CN-121997610-A - Physical constraint model for material formula optimization and construction method thereof

CN121997610ACN 121997610 ACN121997610 ACN 121997610ACN-121997610-A

Abstract

The invention relates to the technical field of material informatics and discloses a physical constraint model for optimizing a material formula, which comprises a component proportion constraint model for limiting the proportion of each component to be in a thermodynamic stability region, a process-structure constraint model for characterizing the regulation and control of a molecular chain structure and an aggregation state structure of process parameters and limiting the structure parameters to be in a manufacturable region, a performance prediction constraint model for limiting the prediction performance to be in a physical realizable range, and a special constraint module for embedding thermodynamic stability, compatibility/phase separation criteria, reaction kinetics, rheology and other rules by constructing a three-layer constraint framework of component proportion-process-structure-performance prediction, and configuring the special constraint module according to ten kinds of product characteristics, thereby screening out a pseudo-optimal scheme which is not feasible in physics or process in the optimization process and improving the recommended floor-down property of the formula.

Inventors

ZHANG XIN
JIANG ZHIYING
FANG ZHAOHUA

Assignees

房兆华
张鑫

Dates

Publication Date: 20260508
Application Date: 20260206

Claims (10)

1. The utility model provides a physical constraint model for material formula optimization, its characterized in that, physical constraint model is applicable to the formula design and the performance prediction of polymer fine processing product, adopts three-layer constraint framework, includes: (1) The component proportion constraint model establishes a component molar ratio constraint equation or a mass ratio constraint equation based on the chemical composition and the thermodynamic stability principle so as to limit the proportion of each component to be in a thermodynamic stability interval; (2) The process-structure constraint model adopts a reaction dynamics theory equation or a rheology theory equation to establish a mapping relation between processing process parameters and material structure parameters, is used for representing the regulation and control of the molecular chain structure and the aggregation state structure of the process parameters, and limits the structure parameters to be in a manufacturable interval; (3) The performance prediction constraint model is used for constructing a theoretical value interval of a performance index based on a material science classical theory and a mixing law and limiting that the predicted performance is in a physical realizable range; the component proportion constraint model, the process-structure constraint model and the performance prediction constraint model are used for cooperatively constructing a full-link quantitative mapping relation of component-process-structure-performance and are used for eliminating candidate solutions which violate any constraint condition so as to avoid generating a pseudo-optimal scheme exceeding a theoretical limit.
2. The physical constraint model for material formulation optimization of claim 1, wherein the polymer fine processed product is selected from at least one of plastics, rubber, adhesives, inks, paints, oil products, surface treatments, metal working fluids, cleaning agents, and textile chemicals.
3. The physical constraint model for material formulation optimization according to claim 1, wherein the component proportion constraint model defines a component proportion range from a thermodynamic stability angle, the process-structure constraint model describes a regulation rule of a process parameter to a structure from a dynamics angle, and the performance prediction constraint model defines a value interval of a performance index from a performance theoretical limit angle.
4. A physical constraint model for material formulation optimization according to claim 3, wherein the constraint conditions of the component ratio constraint model are selected from at least one of component molar ratio constraint, component mass ratio constraint, compatibility constraint, and phase separation risk constraint.
5. The physical constraint model for material formulation optimization according to claim 2, wherein the component ratio constraint model is constrained based on a principle of a mechanism of a category to which a target product belongs, the principle of a mechanism being selected from at least one of a radical polymerization reaction functional group activity principle, a rubber vulcanization reaction principle, an adhesion reaction functional group activity principle, a pigment dispersion and film forming mechanism, a film forming resin crosslinking reaction mechanism, a lubrication mechanism, a surface modification reaction mechanism, a cooling-lubrication-rust prevention synergistic mechanism, a decontamination mechanism, and a fabric modification mechanism.
6. The physical constraint model for material formulation optimization of claim 4, wherein the phase separation risk constraint is established based on at least one of an interaction parameter, a solubility parameter difference, a pigment volume concentration to a critical pigment volume concentration ratio.
7. The physical constraint model for material formulation optimization of claim 1, wherein the theoretical equation employed in the process-structure constraint model is selected from at least one of Arrhenius equation, sulfidation reaction kinetics equation, mooney-Rivlin equation, solidification reaction kinetics equation, viscosity-temperature equation, drying kinetics equation, coating kinetics equation, adsorption kinetics equation, film formation kinetics equation, cooling kinetics equation, diffusion kinetics equation, adsorption-diffusion equation.
8. The physical constraint model for material formulation optimization of claim 1, wherein the theoretical equation employed in the performance prediction constraint model is selected from at least one of a mark-hao Wen Fangcheng, a rubber elastic modulus equation, an acle abrasion equation, a cohesive energy density equation, an interfacial tension equation, an abrasion resistance equation, a hardness equation, an oxidation dynamics equation, and a decontamination dynamics equation.
9. A method of constructing a physical constraint model for material formulation optimisation according to any one of claims 1 to 8, comprising: s1, collecting multisource basic data, carrying out standardization processing, and then constructing a four-level standardized data set structure; S2, establishing a physical constraint model, constructing a full-link quantitative mapping relation of component, process, structure and performance, and outputting a plurality of candidate formulas meeting the physical constraint.
10. The method of claim 9, wherein the four-level standardized dataset structure is a hierarchical data structure classified by purpose, main performance, manufacturing process, auxiliary performance.

