Urea-based water-cooling system for servers

Abstract

A cooling system for electronic components comprises a temperature sensor, a controller, and a flow management device, facilitating fluid release in response to temperature thresholds. The system includes features like a backup power source, mixing motor, and thermal insulation chamber to enhance heat management efficiency and ensure operational reliability.

Description

UREA-BASED WATER-COOLING SYSTEM FOR SERVERSFIELD OF THE PRESENT INVENTION

[0001] The technology pertains to thermal management systems and methods thereof, specifically addressing the cooling of server farms and lithium-ion batteries utilizing an advanced watercooling method comprising urea. The system integrates urea-water reactions with automated control systems to enhance energy efficiency, water conservation, and environmental sustainability. The cooling units incorporate sensors to monitor temperature and urea concentration, and a feedback loop for dynamically adjusting the urea-water mixture based on realtime data. The system further includes heat exchangers positioned to optimize the transfer of thermal energy away from critical components, with flow regulators to maintain consistent cooling performance under varying operational loads.BACKGROUND OF THE PRESENT INVENTION

[0002] Cooling electronic components (including servers and lithium-ion batteries) is increasingly important as modern computing and energy storage drive higher thermal loads. Conventional approaches include air cooling (e.g., air conditioning / forced air), liquid cooling (e.g., water-based loops), and passive thermal buffering (e.g., phase change materials).

[0003] Publications and patents describe air cooling for electronic equipment and server racks, typically using controlled airflow paths, plenums, and fans to route cooling air through heat sources to remove heat and maintain operating temperatures.

[0004] Publications and patents also describe liquid cooling in which a coolant (e.g., water or a waterbased mixture) circulates through cold plates, heat exchangers, and manifolds to extract heat and reject it remotely.

[0005] In lithium-ion battery systems, thermal management reduces thermal-runaway risk and preserves performance and cycle life. Described approaches use phase change materials, liquid coolants, or hybrids, in which phase change materials absorb transients and liquid cooling removes heat to keep cells within target temperatures.

[0006] With increasing thermal loads and high-density, large-scale deployments, challenges include providing sufficient heat removal without undue integration complexity, responding to transient or abnormal thermal conditions (including in battery systems), and reducing installation / maintenance burdens (e.g., fluid handling, leak management, servicing).

[0007] Conventional cooling can also be energy-intensive and, in some implementations, water-intensive, increasing operating cost and environmental impacts, including greenhouse gas emissions.

[0008] Improved thermal management is therefore needed for electronic components, including server farms and lithium-ion battery assemblies, to handle increasing heat flux while remaining practical for large-scale deployment. Desired solutions provide effective heat dissipation in compact configurations, adapt to changing loads, mitigate transient or abnormal thermal events more rapidly, and reduce operational complexity, energy use, water use, and related environmental impacts.SUMMARY OF THE PRESENT INVENTION

[0009] The CoolGen-U system is a closed-loop cooling technology that uses a urea-water process to absorb heat through an endothermic reaction. By doing so, it reduces energy demand and water consumption relative to prior approaches. The system can also automatically activate when predefined temperature thresholds are reached, improving reliability and reducing the need for manual intervention.

[0010] The CoolGen-U system improves cooling efficiency and responsiveness to changing thermal loads in electronic-component applications. Compared with traditional methods described in existing patents, it provides closed-loop urea-water cooling that absorbs heat efficiently and autonomously responds to thermal fluctuations. These features reduce energy use, conserve water, and lower associated carbon emissions, supporting sustainability objectives and addressing limitations of prior systems.

[0011] The invention provides a closed-loop cooling system based on controlled endothermic dissolution of urea, wherein inclusion of glycerol extends cooling duration while circulation and sensor-based control regulate cooling intensity and timing.

[0012] Unlike conventional cooling systems that rely on pre-cooled fluids, ice, gel packs, or external refrigeration, the disclosed system generates cooling in situ through a chemical endothermic process, enabling rapid activation and extended cooling without the need for continuous external cooling input.

[0013] In some embodiments, after completion of the cooling cycle, the system is configured to be reset by replacing the cooling composition, regenerating the composition by recrystallization of urea, or cooling the solution to enable reuse, thereby maintaining closed-loop operability.

[0014] The CoolGen-U system is designed for integration flexibility, enabling adaptation to existing server and battery infrastructure. Its modular architecture supports simpler installation and maintenance, helping reduce operational disruption and cost. By reducing carbon emissions and conserving water, it provides an environmentally focused alternative not adequately addressed by conventional cooling systems. Accordingly, the CoolGen-U system meets a long-felt need for a more efficient, responsive, and environmentally conscious thermal-management solution for electronic components.

[0015] It is another embodiment of the invention to disclose a cooling system for electronic components, which comprises a reservoir configured to store a urea-water mixture, a temperature sensor operatively coupled to monitor ambient temperatures, a flow management device configured to manage fluid distribution from the reservoir, and a controller adapted to receive data from the temperature sensor and govern the operation of the flow management device. According to an embodiment of the invention, this system facilitates an endothermic reaction that absorbs heat from electronic components through regulated fluid distribution.

[0016] It is another embodiment of the invention to disclose that the temperature sensor may be a DS18B20 or LM35 component capable of providing digital output of real-time temperature data. According to another embodiment of the invention, the controller may be an Arduino or Raspberry Pi device configured to activate the flow management device when the ambient temperature surpasses a threshold of 50°C.

[0017] It is another embodiment of the invention to disclose that the flow management device includes a solenoid valve for precise control of fluid release from the reservoir. Furthermore, it is another embodiment of the invention to disclose a backup power source configured to maintain system operation during main power interruptions.

[0018] It is another embodiment of the invention to disclose that the reservoir comprises separate compartments for urea and water to prevent premature reactions, and the system further includes a mixing motor to enhance the reaction rate by efficiently mixing urea and water. According to this embodiment, the system includes a thermal insulation chamber to reduce heat transfer to the external environment.

[0019] It is another embodiment of the invention to disclose a lithium-ion battery cooling subsystem, which comprises a temperature sensor array configured to monitor the temperature of battery cells, a controller operatively linked to the temperature sensor array, an automatic release mechanismfor directing a urea-water mixture over battery cells, and a thermal insulation shell enveloping the battery cells. According to an embodiment of the invention, this subsystem initiates an endothermic cooling reaction to prevent thermal runaway upon exceeding a critical temperature range.

[0020] A person skilled in the art would appreciate that directing a urea-water mixture over battery cells refers to a thermal interface region thermally coupled to the battery cells. In an embodiment, the thermal interface region comprises at least one of (i) a cooling platejacket, serpentine channel, or manifold positioned adjacent to the battery cells, or (ii) a urea-based cooling layer positioned within a contained region of the thermal insulation shell. In a further embodiment, the subsystem includes a collection region configured to capture cooling medium after use and a return conduit configured to return captured cooling medium to a reservoir, thereby enabling closed-loop or semi- closed-loop operation. According to an embodiment of the invention, this subsystem initiates an endothermic cooling reaction to prevent thermal runaway upon exceeding a critical temperature range.

[0021] It is another embodiment of the invention to disclose that the temperature sensor array may include components such as DS18B20 sensors for precise thermal data acquisition, and the controller may utilize a Raspberry Pi platform to process thermal data and engage the automatic release mechanism.

[0022] It is another embodiment of the invention to disclose that the urea-water mixture is maintained in a reservoir separate from the thermal insulation shell. Furthermore, it is another embodiment of the invention to disclose that the automatic release mechanism employs solenoid valves to control fluid flow in response to thermal thresholds.

[0023] It is another embodiment of the invention to include a backup power source to ensure system functionality during power outages, and to fabricate the thermal insulation shell from materials designed to withstand high pressure and heat. According to this embodiment, the system is capable of autonomously operating without manual intervention.

[0024] It is another embodiment of the invention to disclose a method for cooling electronic components, which involves monitoring temperature using a temperature sensor, continuously analyzing temperature data with a controller, activating a flow management device to deliver a urea-water mixture when a temperature threshold is exceeded, executing an endothermic reaction to facilitate cooling, and halting fluid delivery upon achieving temperature stabilization. According to anembodiment of the invention, this method provides efficient thermal management through controlled urea-water reaction dynamics.

[0025] It is another embodiment of the invention to disclose that the fluid flow rate may be adjusted based on real-time temperature data and to include the provision of backup power for the system to operate during main power failure. It is also another embodiment of the invention to disclose separating urea and water until activation to avoid premature chemical reactions.

[0026] It is another embodiment of the invention to also disclose the step of mixing urea and water using a device that promotes thorough mixing, evaluating historical temperature patterns to predict potential hot spots, dispersing heat using radiators with fin configurations for enhanced cooling efficiency, and maintaining thermal insulation to encapsulate the cooling effect.

[0027] It is another embodiment of the invention to disclose a method for assembling a cooling system, which includes configuring a reservoir with separate compartments for urea and water, installing a temperature sensor adjacent to electronic components, establishing communication links between the temperature sensor and a controller, connecting a flow management device to the reservoir, and integrating a thermal insulation chamber around the system components. According to an embodiment of the invention, this assembly method ensures precise thermal management through accurate component placement and connectivity.

[0028] It is another embodiment of the invention to disclose further the calibration of temperature sensors using predefined temperature thresholds, integrating a backup power source to ensure system reliability, and configuring the flow management device to align with operational fluid dynamics. It is also another embodiment of the invention to disclose the installation of a mixing motor as required for desired cooling efficiency, implementing communication protocols for real-time data exchange between components, and securing the thermal insulation chamber with materials that provide optimal heat resistance.

