Abstract: Artificially structured materials are created artificially and offer customizable properties. They are being used in various fields. A system and method for designing artificially structured materials have been provided. The system and method is based on neural networks for approximating the electromagnetic (EM) responses of the artificially structured materials. By treating the EM spectral data as time-varying sequences and the inverse problem as a single-input, multi-output model, the architecture is forced to learn the geometry of the designs from the training data as opposed to abstract features thereby addressing both the forward and the inverse design problems.

Abstract: State of the art systems being used for determining free energy of permeation have the disadvantages that estimations purely based on molecular simulations is computationally expensive, and thus not suitable for high throughput calculation and screening. Existing machine learning approaches suffer from low accuracy and generalizability. The free energy of permeation is based on the molecule only, without considering lipid membranes. Hence, the models can't capture the difference between lipids. The disclosure herein generally relates to molecular processing, and, more particularly, to a method and system for determining free energy of permeation for molecules. The system creates features based on interaction of a molecule with solvent and lipid membranes. The features are then processed to determine time dependency, feature dependency, and feature relevance, and in turn the free energy of permeation is determined. The determined free energy of permeation is then given as a recommendation to a user.

Abstract: This disclosure relates generally to method and system for designing the formulated products. Conventional techniques for designing the formulated products, meeting final functional properties, are limited. Further, understanding user requirements and active incorporation of the user requirements during design phase is quite challenging. The present disclosure herein provides method and system that solve the technical problem of extracting the functional requirement by establishing continuous conversation with the user. An optimal prediction function for each functional requirement is determined by using a plurality of prediction models. An optimization technique along with an objective function is employed to determine optimized solutions comprising list of ingredients, possible concentration level of each ingredient, the process parameters, and the operating parameters for obtaining the desired formulation based on the user requirement.

Abstract: Artificially structured materials are created artificially and offer customizable properties. They are being used in various fields. A system and method for designing artificially structured materials have been provided. The system and method is based on neural networks for approximating the electromagnetic (EM) responses of the artificially structured materials. By treating the EM spectral data as time-varying sequences and the inverse problem as a single-input, multi-output model, the architecture is forced to learn the geometry of the designs from the training data as opposed to abstract features thereby addressing both the forward and the inverse design problems.

Abstract: This disclosure relates generally to method and system for designing the formulated products. Conventional techniques for designing the formulated products, meeting final functional properties, are limited. Further, understanding user requirements and active incorporation of the user requirements during design phase is quite challenging. The present disclosure herein provides method and system that solve the technical problem of extracting the functional requirement by establishing continuous conversation with the user. An optimal prediction function for each functional requirement is determined by using a plurality of prediction models. An optimization technique along with an objective function is employed to determine optimized solutions comprising list of ingredients, possible concentration level of each ingredient, the process parameters, and the operating parameters for obtaining the desired formulation based on the user requirement.