Abstract: This disclosure relates generally to a sunscreen composition containing visibly transparent biocompatible ultraviolet blocking polymer nanoparticles. The sunscreen composition comprising polydimethylsiloxane (PDMS) nanoparticles, at least one flavoring agent, at least one coloring agent, at least one stabilizer, and at least one preservative, in a defined form, wherein size of the PDMS nanoparticles ranging from 200 to 1200 nm. The size of the PDMS nanoparticles ranging from 200 to 500 nm for air medium and from 800 to 1200 nm for water medium. The PDMS nanoparticles comprise a PDMS polymer having terminal functional group selected from alkyl, alkoxy, vinyl, hydroxyl, or a combination thereof. The sunscreen composition is available in the defined form selected from a group consisting of a skin cream, a skin lotion, a powder, a gel, and a sprayable liquid.

Abstract: Multispectral laser speckle analysis techniques have been widely used for applications such as the analysis of seed qualities, detection of fungal infections in fresh produce, estimation of blood flow velocities, and the like. However, the conventional methods fail to address color bias in images which is a major concern in terms of accuracy in applications like activity prediction. and the present disclosure provides a novel image processing algorithm which performs activity prediction without any color bias. Here, an RGB input image is segmented, and mask is generated. Distance based clustering is performed on the masked image to obtain cluster map. Simultaneously, color coded activity map is generated for each color component of the image. Further, the color coded activity map is multiplied with cluster contrast values and thereby an optimal color coded activity region is selected for activity map generation.

Abstract: Health of perishable commodities such as eatables deteriorate over time. State of art systems for health monitoring of perishable commodities rely on measurement of limited parameters and also fail to consider effect of environment on the health of the perishable commodities. Disclosed herein is an apparatus and method for multimodal sensing and monitoring of perishable commodities. The apparatus allows to change environment within a closed chamber in which the perishable commodity being monitored is kept, and in turn allows to generate health data in different environment settings. This data is used to generate a health model. Data collected in real-time are processed with the health model to establish a correlation with at least one image, wherein each of such images in the health model represents certain health state. Based on the established correlation, health of the perishable commodity is determined.

Abstract: Conventional approaches are not efficient for the screening of active multi component alloy catalysts. Present disclosure provides systems and method that incorporate elements of materials chemistry, artificial intelligence (AI)/machine learning (ML) and optimization for the screening of such active catalysts for a target chemical reaction. Given a set of elements constituting the alloy and the target reaction, surface atomic structures of several different alloy composition and configurations are constructed. Then, adsorption energy of key reaction intermediates on the surface atomic structures are computed using quantum chemical methods (QCM). Next, an AI/ML model is trained using data obtained from QCM to predict the adsorption energy of the reaction intermediates on the alloy surface. Finally, numerical optimization is used to identify alloy compositions that maximize the activity and selectivity of the catalyst for a target chemical reaction.

Abstract: State of the art mechanisms for edible food coating design have the disadvantage that they fail to accommodate various factors such as type of compounds, chemical composition, and processing parameters such as pH, drying rate, temperature affect the nano-microstructure of the film. The disclosure herein generally relates to edible food coating, and, more particularly, to a method and system for developing and characterizing edible films using molecular dynamic simulations. The molecular dynamic simulations help design the edible food coatings, which maybe further used for practical applications.

Abstract: This disclosure relates generally to the field of retrieval and extraction for designing formulated products by constructed ingredient-functionality lists for formulated products using search engine result excerpts in an automated manner. Many ingredients used in formulated products are multi-functional. Conventionally, in a given category of formulated product, only a single functionality or subset of functionalities of an ingredient is used ignoring other functionalities of which the ingredient is representative. However, there is a need to put together representative ingredients before proceeding further with process steps of making and testing the formulated product. The present disclosure addresses unresolved problems of the conventional methods by obtaining information regarding the functionalities of ingredients used in formulated products using search engines based on a loop processing involving query formation, and construction of a list of ingredients and functionalities till exhaustion.

