[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
Schrödinger provides a software platform for innovation in the development of diverse materials, including polymer materials, organic electronics, catalysis and reactivity, thin film processes, energy recovery and storage, pharmaceutical formulations, consumer goods, metals, alloys, and ceramics. By exploring vast compound spaces and predicting molecular properties with high precision, it supports the rapid design of new materials and enhances cost efficiency. This document provides an overview of the platform for materials development. *For more details, please feel free to contact us.*
basic information
Our Materials Science Suite is capable of addressing a wide range of materials research fields. ■ Property predictions using Density Functional Theory (DFT) calculations and first-principles calculations for periodic systems 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 ■ Property predictions using Molecular Mechanics (MM) methods, Molecular Dynamics (MD) methods, and coarse-grained MD Density/conformation analysis/crosslinked structures/Young's modulus/viscosity/surface tension/glass transition temperature (Tg)/molecular diffusion/thermal expansion/crystal morphology/swelling/stress-strain curves/solubility parameters Methods available for use in machine learning Generation of various descriptors and fingerprints/Partial Least Squares (PLS) method/multiple linear regression (MLR)/Principal Component Regression (PCR)/Kernel PLS method/Bayesian classification/Recursive Partitioning (RP) analysis/Self-Organizing Maps/Tg, dielectric constant, boiling point, vapor pressure prediction models/genetic algorithms/active learning
Price information
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Applications/Examples of results
For more details, please refer to the PDF document or feel free to contact us.
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