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soft(Materials) - List of Manufacturers, Suppliers, Companies and Products | IPROS GMS

Last Updated： Aggregation Period:Sep 16, 2026～Oct 13, 2026
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soft Product List

91～105 item / All 105 items

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Semiconductor Material Development Analysis Software 'Materials Studio'

Semiconductor Material Development Analysis Software 'Materials Studio'

Effective materials development simulation software for "Materials Informatics" - 'Materials Studio'

By utilizing tools and collaborating, we can contribute to new material development more efficiently and easily. ■ Ideal for "Materials Informatics" This is a group of molecular modeling/simulation tools for next-generation material development equipped with quantum mechanics, classical mechanics, mesoscale, statistics, and analysis/crystallization tools. 【Features】 ■ Simulation software that streamlines material development It can be used by those engaged in research, development, design, and manufacturing across various industries. ■ Supports various types of materials ■ All tasks, including crystal structure creation, calculation condition settings, and calculation result display, can be performed on a single GUI screen. 【Examples】 Tribochemical (lubrication) reactions Analysis of CFRP (carbon-based materials) Crystal growth, thin film formation, fuel cells, lubricants, catalysts, polymers, mixtures, metals and alloys, batteries, and fuel cells, etc. *For more details, please feel free to contact us. Wavefront Co., Ltd. Sales Department MAIL: sales@wavefront.co.jp URL: http://www.wavefront.co.jp/

  • others
  • plastic
  • Other metal materials
  • soft

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AI Platform for Materials Informatics [Simplified Version]

AI Platform for Materials Informatics [Simplified Version]

Instant answers to your materials informatics concerns! The evolved AI platform LiveDesign accelerates new material development.

Do you have any of the following concerns in materials informatics? Schrödinger's LiveDesign solves these issues and accelerates MI, from data recording, completion, automation of machine learning, to sharing analytical methods and results. 【Concern 1】 Data quality issues: Formats and terminology are inconsistent ➡ We register data in a unified language in the same spreadsheet. 【Concern 2】 Data quantity issues: The data is full of missing values ➡ We complete the data using physical chemistry calculations and machine learning. 【Concern 3】 Undemocratic AI, machine learning, and analytical methods: Not knowing where to start ➡ We automatically generate suitable machine learning models while accumulating data, creating high-precision models without relying on computational chemists. 【Concern 4】 Internal sharing issues: A good predictive model has been created, but there is no mechanism to deploy it internally ➡ Analytical methods and results can be shared within a group via a web interface. *For more details, please feel free to contact us.

  • Embedded OS
  • soft

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