[0029] In some embodiments, calibration and validation of temperature measurements are performed prior to deployment and / or periodically during operation. For example, a PHOSITA may validate one or more temperature sensors by comparing sensor readings to a reference temperature device (including a calibrated thermocouple, RTD, or certified temperature probe) at one or more predetermined test points within an expected operating range. In some embodiments, the controller applies an offset and / or gain correction based on the comparison, stores calibration coefficients in memory, and repeats the validation at a defined interval, after maintenance, and / or after detectionof abnormal sensor behavior (including drift, noise, or out-of-range values). In some embodiments, validation further includes a functional verification in which the system is operated under a known thermal load and the measured temperature response (including a cooling onset temperature, a temperature drop over time, and a stabilization temperature) is compared to expected performance criteria, thereby confirming correct sensor operation and closed-loop control behavior.

[0030] It is another embodiment of the invention to disclose an Al- and machine learning-enhanced cooling system, which comprises an Al-enhanced temperature sensor array for predictive thermal data analysis, a machine learning controller processing real-time and historical thermal data, an adaptive flow management device that dynamically adjusts fluid distribution, and an intelligent urea-water container system monitoring reactant levels. According to an embodiment of the invention, this system optimizes cooling processes through data-driven insights and anticipatory adjustment strategies.

[0031] It is another embodiment of the invention to disclose that the temperature sensor array may include Al-driven algorithms to forecast thermal peaks. Furthermore, it is another embodiment of the invention to disclose that the machine learning controller is operatively linked to cloud-based analytics platforms for enhanced data processing.

[0032] It is another embodiment of the invention to disclose that the adaptive flow management device employs Al models for real-time system calibration, and to include a predictive analytics module for maintaining optimal urea and water levels. Additionally, it is another embodiment of the invention to disclose an automated thermal insulation optimization mechanism based on environmental conditions.

[0033] It is another embodiment of the invention to disclose a deep learning-enabled backup power management feature to ensure continuous operation during power outages. According to this embodiment, the system components collectively facilitate efficient decision-making and prompt response to thermal fluctuations.

[0034] BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Fig. 1 is a perspective view of a cooling system comprising multiple components, including a temperature sensor and a reservoir;

[0036] Fig. 2 is a detailed perspective view of a battery cooling system including temperature sensors, a controller, and a battery cell array;

[0037] Fig. 3 is a perspective view of a cooling system featuring transparent housing for internal component visibility;

[0038] Fig. 4 is a graph illustrating normalized temperature changes over time for various solvents;

[0039] Fig. 5 is a graph depicting recovery percentages over time for different fluid mixtures;

[0040] Fig. 6 is a bar graph showing the temperature change for different solvents;

[0041] Fig. 7 is a flowchart of a cooling method implemented by the device in Fig. 1;

[0042] Fig. 8 is a flowchart of a battery temperature management methodology, related to Fig. 2;

[0043] Fig. 9 is a perspective view of a fluid management system integrated with thermal monitoring;

[0044] Fig. 10 is a perspective view of a home energy storage system cooling process;

[0045] Fig. 11 is a flowchart detailing a method of battery cooling that may be utilized with the system in Fig. 2;

[0046] Fig. 12 is a flowchart of an Al-enhanced cooling system featuring predictive temperature management;

[0047] Figs. 13-14 are perspective views of alternative embodiments of a server farm;

[0048] Fig. 15 illustrates byproduct energy generation;

[0049] Fig. 16 illustrate inflammability of lithium-ion batterie;

[0050] Figs. 17-23 illustrate urea-modified lithium-ion batteries; and

[0051] Figs. 24-25 illustrate urea-based charging station.DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT DEFINITIONS

[0052] Adaptive Flow Management Device: A system that regulates movement of fluid dynamically based on real-time data inputs. In some embodiment the CoolGen-U cooling system, comprises a component employing algorithmic control to adjust water distribution rates to one or more urea- water chambers in response to measured thermal conditions, thereby controlling urea-water endothermic cooling.

[0053] AI-Enhanced Temperature Sensor Array: A temperature measurement system augmented with artificial intelligence to provide enhanced data accuracy and predictive capabilities. It includes a network of temperature sensors within the CoolGen-U system, integrating Al algorithms for analysis of thermal data to generate temperature measurements and predicted temperature trends for cooling management.

[0054] Backup Power Source : A supplementary power system ensuring continued operation during main power supply failures. In the CoolGen-U system, it involves a battery or other energy storage unit that supplies power to one or more system components sufficient to maintain at least urea-water cooling functionality during a power outage.

[0055] Chemical Reaction: A process where substances interact to form new materials, often involving energy changes. Within the CoolGen-U system, it refers to an endothermic reaction urea and water that absorbs heat and generates a cooling effect.

[0056] Controller: A device or system that processes inputs from one or more sensors and governs system operations accordingly. It includes a processing unit in the CoolGen-U cooling system that interprets data from temperature sensors and controls one or more cooling procedures based on predefined conditions.

[0057] Endothermic Reaction: A type of chemical reaction that absorbs heat from its surroundings. Within the CoolGen-U system, it involves a process where urea reacts with water, absorbing heat and facilitating cooling.

[0058] Flow Management Device: A system component that controls the transfer of fluids in a process.In the CoolGen-U system, it comprises a pump, valve, or combination thereof, managing delivery of water to one or more urea-water chambers during cooling operations. In some embodiments, the valve is a solenoid valve.

[0059] Machine Learning Controller: A processing unit incorporating machine learning models for data analysis and system regulation. It includes a component of the CoolGen-U system configured for real-time data analysis and dynamic adjustment of cooling protocols based on historical and / or predicted thermal data. In some embodiments, the component of the CoolGen-U system utilized the NVIDIA Jetson platform.

[0060] Mixing Motor: A mechanical device used for blending materials. An optional component in the CoolGen-U system is configured to mix urea and water to increase a reaction rate of the urea-water endothermic reaction.

[0061] Temperature Sensor: A device that measures temperature and converts it into a readable signal for monitoring or control. One or more temperature sensors are used in the CoolGen-U system for monitoring real-time temperature and relaying temperature data to a controller for responsive cooling management. In some embodiments, the temperature sensors is of comprises DS18B20 or LM35.

[0062] Thermal Insulation Chamber: A structure designed to reduce heat exchange between its interior and exterior environments. In the CoolGen-U system, it comprises an insulating barrier positioned to reduce heat transfer between a urea-water cooling region and an external environment.

[0063] Urea-Water Chamber: A chamber configured for controlled interaction of urea and water. In the CoolGen-U system, it includes a container having a reservoir urea region and a water region arranged to limit contact prior to activation and configured to initiate controlled endothermic cooling upon introduction of water to urea.

[0064] Urea-Based Cooling Layer: A material layer incorporating urea for heat absorption. In the CoolGen-U system, it comprises a layer including urea arranged such that, upon wetting with water, the urea-water endothermic reaction absorbs heat to provide cooling.

[0065] Quenchers: One or more additives included in the urea-water mixture that reduce, inhibit, or delay one or more undesired reactions or processes that would otherwise shorten, diminish, or destabilize the cooling effect. In the CoolGen-U system, quenchers may function, for example, by inhibiting or mitigating urea decomposition, catalysis, oxidation, hydrolysis, precipitation and / or crystallization, corrosion, microbial growth, and / or gas formation within the cooling system. A person skilled in the art would appreciate that non-limiting examples of quenchers include stabilizers, antioxidants, corrosion inhibitors, chelating agents, pH buffers, biocides, anti-foaming agents, and combinations thereof. In some embodiments, the quencher(s) are present in an amount effective to enhance and / or extend the cooling duration under the system’s operating conditions. In some embodiments, the quencher is or comprises glycerol.Description of the System, Subsystems, and Modules

[0066] In basic terms, this is a specialized water cooling system designed to manage heat in server farms and lithium-ion batteries. It achieves cooling by mixing urea with water in a controlled way to absorb heat. This system helps keep servers and batteries cool, saving energy, using less water, and lowering carbon emissions.

[0067] For a person having ordinary skill in the art (PHOSITA), who typically might have a degree in mechanical engineering or similar field and several years of experience in thermal management systems, the CoolGen-U system presents a urea-water-based cooling solution operating within a closed-loop configuration. It includes temperature sensors, such as DS18B20 or LM35, providing real-time thermal data. This data is processed by a controller, which could be an Arduino orRaspberry Pi, that assesses when the system must be activated based on predefined thermal conditions, such as exceeding 50°C.

[0068] The urea-water cooling process is facilitated through a reservoir with distinct compartments segregating urea and water to prevent premature reactions. Upon activation, a flow management device, potentially a small electric pump or solenoid valve, transfers water to the urea chamber, ensuring effective cooling. The modular design allows optional inclusion of a mixing motor to enhance reaction rates.

[0069] Encapsulated within thermal insulation chambers, this setup maintains its cooling efficacy by hindering heat dissipation to external environments. Backup power solutions ensure operational continuity under power outages, while optional heat dispersion bodies like radiators can further improve system performance. According to one embodiment of the present invention, the closed loop system further comprises an external circulation system configured for recycling the circulating chemical materials. The recycled materials are usable again for cost- and material cutting. As an illustrative, non-limiting example that a person having ordinary skill in the art (PHOSITA) could implement, the closed-loop system can further include a recirculation path having at least one return conduit fluidly coupling a thermal interface region and / or a reaction region back to the reservoir, such that used urea-water cooling medium is collected and returned for repeated circulation. In some examples, the recirculation path includes a collection region positioned beneath or adjacent to at least one cooled component and a return pump configured to return captured cooling medium to the reservoir, optionally via one or more filters and / or a degassing device.Methods and Applications

[0070] This system is used to manage heat in places like server farms and battery cells. It works automatically; when things get too hot, the system kicks in to cool them down efficiently. It can keep batteries from starting fires and servers running smoothly without much manual effort.

