[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.
Schrödinger's advanced physics-based modeling and AI/machine learning software supports the development of a wide range of materials, including polymer materials, batteries, semiconductors, organic electronics, catalysts, pharmaceutical formulations, cosmetics, metals, alloys, and ceramics.
Inquire About This Product
Related Videos
basic information
■Density Functional Theory (DFT) calculations and first-principles calculations for periodic systems for physical property predictions HOMO/LUMO/pKa/solvent effects/IR/Raman/UV-vis/VCD/NMR/oxidation-reduction potential/triplet excited state energy/TADF S1-Tx gap/fluorescence/phosphorescence/vibrational calculations/structure optimization/transition state calculations/reaction pathway analysis/adsorption energy/bond dissociation energy/electron and hole mobility/reorientation (rearrangement, reconfiguration) energy ■Molecular Mechanics (MM) method, Molecular Dynamics (MD) method, and coarse-grained MD for physical property predictions Density/conformation analysis/cross-linked structures/Young's modulus/viscosity/surface tension/glass transition temperature (Tg)/molecular diffusion/thermal expansion/crystal morphology/swelling/stress-strain curves/solubility parameters Methods applicable in machine learning Various descriptor and fingerprint generation/Partial Least Squares (PLS) regression/multiple linear regression (MLR)/Principal Component Regression (PCR)/Kernel PLS/Bayesian classification/Recursive Partitioning (RP) analysis/Self-Organizing Maps/Tg, dielectric constant, boiling point, vapor pressure prediction models/genetic algorithms/active learning *For more details, please feel free to contact us.
Price information
For more details, please feel free to contact us.
Delivery Time
Applications/Examples of results
For more details, please feel free to contact us.
catalog（9）
Download All Catalogs![[Data] Advanced physics-based modeling and AI/machine learning software for materials science.](https://image.mono.ipros.com/public/catalog/image/01/e1b/804379/IPROS7318253104951331547.jpeg?w=120&h=170)
![[Japanese Brochure] An Integrated Platform Supporting the Development/Analysis of Semiconductors and Related Technologies](https://image.mono.ipros.com/public/catalog/image/01/b0c/665711/IPROS16028080638677669657.jpeg?w=120&h=170)
![[Japanese Brochure] Integrated Platform Supporting Battery Material Development](https://image.mono.ipros.com/public/catalog/image/01/34a/682443/IPROS10537371865136302010.jpeg?w=120&h=170)
![[Case Study] Machine Learning Force Fields for Material Modeling](https://image.mono.ipros.com/public/catalog/image/01/230/711096/IPROS94455029402092934503.jpeg?w=120&h=170)
Company information
Schrödinger Co., Ltd. is the Japanese subsidiary of Schrödinger Inc., headquartered in New York, USA. Schrödinger has a history of about 30 years in developing software that integrates advanced technologies in chemistry and computer science, primarily in the fields of materials science and life sciences, providing advanced solutions for drug discovery, biologics, and materials research and development.