Abstract: Most techniques to estimate the service life of coatings are experimental in nature. Experimental testing of coatings is expensive (destructive in nature) and time consuming. Present disclosure provides system and method that predict change in chemical composition of the coating using reaction mechanism of the coating components in presence of weathering causing environmental agents. The system partial differential equations wherein chemical model is combined with the physical model. The changes in chemical composition enable determining the change in surface roughness and thickness as the weathering of the coating happens which can be correlated with other parameters such as gloss loss, fracture toughness, and the like. Rate of initiation reaction which leads to micro-randomness in concentration profile is randomized to mimic inherently stochastic (random) nature of coating degradation.

Abstract: Non-Pneumatic Tire (NPT) has been widely used due to their various advantages. Existing solutions/approaches provide limited flexibility on the overall tire performance and have less stiffness and poor damage performance. Embodiments of the present disclosure provides systems and methods that generate optimized spoke design for non-pneumatic tires. More specifically, the system of the present disclosure can generate optimized topology with customized property/performance outcomes for NPTs. The variety of spoke designs have been created using a computer generative method. The performance of these generative spoke designs has been investigated using a finite element method (FEM) technique, wherein output of the FEM technique is used for training machine learning model(s) that enable selection of optimal spoke design for tire manufacturing.

Abstract: Traditional food quality monitoring systems fail to monitor the variation of food quality in real-time scenarios. Existing machine learning approaches require dedicated data models for different classes of food items due to differences in characteristics of different food items. Also, to generate such data models, a lot of annotated data is required per food item, which are expensive. The disclosure herein generally relates to monitoring and shelf-life prediction of food items, and, more particularly, to system and method for real-time monitoring and shelf-life prediction of food items. The system generates a data model using a knowledge graph indicative of a hierarchical taxonomy for a plurality of categories of the plurality of food items, which in turn contains metadata representing similarities in physio-chemical degradation pattern of different classes of the food items. This data model serves as a generic data model for real-time shelf-life prediction of different food items.

Abstract: Metal corrosion is a ubiquitous phenomenon costing the global economy, trillions of dollars annually. Conventional corrosion inhibitor compounds are either not so effective or require huge amount of inhibitor for adequate protection. The present disclosure addresses the problem of acid corrosion of iron and iron alloys which is relevant for a wide variety of industries such as oil and gas production and acid pickling etc. The technical solution provided in the present disclosure is a new corrosion inhibitor composition including Naphthalene-1-thiocarboxamide for iron and iron alloys in HCl media. This is specifically relevant for acid well stimulation in the oil and gas industries.

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 predicting shelf life of perishable food items. In supply chain management, current technology provides limited capability in providing relation between visual image of food item and a quality parameter value at different storage conditions. The system includes a quality parameter prediction module and a shelf life prediction module. The method obtains input data from user comprising a visual data and a storage data of each food item. The quality parameter prediction module determines a current quality parameter value of the food item from a look-up table. The shelf life prediction module predicts the shelf life of food item based on the current quality parameter value, a critical quality parameter value and the storage data. The look-up table comprising a plurality of weather zones are generated based on relationship dynamics between the visual image of food item and the quality parameter value.

Abstract: Most techniques to estimate the service life of coatings are experimental in nature, cost expensive and are computationally heavy. Present disclosure provides systems and methods that predict the combined effects of crack path propagation and zones of delamination, that form on coating material and its surface due to weathering. The system of the present disclosure implemented a combined Finite Element Method (FEM) and Monte Carlo based simulation approach to capture the effects of delamination and crack propagation, respectively. The crack paths are predicted using a probabilistic model, considering crack propagation, branching, and keeping a record of crack age. Stress distribution computations are performed using FEM to understand stress concentration zones and delamination behavior with time, which is methodically also combined with the time sequence of cracking as well.

Abstract: Conventionally, manufacturing of molded parts using composite materials has led to poor dimensional accuracy and tensile strength due to improper curing thus resulting in rejection or early/premature failure of composite part. Embodiments of the present disclosure provide simulation-based systems and methods for manufacturing/generating molded parts using reinforced composite materials. The optimized cure cycle is computed for a given component without carrying out numerous experiments. The present disclosure implements multiscale method and surrogate modeling in virtual testing for more accurate and faster manufacturing of molded parts. Process parameters for specified qualities (e.g., minimum residual stresses, minimum deformation, etc.) required for a part are determined along with least process manufacturing time. The resulting optimized time dependent cure cycle for each thermal zone of the heated mold is transferred to a master controller (e.g.