[0071] For PHOSITA, the method involves continuous temperature monitoring via sensors, which send data to a controller. Activation occurs when temperatures exceed a threshold, leading to the circulation of water from a separate holding chamber into a urea-based reaction chamber. This interaction triggers an endothermic cooling reaction, absorbing heat and stabilizing temperatures. The process halts once the desired thermal balance is achieved, optionally enhancing heat dispersion through radiators and cooling fins.

[0072] A secondary application of the technology involves placing a urea-based cooling layer over lithium-ion battery cells. At critical temperatures, typically ranging between 150°C and 200°C, a thermal release mechanism directs water to the urea-based cooling layer to initiate an endothermic cooling reaction. In an embodiment, the cooling layer and associated fluid pathways are contained within a shell or enclosure such that cooling medium is retained within a protected region and is conveyed to a collection region for capture. The captured cooling medium is then returned via a return conduit to a reservoir for reuse, thereby operating in a closed-loop or semi-closed-loop manner. Thermal insulation envelopes may be employed to limit external heat transfer and improve response time, contributing to increased safety and reliability in high-thermal-demand scenarios.

[0073] Using urea, water and, optionally, glycerin for cooling is a unique way to handle high heat loads.It's not just effective but also saves energy and water, which makes it stand out from other cooling methods.

[0074] The CoolGen-U system leverages the endothermic properties of a urea-water reaction, creating a non-obvious solution that departs from traditional air- or liquid-based cooling approaches. The closed-loop design and capability for autonomous operation reduce maintenance demands and installation complexities, offering significant adaptability to existing thermal management infrastructures. Its modularity facilitates easy integration and scalable deployment across varied applications, encapsulating the system's innovation in response features, environmental impacts, and operational efficiency in high-density electronic settings.

[0075] The apparatus features a series of modular fluid channels, displaying an organized pathway for fluid distribution. This configuration suggests a system designed for flexibility and adaptability, possibly accommodating variations in fluid composition or processing requirements. The user interface panel offers advanced control options, complementing the system’s dynamic capabilities and promoting user-friendly interaction.

[0076] Reference is now made to Fig. 1, this illustration depicts a fluid management and thermal regulation system. The temperature sensor 1 is positioned adjacent to the reservoir 3 to measure fluid temperature. The controller 2 is connected to both the temperature sensor 1 and the flow management device 4, coordinating the regulation of fluid flow and thermal conditions. The reservoir 3 stores the medium that is subject to temperature regulation. Flow management device4 is structured to direct the fluid efficiently within the system. The thermal insulation chamber 5 envelops the reservoir 3, providing thermal stability.

[0077] Reference is now made Fig. 2, this figure extends the system described in Fig. 1 by integrating a set of battery cells 7 for powering the components. Like in Fig. 1, temperature sensor 1 and controller 2 are central to the operation, ensuring precise thermal regulation in the reservoir 3. The flow management device 4 remains an integral conduit for fluid movement, now powered by battery cells 7. The thermal insulation chamber 5 enhances efficiency by maintaining desired temperatures. Additionally, the inclusion of a secondary thermal insulation chamber 8 ensures optimized temperature management around the battery cells 7.

[0078] In Fig. 2, the system components are depicted with reference to their roles in managing thermal conditions around battery cells 7. The system comprises a temperature sensor 1, configured for real-time monitoring of battery cell temperatures and transmitting this data to the controller 2. The controller 2, which could be a Raspberry Pi or Arduino, processes this data and engages the cooling process upon detecting a thermal increase beyond a preset threshold.

[0079] The flow management device 4 is represented as either a small electric pump or solenoid valve, responsible for transporting water to the urea chamber. This component is integral during emergency conditions necessitating rapid cooling. The reservoir 3 is strategically compartmentalized to separately contain the materials required for the chemical reaction, thereby preventing unintended interactions.

[0080] An optional small mixing motor can be included to enhance the reaction rate by efficiently blending water and urea within the chamber. Ensuring continuity of operations, a backup power source guarantees system functionality during power outages or failures. Encapsulated within the thermal insulation chamber 5 are the battery cells, providing protection and extending the efficacy of the cooling effect. The described configuration reflects the synergies between each component as detailed in the function table, emphasizing a holistic approach to thermal management in high- stress environments.Function ComponentMonitors the temperature of the batteries in real-time and Temperature Sensor transmits data to the controller. (DS 18B20 or LM35)Function ComponentProcesses the data and activates the cooling process in case of a Controller (Raspberry Pi or temperature increase. Arduino)Pumps water to the urea chamber when necessary. Small Electric Pump or Solenoid ValveContains the necessary materials for the chemical reaction, Separate Urea-Water separated to prevent premature reactions. ContainerImproves the reaction rate by efficiently mixing the water and Small Mixing Motor urea. (Optional)Ensures continuous operation in case of power outages or Backup Power Source failures.Protects the battery cells and extends the cooling effect. Thermal Insulation Shell

[0081] Finally, Fig. 3 demonstrates another embodiment facilitating advanced fluid management and thermal regulation. This figure might illustrate an alternate configuration or supplementary technology enhancing the systems exhibited in prior figures. Potential components similar to those in Figs. 1 and 2 could be present, further expanding on the capacities of fluid storage, temperature monitoring, and control, albeit without explicit label designation in this particular depiction. Embodiment 1 : Urea-Based Emergency Cooling System for Electric Vehicle Batteries Key Components and Configuration:

[0082] Urea-Based Cooling Layer: Positioned directly above the battery cells, the cooling layer comprises a blend of urea designed to maximize thermal absorption. The selection of urea blend composition, particle size, and layering thickness is determined based on temperature dynamics specific to electric vehicle (EV) battery architecture. Temperature Sensor (LM35): The LM35 temperature sensor, manufactured by Texas Instruments (USA), is installed adjacent to critical battery cell clusters. Its role is to provide precise, continuous temperature readings to the system's controller, enabling rapid response to thermal excursions. Controller (Raspberry Pi): A Raspberry Pi controller serves as the central processing unit, interpreting data from the temperature sensors. Upon detecting temperatures within the critical range of 150°C to 200°C, the controller activates the cooling system. The Raspberry Pi platform, developed by the Raspberry Pi Foundation (UK), offers open-source software capabilities, enhancing system flexibility. Automatic Release Mechanism: The system incorporates solenoid valves from Parker Hannifin (USA) to channel water into the urea layer. These valves are triggered by the Raspberry Pi upon receiving signalsfrom the temperature sensors. Urea-Water Chamber: Constructed with separate compartments for urea and water to prevent premature chemical reactions, this configuration manages chemical stability prior to activation. Setup guidance is available through resources provided by Dupont (USA). Thermal Insulation Shell: Fabricated from high-pressure resistant material provided by BASF (Germany), this shell ensures thermal separation from external environmental conditions, preserving cooling efficacy during operation.

[0083] Operational Process: The LM35 sensor provides real-time temperature data to the Raspberry Pi controller. If excessive temperatures are detected, the controller engages solenoid valves to facilitate water delivery to the urea layer. The endothermic reaction between urea and water significantly lowers system temperatures by absorbing heat and releasing cooling gases, effectively decreasing oxygen levels to avoid ignition risks. Continuous monitoring is sustained, and once temperatures are stabilized within safe operational parameters, water delivery ceases. The thermal insulation shell helps maintain the cooling effect, curtailing heat dissemination.

[0084] Advantages and Applications: Provides a rapid cooling response, enhancing safety during charge cycles. Utilizes non-toxic materials that ensure environmental compatibility. Integrates seamlessly with existing EV battery systems, requiring minimal redesign efforts.Embodiment 2: Urea-Based Cooling System for Home Energy Storage Systems

[0085] System Components and Features: Urea-Based Cooling Layer: Designed to span over the surface of lithium-ion battery arrays, ensuring a uniform response under severe thermal conditions across energy storage units. Temperature Sensor (DS18B20): This digital temperature sensor, available from Maxim Integrated (USA), is placed near crucial battery components. It provides accurate temperature data to an Arduino controller, enabling precise thermal management. Arduino Controller: Executes cooling operations when threshold temperatures, typically set at 150°C, are surpassed. The Arduino platform, available from Arduino LLC (USA), provides customizable modules for varied heating scenarios. Small Electric Pump: Manufactured by Grundfos (Denmark), this device is responsible for transferring water to the urea chamber, initiating the cooling process. Thermal Release Mechanism: Engages the fluid propulsion system upon receiving activation signals from the Arduino, ensuring a rapid and efficient emission of cooling gases. Insulated Shell: Provided by Johns Manville (USA), the system's insulation prevents heat loss, conserving the effectiveness of the cooling reactions within the home storage unit's confines.

[0086] Functional Process: The DS18B20 sensor constantly monitors the storage system's internal temperature. Upon detecting elevated temperatures, the controller triggers the electric pump, delivering water into the cooling layer. A swift chemical reaction ensues, performing endothermic cooling and generating cooling gases. The system continues monitoring and halts pump functions once optimal operational temperatures are restored. The thermal insulation shell aids in reducing external thermal influences, preserving temperature decreases achieved through chemical reactions.Embodiment 3: Urea-Based Safety Cooling for Industrial Equipment

[0087] System Architecture and Components: Urea-Based Cooling Layer: This layer is strategically fixed near heat-intensive industrial components to tackle high thermal output effectively. It allows for quick thermal responsiveness, adapting to diverse industrial applications. Temperature Sensor Array (LM35 and DS18B20): Distributed across various regions to provide detailed temperature assessments, using components available from Texas Instruments (USA) and Maxim Integrated (USA) respectively. These sensors support comprehensive analysis of thermal environments. Central Controller (Raspberry Pi): The central processor interprets sensor data and controls the activation of cooling mechanisms, ensuring response precision during temperature spikes. Its versatility allows for integrations in different industrial infrastructures. Solenoid Valve System: Employing Parker Hannifin (USA) high-performance valves to direct water into reactive zones, instigated by centralized instructions from the control unit. Interior Cooling Chamber: Features distinctly separated urea and water segments, preventing premature engagement. Provided by Merck KGaA (Germany), this chamber allows for targeted cooling only under critical temperature scenarios. Thermal Insulation Shell: Designed to withstand mechanical stress and thermal pressures, sourced from Saint-Gobain (France), this shell prevents unwanted heat transfer, safeguarding both internal and external environments.

