MICROFLUID LEARNING CORE

Abstract

This invention relates to a microfluidic learning core that can adaptively reconstruct its own flow channels by analyzing the biological and physical behavior of liquid samples in real time and deriving decision rules from them, and which can operate without requiring electronic components;The system has a liquid analysis module (1) that enables the density, flow rate and biological-chemical parameters of liquid samples to be measured for the first time and transferred as data to the system, a cellular reservoir (2) that monitors the orientation, vibration, interaction and dispersion behaviors of cells in the flow at the microscopic level and converts them into behavioral codes, a logic processing channel (3) that contains flow-based logical processing paths that create decision functions using the pressure, direction, time and diffusion changes of the fluid, a learning reactor (4) that enables the channel resistances and orientation paths to be permanently changed by analyzing the behavioral patterns of the liquid in each flow cycle and a liquid outlet port (5) that allows the liquid with completed logic processing to be discharged from the system and transferred to the next unit.

Description

1 TARIFF MICROFLUID LEARNING CORE Technological Field: 5 This invention enables the biological and physical behavior of liquid samples to be monitored in real time. by analyzing these and deriving decision rules from them, adapting their own flow channels accordingly. reconfigurable and able to operate without requiring electronic components It is related to the microfluidic learning core. 10 State of the Art: Current liquid analysis systems rely largely on electronic sensors, membrane-based measuring units and heat-pressure controlled separation mechanisms 15 These technologies are based on detecting specific components within a liquid. Although it is effective in this regard, it does not affect the behavioral properties of the fluid, cellular movements, or Ability to process biological responses to environmental changes in real time. They lack the capacity. Most systems only measure chemical content or components. It performs separation; however, it also analyzes the microdynamic processes occurring in the liquid, its behavior 20 by analyzing the patterns or responses of biological organisms in a flow medium It does not possess a physical decision-making mechanism capable of deriving meaning from these. Furthermore... Current solutions deal with environmental noise, electromagnetic interference, sensor wear, and Stability in wide range of applications due to constraints such as high energy consumption. cannot provide. 25 Electronic and silicon-based processor architectures are commonly used in liquid analysis. Although it is used, it has a limited structure that can only process numerical data. The systems process environmental variables only as predefined sensor outputs. can be perceived; whereas biological or organic behaviors are directly observed in the physical environment. 30 It is not possible to evaluate electronic-based learning mechanisms. Because it relies on software simulations, it shows its direct impact on the physical environment. 2 Data processing is performed without a learning cycle occurring. These structural limitations, while slowing down the speed at which systems adapt to environmental changes, real-time It completely eliminates the ability to learn behavior. Silicon-based structures experience performance loss at high temperatures, and electromagnetic 5 It is sensitive to interference and due to energy consumption in long-term operation. This creates a need for additional cooling. Industrial facilities, defense such systems in challenging conditions such as applications and high radiation environments Its stability is decreasing, and its measurement accuracy is declining. Current electronic-based analysis... devices, especially for interpreting complex biological systems or cohering with environmental conditions 10 It is limited in terms of its capacity to interact in real time. Therefore, to the physical environment There is a need for next-generation solutions that are embedded and can interact simultaneously with the environment. It is heard. Patent application number US10788447B2, “Liquid Analyzer and Liquid Analysis System” 15 The invention describes an analytical device that analyzes while immersed in a flowing analytical target fluid. It is a device that performs this function and simply makes a good / bad determination and assesses reliability. To enhance this, it involves immersing a sensitive membrane in a flowing target fluid for analysis. In this case, the analysis aims to detect a predetermined component present in the target fluid. a sensor adapted for this purpose; using the voltage generated by the sensor, it analyzes the target liquid 20 an analytical mechanism adapted for analysis; and the flow of the sensitive membrane to measure the resistance of the sensitive membrane when immersed in the target analytical fluid. A resistance measuring device adapted to apply a DC voltage to a sensitive membrane. mechanism. The invention described above performs liquid analysis using a sensitive membrane and sensor-based electronics. While this is accomplished with measurement structures, the working principle is entirely based on electrical signals. It is based on perception and evaluation. This structure, during analysis... sensitivity of the membrane surface, electrical noise, ionic imbalances in the liquid and becomes sensitive to disturbances in electromagnetic environments. Also 30 The system is designed to detect only specific components in the liquid. biological behaviors, microscopic movement patterns, or environmental changes 3 It does not have a structure that can be transformed into a physical learning