Abstract: This disclosure relates generally to method to determine an optimal set of atom centered symmetry functions. One or more parameters associated with one or more atom centered symmetry functions (ACSFs) are received. An initial set of ACSFs is generated by varying the one or more parameters. A histogram with a prespecified bin size is constructed to obtain a distribution of value of each of the initial set of ACSFs. A pruned list of ACSFs is obtained based on width and maximum value of the distribution of the value of initial set of ACSFs. The pruned list of ACSFs is sorted in decreasing order of spread to obtain a sorted list of ACSFs. An optimal set of one or more shortlisted ACSFs is determined by traversing through the sorted list of ACSFs. A high dimensional neural network potential is trained based on the optimal set of one or more shortlisted ACSFs.

Abstract: Nanomaterials are an important class of materials for sunscreens. Conventional metal oxide nanoparticles are toxic in nature and leave white patches on skin after application. This disclosure provides a sunscreen composition containing biodegradable antimicrobial polymer nanoparticles as UV filter. The sunscreen composition comprising chitosan nanoparticles, at least one flavoring agent, at least one coloring agent, at least one stabilizer, and at least one preservative, in a defined form, wherein size of the chitosan nanoparticles is ranging from 200 to 900 nm. The size of the chitosan nanoparticles ranging from 200 to 400 nm for air medium, 500 to 700 nm for water medium and 700 to 900 nm for ethanol medium. The chitosan polymer is derived from chitin, a glucosamine polymer. The sunscreen composition is available in the defined form selected from a group consisting of a skin cream, a skin lotion, a powder, a gel, and a sprayable liquid.

Abstract: The present invention relates to the field of electrolyte design. Existing methods focus on optimizing the electrolyte composition on a stand-alone basis with respect to its properties and validating battery performance experimentally which is a time-consuming process. Thus, embodiments of present disclosure provide an automated method and system for identifying electrolyte composition for optimal battery performance. The system receives certain input parameters and computes transport properties using the input. Then, a feasible electrolyte composition is identified from a material database based on deviation index metric. The identified electrolyte composition is then optimized based on the input by considering the deviation index and battery performance metrics such as capacity fade and internal heat generation.

Abstract: This disclosure relates generally to methods and systems for designing an optimal dual-band metamaterial polarization converter for refractive index sensing applications. Most of the existing techniques for designing the metamaterial-based polarization converters operating at very high frequency range limits the sensing performance and increases fabrication complexity. In the design of the optimal dual-band metamaterial polarization converter, first a circular split-ring resonator (SRR) as a unit cell is designed. Secondly, the two capacitive gaps of the top layer, are aligned at 180 degrees with respect to each other and at 45 degrees with respect to X-axis and Y-axis. Lastly, step-by-step tuning the one or more key design parameters of the SRR, is performed until an optimum frequency response is obtained, to obtain the optimal dual-band metamaterial polarization converter.

Abstract: Milk is consumed in large quantities across the world and quality of milk is important to consumer. Multilayer packaging is one of solution to maintain quality of milk for prolonged period. However, quality of milk may change due to issues in handling, transportation, environment, and packaging. Currently available techniques fail to detect milk quality when packaging is opaque. Hence, common methods that are used for detecting quality of milk cannot be easily used over packaged milk. Present application provides non-invasive method and system for detecting quality of packaged milk. More specifically, system uses a sensing technique enabled in a capacitive Near-field communication (NFC) tag and an NFC enabled device for detecting quality of the packaged milk in real-time. In particular, the capacitive NFC tag is configured to provide milk quality information on NFC enabled device when NFC enabled device comes near capacitive NFC tag configured on packaged container.

Abstract: A processor implemented method of evaluating at least one potential tastant from a plurality of tastants is provided. The processor implemented method includes at least one of: receiving, information associated with a plurality of molecular activities; generating, a plurality of data-based models based on the known taste index associated with at least one tastant and information from associated molecular structure/descriptors; classifying, a new molecule based on the generated data-based models for the at least one tastant; screening, the one or more classified new molecules in an applicability domain of the generated data-based models based on the physics-based models by at least one molecular modeling technique; and evaluating, the at least one potential tastant from the screened molecules based on at least one of a bioavailability and a toxicity. In an embodiment, the plurality of molecular activities corresponds to a taste index and a binding energy.