シュレーディンガー Official site

• General materials development, machine learning

Presentation of Japanese Language Materials: Target Enablement Service

シュレーディンガー

• General materials development, machine learning

Presentation of Japanese Language Materials: Information on Hit Exploration Services

シュレーディンガー

• Cosmetics, daily necessities, food

Presentation of Materials: Molecular Simulation and Machine Learning for Daily Consumer Goods

シュレーディンガー

• General materials development, machine learning

[Presentation of Materials] Information on Modeling Services

シュレーディンガー

• Semiconductor materials

[Presentation of Materials] A materials research DX tool chosen by leading companies in various industries.

シュレーディンガー

• Polymer materials

[Presentation of Japanese Materials] Enhancing the Precision and Speed of Material Development with High-Performance Computational Tools

シュレーディンガー

• Bio and antibody drug discovery

[Presentation of Japanese Materials] Strengthening Research and Development with Industry-Leading Computational Chemistry Tools

シュレーディンガー

• Formulation

[Presentation of Data] Improvement of Formulation Design Optimization through Coarse-Grained Molecular Simulation

シュレーディンガー

• Organic electronics

Promotion of Organic Electronics Materials Development

シュレーディンガー

• Bio and antibody drug discovery

Utilizing advanced technology to tackle efficient biopharmaceutical design.

シュレーディンガー

• Organic electronics

Utilization of the Schrödinger Platform at Panasonic

シュレーディンガー

• Cosmetics, daily necessities, food

Collection of Japanese Examples: Moisture Absorption Prediction and Its Effects on Amorphous Amylose Starch

シュレーディンガー

• Cosmetics, daily necessities, food

Free Webinar: Cosmetics Development Utilizing Digital Chemistry, February 19

シュレーディンガー

• Cosmetics, daily necessities, food

[Japanese Example] Calculation and Analysis Tool for Environmentally Friendly Cosmetic Formulation Design

シュレーディンガー

• Bio and antibody drug discovery

High-Efficiency Compound Exploration Realized by FEP+

シュレーディンガー

• General materials development, machine learning

Presentation of Case Studies: Machine Learning Force Fields for Material Modeling

シュレーディンガー

• Informatics

Realizing molecular design, prediction, analysis, and collaboration in digital space.

シュレーディンガー

• Battery and energy storage materials

Integrated platform supporting battery material development

シュレーディンガー

• Semiconductor materials

Integrated platform to support the development/analysis of semiconductor-related technologies.

シュレーディンガー

• Organic electronics

[Case Study] Accelerating the Design of Organic EL Materials through Active Learning

シュレーディンガー

• Battery and energy storage materials

[User Case Presentation] Development of Next-Generation Lithium-Ion Batteries

シュレーディンガー

• Bio and antibody drug discovery

Challenging the structural prediction of unstructured epitopes and long CDR H3 loops.

シュレーディンガー

• Bio and antibody drug discovery

[Data] Integrated simulation software for bio and antibody drug discovery.

シュレーディンガー

• Organic electronics

[Case Presentation] Panasonic New Design of Materials for Organic Electronics

シュレーディンガー

• General materials development, machine learning

[Data] Materials Science Reaction Workflow

シュレーディンガー

• Formulation

[Information] Software that promotes the rapid and efficient development of new pharmaceuticals.

シュレーディンガー

• General materials development, machine learning

AI Platform for Materials Informatics [Simplified Version]

シュレーディンガー

• Polymer materials

[Presentation of Japanese Materials] Supporting high-speed and high-precision prediction of physical properties of polymers and resins.

シュレーディンガー

• Polymer materials

Introducing Schrödinger's materials development support products in an easy-to-understand manner.

シュレーディンガー

• General materials development, machine learning

AI platform for materials informatics

シュレーディンガー

• General materials development, machine learning

Case Studies: Machine Learning for Materials Research

シュレーディンガー

• General materials development, machine learning

[Case Study] Machine Learning Enabling Accurate Prediction of Precursor Volatility

シュレーディンガー

• Semiconductor materials

Product Guide Presentation: What High-Speed Molecular Simulation is and How it Accelerates Material Development

シュレーディンガー

• General materials development, machine learning

[Data] Quantum ESPRESSO Interface

シュレーディンガー

• Organic electronics

Presentation of Japanese Materials: Organic Electronics

シュレーディンガー

• General materials development, machine learning

[Presentation of Materials] Machine Learning and Material Property Prediction

シュレーディンガー