Intelligent quintuplet synergistic sterilization, toxicity reduction and long-term storage system
Through an AI-driven five-in-one synergistic sterilization and detoxification system, combined with cold plasma, ozone, NO self-generating system and nitrogen barrier module, molecular-level lysis of microorganisms and toxins is achieved. This solves the problems of insufficient anti-mold and sterilization and toxin treatment in existing storage technologies, reduces energy consumption and adapts to the long-term storage needs of various materials, and has self-learning and self-repair capabilities.
Patent Information
- Application Number
- CN202511758063.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-27
- Publication Date
- 2026-03-17
AI Technical Summary
Existing storage technologies are insufficient in preventing mold and sterilization in long-term storage and complex environments, are difficult to handle toxins, are highly dependent on external gases, have high operating costs, have simple control logic, poor adaptability to multiple materials, have a high risk of secondary pollution, lack toxin detection and response mechanisms, and lack green environmental protection and digital management capabilities.
The AI-driven five-in-one synergistic sterilization and detoxification system utilizes the time-series coupling of cold plasma, ozone, NO self-generating system, chlorine dioxide and nitrogen barrier modules, combined with an AI central control module, to achieve a multi-stage free radical oxidation-nitrogen barrier synergistic mechanism for real-time monitoring and intelligent control, thereby realizing microbial identification, oxidative pyrolysis, toxin degradation and environmental homeostasis maintenance.
It achieves broad-spectrum and efficient sterilization and deep detoxification, reduces energy consumption, adapts to a variety of materials, has self-learning and self-repair capabilities, meets the needs of long-term steady-state storage, and is suitable for the safe storage of grains, medicinal materials, seeds, nuts, spices and animal-derived raw materials.
Smart Images
Figure CN121668359A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of storage technology, and in particular to an AI-driven five-in-one synergistic sterilization, detoxification and long-term storage system, which can be widely used for the prevention of mold, corrosion, toxin degradation and long-term stable preservation of plant and animal storage materials. Background Technology
[0002] Existing storage anti-mold and anti-corrosion technologies mainly rely on low temperature, drying, nitrogen filling or chemical antibacterial agents to extend the storage period. Common technical routes include: (1) low temperature refrigeration: inhibiting microbial metabolism by cooling; (2) drying and dehumidification: reducing water activity to slow down mold growth; (3) nitrogen filling or vacuum sealing: using inert gas to isolate oxygen; (4) chemical preservative method: using chemical additives such as antioxidants and anti-mold agents to achieve short-term inhibition.
[0003] However, the above methods have obvious limitations under long-term storage and complex environmental conditions: insufficient depth of mold prevention and sterilization; low temperature and drying methods can only delay the growth of mold and bacteria, and have limited killing ability against spore-type microorganisms and stress-resistant spore-forming bacteria; nitrogen-filled environments cannot destroy the existing colony structure.
[0004] Toxins are difficult to handle: In plant and animal-based storage materials, fungal metabolites such as aflatoxin B1, ochratoxin A, and zearalenone can be continuously generated or accumulated during conventional storage. Existing storage systems cannot effectively degrade these highly stable toxins, and there are still potential food safety hazards.
[0005] High dependence on external gases and high operating costs: Traditional nitrogen, carbon dioxide or ozone protection systems rely on high-pressure steel cylinders or external gas source devices, resulting in high energy consumption and maintenance costs, which is not conducive to long-term continuous operation.
[0006] The control logic is simple and lacks dynamic intelligent adjustment: Most storage devices rely solely on temperature and humidity monitoring and cannot identify the types of microorganisms, toxin concentrations, or redox states, resulting in delayed or excessive reaction control and making it difficult to achieve a balance between precise inhibition and energy saving.
[0007] Poor adaptability to various materials: Various storage materials such as grains, seeds, Chinese medicinal materials, proteins and dried animal products vary significantly in terms of composition, water activity and oxygen sensitivity. Existing systems lack adaptive algorithms and multi-mode switching capabilities.
[0008] High risk of secondary contamination: Traditional storage methods are prone to air backflow after opening the warehouse or after air pressure fluctuations, which can introduce external sources of pollution; chemical preservative residues may also cause a decline in material quality or safety risks.
[0009] Lack of toxin detection and response mechanisms: Most existing technologies rely on manual or periodic detection, which cannot identify and respond quickly in the early stages of toxin formation, and lack a systematic "monitoring-response-stabilization" closed-loop control system.
