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"Polymerize One" is an all-in-one material development support service that combines three elements: the MI platform, prototype and testing outsourcing, and professional support. 【Do you have any of these concerns in new material development?】 ■ Lack of experimental data ■ Insufficient environment and capacity for in-house prototyping and testing ■ Wanting to advance development to a higher upstream level to achieve breakthroughs in product performance (for example, aiming for optimization at the synthesis level rather than just formulation), but lacking the equipment capabilities in-house. *For more details, please download the PDF or feel free to contact us.
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Free membership registration"Polymerize Labs" is an all-in-one materials informatics platform designed by professionals in material development, enabling seamless data management and AI utilization without the need for programming knowledge. Based on a data management infrastructure specialized in organizing various materials development data and a highly flexible AI engine equipped with a diverse range of machine learning algorithms, it provides a data-driven development process across various materials fields. It addresses the resource shortages, high-cost structures, environmental regulation compliance, resolution of supply chain bottlenecks, and the need for rapid responses to market changes faced by various research and development departments, contributing to enhanced corporate competitiveness and establishing a new standard for research and development processes in the AI era. 【Features】 ■ Centralized management of experimental and materials data ■ Extraction of important features and variables with no-code AI ■ Data expansion for additional learning and experimental planning based on AI predictions ■ Prediction of properties and recommended experimental conditions by AI *For more details, please download the PDF or feel free to contact us.
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Free membership registration"Polymerize Labs" is an all-in-one materials informatics platform designed by professionals in material development, enabling seamless data management and AI utilization without the need for programming knowledge. Based on a data management infrastructure specialized in organizing various materials development data and a highly flexible AI engine equipped with a diverse range of machine learning algorithms, it provides a data-driven development process across various materials fields. It addresses resource shortages, high-cost structures, compliance with environmental regulations, alleviation of supply chain bottlenecks, and rapid responses to market changes faced by various research and development departments, contributing to enhanced corporate competitiveness and establishing a new standard for research and development processes in the AI era. 【Features】 ■ Centralized management of experimental and materials data ■ Extraction of important features and variables using no-code AI ■ Data expansion for additional learning and experimental planning based on AI predictions ■ Prediction of properties and recommended experimental conditions by AI *For more details, please download the PDF or feel free to contact us.
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Free membership registrationWe would like to introduce a case study of a customer in the elastomer seal product industry who has implemented "Polymerize." 【Customer Company Overview】 ■ Number of Employees: 100-1000 ■ Main Products: Seal Manufacturing (Elastomers) ■ Location: Japan, USA 【Challenges】 In recent years, there has been a strong trend for seal products to be used in various harsh environments. From high-temperature and high-pressure steam and acidic gas environments in the oil refining process to plasma processes in the semiconductor industry, the demands for mechanical performance of seal products have increased. The performance of the product is greatly influenced by the component ratios and formulations during compounding. In this case study, the customer aimed to maximize the performance of elastomer seals at high temperatures while maintaining elongation at the break point and minimizing compression set. After a standard three-month trial, the customer experimentally introduced Polymerize. *For more details on solving challenges, please download the catalog or feel free to contact us.
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Free membership registrationWe would like to introduce a case study of a customer in the elastomer seal product industry who has implemented "Polymerize." 【Customer Company Overview】 ■ Number of Employees: 100-1000 ■ Main Products: Seal Manufacturing (Elastomers) ■ Location: Japan, USA 【Challenges】 In recent years, there has been a strong trend for seal products to be used in various harsh environments. From high-temperature, high-pressure steam and acidic gas environments in oil refining processes to plasma processes in the semiconductor industry, the mechanical performance requirements for seal products have increased. The performance of the product is greatly influenced by the component ratios and formulations during compounding. In this case study, the customer aimed to maximize the performance of elastomer seals at high temperatures while maintaining elongation at the break point and minimizing compression set. After a standard three-month trial, the customer experimentally introduced Polymerize. *For details on solving challenges, please download the catalog or feel free to contact us.
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Free membership registration"Polymerize Labs" is an all-in-one materials informatics platform designed by professionals in materials development, enabling seamless data management and AI utilization without the need for programming knowledge. Based on a data management infrastructure specialized in organizing various materials development data and a highly flexible AI engine equipped with a wide range of machine learning algorithms, it provides data-driven development processes across various materials fields. It addresses resource shortages, high-cost structures, compliance with environmental regulations, alleviation of supply chain bottlenecks, and rapid responses to market changes faced by various research and development departments, contributing to enhanced corporate competitiveness and establishing a new standard for research and development processes in the AI era. [Features] ■ Centralized management of experimental and materials data ■ Extraction of important features and variables using no-code AI ■ Data expansion for additional learning and experimental planning based on AI predictions ■ Prediction of properties and recommended experimental conditions by AI *For more details, please download the PDF or feel free to contact us.
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Free membership registrationMaterials Informatics is a data-driven approach that uses various informatics techniques, such as statistical analysis, experimental design, computational science, and artificial intelligence, to accelerate innovation and product development processes. The materials industry requires digitization not only to manage previous experimental data but also to use past datasets for feature extraction, understand the key factors that influence the results in developing new materials, predict functional properties, and optimize compositions. Customers utilizing our cloud-based Materials Informatics platform, "Polymerize Labs," have achieved a reduction in new product development time by one-third and a 40% decrease in development costs. **Features of Polymerize Labs** - Project management - Analysis of past experimental data - Data management - Experimental design - Result prediction using AI engines *For more details, please download the PDF (case study) or feel free to contact us.*
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Free membership registrationThe cloud-based materials informatics platform "Polymerize" is equipped with unique data processing capabilities, allowing it to import spreadsheet data in any format, making it easy to implement. It features centralized data management and predictive capabilities powered by proprietary AI algorithms, enabling users to obtain suggestions, analyses, and insights related to experiments to achieve development goals. 【Features】 ■ Project management ■ Analysis of past experimental data ■ Data management ■ Experimental design ■ Result prediction using AI engines *For more details, please download the PDF (case study materials) or feel free to contact us.
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Free membership registrationIn a digital-first world, data is a valuable asset. By accessing relevant data, organizations can minimize potential errors, establish provisional processes, and respond efficiently to market fluctuations. First, it is necessary to learn about efficient data organization and understand best practices in research data management. Modern life sciences companies are beginning to leverage technology for experimental data management. *For more details, you can view the related links. Please feel free to contact us for more information.*
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Free membership registrationWe would like to introduce a case where our customer in the elastomer seal product industry implemented "Polymerize." The company aimed to maximize the performance of elastomer seals at high temperatures while maintaining elongation at the breaking point and minimizing permanent compression strain. In the initial proof-of-concept process, we confirmed that the system could meet the desired performance in 4 out of 5 experiments proposed by the system. [Challenges] - Establishing the optimal combination of components and synthesis methods to ensure efficiency and quality. - Seeking an AI solution that supports the development of new products while minimizing setbacks from a trial-and-error development process. *For more details, please refer to the PDF document or feel free to contact us.
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Free membership registration"Polymerize Labs" is a platform equipped with unique data processing capabilities that can import various formats of spreadsheet data and is easy to implement. It features centralized data management and predictive capabilities powered by proprietary AI algorithms, allowing you to obtain proposals and analyses/insights related to experiments to achieve development goals. 【Features】 ■ Project management ■ Analysis of past experimental data ■ Data management ■ Experimental design methods ■ Result prediction using AI engines *For more details, please download the PDF or feel free to contact us.
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