calcination temperature of 900 °C, and these nano fibers were crystallized through various analytical instruments. Furthermore, nanofibers calcined at 900 °C exhibited high responsivity and fast rise, decay times under a light source with a wavelength of 635 nm. Thus, with such high reactivity, fast response time, and clear selectivity, Mn0.68Cr0.8Rh0.64Co0.87O4 indicates promising potential as a material for future photo-catalytic research.

Structural and Spectroscopic Characterization of Supported Sarcoplasmic Reticulum Membranes on Solid Substrates.

Sarcoplasmic reticulum (SR) membranes from rabbit muscle were deposited on silicon substrates and characterized by the combination of spectral ellipsometry (SE), high energy specular X-ray reflectivity (XRR), specular neutron reflectivity (NR), and attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy. Following the optimization of the preparative conditions by SE, the detailed structures in the direction perpendicular to the membrane were probed by XRR. ATR-FTIR data showed strong signals from amide I and amide II bands of the native SR membranes containing a large amount of Ca2+-ATPase, which could not be achieved by the reconstitution in artificial lipid membranes. The treatment with protease led to a significant decrease in the amide peaks, and the XRR data confirmed the modulation of the membrane structures. The obtained data show the potential of the in situ combination of reflectivity and vibrational spectroscopy of native supported membranes in order to unravel both structure and dynamics of complex biological membranes.

Versatile Molecular Structure Strategy Toward Highly Efficient Single‐Component White Organic Light–Emitting Diodes

AbstractLuminophores' dual emission (DE) properties hold great potential for realizing single‐component white organic light–emitting diodes (WOLEDs). This study illustrates that the unique and vibrant DE phenomena with different luminous mechanisms can be formed through simple modulation of molecular structures. Four target luminophores, namely 2‐TPE‐PPI, 2‐TPE‐PI, 2‐TPE‐An‐PPI, and 2‐TPE‐An‐PI, capable of DE under different conditions, are intentionally designed and successfully synthesized. Owing to the inherent flexibility of the minor molecular backbone and minor steric hindrance, 2‐TPE‐PPI and 2‐TPE‐PI exhibit DE spectra in dilute solutions with different solvent polarities. The intrinsic cause of the DE phenomenon in 2‐TPE‐An‐PPI and 2‐TPE‐An‐PI arises from the localized distribution of frontier molecular orbits resulting from the presence of an anthracene unit and the formation of an exciter group through intermolecular interactions involving anthracene. Remarkably, single‐emissive‐layer WOLEDs based on 2‐TPE‐An‐PPI and 2‐TPE‐An‐PI demonstrate stable white emission with CIE coordinates at (0.33, 0.39) and (0.30, 0.39), respectively, closely approaching the CIE coordinates of standard white light. Moreover, they maintain stable EL spectra from 4 to 10 V, an exceptional attribute rarely observed in many white light devices.

Structural–Parametric Synthesis of Path-Generating Mechanisms and Manipulators

This paper presents a structural–parametric synthesis of the four-link and Stephenson I, Stephenson II, and Stephenson III six-link path-generating mechanisms. The four-link path-generating mechanism is formed by connecting the output point and the base using an active closing kinematic chain (CKC) with two DOFs and a negative CKC of the type RR. The six-link path-generating mechanisms are formed by connecting the output point and the base by active, passive and negative CKCs. Active CKC has active kinematic pair, passive CKC has zero DOF, and negative CKC has a negative DOF. Active and negative CKCs impose geometrical constraints on the movement of the output point, and the geometric parameters of their links are determined by least-square approximation. Geometric parameters of the passive CKC are varied to satisfy the geometrical constraints of the active and negative CKCs. The CKCs of the active, passive and negative types, connecting the output point and the base, are the structural modules from which the different types of the path-generating mechanisms are synthesized. Numerical examples of the parametric synthesis of the four-link and six-link path-generating mechanisms are presented.