[0010] Lack of green and digital management capabilities: Chemical additive storage solutions have residue and emission problems; traditional refrigeration and gas systems have high energy consumption and large carbon footprints; most systems have failed to achieve cloud management or AI self-learning optimization, making it difficult to meet the requirements of modern smart storage and green sustainable development.
[0011] Therefore, current storage technologies urgently need a system platform with a multi-stage free radical oxidation-nitrogen barrier synergistic mechanism and AI intelligent sensing and control, which can monitor the levels of microorganisms and toxins in a dynamic environment in real time, automatically adjust the reaction sequence and energy consumption parameters, and achieve broad-spectrum sterilization, deep detoxification and long-term steady-state storage without relying on external gas sources, so as to meet the high-quality and long-term safe storage needs of plant and animal materials. Summary of the Invention
[0012] This invention aims to provide an AI-driven five-in-one synergistic sterilization, detoxification, and long-term storage system. This system achieves intelligent control of the entire process from microbial identification to oxidative pyrolysis, toxin degradation, nitrogen barrier stabilization, and intelligent reset through the five-in-one temporal coupling of cold plasma, ozone, NO self-generating system, chlorine dioxide, and nitrogen barrier stabilization modules. Driven by the dynamic monitoring, data decision-making, and energy consumption self-adjustment algorithm of the artificial intelligence (AI) central control module, the system is powered by AI.
[0013] This invention breaks through the passive mold prevention mode of traditional storage systems that rely solely on low temperature, dryness, or inert gas protection. It constructs an active intelligent storage platform that integrates chemical kinetics, electronic layer energy level control, and AI algorithm decision-making. This platform achieves molecular-level lysis and complete inactivation of microorganisms (bacteria, molds, spores) and their metabolic toxins (aflatoxin, ochratoxin, etc.), and maintains a low-oxygen, clean, and self-healing steady-state environment during the storage period. It provides a systematic solution for the long-term safe storage and green pest control of grains, Chinese medicinal materials, seeds, nuts, spices, and animal-derived raw materials.
[0014] Technical solution System Overall Structure
[0015] This invention proposes an intelligent five-unit synergistic sterilization, detoxification, and long-term storage system. The system consists of an AI central control module and five sequentially linked reaction modules: a cold plasma module, an ozone generation module, a self-generating NO system, a chlorine dioxide activation module, and a nitrogen barrier stabilization module. The system adopts a hierarchical architecture + AI dynamic temporal synergistic control mode, forming seven functional layers in terms of hardware, algorithms, and energy level mechanisms. AI perception and decision-making layer: Real-time perception of environment and biological signals to achieve "self-perception - self-judgment - self-response"; Five-stage synergistic reaction layer: Sterilization and detoxification are achieved through multi-stage free radical and complex oxidation chain reactions; Electronic level excitation layer (ELAM): High-frequency electric field induces electronic level rearrangement, triggering directional breaking of molecular bonds; Gas dynamics and mixing equilibrium layer: Maintains uniform distribution of reactant gases and free radicals through flow guiding structures; Nitrogen barrier stable layer: Establishing a long-term clean barrier with low oxygen and weak oxidation; Energy self-adjustment layer: Based on AI algorithm power-time optimization, it achieves the optimal energy efficiency ratio; Cloud-based learning and traceability layer: supports remote control, model updates, and multi-warehouse network collaboration.
[0016] II. Core Reaction Mechanism and Electron Layer Interaction Mechanism (1) Multilevel free radical and complex oxidation synergistic system (ROS / RNS / AOS)
[0017] The cold plasma module operates at a discharge frequency of 5–200 kHz and a voltage of 2–25 kV. It can generate high-energy electron flow (e⁻) and various free radicals such as ·OH, ·O, O⁻·, and HOO· in normal or slightly negative pressure environments, thereby realizing the physical lysis of microbial cell walls and membranes and the primary reaction of electron layer excitation.
[0018] The ozone generation module outputs a concentration of 5–500 mg / m³, which enters the reaction zone after a delay of 1 s to 3600 s following plasma excitation, forming an O3–·OH composite oxide layer. This composite layer is coupled with the electron layer excitation mechanism (ELAM) to form an energy level progressive oxidation system, which is used to improve the reaction rate, spatial penetration, and toxin molecule chain scission efficiency.
