Jaguar for Materials Science

Quantum mechanics solution for rapid and accurate prediction of molecular structures and properties

Jaguar for Materials Science

Structure prediction of molecular systems at unmatched speed

Jaguar is a well-validated, robust, high-performance quantum mechanics package that specializes in fast predictions of electronic structure and properties for molecular systems of all sizes via the use of pseudospectral density functional theory (PS-DFT) based method which scales favorably with system size.

Jaguar can also be used for the ab initio-assisted design and high throughput virtual screening of new materials solutions with novel or enhanced properties for a variety of applications such as catalysts, batteries, organic electronics, and more.

Key Capabilities

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Perform a wide range of QM calculations

Including geometry optimization, transition state search, thermo-chemical properties, implicit solvation, spectra prediction, and more

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Access a diversity of DFT functionals

With analytic second derivatives and dispersion corrections

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Speed up calculations at a negligible loss of accuracy

Using the optional pseudospectral approximation

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Use automated workflows for advanced analysis

Including pKa prediction, conformationally-averaged VCD and ECD spectroscopy, tautomer generation and ranking, heat of formation, etc.

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Generate publication-quality 3D surfaces

Including molecular orbitals, electrostatic potential projected on isodensity, spin density, non-covalent interactions, etc.

Case Studies

Discover how Schrödinger technology is being used to solve real-world research challenges.

Innovation in atomic-level processing with atomistic simulation and machine learning

De Novo design of hole-conducting molecules for organic electronics

Accelerating the design and optimization of OLED materials using active learning

Jaguar Datasheet for Materials Science

Learn more about the technical details of Jaguar and its applications.

Broad applications across materials science research areas

Get more from your ideas by harnessing the power of large-scale chemical exploration and accurate in silico molecular prediction.

Catalysis & Reactivity
Energy Capture & Storage
Organic Electronics

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Atomistic simulation and analysis of charge mobility in solid-state films of organic semiconductors

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Automatic workflow to calculate dielectric properties and refractive index

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Automatic workflow for accurate prediction of reactivity and catalysis

Publications

Browse the list of peer-reviewed publications using Schrödinger technology in related application areas.

Materials Science
Computational and Machine Learning-Assisted Discovery and Experimental Validation of Conjugated Sulfonamide Cathodes for Lithium-Ion Batteries
Materials Science
Towards long-life 500 Wh kg−1 lithium metal pouch cells via compact ion-pair aggregate electrolytes
Materials Science
Structure of methylaluminoxane (MAO): Extractable [Al(CH3)2]+ for precatalyst activation
Materials Science
Modified t-butyl in tetradentate platinum (II) complexes enables exceptional lifetime for blue-phosphorescent organic light-emitting diodes
Materials Science
Calculating Apparent pKa Values of Ionizable Lipids in Lipid Nanoparticles
Materials Science
Understanding of complex spin up-conversion processes in charge-transfer-type organic molecules
Materials Science
Highly efficient implementation of analytic nonadiabatic derivative couplings within the pseudospectral method
Materials Science
Insights into the binding mechanism of 2,5-substituted 4-pyrone derivatives as therapeutic agents for fused dimeric interactions: A computational study using QTAIM, dynamics and docking simulations of protein–ligand complexes
Materials Science
Self-Assembled Tamoxifen-Selective Fluorescent Nanomaterials Driven by Molecular Structural Similarity
Materials Science
Tuning the Mobility of Indacenodithiophene-Based Conjugated Polymers via Coplanar Backbone Engineering

Training & Resources

Online certification courses

Level up your skill set with hands-on, online molecular modeling courses. These self-paced courses cover a range of scientific topics and include access to Schrödinger software and support.

Tutorials

Learn how to deploy the technology and best practices of Schrödinger software for your project success. Find training resources, tutorials, quick start guides, videos, and more.