[0088] Operational Workflow: The temperature sensor array continuously monitors for abnormal thermal activity across equipment. Upon the central controller's detection of temperature surges, solenoid valves engage, releasing water into the cooling area. The ensuing endothermic reaction immediately absorbs heat, dispersing cooling gases accordingly. The central controller diligently manages the cooling process, ceasing water activities once operational temperatures are returned to stable levels. Interior insulation supports the retention of the cooling effect, ensuring prolonged equipment safety.

[0089] Advantages and Applications: Provides dependable cooling response in industrial settings amid fluctuating thermal conditions. Comprehensive monitoring ensures timely addressing of thermal irregularities. Simplified integration with established machinery systems minimizes redesign efforts, bolstering equipment safety and longevity.Embodiment 4: Urea-Based Cooling Composition Examples

[0090] Chemical Composition Examples for Urea-Based Cooling Systems, Including Water Miscible and Water Immiscible Solutions: Urea and Glycerol Mixture: Composition: Urea (40-60% wt) mixed with Glycerol (40-60% wt). Chemical Names: Carbamide and Propane-1, 2, 3-triol. Manufacturer: Sigma-Aldrich (USA). Urea and Isoparaffin Combination: Composition: Urea (30-50% wt) with Isoparaffin (50-70% wt). Chemical Names: Carbamide and Mixture of Branched Alkanes. Manufacturer: TotalEnergies (France). Urea and Aqueous Solution of Polyhydric Alcohol: Composition: Urea (30-50% wt) with Aqueous Glycerol Solution (10-40% wt glycerol in water). Chemical Names: Carbamide and Glycerol-water solution. Manufacturer: TCI America (USA). Urea, Ethylene Glycol, and Water Emulsion: Composition: Urea (25-45% wt), Ethylene Glycol (10-30% wt), and Water (25-50% wt). Chemical Names: Carbamide and Ethane- 1,2-diol. Manufacturer: Dow Chemical Company (USA). Urea and Fatty Ester Oil Mixture: Composition: Urea (30-50% wt) with Fatty Ester Oil (40-60% wt). Chemical Names: Carbamide and Methyl Oleate. Manufacturer: BASF (Germany). Urea, Water Miscible Organic Solvent: Composition: Urea (30-50% wt) with a water-miscible organic solvent such as Methanol (30-50% wt). Chemical Names: Carbamide and Methanol. Manufacturer: LyondellBasell Industries (Netherlands). Urea and Water Immiscible Organic Phase: Composition: Urea (20-40% wt) with Cyclohexane (60- 80% wt). Chemical Names: Carbamide and Cyclohexane. Manufacturer: Chevron Phillips Chemical Company (USA).

[0091] Hydrogen Bond Acceptor and Donor Compositions for Urea-Based Cooling: Hydrogen Bond Acceptor and Donor Example 1 : Acceptor: Tetraoctylphosphonium Bromide (20-30% wt). Donor: Lactic Acid (10-20% wt). Chemical Names: (C8H17)4PBr and 2-Hydroxypropanoic Acid. Manufacturer: Merck KGaA (Germany). Hydrogen Bond Acceptor and Donor Example 2: Acceptor: l-Ethyl-3-methylimidazolium Bromide (15-25% wt). Donor: Malic Acid (10-20% wt). Chemical Names: C6HllN2Br and Hydroxybutanedioic Acid. Manufacturer: Ionic Liquids Technologies (Germany). Hydrogen Bond Acceptor and Donor Example 3: Acceptor: Alanine (10-20% wt). Donor: Citric Acid (5-15% wt). Chemical Names: 2-Aminopropanoic Acid and 2-Hydroxypropane-l,2,3-tricarboxylic Acid. Manufacturer: Ajinomoto Co., Inc. (Japan). Hydrogen Bond Acceptor and Donor Example 4: Acceptor: Trihexyltetradecylphosphonium Chloride (20- 30% wt). Donor: Succinic Acid (5-10% wt). Chemical Names: C10H21PC1 and Butanedioic Acid. Manufacturer: Cytec Industries Inc. (USA). Hydrogen Bond Acceptor and Donor Example 5: Acceptor: Choline Nitrate (10-15% wt). Donor: Imidazole (5-10% wt). Chemical Names: (CH3)3NCH2CH2OHNO3 and C3H4N2. Manufacturer: ABCR GmbH (Germany). Hydrogen Bond Acceptor and Donor with Water Miscible Solvent: Acceptor: Polyethylene Glycol (10-20% wt). Donor: Polyacrylic Acid (5-10% wt). Chemical Names: HO-CH2-(CH2O-CH2)n-CH2-OH and C3H4O2)n. Manufacturer: Sigma- Aldrich (USA). Hydrogen Bond Acceptor and Donor with Water Immiscible Oil Phase: Acceptor: Phosphatidylcholine (15-25% wt). Donor: Tartaric Acid (5-10% wt). Chemical Names: C42H80NO8P and 2,3 -Dihydroxybutanedioic Acid. Manufacturer: ADM (USA).

[0092] Cooling Effectiveness Over Time: Initial Activation Phase: Upon activation as a response to temperature exceeding the predetermined threshold, the urea-based cooling system initiates a swift decline in temperature. This rapid cooling is observed as the endothermic reaction begins, absorbing significant amounts of thermal energy. Cooling effectiveness within the first 10 minutes of activation should demonstrate a temperature reduction of at least 10-20°C, contingent upon the initial thermal load conditions. Stabilization Phase: Continued operation over a period of 30 minutes should achieve a stabilization of temperatures at a consistent level, typically reaching within the safe operational range of the system. For server farms, reduction to approximately 30- 40°C is expected, whereas for lithium-ion battery systems, stabilization is projected within the 60- 80°C range. Extended Cooling Phase: Sustained cooling effectiveness over time, typically evaluated at 1-hour and 2-hour intervals, should illustrate the system’s capability to maintain reduced thermal conditions despite ongoing heat generation by electronic components or battery assemblies. Metrics for this phase might indicate a steady state where temperature variations do not exceed ±2°C, indicating successful temperature management without manual system intervention.Compositions and Mixtures

[0093] Urea and Glycerol Mixture: Thermal Imaging and Temperature Mapping: During tests using thermal imaging cameras, initial heat distribution maps should show high thermal intensity across components pre-activation. Post-activation, the imaging should highlight pronounced areas oftemperature decline, particularly over critical zones where the mixture is applied, indicative of effective heat reduction. Temperature Sensor Data Collection: Temperature readings should indicate an immediate cooling trend upon system activation, with data points showing temperature declines of approximately 10-15°C in the initial 10 minutes post-activation, stabilizing as the mixture reaches equilibrium with absorbed heat. Controlled Environment Testing: Under cycling temperature conditions, the urea-glycerol mixture should demonstrate rapid response times, effectively maintaining operational temperatures below thresholds despite varied heat loads. Cooling Trend Analysis: Models and simulations should predict significant cooling capabilities, demonstrating system behavior characterized by consistent declines across temperature domains, suggesting robust efficacy in managing disparate thermal loads. Efficiency Evaluation: Energy consumption analysis should indicate reduced power requirements during active phases compared to traditional cooling technologies, confirming enhanced thermal management efficiency. Longitudinal Studies: Over multiple operational cycles, evidence of consistent cooling performance without significant system degradation or material fatigue should be documented, suggesting durability with minimal maintenance events.

[0094] Urea and Isoparaffin Combination: Thermal Imaging and Temperature Mapping: Pre-activation imaging should reflect uniform heat across applied surfaces, transitioning to reduced thermal signatures post-cooling initiation, with marked drops in areas directly treated with the isoparaffin mixture. Temperature Sensor Data Collection: Data should reveal sharp temperature decreases within the first 20 seconds, stabilizing within 5 minutes to maintain controlled environments effectively at predefined safety limits. Controlled Environment Testing: During varied thermal conditions, the mixture should exhibit rapid initiation of cooling processes, effectively managing heat surges while maintaining stable operational temperatures. Cooling Trend Analysis: Both empirical and theoretical models should show robust predictions, indicating readiness of the system to handle diverse thermal shocks consistently. Efficiency Evaluation: The mixture should present reduced energy demands during tests, signifying substantial efficiency gains over comparable technologies. Longitudinal Studies: Maintenance logs expected to reflect minimal wear, supporting assertions of long-term viability without significant intervention needs.

[0095] Urea and Aqueous Solution of Polyhydric Alcohol: Thermal Imaging and Temperature Mapping:Immediate post-activation imaging should delineate a noticeable cooling pattern, contrasting preactivation thermal spots with significantly lower post-cooling heat levels. Temperature SensorData Collection: Sensor networks should capture steep initial temperature declines, quantified at 15-25°C within the first few activation minutes, stabilizing thereafter. Controlled Environment Testing: The aqueous glycerol solution should perform optimally under high temperature scenarios, achieving swift stabilization within operational thresholds. Cooling Trend Analysis: Simulation models are anticipated to confirm rapid cooling trends, endorsing the solution’s adaptability and correctness in thermal management roles. Efficiency Evaluation: Comparative energy analysis is expected to demonstrate this mixture's superior efficiency, reducing operational energy footprints significantly. Longitudinal Studies: Results should demonstrate consistent cooling effects with minimal impacts on materials, indicating favorable longevity and reliability.