[0019] The NO self-generating system is a group of precursor chemical systems that can generate NO and trace amounts of NO2 through redox reactions under acidic-humid conditions. By controlling pH, ionic strength, and water activity, it can achieve the stable release of **RNS (Reactive Nitrogen Species)** and synergistically generate high-energy complex species such as ONOO⁻ with the ROS system.
[0020] The chlorine dioxide activation module generates free radicals such as ClO·, ClO2·, and Cl· through microcurrent excitation or photochemical reduction. These free radicals, together with NO / NO2, form a NO–ClO2 synergistic system, which enables the breaking and structural inactivation of C=C, C–N, and C–S bonds in molecules such as aflatoxin, ochratoxin, and fumonisin.
[0021] The entire system forms an oxidation-reduction equilibrium closed loop under the dynamic control of AI algorithms, achieving an optimal balance between efficient sterilization, toxin degradation, and material structure protection. (2) Electron level excitation mechanism (ELAM)
[0022] During the plasma and ozone stages, a high-frequency pulsed superimposed electric field is applied to the system, inducing energy level rearrangement of gas molecules and perturbation of valence electron density, forming short-lived high-energy excited states. This mechanism can increase the free radical regeneration rate by about 3–5 times and promote energy level resonance and electronic transition coupling between ROS, RNS, and AOS, forming an e⁻–O–N–Cl multidimensional cooperative chain.
[0023] Through ELAM, the system can achieve directional breaking of molecular bonds in the sub-nanosecond range, especially producing highly selective cleavage of mycotoxin molecules with π-bond structures, thereby achieving deep detoxification without damaging the material matrix.
[0024] III. AI Intelligent Control and Dynamic Scheduling Mechanism The AI central control module consists of four core units: Environmental sensing unit: detects temperature and humidity, O2 content, gas composition and redox potential; Biological and toxin monitoring unit: Based on spectral, electrochemical and gas sensing, it realizes real-time monitoring of colony density and toxin content; Data analysis unit: Employs a contamination threshold algorithm and a self-learning storage model to dynamically calculate the optimal reaction sequence; Execution control unit: The timing, power and delay of the scheduling module are set according to the AI algorithm to realize intelligent closed-loop control with self-sensing, self-decision and self-execution.
[0025] When the system detects a value that reaches a threshold, it automatically triggers five-stage, four-stage, three-stage, or two-stage modes. Once the detection results return to a safe range, it automatically downgrades to a nitrogen barrier steady-state cycle to maintain a low-oxygen clean storage environment.
[0026] IV. Nitrogen Barrier Stabilization and Long-Term Storage Mechanisms After sterilization and detoxification are completed, the system enters the nitrogen barrier stabilization phase. This module maintains the O2 content in the storage space below 2% through dual-valve pressure stabilization and differential pressure-concentration algorithm, while retaining trace amounts of NO and ClO2 to form a weakly oxidizing clean atmosphere to prevent microbial recontamination.
[0027] The AI system continuously monitors environmental parameters. If it detects abnormal oxidation-reduction potential or mold recovery trends, it automatically activates a micro-strong oxidation reset cycle to achieve long-term self-stabilization and storage environment self-healing functions.
[0028] V. System Operation Logic and Gas Dynamics Optimization The storage reaction chamber is equipped with a multi-stage flow guiding and mixing structure: The first excitation region (plasma + electron layer) generates primary free radicals such as e⁻, ·OH, and ·O; The second oxidation zone (ozone + RNS) forms an O3–NOx complex field; The third synergistic region (ClO2 activation) performs deep molecular chain severing; The fourth recirculation zone (free radical regeneration) utilizes the remaining energy to achieve free radical recirculation.
[0029] This multi-zone circulation system, under the control of AI algorithms, achieves uniform gas mixing, continuous reaction chain, and maximizes energy utilization, significantly improving sterilization and detoxification efficiency.
[0030] VI. Energy Consumption Optimization and Intelligent Self-Learning Mechanism The system's energy consumption optimization is achieved through a real-time adjustment by an AI module based on material type, contamination level, storage volume, and energy consumption feedback data. Its deep learning algorithm continuously optimizes discharge power, reaction time, and delay logic to achieve a global balance between minimizing energy consumption and maximizing detoxification efficiency. Through a cloud-based learning module, the system enables multi-warehouse collaboration, remote parameter updates, and batch safety traceability.