process. Liquid because it lacks the ability to adapt to the dynamic changes in its behavior, once The flexibility to respond to new situations outside of defined measurement parameters. It is limited. Electrical measurement mechanisms have high energy requirements and heat generation. because it creates disadvantages such as these, it is not suitable for long-term, unstable environmental conditions or 5 Reliability in applications with high levels of electromagnetic noise. It can decrease. Patent application number US2014224638A1 describes a method for dissolving fluid liquids and... The device is described. The invention increases the temporal resolution of dissolved substrates by 10. Methods and devices for removing solvent from flowing liquid streams while protecting them. It explains a new small-scale, self-regulating spray dryer. a liquid chromatography eluent stream while removing solvent and solute Temporal resolution when depositing onto an optical surface for infrared spectrographic analysis It protects. A high-speed jet of solute containing liquid eluent, liquid and solvent vapor 15 It is pumped from a heated nebulizer to create a jet. This jet then passes through a hot cylindrical tube. Centrifugal force is directed circumferentially into the void. The larger the fluid... This causes the droplets to move along the outer diameter of the gap. The gap surface, The droplets are heated to cause film boiling. Film boiling, By reducing the contact of the droplets with the pore surface, the dissolved substance in the droplets is 20 It ensures that the temperature of the solute causes the solvent to evaporate from the droplets. This is limited by controlling the pressure. When the droplets are small enough, Stokes drag, caused by the emerging solvent vapor, keeps the droplets cylindrical. It exits from the center of the void. After exiting, the superheated solvent vapor It further dries the droplets. The solvent vapor is condensed onto a cooled surface. 25 It is removed. To better remove solvent concentration, the freezing point is lowered. A substance that reduces Stokes resistance from a non-condensable gas can be added. It keeps the dried droplets in suspension. This suspension is used for infrared analysis. The dried droplets pass through a hole that focuses their impact on the optical surface. The accumulation surface is located in a vacuum chamber and is designed to freeze liquid solutes. The temperature is controlled, but it allows the remaining solvent to sublimate. 4 The invention described above determines the temporal solubility of solutes in flowing liquid. thermal and mechanical processes aimed at removing the solvent while protecting it The system's operation relies heavily on heating, evaporation, and spraying. multi-stage processes including centrifugal effect, infrared analysis and vacuum surface deposition. It depends on complex physical processes. This multi-layered mechanism reduces energy consumption by 5. while increasing the system's sensitivity to heat, certain biological or Its applicability is limited to liquids with sensitive contents. The working principle involves the dissolved substance. Because it focuses on physically separating matter, it also examines biological interactions within the liquid. behavioral patterns or informational aspects of microscopic movements It does not offer an infrastructure that can detect this. Furthermore, the high temperature, vacuum, and gas in the system... 10 Elements such as currents create a structure that can adapt to changes in environmental factors. It is not suitable for manufacturing. The large number of sensitive components, high maintenance requirements, and thermal issues. Disadvantages such as instability and the necessity of working in short cycles, method and This reduces the device's flexibility across a wide range of applications. In conclusion, a new one that can overcome the disadvantages mentioned above. Technology is needed. Description of the invention: This invention is a microfluidic system that can overcome the disadvantages mentioned above. It is a learning core; its characteristic feature is that it does not require electronics, it is high-performance. electromagnetic and radiation resistance, low energy consumption, real-time learning. and adaptation, physically reshaped flow structure, low production cost, The sustainable and environmentally friendly structure offers a multidisciplinary range of uses. 25 This invention surpasses classical intelligence thanks to its use of a completely fluid-based intelligence architecture. It offers significant technical advantages compared to electronic processors. Electronic circuit It operates without requiring electromagnetic waves, magnetic fields, and It prevents them from being affected by radiation. This is especially true for space technologies and defense. 30 reliable decision-making unit in systems and industrial environments exposed to high temperatures. It meets the need. Fluid behavior directly leads to logical decision-making mechanisms. Because it is transformed, data processing takes place seamlessly and on a physical basis. The system's energy efficiency is significantly better compared to other processor architectures. It is high. This architecture, which harnesses the natural kinetic energy of the fluid, produces electricity. 5 It minimizes consumption and operates on low energy without causing heating problems. It creates a sustainable computing infrastructure based on this principle. This structure is especially suitable for low-power applications. This provides a significant advantage in long-term tasks requiring energy consumption. The invention has the capability of real-time learning and environmental adaptation. 