[0096] The anticipated results outlined serve to illustrate the cooling capabilities of the urea-based system across various compositions, employing rigorous methodologies to observe performance under diversified thermal constraints. This comprehensive analysis supports the potential optimization and validation of the system's application within modern thermal management solutions.Embodiment 5: Urea-Based Cooling System for Electric Vehicle Battery Protection

[0097] Components and Configuration: Temperature Sensor (LM35 or DS18B20): Positioned strategically to monitor the temperature of battery cells. Real-time data is transmitted to a central controller. Controller (Raspberry Pi or Arduino): Engages in processing the sensor data to initiate cooling processes when temperature rises beyond a critical threshold, for example, 50°C. Small Electric Pump or Solenoid Valve: Administers water delivery to a designated urea chamber under identified emergency conditions. Separate Urea-Water Container: Maintains urea and water separately to avert any premature chemical reactions before controlled activation. Optional Small Mixing Motor: Enhances the chemical reaction rate via effective mixing of water and urea. Backup Power Source: Ensures consistent operation continuity even during power failures or system faults. Thermal Insulation Shell: Safeguards battery cells against excessive heat transfer, extending the cooling effect within the insulation confines.

[0098] Operation Process: Temperature Monitoring: The temperature sensor continuously assesses battery temperatures and relays data to the controller. Emergency Activation: At the detection of temperature surpassing a critical threshold, the controller actuates the pump or solenoid valve. Chemical Reaction: Water is directed into the urea chamber, catalyzing an endothermic reaction that absorbs heat and emits cooling gases. Temperature Stabilization: As the system detects a drop in temperature, it deactivates the pump to stabilize within a defined temperature range. HeatRetention: The thermal insulation maintains the cooling effect within the battery cells, preventing heat transfer to adjacent zones.

[0099] Benefits: Prevention of Overheating: Immediate response to potential thermal runaway scenarios, reducing ignition risks. Autonomous Safety: Functions independently, reducing the requirement for complex external systems. Environmentally Friendly: Utilizes non-toxic materials, ensuring no environmental contamination. Simple Integration: Easily incorporated within existing EV battery systems with minimal modifications. High Durability: Sustains safe operation under demanding conditions and emergency scenarios.Applications:

[0100] Electric Vehicles (EVs): Ensures the protection of vehicle batteries during rapid charging or overload situations. Home Energy Storage Systems: Provides efficient cooling in compact systems employed for renewable energy storage solutions. Industrial and Mobile Devices: Enhances safety and reliability in portable or industrial products. The system demonstrates a robust, autonomous approach to lithium-ion battery protection, catering to high thermal loads in complex operational settings and promoting environmental sustainability.Embodiment 6: Methods of use

[0101] Temperature Monitoring: Utilizing temperature sensors for detecting an increase in temperature above a predetermined threshold, such as 50°C. System Activation: Engaging the controller to activate a pump or solenoid valve, directing water from a separate chamber to the urea chamber. Chemical Reaction: Facilitating an endothermic reaction of urea with water, which is absorbing heat and releasing cooling gases. Temperature Stabilization: Monitoring the decreasing temperature and deactivating the pump when the temperature is stabilizing within the desired range. Heat Dispersion: Efficiently dissipating heat using radiators with cooling fins or an alternative heat dispersion body.Cooling efficiency of urea

[0102] In a series of empirical studies conducted to evaluate the cooling efficiency of urea in conjunction with various solvents, a specified quantity of 10 grams of urea, obtained from Sigma-Aldrich (Catalog No. CAS: 57-13-6), was introduced into 100 milliliters of each of the following solvents: triple-distilled water (hereinafter referred to as TDW), acetonitrile (ACN, Catalog No. CAS: 75- 05-8), and ethanol (EtOH, from RomiCal, Catalog No. CAS: 19-009106-72). The respectivemixture of urea and solvent was subjected to continuous agitation at a speed of 125 revolutions per minute (rpm) to achieve a uniform distribution and facilitate the dissolution process of the urea.

[0103] Observations recorded upon the dissolution of urea in TDW indicated that the endothermic nature of the dissolution process contributed to a perceivable decrease in temperature. This indicates the solvent's capability to achieve effective absorption of thermal energy. Similarly, the urea-ACN system exhibited a discernible reduction in temperature, suggesting ACN's potential applicability in scenarios necessitating rapid cooling. In contrast, when ethanol served as the solvent medium, it demonstrated moderate cooling characteristics attributable to its inherent solvent properties. However, the efficiency observed was comparatively less pronounced than that achieved in TDW and ACN systems.

[0104] Experimental findings emphasize the relevance of solvent selection in enhancing the thermal absorption characteristics of urea-based cooling processes. TDW exhibited the most substantial temperature reduction, recorded at -4.6 ± 0.9 °C, as depicted in Figure 1 and further enumerated in Table 1. This minimum temperature was attained within a timeframe of 20 seconds. The recovery period for the temperature in TDW was measured at 49.7 ± 1.6 minutes, which was notably extended compared to ACN, but marginally less extended than EtOH. Urea exhibited immediate solubility in water, partial solubility in EtOH, and limited solubility in ACN. These solubility properties, in conjunction with the recorded recovery durations, suggest that EtOH may be favorable for utilization in applications requiring sustained cooling, attributable to its partial solubility that may instigate prolonged cooling effects. Conversely, TDW is more appropriate for applications necessitating rapid and efficient cooling processes.

[0105] Fig. 4 shows a graph depicting the normalized temperature percentage over time measured in seconds. The graph includes three data sets labeled as TDW, ACN, and EtOH, represented by different colored lines: TDW in black, ACN in red, and EtOH in blue.

[0106] The x-axis represents time in seconds, ranging from 0 to 120 seconds. The y-axis displays the normalized temperature as a percentage, starting from 70% to slightly above 100%. Initially, all three lines commence at the 100% temperature mark. Over the duration of the graph, each line follows a distinct trajectory.

[0107] The TDW line initially decreases sharply, dropping to around 80% within the first 30 seconds, and gradually rises thereafter, maintaining a consistent level just below 90% for the remainder of the period. The ACN line experiences a slight and gradual decrease, settling slightly below 100% andmaintaining stability at that level throughout the observed timeframe. In contrast, the EtOH line shows a rapid decrease, reaching approximately 75% by the 60-second mark, followed by a gentle increase and stabilization around 85% towards the end of the graph.

[0108] This illustration provides a comparison of the cooling efficiencies of different agents (TDW, ACN,EtOH) over time, indicating that each agent reaches and stabilizes at different temperature levels, showcasing the varying thermal responses when applied in the cooling process.Prolonged Cooling Effect Using Quenchers

[0109] To enhance the duration of the cooling effect in urea- water mixtures, quenchers were incorporated into the solutions. The experimental procedure involved dissolving 10 grams of urea in 100 milliliters of water, with and without the inclusion of 10% volume / volume (v / v) quenchers. Silicone oil, available from Sigma-Aldrich (CAS: 63148-62-9), and glycerol, also from Sigma- Aldrich (CAS: 82425-96-5), were utilized as quenchers.

[0110] Procedure Overview: To achieve uniform dissolution and distribution, the mixtures were subjected to mechanical stirring at a rotational speed of 125 revolutions per minute (rpm). The incorporation of quenchers aimed to extend the thermal stabilization period by reducing the rate of thermal recovery.

[0111] Thermal Performance Assessment: Upon activation, the initial cooling was characterized by a swift reduction in temperature, mediated by the endothermic dissolution of urea in water. The presence of silicone oil as a quencher resulted in a prolongation of the cooling effect, as it influenced the thermal conductivity and viscosity of the solution, moderating the heat transfer dynamics. Similarly, when glycerol was used as a quencher, the enhanced viscosity played a role in maintaining the stabilized cooling state, thereby delaying the heat recovery process.

[0112] Measured Outcomes: Preliminary data indicated that the incorporation of silicone oil as a quencher contributed to extended cooling effects, as evidenced by a delayed recovery observed in the temperature recordings. The use of glycerol similarly demonstrated an increased cooling duration, attributed to its higher boiling point and viscosity, which supported a reduced rate of heat transfer back into the system.

[0113] These findings suggest that the strategic inclusion of quenchers such as silicone oil and glycerol in urea-water mixtures effectively prolongs the cooling effect by modulating the thermal properties of the mixture, thereby offering improved cooling performance under operational conditions. Such modifications can be applied to urea-based cooling systems to enhance their effectiveness inmanaging thermal loads in electronic components, including server farms and lithium-ion battery systems.

[0114] The addition of quenchers (silicone oil and glycerol) to the TDW mixture was examined to evaluate their impact on cooling efficiency (Figure 2, Table 2). Incorporating 10% glycerol (v / v) resulted in a slight reduction in the temperature drop to -4.3 ± 0.5 °C, while significantly prolonging the recovery time to 118 ± 23 minutes. This represents approximately a three-fold increase compared to the recovery time of TDW alone and a 2.5 -fold increase compared to the recovery with silicon oil. Consequently, the TDW-glycerol mixture emerged as the most effective method for achieving extended cooling durations.

[0115] In some embodiments, a preferred implementation comprises about 10% (w / v) urea and about 10%(v / v) glycerol in water, circulated through a wearable or industrial cooling interface, providing rapid temperature drop followed by extended cooling duration under closed-loop control.