[0031] VII. Industrialization and Platform Application Value The system of this invention is not only a storage device, but also a multimodal intelligent storage platform, suitable for: Grains, medicinal herbs, seeds, nuts, spices, dried meats, animal and plant-derived medicinal materials, and other materials that require long-term clean storage.
[0032] The system has the following combined advantages: Broad-spectrum, highly effective sterilization and deep detoxification; No external gas input required; low energy consumption operation. Modular architecture and cross-domain compatibility; Fully intelligent control and data traceability; Green and safe, with no harmful residues; It can be extended to cold chain, pharmaceutical storage and high-value biological raw material preservation scenarios.
[0033] VIII. Technological Frontiers and Long-Term Strategic Value This invention marks the first deep integration of the ELAM electronic layer energy level excitation mechanism, the ROS–RNS–AOS multidimensional free radical system, and an AI intelligent control platform in the field of storage technology, constructing an active storage system with self-learning, self-repair, and full-process closed-loop control. This technology has achieved international leading levels in energy level synergy, free radical recombination reaction, and AI self-decision control, signifying a fundamental leap from passive storage to active intelligent storage. (I) System Operating Principle
[0034] After system startup, the AI module first establishes a "state matrix" in the storage space to calculate the oxidation demand and energy consumption balance in real time. Based on the monitoring results, the system sequentially activates the cold plasma, ozone, NO, ClO2, and nitrogen barrier modules. The multi-level free radicals and oxidation system superimpose to complete the process. Primary cleavage → Deep oxidation → Toxin chain scission → Nitrogen barrier sealing The AI module continuously corrects the reaction parameters to ensure that the space environment is in a triple balance state of "low oxygen + trace oxidizing gases + stable nitrogen barrier". (II) International Expansion and Green and Safe Characteristics
[0035] Cross-species adaptability: Suitable for the storage of grains, medicinal herbs, nuts, spices and dried animal products.
[0036] Modular structure: The five-unit system can be independently embedded into existing storage or cold chain systems.
[0037] Environmentally friendly and zero-residue: The reaction byproducts are water and volatile micro-gases, with no harmful emissions.
[0038] AI Cloud Interconnection: Supports cross-warehouse remote control, algorithm updates, and multi-point data collaboration. (III) Summary of Technological Value and Advantages
[0039] Multi-stage free radical chain reactions enable the simultaneous lysis of microorganisms and toxins; AI-driven self-learning system, dynamic decision-making and energy consumption optimization; NO self-generating systems do not require external gas supply, greatly reducing operating costs; Nitrogen barrier stabilization prevents secondary pollution and ensures long-term cleanliness; Green sustainability meets global food and drug safety standards (ISO 22000 / GMP / FDA). End-to-end traceability and cloud-based monitoring endow the system with Industry 4.0-level intelligent features. Attached Figure Description
[0040] Figure 1 is a schematic diagram of the structure and timing logic of the present invention: it includes an AI central control module and five linkage modules, and the modules achieve dynamic collaborative control through timing logic.
[0041] Figure 2 This is a schematic diagram of the structure of the present invention. Beneficial effects
[0042] Broad-spectrum and highly efficient sterilization: a multi-stage free radical and oxidation system achieves deep lysis.
[0043] Strong toxin degradation ability: The NO–ClO2 synergistic system can break down and oxidize mycotoxins.
[0044] Low energy consumption and low cost: The NO self-generating system eliminates the need for external gas supply, reducing overall energy consumption by 30-50%.
[0045] AI-powered intelligent control: real-time decision-making, dynamic adjustment, and automatic prevention and control.
[0046] High versatility: suitable for grains, medicinal herbs, nuts, seeds, spices and dried animal products.
[0047] Long-term stability: Nitrogen barrier and algorithm control significantly extend the storage cycle.
[0048] This invention provides an intelligent five-in-one synergistic sterilization, detoxification, and long-term storage system. Through the sequential synergy of cold plasma, ozone, a self-generating NO system, chlorine dioxide, and a nitrogen barrier, and under the dynamic monitoring and algorithmic decision-making of an AI central control module, it achieves multi-stage sterilization and toxin degradation of the storage environment. The system features broad-spectrum and highly efficient sterilization, powerful mycotoxin lysis, low energy consumption and low cost, and long-term stability. The AI module can automatically switch reaction modes based on microbial and toxin thresholds for precise control. This system is suitable for the intelligent storage of grains, medicinal herbs, seeds, nuts, spices, and dried animal products, extending the storage period several times over, providing an integrated intelligent storage solution for biological raw materials and food safety. Implementation Example 1: Storage of plant-based materials (taking grain as an example)
[0049] The system is applied to large-scale grain storage. The AI module collects real-time data on temperature, humidity, oxygen concentration, and mold spore count. When the spore concentration exceeds 10³ CFU / m³, the AI module automatically switches to a five-stage synergistic mode. The execution sequence is as follows: cold plasma → ozone → NO → ClO2 → nitrogen barrier. The entire reaction cycle takes approximately 10 minutes, including 30 seconds of cold plasma action, 90 seconds of ozone, 5 minutes of NO–ClO2 recombination, and 3 minutes of nitrogen barrier stabilization.