Design and experimental study of solar-driven biomass gasification based on direct irradiation solar thermochemical reactor

Solar-driven biomass steam gasification is a promising technology to produce H2-rich syngas, meanwhile achieve flexible storage of renewable energy. However, the solar gasification application also faces numerous challenges, due to its involved complex chemical reaction characteristics and the inherent the multi-physics energy conversion processes. This work designs a novel direct irradiation solar gasification reactor, with the improved optical acceptance structure and reasonable test module, and the wheat straw particle is selected as experimental sample. Employing a 9 kWe high flux solar simulator, the maximum temperature of reaction bed in this prototype reactor reaches to 1260 °C, with the average solar flux of 1171.3 kW/m2. With adjustable radiation flux as experiment factor, under the highest total radiation of 3.35 kW, the molar fraction of H2 in the produced syngas is 47.1 % with the energy upgrade factor of 1.15, and the cellulose component completes decomposition. Increasing the mass flow rate of steam reduces the syngas output while raising the H2/CO ratio of the syngas. In addition, smaller biomass particle size facilitates the reaction, thereby improving the conversion efficiency of direct irradiation gasification. The investigation results provide a meaningful reference for the efficient utilization of abundant solar and biomass energy.

A simple method and case study of task planning for collaborative design based on FDSM

In multiperson collaborative mechanical product design, unreasonable task allocation can result in excessive coupling between tasks, complex design communication, and rework, particularly in small enterprises and teams that rely primarily on experience. Hence, this study proposes a simple and efficient task-planning method based on a fuzzy design structure matrix (FDSM), which involves single-level task decomposition, three-level number assignment of the coupling relationship, decoupling of the structural tree algorithm, and validation of the optimization results based on the G-value. Design tasks are promptly allocated into a single level based on the functional structure module of the product. The task-correlation degree is quantified based on three levels of numerical values through personal experience to construct an FDSM, the latter of which is decoupled by the correlation degree of the structural tree algorithm to obtain the optimized sequence and allocation of the collaborative design task. Finally, the effectiveness of the planning is verified by calculating the tightness of the corresponding matrix before and after the planning. A task-planning case of a riveting-machine design for capacitor cover plates is established to validate this method.

Safety Analysis of Metallic Tokamak-I Against Electromagnetic and Structural Loads

During tokamak operation, the structural integrity of the vacuum vessel (VV) of Metallic Tokamak-I (MT-I), a small spherical tokamak, was evaluated. This evaluation involved simulating real experimental data of electromagnetic (EM) and structural loads using the ANSYS platform. Internal heat generation, induced currents, and inertial and pressure loads in the VV were analyzed to determine their effects on the VV. This analysis was conducted on a 180-deg sector model over a 10-ms-event period. To create multiple checkpoint events, the plasma current was assumed to be formed at variable positions of the VV, hence inducing variable current for each event. The events are divided into four cases based on the radial and vertical displacements of plasma. The response of the VV structure was calculated using coupling of EM and structural modules of ANSYS. It is observed from the numerical results that the maximum stress on the VV is in a safe range and that the temperature rise on the vessel can be reduced by natural convection only if the event is ended in 10 ms. A prolonged event can result in permanent deformation in the VV structure. A disruption event on the limiter region is also studied.

Modulation of p-Block Electron Orbits in Metal-Organic Frameworks for CO2 Capture and Electrochemical Reduction.

Developing catalysts with excellent CO2 capture capability and electrochemical CO2 reduction reaction (CO2RR) at a wide potential range simultaneously is significant but remains a formidable challenge. Here, two novel InMg defective trinuclear cluster-based MOFs (SNNU-41 and SNNU-42) with abundant p-block unsaturated coordinated sites were reported and exhibited good CO2 capture and CO2RR performance simultaneously. Due to the suitable micropores, SNNU-41 showed higher CO2 capture ability at different adsorption pressure conditions. On account of the rigid framework and the closer p band center to Fermi level, SNNU-42 accelerated the conversion of CO2 molecule to C1 efficiency. Notably, via adjusting the ratio of p-block metal (In) in the SNNU-42 framework, the performance of the CO2RR was promoted drastically. SNNU-42 with the InMg (1:1.8) mixed cluster delivered an excellent Faradaic efficiency of 91.3% for C1 products and high selectivity of 72.0% for HCOOH at -2.5 V (vs Ag/Ag+) with a total current density of 77.2 mA cm-2. This work provides a possibility for efficient CO2 capture and CO2RR electrocatalysts through the modulation of electronic structures and composition in MOFs.

Preventing Inappropriate Signals Pre- and Post-Ligand Perception by a Toggle-Switch Mechanism of ERECTA.