10 Its ability to sense the behavior of cells within the liquid and generate decision codes from them, This enables the system to react instantly to changes in the environment during the learning process. The physical reshaping of the resulting flow paths over time, a unique intelligence that can produce more efficient results from adaptive and repetitive cycles It creates the form. 15 Low production costs increase the system's potential for large-scale use. It increases [the impact of] its structure, which does not require silicon or advanced semiconductor materials. It enables easy and economical production with biopolymer-based microchannels. The fact that the materials are recyclable and the system has low energy consumption makes the invention 20 This places it in the category of environmentally friendly and sustainable technologies. The invention's potential for multidisciplinary applications makes it not just a computational tool. by transforming it from a mere device into a tool for biotechnology, healthcare, energy management, defense industry, and Artificial intelligence can be used in many different technical fields, such as hardware research. It transforms it into a purposeful platform. In this respect, the invention both explores the concept of biofluid intelligence and... It transforms it into a new class of technology, both theoretically and practically. The invention is easy to assemble thanks to the fact that its components can be easily fastened together. It is being installed, and thanks to the short assembly time, the costs are low. 30 Furthermore, the invention has a robust structure. 6 Explaining the Figures: The invention will be described by referring to the attached figures, so that the features of the invention can be explained. It will be understood and appreciated more clearly, but the purpose of this invention is this obvious It is not about limiting it with regulations. On the contrary, the invention is defined by the accompanying claims in 5 all alternatives, modifications, and options that could be included within the defined area The aim is to cover their equivalences. The details shown are only for the present invention. It is shown to illustrate the preferred arrangements and both the methods shaping, as well as the rules and conceptual features of the invention, in the most useful way. It should be understood that they are presented to provide a readily understandable definition. These 10 in the drawings; Figure 1 shows a top view of the system. Figures that will help to understand this invention are shown in the attached image (15). They are numbered and their names are given below. Explanation of References: 1. Liquid Analysis Module 20 2. Cellular Reservoir 3. Logic Processing Channel 4. Learning Reactor 5. Liquid Outlet Port Description of the Invention: The invention relates to the density, flow rate, and biochemical content of liquid samples. Liquid analysis enables the parameters to be measured for the first time and transferred to the system as data. module (1), orientation, vibration, interaction and distribution exhibited by cells in flow 30 by observing their behavior at a microscopic level and transforming it into behavioral codes cellular reservoir (2), using changes in fluid pressure, direction, time and diffusion 7 Logic that contains flow-based logical processing paths that generate decision functions. The process channel (3) analyzes the behavior patterns of the fluid in each flow cycle. learning that enables the permanent alteration of resistances and orientation pathways reactor (4) and logic operation completed liquid discharged from the system next It has a liquid outlet port (5) that allows liquid to be transferred to the unit. 5 The invention balances the temperature, pressure, and flow stability of the fluid introduced into the system, thereby improving cellular stability. Liquid analysis with a regulating layer providing a stable input suitable for observation. It has module (1). The invention slows down the fluid flow according to the complexity of the observed cell behavior. cellular reservoir (2) which increases the accuracy of analysis with its accelerating regulatory structure has. The invention treats each change in resistance encountered by the liquid as a decision point and analyzes 15 different resistances. It has a logic processing channel (3) that creates exit paths with natural flow physics. The invention applies behavioral data obtained from previous cycles to the pathways of the fluid. Adaptive learning creates the flow pattern with the lowest energy loss over time by transferring information. It has a reactor (4). 20 The invention prevents backflow of treated fluid by balancing the internal pressure of the system. and has a liquid outlet port (5) which provides one-way flow safety. Detailed Description of the Invention: 25 The components that make up the invention are basically: liquid analysis module (1), cellular reservoir (2), The logic processing channel (3) consists of the learning reactor (4) and the liquid outlet port (5). This invention enables the physical and behavioral analysis of liquid samples containing biological or chemical substances. a fluid-based system that can make decisions using its features and has learning capabilities It relates to the intelligence system. The system obtains the final data output from the initial analysis of the liquid sample. 8 The entire process, from its inception to completion, is physically carried out within microfluidic-based channels. It has a multi-layered structure that accomplishes this. The liquid analysis module (1) included in the invention measures the density, flow rate of the liquid taken into the system. Measurement by sensing speed, viscosity and the biological-chemical parameters it carries 5 This module (1) is a component that keeps the temperature, pressure and flow stability of the liquid in balance. By including a regulatory layer, the fluid will be cellular in subsequent modules. and creates a suitable and stable input for fluid-based analyses. This allows The properties of the fluid introduced into the system are stabilized, and the entire process is managed accordingly. Accuracy is increased. 