[0050] Testing revealed that the total mold and bacteria count exceeded 99.9%, the aflatoxin B1 degradation rate was >95%, and the moisture content and lipid oxidation of the stored grain remained stable, extending the storage period by approximately three times compared to conventional storage. When environmental pollution indicators returned to below safe thresholds, the system automatically switched to a "triple energy-saving mode" (plasma-ozone-nitrogen barrier), achieving a comprehensive energy-saving rate of approximately 40%. Example 2: Storage of animal-derived materials (taking dried animal protein as an example)
[0051] In the storage of dried animal-derived proteins (such as fish meal, meat meal, and bone meal), the system operates in a low-oxygen, constant-humidity mode. The AI module detects the concentration of volatile amines and sulfides, and automatically activates the five-stage reaction system when the total volatile content is >15 ppm.
[0052] Cold plasma stage (15 s) pyrolysis of residual microorganisms on the surface; Ozone phase (1 minute) decomposes amines and organic sulfides; The NO self-generating system reacts synergistically with ClO2 (approximately 6 minutes) to further oxidize and degrade protein breakdown products and odor molecules; Finally, the nitrogen barrier module restores the storage environment to O2<1.8%, maintaining a constant low-oxygen state.
[0053] Actual test results showed that the total bacterial count in the storage space decreased by three orders of magnitude, the lipid oxidation value decreased by 45% compared to conventional storage, the volatile amine content decreased by 92%, and there was no significant degradation in protein structure. Even after six months of long-term operation, the system maintained its antibacterial, deodorizing, and recontamination-preventing effects. Example 3: Storage of medicinal and highly active biomaterials (taking traditional Chinese medicine and protein extracts as examples)
[0054] The system is used for the storage environment of Chinese medicinal materials and bioactive protein preparations. The AI module has a built-in database of medicinal material sensitivity. By identifying the type of material and water activity, it automatically limits the gas concentration and reaction time to ensure that the active ingredients are not oxidized.
[0055] During the storage startup phase, the AI determines that the moisture content of the medicinal materials is less than 12% and automatically adopts the "four-link mode" (plasma – NO – ClO2 – nitrogen barrier), omitting the ozone step to avoid polyphenol oxidation.
[0056] Cold plasma treatment for 20 seconds destroys potential spores; The NO self-generating system reacted for 3 minutes, inhibiting latent hyphae; Toxin degradation is achieved through micro-injection of ClO2 (0.02 ppm); During the nitrogen barrier phase, the oxygen concentration is maintained at 1.5%, and trace amounts of NO are released to achieve sustained antibacterial activity.
[0057] The test results showed that the total amount of mold in the medicinal materials decreased by 99.7%, the degradation rate of ochratoxin A reached 93%, and the retention rate of the main active ingredients (total flavonoids, saponins, polysaccharides, etc.) exceeded 98%. For freeze-dried protein extract samples, the system can achieve low-temperature and low-oxygen storage for 12 months without significant activity degradation. Example 4 (Optional Extension): Remote Collaborative Control of Integrated Warehouse Clusters
[0058] Multiple storage units (such as grain silos or medicinal herb warehouse clusters) are interconnected through a cloud-based AI management platform. Real-time data on the status of each storage unit is uploaded, and the AI module dynamically optimizes the response parameters of each unit based on a swarm learning algorithm, enabling collaborative prevention and control across multiple units. The system allows for remote scheduling, early warning notifications, and storage safety traceability, ensuring the stable operation and compliance of a large-scale intelligent warehousing system. Summary of Implementation Methods
[0059] The above embodiments demonstrate that the system of the present invention possesses the following comprehensive performance advantages: It is suitable for use on plants, animals, and medicinal materials; Sterilization, detoxification, deodorization, and preservation are achieved simultaneously; It features adaptive energy consumption adjustment and AI-powered dynamic mode switching. It can be remotely managed and batch traced, meeting the storage needs of industrialization and globalization.