[0116] Fig.5 shows a graph illustrating the recovery percentages over time of three different fluids: TDW,10% silicon oil, and 10% glycerol. The x-axis represents the time in seconds, ranging from 0 to 160. The y-axis represents the recovery percentage, ranging from 0% to 40%.

[0117] The data for TDW is depicted by a gray line, which demonstrates a sharp initial drop followed by a gradual recovery, reaching approximately 30% recovery by the end of the observation period at 160 seconds. The line representing 10% silicon oil is shown in red, similarly exhibiting a steep decline initially but recovering more slowly than TDW, achieving about 25% recovery at 160 seconds.

[0118] The blue line represents 10% glycerol, starting with a significant drop and following a slower recovery trajectory compared to the other two fluids. By 160 seconds, the recovery for 10% glycerol reaches around 10%. This graph provides a comparative analysis of the recovery behaviors of these fluids, illustrating distinct recovery profiles and efficiencies over the specified time period.

[0119] Table 3. Thermodynamic parameters of mixture of urea with different solvents, with and without quenchers.Solvent AT (°C) AT to Recovery (°C) Full Recovery (min)+silicon -4.6±0.8 0.55±0.02 59.6±6.3+glycerol -4.3±0.5 0.22±0.00 147±23 EXAMINATION OF PRE-MIXED UREA AND WATER FOR COOLING EFFECTS WITH ALCOHOLS AND DICHLOROMETHANE (DCM)

[0120] In assessing the cooling performance of various solvents mixed with urea, a detailed examination was conducted focusing on the temperature changes and cooling effects exhibited by different alcohols and dichloromethane (DCM). This study aimed to identify the differential cooling capabilities of each combination and their potential applications within thermal management systems.

[0121] Materials and Methods: The pre-mixed urea was standardized across tests at a concentration of 10 weight percent (wt%) in each solvent, maintaining consistent conditions for comparison. Solvents used included ethanol, methanol, isopropyl alcohol, and DCM, obtained from Merck KGaA (Germany) with catalogue numbers, as applicable. Temperature shifts were observed through calibrated thermocouple sensors, connected to data logging equipment, to track thermal fluctuations over time.

[0122] Results and Observations: Solvent Temperature Shifts: Initial cooling was measured immediately following the introduction of urea to each solvent. The graph (Figure 3) illustrates the comparative cooling effects for each mixture. Cooling Effects: Ethanol-based Mixture: Indicated a moderate reduction in temperature, effecting a decrease by approximately 2.5°C within the first three minutes, as depicted in the graph. This, however, was less effective compared to water-based mixtures, particularly in maintaining extended cooling durations. Methanol-based Mixture: Demonstrated a slight cooling effect with temperature reductions peaking at 3 °C. While providing an initial cooling phase, the recorded data suggested limited efficacy for long-term temperature stabilization. Isopropyl Alcohol Mixture: Resulted in minimal cooling effects, with a temperature decrease of about 1.8°C. The use of isopropyl alcohol did not present significant improvements over water, indicating its lower potential for maintaining prolonged cooling.DCM-based Mixture: Although detectable cooling effects of approximately 3.5°C were observed, the analysis lacked recovery time evaluation, which limited the assessment of DCM's capability for prolonged cooling lifespan. Comparative Analysis: Alcohol-based mixtures generally achieved lower initial cooling effects compared to triple-distilled water (TDW), echoing the observation that they may be lesseffective in applications requiring sustained thermal management. The lack of detailed recovery time consideration in the graph prevented the identification of mixtures best suited for long-lasting cooling.

[0123] The study identifies the cooling limitations of alcohol-based mixtures when combined with urea for the purpose of managing temperatures in electronic and battery systems. The data underline the superior initial cooling attributes of DCM, yet without comprehensive recovery metrics, their effectiveness for extensive cooling durations remains inadequate. Further evaluation involving detailed recovery periods is recommended to conclusively determine the viability of these mixtures in practical thermal management applications. These insights can guide improvements in urea- based cooling systems, particularly in technology sectors demanding efficient and sustainable thermal control solutions.

[0124] Fig. 6 shows a bar graph representing the change in temperature (Atemperature, °C) as influenced by various solvents. The x-axis details the types of solvents examined, which include methanol (MeOH), ethanol (EtOH), isopropanol, and dichloromethane (DCM). Each solvent category is associated with a distinct bar reflecting its impact on temperature.

[0125] The y-axis indicates the temperature change in degrees Celsius, showing both positive and negative values, thus illustrating the cooling or heating effects of the solvents. Methanol (MeOH) and isopropanol exhibit slight positive temperature changes, indicating a warming effect. In contrast, ethanol (EtOH) shows a small negative temperature change, suggesting a slight cooling effect. Dichloromethane (DCM) exhibits a more pronounced negative temperature change, indicating a significant cooling effect compared to the other solvents.

[0126] The error bars on each bar signify the variability or uncertainty in the data, adding reliability to the results presented. This figure may facilitate a comparative analysis of the cooling efficiency of different solvents in specific applications, such as the CoolGen-U system's integration with lithium-ion batteries and server farms.

[0127] The experimental data indicate that triple-distilled water (TDW) delivers the most rapid cooling effect, reaching a minimum temperature of -4.6 ± 0.9 °C within 20 seconds and displaying a recovery duration of 49.7 ± 1.6 minutes. Ethanol and acetonitrile, while resulting in lower temperature reductions, demonstrate distinct recovery profiles, with ethanol's partial solubility characteristic suggesting potential for extended cooling duration. The application of quenchers, particularly glycerol, significantly prolongs cooling duration, with the TDW-glycerol mixtureachieving the most extended recovery interval of 147 ± 20 minutes. Collectively, these results imply that TDW is optimally suited for scenarios necessitating rapid cooling, whereas ethanol and TDW-glycerol combinations might be advantageous in contexts where sustained cooling is crucial.

[0128] Reference is now made to Fig. 7 a flowchart illustrates a temperature monitoring and urea-based cooling process. The process begins at step 10. At step 11, temperature is monitored using one or more temperature sensors (e.g., sensor 1 and / or a sensor array) to generate temperature data. In some embodiments, the monitored temperature is ambient temperature. In some embodiments, the monitored temperature is a temperature of an industrial equipment component and / or a temperature within an enclosure. At step 12, the temperature data are evaluated and / or diagnosed to determine whether a cooling condition is satisfied. In some embodiments, the evaluation includes determining whether the temperature exceeds a preset threshold (e.g., 50°C). In some embodiments, the evaluation includes determining whether the temperature exceeds one or more preset limits and / or falls outside an allowable range. At decision step 13, if the cooling condition is not satisfied, the process returns to step 11 to continue monitoring. If the cooling condition is satisfied, then at step 104 the temperature data are provided to control logic and a cooling protocol is initiated (e.g., by transmitting the temperature data to controller 2). At step 15, a flow management device (e.g., device 4) is actuated to cause cooling fluid to flow from a reservoir (e.g., tank 3) into a reaction chamber (e.g., a urea chamber and / or reactive chamber). At step 16, a cooling reaction is performed in the reaction chamber to absorb heat. In some embodiments, the reaction is endothermic. In some embodiments, the reaction is facilitated by heat absorption properties of the cooling fluid. At step 17, temperature monitoring continues during the cooling operation (e.g., by repeating step 11) to determine whether the temperature has stabilized and / or returned to within an acceptable range. At decision step 108, if stabilization has not been achieved, the process returns to step 17 to continue cooling and monitoring. If stabilization has been achieved, then at step 19 the flow management device is deactivated to stop or reduce fluid flow. In some embodiments, residual heat is further dispersed at an optional step using one or more heat dissipation elements (e.g., radiators). The process ends at step 20, or returns to step 11 for repeated operation as needed.

[0129] In some embodiments, the monitored temperature is ambient temperature. In some embodiments, the monitored temperature is a temperature of an industrial equipment component and / or a temperature within an enclosure housing industrial equipment.

[0130] In some embodiments, evaluating the temperature data comprises determining whether the temperature exceeds a preset threshold, such as 50°C. In some embodiments, evaluating the temperature data comprises diagnosing the temperature data using a plurality of preset limits and / or a dynamic threshold.

[0131] In some embodiments, the controller receives transmitted temperature data from the one or more temperature sensors and, responsive thereto, initiates the cooling protocol.

[0132] In some embodiments, the cooling reaction is an endothermic reaction. In some embodiments, the cooling reaction is facilitated by heat absorption properties of the cooling fluid.

[0133] In some embodiments, after stopping or reducing the fluid flow, heat is further dispersed using one or more heat dissipation elements, such as radiators.

[0134] Fig. 8 details a battery temperature management process. Starting at step 21, the system monitors battery temperature. In step 22, a temperature sensor integrates to assess cell temperatures, sending the data to the controller at step 23. Upon detecting a critical temperature range (150°C to 200°C) at step 24, the process instructs a flow device at step 25 to deliver liquid initiating an endothermic reaction at step 26. Step 27 involves maintaining thermal insulation to prevent heat transfer. The temperature stability check at step 28 determines whether to deactivate water flow at step 29. The cooling cycle ends at step 30, concluding the process.

[0135] Fig. 9 exhibits a configuration for industrial equipment cooling involving various components. A temperature sensor collects data for effective temperature surveillance. The sequence features multiple tanks and devices ensuring fluid collection and temperature regulation throughout the system. The reservoir gathers necessary volumes within protocols established by interconnected systems. Components labeled across the diagram facilitate continuous monitoring and cooling, ensuring optimal performance of industrial equipment.

[0136] Fig. 10 demonstrates a home energy storage system's cooling process. This schematic embodies the relationship between sensor data acquisition and cooling mechanisms. In this view, the flow management device, temperature sensors, and urea-cooling apparatus collaborate to maintain energy system efficiency. Reactants within the cooling system react to thermal fluctuations, with the diagram emphasizing integration with domestic energy storage solutions.