10 The fluid entering the liquid analysis module (1) is directed into the cellular reservoir (2). The cellular reservoir (2) is the microscopic level of cells and particles in the fluid. its exhibited orientation, vibration, interaction, clustering and dispersion behaviors are real It perceives them in real time and converts them into behavioral codes. Reservoir (2) 15 The flow-regulating structure within its composition regulates the fluid according to the complexity of cellular behavior. It increases the sensitivity of observation by increasing or decreasing the flow rate. This section (2), It is the main analysis module of the system that converts biological responses into physical decision input, It makes it possible to obtain biomimetic data. Behavioral codes obtained from the cellular reservoir (2), logic processing channel (3) It is processed through. The logic processing channel (3) processes the pressure changes and direction of the fluid. flow-based systems using their differentiations, flow duration, and diffusion behaviors. It creates logical processing pathways. Every change in resistance the fluid encounters, the system It is evaluated as a decision point by [the relevant authority], and the fluid is divided into 25 different sub-sections according to this decision. This structure allows decision-making mechanisms such as AND, OR, and NOT to be directed to channels. Physically, solely through fluid movement, without the use of any electronic circuits. This is achieved. These logical pathways, created using natural flow physics, It provides the system's basic decision-making capacity. Fluid learning, which passes the first stage of the decision-making process via the logic processing channel (3). It reaches the learning reactor (4). The path followed by the fluid in each flow cycle in the learning reactor (4), 9 flow duration, behavioral patterns, and biological response codes from the reservoir are analyzed. By doing so, it permanently alters the system's channel resistances and routing paths. Thus, the system reinforces the flow paths that were found to be successful in previous cycles and eliminates those that failed. By weakening the pathways, it creates a flow pattern with the lowest energy loss over time. The learning reactor (4), in this respect, constitutes the adaptive intelligence structure of the system. It is the core element. The processed fluid is directed to the liquid outlet port (5). The liquid outlet port (5), discharge of fluid from the system after it has undergone logical processing and learning processes and allows it to be transferred to another module or external device if necessary. Port (5) 10 Its structure balances internal pressure, preventing backflow and ensuring a one-way, safe flow of fluid. This section enables the system's decision output to proceed in a physical fluid manner. It is the terminating unit that enables the product to be obtained in this form. 20 30

Claims

REQUESTS 1- The invention relates to a microfluidic learning core, the characteristic of which is;  density, flow rate and biological-chemical content of liquid samples Liquid 5, which enables the parameters to be measured for the first time and transferred to the system as data. analysis module (1),  The orientation, vibration, interaction, and distribution exhibited by cells in the flow By observing their behavior at a microscopic level, they can be translated into behavioral codes. transforming cellular reservoir (2),  Decisions are made using changes in fluid pressure, direction, time, and diffusion. 10 logic that contains flow-based logical paths that create functions transaction channel (3),  By analyzing the behavioral patterns of the fluid in each flow cycle, channel resistances can be determined. and learning that enables the permanent alteration of pathways of orientation. reactor (4) and 15  The logic process is complete; the liquid is discharged from the system and transferred to the next unit. It has a liquid outlet port (5) which allows it to be transferred. 2- The microfluidic learning kernel mentioned in Claim 1 is characterized by the following: the data taken into the system By balancing the temperature, pressure, and flow stability of the liquid, a constant 20 suitable for cellular observation is achieved. having a liquid analysis module (1) with a regulatory layer that provides an input It is the characterization of the situation. 3- The microfluidic learning kernel mentioned in Claim 1 is characterized by its observed properties. 25 with its regulatory structure, it has a cellular reservoir (2) which increases the accuracy of analysis. It is the characterization of the situation. 4- The microfluidic learning core mentioned in Claim 1 is characterized by its properties; the liquid It processes each change in resistance it encounters as a decision point and explores different exit routes. 30 It is characterized by having a logic processing channel (3) formed by natural flow physics. It is done. 11 5- The microfluidic learning kernel mentioned in Claim 1 is characterized by its previous feature; By transferring behavioral data obtained from cycles to the fluid's pathways, the most efficient over time It has an adaptive learning reactor (4) that creates a low energy loss flow pattern. It is characterized by being. 5 6- The microfluidic learning kernel mentioned in Claim 1 is characterized by its ability to operate within the system. By balancing the pressure, it prevents backflow of the treated fluid and ensures one-way flow. It is characterized by having a liquid outlet port (5) which ensures safety. 15 25