Claims
1. An intelligent pentad collaborative sterilization and detoxification and long-term storage system, characterized in that The system comprises a cold plasma module, an ozone generation module, a NO autogenic system, a chlorine dioxide activation module, a nitrogen barrier stabilization module, and an AI central control module; the AI central control module is used for timing scheduling, power regulation, and parameter optimization of the above-mentioned modules; each module is sequentially or dynamically linked according to the AI algorithm to form a multi-stage composite oxidation system containing active species such as ·OH, ·O, O2⁻·, HOO·, NO·, ONOO⁻, ClO·, ClO2·, which realizes the prevention of mildew, corrosion, toxin degradation, and long-term low-oxygen stable storage of plant and animal storage materials through free radical chain reaction, oxidation-reduction coupling, and nitrogen barrier steady-state mechanism.
2. The system of claim 1, wherein the AI central control module comprises an environmental sensing unit, a microorganism and toxin monitoring unit, a data analysis unit, and a control execution unit; The environmental sensing unit is used to collect temperature and humidity, oxygen content, gas concentration, and oxidation-reduction potential; the data analysis unit calculates the optimal reaction sequence based on the pollution threshold algorithm and the storage model; when the detection value reaches the threshold value, the pentad, tetrad, triad, or dual collaborative mode is automatically triggered.
3. The system of claim 1, wherein the discharge frequency of the cold plasma module is 5 kHz – 200 kHz, and the voltage is 2 kV – 25 kV, which is used to generate high-energy electron flow (e⁻) and various free radicals (including ·OH, ·O, O2⁻·, HOO·, etc.) under normal pressure or micro-negative pressure conditions, to realize the physical lysis of microbial cell wall and membrane, the primary reaction of electron layer excitation, and the initiation of molecular level oxidation.
4. The system of claim 1, wherein the output concentration of the ozone generation module is 5–500 mg / m³, and it enters the reaction zone after a delay of 1 second to 3600 seconds after plasma excitation to form an ozone-hydroxyl radical composite oxidation layer; this composite layer is coupled with the electron layer excitation mechanism (ELAM) to form an energy level progressive oxidation system, which is used to improve the oxidation reaction rate, spatial penetration depth, and toxin molecule cracking efficiency.
5. The system of claim 1, wherein the NO autogenic system comprises a group of precursor compounds that can generate nitric oxide (NO) and trace nitrogen dioxide (NO2) through oxidation-reduction reaction in acidic environment; this system stabilizes the release of RNS by controlling acidity, ionic strength, and water activity, and generates ONOO⁻ complex active species in cooperation with the ROS system.
6. The system of claim 1, wherein the chlorine dioxide activation module generates ClO·, ClO2·, Cl·, etc. through micro-current excitation or photo-reduction, and forms a NO-ClO2 collaborative system with NO / NO2 to break C=C, C–N, C–S bonds and deactivate toxin molecules such as aflatoxin, ochratoxin, and fumonisin.
7. The system of claim 1, wherein the nitrogen barrier stabilizing module maintains the oxygen content in the storage space below 2%, and preserves a small amount of NO and ClO2 to form a weak oxidizing clean environment, preventing recontamination and prolonging the storage period.
8. The system of claim 1, wherein the reaction cavity is provided with a multi-stage flow guide and gas mixing structure, including a first excitation zone (plasma + electron layer), a second oxidation zone (ozone + RNS), a third synergistic zone (ClO2 activation), and a fourth reflux zone (free radical regeneration), each zone forming a continuous oxidation chain through gas circulation driving to maximize energy utilization.
9. The system of claim 1, wherein the AI central control module is built-in with a microbial threshold decision algorithm and a self-learning model, based on spectral, electrochemical, and gas data to achieve dynamic biological safety balance control; and can perform remote learning and parameter optimization through a cloud algorithm library, realizing multi-warehouse networking, full-process traceability, and energy consumption self-adaptation.
10. The system of any one of claims 1-9, suitable for intelligent storage prevention and control of materials such as grains, medicinal materials, seeds, nuts, spices, dried meats, and animal and plant source medicinal materials, with comprehensive technical advantages of broad-spectrum and efficient sterilization, deep decontamination, low energy consumption, and long-term stable maintenance.