材料開発全般、機械学習
材料開発全般、機械学習
シュレーディンガーのマテルアルズ・サイエンス ソリューション(MSS)は、幅広い材料研究分野への対応が可能です。
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Introducing Schrödinger's materials development support products in an easy-to-understand manner.
Support for property prediction, analysis, and design based on molecular structure and nanoscale structure through large-scale statistical analysis of experimental data and high-precision nanoscale simulations.
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AI Platform for Materials Informatics [Simplified Version]
Instant answers to your materials informatics concerns! The evolved AI platform LiveDesign accelerates new material development.
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[Presentation of Japanese Materials] Supporting high-speed and high-precision prediction of physical properties of polymers and resins.
A GPU-assisted high-speed molecular dynamics engine that supports the rapid and high-precision prediction of physical property values of polymers and resins.
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Integrated platform to support the development/analysis of semiconductor-related technologies.
An integrated platform that supports the development/analysis of semiconductors and related technologies with high speed and high precision.
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Integrated platform supporting battery material development
Accelerating research and development of next-generation battery materials through atomic-level simulations and machine learning.
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[Case Presentation] Panasonic New Design of Materials for Organic Electronics
Panasonic and Schrödinger have designed over 50 new molecules that improve hole mobility.
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[Data] Materials Science Reaction Workflow
It can cover often overlooked conformers, streamline workflows, and enhance reproducibility and predictability.
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[Information] Software that promotes the rapid and efficient development of new pharmaceuticals.
We promote the rapid and efficient development of new drugs through physics-based modeling and simulation, along with automated workflow solutions.
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AI platform for materials informatics
A quick solution to your materials informatics problems! The evolved AI platform LiveDesign accelerates new material development.
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Product Guide Presentation: What High-Speed Molecular Simulation is and How it Accelerates Material Development
Supporting material research and development through high-speed molecular simulations! Here is an overview of our products.
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Case Studies: Machine Learning for Materials Research
Case studies on inorganic solids and polymers! Designing new compounds in a cost-effective and time-efficient manner.
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[Case Study] Machine Learning Enabling Accurate Prediction of Precursor Volatility
Predict the evaporation or sublimation temperature with an accuracy of ±9°C on average, calculating hundreds of complexes per second.
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[Presentation of Materials] Machine Learning and Material Property Prediction
Quickly transform data into knowledge based on informatics! Contributing to the field of advanced materials development.
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Presentation of Japanese Materials: Organic Electronics
Identifying promising candidate substances! Useful for selecting compounds that meet the conditions for device optimization.
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[Case Study] Accelerating the Design of Organic EL Materials through Active Learning
High efficiency and cost performance! An active learning workflow that utilizes the synergy of physics-based simulations and machine learning for predicting optoelectronic properties.
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[Data] Quantum ESPRESSO Interface
By performing it on a single graphical interface, calculations can be done efficiently!
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[User Case Presentation] Development of Next-Generation Lithium-Ion Batteries
We will introduce a case of innovative material search implemented in the development of next-generation lithium-ion batteries by the CEO of Eonix.
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Presentation of Case Studies: Machine Learning Force Fields for Material Modeling
Introduction of use cases for machine-learned force fields.
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[Japanese Example] Calculation and Analysis Tool for Environmentally Friendly Cosmetic Formulation Design
[L'Oréal Case] Molecular Dynamics and Coarse-Grained Simulations to Facilitate the Formulation Design of Eco-Friendly Cosmetics
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Free Webinar: Cosmetics Development Utilizing Digital Chemistry, February 19
Physics-based simulation and machine learning software for a wide range of users, from beginners to experts in computational chemistry.
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Collection of Japanese Examples: Moisture Absorption Prediction and Its Effects on Amorphous Amylose Starch
Molecular dynamics simulations that promote the optimization of quality and processing in food and beverages, packaging, and pharmaceuticals.
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Utilization of the Schrödinger Platform at Panasonic
Towards the realization of faster new material development.
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Promotion of Organic Electronics Materials Development
Efficient development of organic electronics materials using the integrated platform Materials Science Suite.
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[Presentation of Japanese Materials] Enhancing the Precision and Speed of Material Development with High-Performance Computational Tools
[Japanese Flyer] Overview of Schrödinger's Materials Science Platform
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[Presentation of Materials] A materials research DX tool chosen by leading companies in various industries.
Leading companies in various industries, such as Panasonic, Bridgestone, Canon, Samsung, and L'Oréal, have adopted it.
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[Presentation of Materials] Information on Modeling Services
We provide advanced technology and expertise to accelerate drug discovery programs.
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Presentation of Materials: Molecular Simulation and Machine Learning for Daily Consumer Goods
Physics-based simulation and machine learning software for a wide range of users, from beginners to experts in computational chemistry.
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Presentation of Japanese Language Materials: Information on Hit Exploration Services
Quickly achieve diverse hits with industry-leading calculation tools.
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Presentation of Japanese Language Materials: Target Enablement Service
Optimize the structure of the target protein for structure-based drug discovery using a series of ligand information.
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