[0137] Turning to Fig. 11, the flowchart outlines a battery temperature regulation process. Step 38 involves monitoring battery temperature using a sensor. Step 39 assesses if a temperature threshold alert is triggered. If so, step 40 involves alerting the controller of approaching predefined limits.Step 41 triggers the flow management device, administering fluid from the tank to the cooling system. At step 42, an endothermic reaction using a urea-liquid combination facilitates heat absorption. Step 43 maintains thermal balance through stability monitoring and fluid flow cessation. The process ensures thermal efficiency at step 44 with a thermal insulation chamber. The process ends at step 45, completing the sequence.Embodiment 7: Al and Machine Learning-Enhanced Cooling System

[0138] System Architecture and Components: AI-Enhanced Temperature Sensor Array: Incorporating advanced sensing technology from Maxim Integrated (USA), the temperature sensor 1 array is enhanced with Al-driven algorithms to provide predictive thermal data analysis. This allows for more accurate temperature readings and forecasting of thermal patterns within server farms and lithium-ion battery environments. Machine Learning Controller (NVIDIA Jetson Platform): Utilizing NVIDIA's Jetson platform, the controller 2 processes real-time thermal data using embedded machine learning models. This component facilitates dynamic adjustment of cooling protocols based on predictive analysis and historical temperature trends, allowing for proactive rather than reactive cooling measures. Adaptive Flow Management Device: Al controls are integrated into the flow management device 4 to adjust fluid flow rates dynamically. The device employs machine learning algorithms, optimizing the operation of electric pumps and solenoid valves based on anticipated thermal fluctuations. Intelligent Urea-Water Container System: The reservoir 3 is equipped with Al-enabled feedback systems that monitor urea and water levels. Predictive analytics provided by the system guide maintenance schedules, optimizing urea replenishment and water recycling to maintain effectiveness in cooling processes. Automated Thermal Insulation Optimization: Machine learning techniques enhance thermal insulation chamber 5 efficiency by analyzing environmental conditions and thermal loads. The system dynamically adjusts insulation configurations to improve operational stability and cooling capacity. Deep Learning-Enabled Backup Power Management: This backup power solution leverages deep learning algorithms to predict potential power disruptions, ensuring uninterrupted cooling activity during power anomalies.

[0139] Operational Workflow: Fig. 12 shows a flowchart depicting the operational sequence for an Al-enhanced cooling process within the CoolGen-U system. At step 46, an Al-enhanced temperature sensor array collects detailed thermal data, providing precise input for the subsequent predictive analysis. Following this, step 47 involves deploying predictive models that forecastpotential hot spots and thermal peaks, allowing the system to anticipate areas of concern efficiently.

[0140] In step 48, the process determines whether a potential temperature rise has been identified. If such a rise is detected, the flowchart proceeds to step 49, where the system's controller preemptively activates the cooling cycle to mitigate any identified risks promptly. This proactive response is crucial in managing thermal loads effectively within servers and lithium-ion batteries.

[0141] Continuing to step 50, Al-driven flow management adjusts the fluid distribution rates accordingly, ensuring the right amount of coolant is applied to the areas that need it most. Step 51 describes the intelligent urea-water system's optimization of reaction timing, which enhances the cooling efficiency by timing the chemical reactions accurately to match the thermal demands.

[0142] The process then moves to step 52, where machine learning models tailor the heat dissipation approach, customizing the method based on the specific conditions encountered in the monitored environment. Finally, at step 53, the series of operations concludes, marking the end of the process. This sequence enables a responsive and adaptive cooling method suitable for handling the high thermal loads of modern technological environments.

[0143] Predictive Temperature Monitoring: The Al-enhanced temperature sensor array, model TS-2000, commercially available from Sensata Technologies, headquartered in Attleboro, Massachusetts, collects detailed thermal data. The array operates within a range of -40 to 125 degrees Celsius. Utilizing predictive models, such as those implemented through TensorFlow or PyTorch, which are frameworks developed by Google LLC and Facebook, Inc., respectively, the system forecasts hot spots and thermal peaks with predictive accuracy metrics exceeding 90%. I ntelligent System Activation: Based on Al predictions and real-time data, the controller, model CX-500, available from ABB Group with its headquarters in Zurich, Switzerland, preemptively activates the cooling cycle. When a potential temperature rise is identified, the lead time for emergency cooling activation is reduced. This is achieved with an algorithm programmed to respond to temperature deviations as low as 1 degree Celsius from baseline specifications, operating efficiently in industrial settings. Optimized Cooling Process: The Al-driven flow management device, FM series from Danfoss A / S, based in Nordborg, Denmark, automatically adjusts fluid distribution rates in response to anticipated thermal demands. This system ensures efficient resource utilization and minimizes manual intervention. The device adapts flow rates within a range of 0.5 to 20 liters per minute to maintain optimal cooling levels aligned with operational guidelines. Reactive ChemicalProcesses: The intelligent urea- water system within reservoir , model UR-300 sourced from BASF SE, with principal office located in Ludwigshafen, Germany, manages chemical reactions around forecasted thermal events. The system optimizes reaction timing for enhanced cooling effectiveness by regulating urea concentrations between 30% to 40%, promoting precise chemical engagement during thermal impact periods. Adaptive Heat Dissipation Management: Utilizing insights from historical data, machine learning models dynamically tailor the heat dissipation approach within the thermal insulation chamber, model TI-800 by Owens Corning, headquartered in Toledo, Ohio. The system is capable of ramping up cooling measures based on identified thermal trends, managing heat conduction within parameters of 0.02 to 0.05 W / m K thermal conductivity, suitable for a variety of industrial applications.

[0144] In the described embodiment, an artificial intelligence (Al) and machine learning system enhances the efficiency of adding urea to solvents to optimize the cooling capability of the CoolGen-U system.

[0145] AI-Enhanced Temperature Sensor Integration: The system integrates the temperature sensor 1, which is augmented with Al algorithms to predict and identify optimal conditions for initiating the urea addition process based on real-time thermal data. This anticipates temperature variations and adjusts system operations dynamically. Machine Learning -Driven Solvent Management: The controller 2 employs machine learning models to analyze historical thermal data alongside realtime inputs. These models inform precise adjustments to the composition ratios within the reservoir 3, ensuring that the urea is mixed with solvents such as triple-distilled water (TDW) or other applicable media at the most effective concentrations. Adaptive Flow Management: The flow management device 4 uses Al-driven algorithms to manage the flow of solvents and urea into the reactive chamber efficiently. This modulation optimizes the dissolution and cooling processes, responding to thermal demands as predicted by the machine learning models. Dynamic Urea Addition: The urea addition system within the reservoir 3 harnesses Al-enhanced analysis to refine urea-solvent interactions. This analytic process ensures precise control over the urea introduction sequence, tailoring it to the predicted cooling load and enhancing the endothermic reaction effectivity. Intelligent Cooling Process Optimization: The thermal insulation chamber 5 benefits from Al algorithms that adjust insulation parameters based on ambient conditions and projected cooling needs. This ensures the maximum retention of the cooling effect generated by the urea- solvent reaction, thus improving overall system efficiency.

[0146] Operational Steps: Predictive Assessment (Step 46): The Al enhancement in the sensor array collects and processes comprehensive thermal data. Model Application (Step 47): Machine learning predictions identify the precise moment for urea addition. System Adjustment (Step 48): Upon identifying optimal conditions, the Al system dynamically modifies the solvent composition through the flow management device 4. Efficient Urea Mixing (Step 49): The predicted mixture proportions are utilized to achieve the best cooling performance. Enhanced Cooling Management (Step 50): Ongoing machine learning analysis ensures that the cooling reaction is sustained and efficiently managed across all system operations.

[0147] The Al and machine learning approaches implemented in this configuration provide a refined methodology for integrating urea into solvent systems, optimizing reaction dynamics, and enhancing the CoolGen-U system's overall thermal management performance.

[0148] Advantages and Applications: Addresses unforeseen thermal challenges preemptively by leveraging machine learning insights, minimizing system downtime and increasing reliability. Reduces overall energy consumption by strategically managing resources based on consumption patterns and predictive analytics. Incorporates seamlessly with existing technology infrastructures, facilitating smart upgrades with minimal interference in prevailing operations. Provides a more sustainable solution by optimizing water and urea usage, aligning operational success with environmental sustainability goals.

[0149] This intelligent Al and machine learning-enhanced cooling system exemplifies a forward-thinking approach to thermal management, offering unprecedented adaptability and efficiency in maintaining optimal temperatures within demanding electronic environments such as server farms and lithium-ion battery systems.

[0150] The CoolGen-U system, which employs a urea- water-based cooling approach, integrates greenenergy concepts that enhance both safety and environmental sustainability. The intrinsic design of the CoolGen-U system aligns with contemporary green-energy objectives, focusing on reducing emissions and conserving resources while ensuring operational safety in high-demand environments, such as server farms and lithium-ion battery arrays.

[0151] One of the system's critical safety aspects lies within its closed-loop operation, which minimizes resource consumption by continuously circulating cooling agents. This reduces the need for external resources, conserves energy, and limits water usage, thereby minimizing environmental footprint. By relying on the endothermic properties of a urea-water reaction, the system ensuresthat hazardous cooling byproducts are not released into the environment, aligning with ecological standards.

[0152] Additionally, the system’ s ability to autonomously respond to critical thermal thresholds enhances operational safety. During excessive thermal events, such as possible thermal runaway scenarios in lithium-ion batteries, the system immediately activates a cooling protocol that effectively absorbs heat and lowers oxygen concentration in the vicinity, reducing ignition risk and potential hazards. This rapid response not only protects the equipment but also safeguards other environmental elements from potential discharge or fire incidents.

