Intellectual Property India Publishes Patent Application for Mathematical-Physics Chemical Modeling System For Predictive Optimization Of Advanced Material Properties

MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641114977 A) filed by Dr. N. G. P. Institute Of Technology on September 25, 2026, for Mathematical-Physics Chemical Modeling System For Predictive Optimization Of Advanced Material Properties.

Inventors include Dr. A. Raji; Dr. S. Baskaran; Dr. G. Menaka; Ms. M. S. Thamarai; Mr. V. Praveenkumar; Dr. P. Vasanthakumar; Dr. R. Kulandaivelu; Dr. R. Jayasudha; Dr. B. Radha; Dr. A. Sathya Kala; and Nalini V.

The application for the patent was published on October 02, 2026, under issue no. 40/2026.

Abstract: The system (100) includes a mathematical-physics chemical modeling system (100) for predictive optimization of advanced material properties comprises a material input unit (102), a material data and property database (104), a mathematical-physics-chemical modelling unit (106), a parameterization and calibration unit (108), a simulation unit (110), a predictive property analysis unit (112), an optimization unit (114). The material input unit (102) receives material composition data, constituent information, processing parameters and target material-property requirements, and the material data and property database (104) stores corresponding material, physical, chemical, mathematical, experimental and simulation information. The mathematical-physics-chemical modelling unit (106) establishes mathematical relationships and combines physical and chemical parameters, while the parameterization and calibration unit (108) calibrates the computational model. The simulation unit (110) generates simulated material behaviour, and the predictive property analysis unit (112) determines predicted material properties. The optimization unit (114) evaluates material compositions and processing parameters to identify an optimized material configuration. The invention facilitates predictive evaluation and optimization of advanced material properties and reduces dependence on repeated experimental trial-and-error evaluation.

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