POLYMERIZE List of Products and Services

"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.

"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.

"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.

"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.

This document discusses "Data Strategies and Practices for MI Utilization." In this article, we organize the challenges related to data in MI utilization and explain specific data strategies and practical approaches to overcome them. Additionally, we introduce the challenges in new material development and Polymerize's solution, "Polymerize One." Please take a look. [Contents] ■ Introduction ■ Importance and Challenges of Data in MI Utilization ■ Data Strategies to Overcome Data Shortages ■ Challenges in New Material Development and Polymerize's Solution "Polymerize One" *For more details, please download the PDF or feel free to contact us.

Maxell Corporation, which has developed a variety of products based on batteries and has core technologies in "mixing, applying, and solidifying," faced challenges in utilizing MI with in-house tools while working on improving the efficiency of material development through AI in 2019. They decided to transition to an integrated MI platform, "Polymerize Labs," that can be used by anyone without coding. **Background of MI Implementation** Maxell offers a diverse range of products, with each business division responsible for its own development. Among them, the New Business Headquarters has the mission of creating new businesses by integrating a wide range of technologies without being limited to specific fields. In such an environment, it is challenging to unify data formats and descriptions, so they initially began utilizing the MI platform with two axes: the "Battery Project" and the "Tape Project using Dispersion Coating Technology." **Establishment and Expansion of Utilization Post-Implementation** Currently, the utilization has expanded not only at the Kyoto office but also at the Kawasaki office. At Kawasaki, the focus is primarily on the use of AI for image analysis rather than material composition. *Polymerize also offers services for image analysis using AI.

From the 19th century to the early 20th century, the focus of materials research was on "experimentation." Researchers combined reagents, observed reactions, and recorded results—truly an era of "trial and error." In the latter half of the 20th century, with the advancement of computers, "computational materials science" expanded. In particular, first-principles calculations (DFT: Density Functional Theory) became a significant turning point, enabling the prediction of material properties without conducting experiments by analyzing the movement of electrons based on quantum mechanics. On the other hand, many phenomena were difficult to reproduce with calculations alone, leading to the emergence of combinatorial chemistry in the 1990s, which allowed for the simultaneous synthesis and evaluation of tens of thousands of compounds. Furthermore, cheminformatics developed, digitizing chemical structures and experimental data to predict molecular properties. These movements converged, giving rise to a new research methodology of "exploring new materials by utilizing vast amounts of data." This has become the foundation of modern materials informatics (MI). *For more details, please download the PDF document or feel free to contact us.*