[0153] Referring to Figs 15-20 present different views of a server farm which is characterized by the following main technical features:

[0154] A. Heat absorption - microchannel units are installed on the servers and absorb the heat generated from their operation.

[0155] B. Transport of heated fluid - the fluid (urea-water mixture and other components) that heats up passes through pipes to a recycling and cooling center.

[0156] C. Fluid flow - the urea-water fluid flows into the turbine at high pressure and rotates the rotor.

[0157] D. Magnetic field - the rotor moves within a permanent magnetic field created by magnets around it.

[0158] E. Electricity generation - the movement of the rotor within the magnetic field causes electromagnetic induction, which produces an electric current (see Fig. 15).

[0159] F. Energy transfer - the electricity generated is transferred for storage in a battery or for immediate use.

[0160] G. Filtration - Multi-stage filtration (coarse -> fine -> chemical filtration) is the core to ensure clean water in a closed circuit + water quality sensors (conductivity / Redox potential / pH, etc.) + Al algorithm will manage the concentrations of urea and other substances and the frequency / nature of the filtration.

[0161] H. Cooling and recycling - In the cooling center, the liquid is cooled and stored for reuse in the system.

[0162] I. Closed circuit - The recycled liquid flows back to the servers to restart the process, without wasting water or energy.

[0163] In the closed system:

[0164] The turbine is mounted in a location characterized by a maximal pressure difference or height (a pressure release point or natural fall). Straight pipes as possible around the turbine in order to minimize losses. Pipe diameter is adjusted to the flow rate of the cooling system in order to avoid too high friction or too low speed. The magnets are a part of the generator structure (water turbine + coils = hydro-generator). They do not add “new” energy, they only convert flow into electricity. Accessibility and maintenance: Leave a bypass and service area for the turbine. Sensors before and after: pressure, flow, temperature - critical for control and monitoring efficiency. This way we can maximize the energy extracted from the flow (or “return” some of the energy invested in pumps / headroom), while at the same time ensuring continuous cooling for the servers.

[0165] Figs 21-25 illustrate easy inflammability of Lithium-ion batteries.

[0166] According to the present invention, the Lithium-ion battery can have a thin urea-polymer layer on the anode and cathode (Fig. 26). The urea-polymer layer provides thermal protection and maintains the compact structure of the battery. Alternatively, the electrolyte is combined with urea to enhance heat resistance (Fig. 27). An electrolyte is a liquid or gel that transfers ions between the anode and cathode. Combining urea with the electrolyte improves its resistance to extreme thermal conditions. Figs 28-34 illustrate different embodiments of the urea-modified Lithium-ion batteries.

[0167] Examples:

[0168] 1. Lithium-ion battery for phones with a thin layer of urea-polymer.

[0169] 2. Lithium-polymer battery for drones with a focused urea layer.

[0170] 3. Lithium-iron-phosphate battery for energy systems with urea layers between the cells.

[0171] 4. Lead-acid battery for cars with an external urea layer.

[0172] Figs 35-38 illustrate a urea-cooled charging station characterized in the following:

[0173] A. Heat absorption from converters - Micro-channel cooling units are installed on the converters at the charging station and absorb the heat generated.

[0174] B. Transport of the heated liquid - The heated liquid (urea- water) is transported through a dedicated pipeline to the cooling center.

[0175] C. Energy generation - During the flow in the pipeline, tiny turbines convert the movement of the liquid into electrical energy.

[0176] D. Filtration - Multi-stage filtration (coarse -> fine -> chemical filtration) is the core to ensure clean water in a closed circuit + water quality sensors (conductivity / Redox potential / pH, etc.) +Al algorithm will manage the concentrations of urea and other substances and the frequency / nature of the filtration.

[0177] E. Cooling and liquid circulation - In the cooling center, the heated liquid is cooled after filtration and recycled for reuse in the system.

[0178] F. Closed circuit - The recycled liquid is returned back to the cooling stations on the converters, completing the cycle.

[0179] From an environmental perspective, the urea and water employed in the process are non-toxic, offering a significant advantage over more hazardous chemical-based cooling agents. This further mitigates environmental contamination risks, ensuring that the system remains compliant with international environmental safety regulations.

[0180] Through its harmonization of safety and green-energy principles, the CoolGen-U system provides a robust solution to the thermal management challenges faced by modern energy-intensive systems. Its conscientious approach to resource efficiency and safety ensures it remains a viable option for reducing ecological impact while maintaining high safety standards.

Claims

ClaimsWhat is claim is:

1. A closed cooling system for electronic components, comprising:a reservoir configured to store a cooling medium comprising urea and water;a temperature sensor operatively coupled to monitor ambient temperatures of electronic components;a flow management device configured to manage fluid distribution from said reservoir ; and a controller adapted to receive data from said temperature sensor and govern the operation of said flow management device,wherein said system facilitates an endothermic reaction, absorbing heat from electronic components through regulated fluid distribution.

2. The system of claim 1 , wherein said temperature sensor is capable of providing digital output of real-time temperature data.

3. The system of claim 1, wherein said controller is configured to initiate delivery of said cooling medium when a temperature exceeds a threshold temperature.

4. The system of claim 3, wherein the threshold temperature is about 50°C.

5. The system of claim 1, wherein said controller is configured to modulate a flow rate of the cooling medium based on the temperature data.

6. The system of claim 1, wherein said flow management device comprises at least one of a valve, a pump, a regulator, a manifold, or a nozzle for precise control of fluid release from the reservoir.

7. The system of claim 6, wherein said at least valve is a solenoid valve.

8. The system of claim 1, wherein said reservoir comprises separate compartments for urea and water.

9. The system of claim 1, wherein said cooling medium further comprises one or more quenchers configured to enhance a duration of a cooling effect.

10. The system of claim 1, further comprising a mixing device configured to enhance said endothermic reaction rate by efficient mixing of urea and water.

11. The system of claim 1 , wherein said system includes a thermal insulation chamber to reduce heat transfer to the external environment.

12. The system of claim 1, further comprising a backup power source configured to power said system during a main power, thereby enable its operation.

13. The system of claim 1, wherein said electronic components comprise one or more battery cells of a battery pack.

14. The system of claim 1, wherein said controller is configured to deliver said cooling medium in response to detecting a temperature indicative of a thermal runaway condition and / or a risk of thermal runaway.

15. A method for cooling electronic components, involving:a. obtaining temperature data from at least one temperature sensor associated with said electronic components and / or an ambient environment;b. controlling, by a controller, a flow control device based on said temperature data to deliver a cooling medium comprising urea and water from a reservoir to a location thermally coupled to said electronic components; andc. generating cooling by an endothermic dissolution of urea in water.

16. The method of claim 15, further comprising initiating delivery of said cooling medium when a temperature exceeds a threshold temperature.

17. The method of claim 15, comprising adjusting a flow rate of said cooling medium based on real temperature data.

18. The method of claim 15, wherein urea and water are stored separately and mixed upon or prior to delivery.

19. The method of claim 15, further comprising a step of mixing urea and water using a mixing device to enhance said endothermic dissolution rate by efficient mixing of urea and water.

20. The method of claim 15, further comprising an evaluating step configured to evaluate historical temperature patterns to predict potential hot spots.

21. The method of claim 15, further comprising dispersing heat using radiators with fin configurations for enhanced cooling efficiency.

22. The method of claim 15, incorporating an additional step of maintaining thermal insulation to encapsulate cooling effect.

23. A method for assembling a cooling system, comprising:configuring a reservoir with separate compartments for urea and water;installing at least one temperature sensor adjacent to electronic components;establishing communication links between said at least one temperature sensor and a controller;connecting a flow management device to said reservoir; andintegrating a thermal insulation chamber around system components,wherein said assembly method ensures precise thermal management through accurate component placement and connectivity.

24. The method of claim 23, further involving the calibration of temperature sensors using predefined temperature thresholds.

25. The method of claim 23, including the implementation of communication protocols for realtime data exchange between components.

26. The method of claim 23, wherein the assembly supports modular adjustments to accommodate varied electronic component arrangements.

27. An Al- and machine learning-implemented method of operating a cooling system for electronic components, said method, comprising:an Al-enhanced temperature sensor array for predictive thermal data analysis;a machine learning controller processing real-time and historical thermal data;an adaptive flow management device dynamically adjusting fluid distribution; and an intelligent urea-water container system monitoring reactant levels,wherein the system optimizes cooling processes through data-driven insights and anticipatory adjustment strategies.

28. The system of claim 27, wherein the temperature sensor array includes Al-driven algorithms to forecast thermal peaks.

29. The system of claim 27, wherein the machine-learning controller is operatively linked to cloud-based analytics platforms.

30. The system of claim 27, wherein the adaptive flow management device employs Al models for real-time system calibration.

31. The system of any one of claims 27-30, including a predictive analytics module for maintaining optimal urea and water levels.

32. The system of any one of claims 27-31, further comprising an automated thermal insulation optimization mechanism based on environmental conditions.

33. A lithium-polymer electric battery comprising:a. a container accommodating an electrolyte;b. an anode and a cathode immersed in said electrolyte;wherein alternatively said electrolyte comprises urea or said anode and cathode have a layer of a urea-polymer layer.

34. The lithium-polymer electric battery of claim 33, is selected from the group consisting of:a battery for phones with a thin layer of urea-polymer, a lithium-polymer battery for drones with a focused urea layer, a lithium-iron-phosphate battery for energy systems with urea layers between the cells, a lead-acid battery for cars with an external urea layer and any combination thereof.

35. A cooling agent comprising:a. glycerol;b. urea; andc. water.

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