Description

Physical constraint model for material formula optimization and construction method thereof Technical Field The invention relates to the technical field of material informatics, in particular to a physical constraint model for material formula optimization and a construction method thereof. Background At present, the material formula design still widely depends on a trial and error method, and the material formula is repeatedly adjusted between a multi-component system and a complex process window, so that the research and development period is long, and the cost is high. The important reasons are that the data of formula components, technological parameters, structural characterization, performance indexes and the like are mutually fractured, and the lack of unified associated modeling leads to the dislocation of a design scheme and actual processing/mass production requirements. Moreover, the existing partial data driving method is biased to fit the correlation, physical and chemical mechanism constraints such as mass/equivalent conservation, compatibility and phase balance boundary, diffusion/curing dynamics, rheology and process window are not explicitly included, a pseudo-optimal formula which is "predicted to reach standard but is not physically feasible or can not be realized by the process" is easy to generate, and the verification failure rate is high. Meanwhile, the multi-mode data structure has large difference, is difficult to fuse and align, and is easy to cause characteristic association distortion. Therefore, there is a need to build a material formulation optimization modeling method that fuses mechanism and data, while guaranteeing the prediction accuracy, enhance the physical rationality and process feasibility of the formulation, thereby improving the research and development efficiency and the touchdown of the results. Disclosure of Invention In order to solve the problem that the prediction result is always disjointed with the actual process due to the lack of physical and chemical mechanism and process manufacturability constraint in the existing material formula design, the invention discloses a physical constraint model for material formula optimization and a construction method thereof, by constructing a three-layer constraint framework of component proportion-process-structure-performance prediction, embedding rules such as thermodynamic stability, compatibility/phase separation criteria, reaction dynamics, rheology and the like, and configuring a special constraint module according to ten kinds of product characteristics, thereby screening out a pseudo-optimal scheme which is not feasible in physical or process in the optimization process and improving the floor property recommended by the formula. In order to achieve the above purpose, the invention adopts the following technical scheme: a physical constraint model for material formulation optimization, the physical constraint model being suitable for formulation design and performance prediction of high molecular fine processing products, employing a three-layer constraint architecture, comprising: (1) The component proportion constraint model establishes a component molar ratio constraint equation or a mass ratio constraint equation based on the chemical composition and the thermodynamic stability principle so as to limit the proportion of each component to be in a thermodynamic stability interval; (2) The process-structure constraint model adopts a reaction dynamics theory equation or a rheology theory equation to establish a mapping relation between processing process parameters and material structure parameters, is used for representing the regulation and control of the molecular chain structure and the aggregation state structure of the process parameters, and limits the structure parameters to be in a manufacturable interval; (3) The performance prediction constraint model is used for constructing a theoretical value interval of a performance index based on a material science classical theory and a mixing law and limiting that the predicted performance is in a physical realizable range; the component proportion constraint model, the process-structure constraint model and the performance prediction constraint model are used for cooperatively constructing a full-link quantitative mapping relation of component-process-structure-performance and are used for eliminating candidate solutions which violate any constraint condition so as to avoid generating a pseudo-optimal scheme exceeding a theoretical limit. Optionally, the polymer fine processing product is at least one selected from plastics, rubber, adhesives, printing inks, paints, oil products, surface treatment agents, metal processing fluids, cleaning agents and textile chemicals. The method comprises the steps of selecting a component proportion constraint model, defining a component proportion range from a thermodynamic stability angle, describing a regulation rule of a