Dynamic control of signaling events requires swift regulation of receptors at an active state. By focusing on Arabidopsis ERECTA (ER) receptor kinase, which perceives peptide ligands to control multiple developmental processes, we report a mechanism preventing inappropriate receptor activity. The ER C-terminal tail (ER_CT) functions as an autoinhibitory domain: its removal confers higher kinase activity and hyperactivity during inflorescence and stomatal development. ER_CT is required for the binding of a receptor kinase inhibitor, BKI1, and two U-box E3 ligases PUB30 and PUB31 that inactivate activated ER. We further identify ER_CT as a phosphodomain transphosphorylated by the co-receptor BAK1. The phosphorylation impacts the tail structure, likely releasing from autoinhibition. The phosphonull version enhances BKI1 association, whereas the phosphomimetic version promotes PUB30/31 association. Thus, ER_CT acts as an off-on-off toggle switch, facilitating the release of BKI1 inhibition, enabling signal activation, and swiftly turning over the receptors afterwards. Our results elucidate a mechanism fine-tuning receptor signaling via a phosphoswitch module, keeping the receptor at a low basal state and ensuring the robust yet transient activation upon ligand perception.

UCFTNet: multi-class dtection of city critical disaster information based on U-shaped cross fusion transformer

ABSTRACT With the continuous enhancement of remote sensing data acquisition capabilities, the demand for efficient extraction of multi-class critical urban disaster information has become increasingly urgent. However, current deep learning-based models primarily focus on single disaster objects and struggle with accuracy in complex post-disaster scenarios. To address this, we propose UCFTNet, a semantic segmentation model for urban post-disaster damaged roads and buildings. UCFTNet employs a U-shaped encoder-decoder structure and ConvNext modules, integrating spatial and multi-scale information of damaged buildings and roads from different scales and channels. Additionally, the decoder uses the CCT module and CFF module to merge multi-scale features and eliminate irrelevant background interference. Finally, a weighted loss function is designed to enhance the model's focus on disaster category pixels. Experimental results demonstrate that UCFTNet improves the accuracy of extracting damaged buildings and roads by at least 5% across three urban disaster datasets, confirming its effectiveness in post-disaster damage information extraction.

Blockchain Based Analytical Bug Tracking in Software Engineering

This article examines a blockchain-based bug tracking system in detail, focusing on its four main components: the Blockchain Platform, the Consensus Mechanism (also known as Proof of Work, PoW), the Data Structure, and Smart Contracts. To improve the efficiency, security, and transparency of bug tracking in software development, we use mathematical models to dissect the operational framework and functionalities that underpin this cutting-edge system. The Blockchain Platform is the foundational layer. It stores data in multiple locations, cannot be changed, and provides a secure environment for fixing software bugs. We use mathematical abstractions to demonstrate how the blockchain is put together, emphasizing the importance of cryptographic hashes in maintaining data integrity and connecting blocks. People pay close attention to the Consensus Mechanism, particularly Proof of Work (PoW), because it is so important for verifying transactions and maintaining the blockchain's integrity. Using a mathematical model, we demonstrate how Proof of Work (PoW) prevents bad behavior while keeping the network safe and democratic by requiring work to be done on a computer to add blocks. The Data Structure module is examined using a model that depicts how bug reports are stored and found on the blockchain. This model demonstrates the efficiency of storing bug reports as transactions, which allows for quick access and unchangeable record-keeping. People associate smart contracts with self-running programs that manage permissions, automate workflows, and provide incentives for reporting bugs. Mathematical models are used to demonstrate how these contracts' conditions and actions are documented, emphasizing their importance in automating tasks and improving system reliability. This article uses mathematical modeling to provide a clear and structured understanding of a blockchain-based bug tracking system and demonstrate how it could change the way bugs are tracked by leveraging blockchain technology's strengths.

Enhancement of peroxymonosulfate activation with nickel foam-supported CuCo2O4 for tetracycline degradation: Performance and mechanism insights

The modulation of bimetallic oxide structures and development of efficient, easily recoverable catalysts are expected to effectively overcome the limitations associated with powdered catalysts in activating peroxymonosulfate (PMS). In this study, CuCo2O4 was successfully immobilized on the surface of nickel foam (NF) via an electrodeposition-calcination procedure, with highly efficient activation of PMS for tetracycline (TC) degradation (0.55 min−1). Besides acting as a support carrier and providing ample active sites, NF mediated electron transport, prevented the leaching of metal ions and enhanced the efficiency of recycling. Density functional theory (DFT) calculations and experimental tests illustrated that Cu/Co dual-sites can efficiently adsorb PMS, enabling simultaneous reduction and oxidation reactions. The dual-site synergy substantially decreased the adsorption barrier and increased the electron transfer rate. Especially, the Cu+/Cu2+ redox couple acted as an electron donor and facilitated rapid charge transfer, leading to the conversion of Co3+ to Co2+. Moreover, the CuCo2O4@NF + PMS system effectively eliminated TC by employing radical pathways (SO4•−, •OH) and nonradical processes (1O2, e−). Therefore, this study introduces a new approach to overcome the limitations of powdered bimetallic oxides, providing a promising solution for practical applications.

