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  6. Material Development Support Service "Polymerize One"

Material Development Support Service "Polymerize One"

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All-in-One Material Development Support Service "Polymerize One"

last updated:Jul 18, 2025

POLYMERIZE ポリマライズ日本法人
POLYMERIZE ポリマライズ日本法人
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Consistently carry out data generation, AI model construction, and validation experiments! It is possible to shorten the lead time for efficient material development and market introduction.

"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.

    Prototype ServicesMaterial Evaluation TestTechnology Development
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Material Development Support Service "Polymerize One"

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  • Related Link - https://prtimes.jp/main/html/rd/p/000000008.000127…
  • Special site - Product/service details - https://pr.mono.ipros.com/polymerize/product/

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basic information

【Service Application Image】 1: Conduct prototype and evaluation tests at partner research institutions to generate experimental data based on the use of MI. 2: Based on the data obtained above, use "Polymerize Labs" to analyze the data and build predictive models, identifying new principles and reverse-engineering experimental conditions that meet target characteristics. 3: Conduct experiments again at partner research institutions based on the conditions derived from the analysis, accumulating data on the platform and improving the model. 4: Final evaluation of materials that meet target characteristics by material manufacturers. 5: The principles derived from the accumulated data and AI models can be continuously utilized as assets for subsequent development. *For more details, please download the PDF or feel free to contact us.

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Solving such challenges in materials development: ■ Insufficient data ■ Unable to obtain information from material suppliers ■ Lack of internal resources ■ Designing formulations in-house but lacking knowledge in synthesis ■ Performance limits in formulation optimization ■ Insufficient prototyping, testing, and analysis capabilities *For more details, please download the PDF or feel free to contact us.

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Polymerization Comprehensive Service Guide

Polymerization Comprehensive Service Guide

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Polymerize releases the interactive AI agent feature 'Pixa' to accelerate data and AI-driven materials R&D.

Polymerize releases the interactive AI agent feature 'Pixa' to accelerate data and AI-driven materials R&D - Making data and AI utilization more commonplace.

  • Product news

Polymerize has officially released "Pixa," the industry's first AI agent on its package-type Materials Informatics (MI) platform. "Pixa" is integrated into our unified MI platform, "Polymerize Labs," and consistently supports researchers through natural language interactions, from advancing machine learning and addressing data challenges specific to materials R&D, to guiding platform operations and resolving minor "stumbles" that arise in daily tasks. In addition to practical consulting support from a team of experts with advanced domain knowledge in materials development, we aim to create an environment where the use of data and AI naturally permeates the research field as part of "daily operations," allowing for a focus on idea generation and core business activities by leveraging the AI agent "Pixa," available 24/7 for consultation.

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[Polymerize Exhibition and Lecture Information] High-Performance Materials Week | 5th Sustainable Materials Exhibition

[Exhibition and Lecture Information] High-Performance Materials Week | 5th Sustainable Materials Exhibition

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At our booth, our members with extensive experience in the chemical industry will respond to your concerns and questions regarding the use of MI, tailored to your challenges and interests. ▼ MI General Consultation Desk Staff with deep knowledge of the chemical industry will answer your individual questions and concerns about MI utilization. Pre-registration here: (https://calendly.com/contact_jp-polymerize/polymerize-clone-1?month=2025-11) ▼ Lecture Information "Pathway to Sustainable R&D — A Data-Driven Approach to Utilizing Recycled Materials" We will introduce Polymerize's AI-driven factor analysis and optimization methods for formulations and manufacturing conditions to address the challenges of quality variability among suppliers and lots when using recycled materials. Date and Time: November 14 (Friday) 13:30 - 14:15 Venue: Next Tech STAGE Seminar Room A Seminar Registration: https://biz.q-pass.jp/f/11224/mw_seminar_apply_tokyo25/seminar_register

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POLYMERIZE

POLYMERIZE ポリマライズ日本法人

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Our company provides a materials informatics platform, PolymerizeLabs, and consulting services for the chemical and materials industries. PolymerizeLabs reflects the unique R&D processes and expertise specific to materials development, enabling seamless data management and AI utilization without the need for programming knowledge. It is the only all-in-one materials informatics platform in the industry that ensures AI prediction accuracy even with limited or sparse data. 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, we offer data-driven development processes across various materials fields. We contribute to addressing resource shortages, high cost structures, compliance with environmental regulations, alleviating supply chain bottlenecks, and responding quickly to market changes faced by all R&D departments, thereby enhancing corporate competitiveness and establishing a new standard for R&D processes in the AI era.

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