Internal Space Modulation of Yolk-Shell FeSe2@Carbon Anode with Peanut-Shaped Morphology Enabling Ultra-Stable and Fast Potassium-Ion Storage.

The poor cycling stability and rate performance of transition metal selenides (TMSs) are caused by their intrinsic low conductivity and poor structural stability, which hinders their application in potassium-ion batteries (PIBs). To address this issue, encapsulating TMSs within carbon nanoshells is considered a viable strategy. However, due to the lack and uncontrollability of internal void space, this structure cannot effectively mitigate the volume expansion induced by large K+, resulting in unsatisfactory electrochemical performance. Herein, peanut-shaped FeSe2@carbon yolk-shell capsules are prepared by modulation of the internal space. The active FeSe2 is encapsulated within a robust carbon shell and an optimal void space is retained between them. The outer carbon shell promotes electronic conductivity and avoids FeSe2 aggregation, while the internal void mitigates volume expansion and effectively ensures the structural integrity of the electrode. Consequently, the FeSe2@carbon anode demonstrates exceptional rate performance (242 mAh g-1 at 10 A g-1) and long cycling stability (350 mAh g-1 after 500 cycles at 1 A g-1). Furthermore, the effect of internal space modulation on electrochemical properties is elucidated. Meanwhile, ex situ characterizations elucidate the K+ storage mechanism. This work provides effective guidance for the design and the internal space modulation of advanced TMSs yolk-shell structures.

An Improved YOLOv8 OBB Model for Ship Detection through Stable Diffusion Data Augmentation.

Unmanned aerial vehicles (UAVs) with cameras offer extensive monitoring capabilities and exceptional maneuverability, making them ideal for real-time ship detection and effective ship management. However, ship detection by camera-equipped UAVs faces challenges when it comes to multi-viewpoints, multi-scales, environmental variability, and dataset scarcity. To overcome these challenges, we proposed a data augmentation method based on stable diffusion to generate new images for expanding the dataset. Additionally, we improve the YOLOv8n OBB model by incorporating the BiFPN structure and EMA module, enhancing its ability to detect multi-viewpoint and multi-scale ship instances. Through multiple comparative experiments, we evaluated the effectiveness of our proposed data augmentation method and the improved model. The results indicated that our proposed data augmentation method is effective for low-volume datasets with complex object features. The YOLOv8n-BiFPN-EMA OBB model we proposed performed well in detecting multi-viewpoint and multi-scale ship instances, achieving the mAP (@0.5) of 92.3%, the mAP (@0.5:0.95) of 77.5%, a reduction of 0.8 million in model parameters, and a detection speed that satisfies real-time ship detection requirements.

Research on the application of AHP-FAST-FBS in the design of home entrance disinfection devices in the post-pandemic era

With the outbreak and continued spread of the COVID-19 pandemic, people's demand for daily disinfection products has increased rapidly, and its innovative design has received widespread attention. In this context, this study aims to propose a design methodology for home entrance disinfection devices based on AHP-FAST-FBS. Firstly, the design requirements of the home entrance disinfection device were collected and analyzed through in-depth interviews and the KJ method, and a hierarchical model of design demand indicators was constructed. Secondly, the Analytical Hierarchy Process (AHP) was employed to quantify these design demand indicators, and core design demands for home entrance disinfection devices were identified by weight calculations. On this basis, the Functional Analysis System Technique (FAST) method was combined to rationally transform the design demands into product functional indicators, constructing a functional system model for the home entrance disinfection device through systematic decomposition and categorization. Lastly, based on the Function-Behavior-Structure (FBS) theoretical model, the mapping of each function of the product to its structure was realized, the product structure modules were determined, and the comprehensive design and output of the innovative design scheme for the home entrance disinfection device were completed. The results of this study indicate that the design methodology combining AHP-FAST-FBS can effectively improve the scientific rigor and effectiveness of the home entrance disinfection device design, thereby generating an ideal product design scheme. This study provides systematic theoretical guidance and practical reference for designers of subsequent related disinfection products and also offers a new path for improving social health and safety.