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Methodology
Formulation ML and Optimization: Making advanced property prediction and experimental design fast and accessible Webinar Materials Science
  • Apr 22, 2026
Formulation ML and Optimization: Making advanced property prediction and experimental design fast and accessible

Join our upcoming webinar to learn how your R&D organization can remove adoption barriers, accelerate discovery cycles, and align with national AI initiatives.

Accessible and automated computational catalyst discovery and reactivity optimization Webinar Materials Science
  • May 7, 2026
Accessible and automated computational catalyst discovery and reactivity optimization

In this webinar, we will demonstrate how an end-user physics–AI platform removes barriers to entry, making this process accessible to both experts and non-experts while enabling seamless scalability.

Fast, accurate, and tunable: Advancing battery materials innovation with Schrödinger’s Machine Learning Force Fields Webinar Materials Science
  • May 12, 2026
Fast, accurate, and tunable: Advancing battery materials innovation with Schrödinger’s Machine Learning Force Fields

Join us for live demos showcasing applications of MLFFs for accurate modeling of complex systems including liquid and solid-state electrolytes.

Integrating AI and Machine Learning to Accelerate Composite Resin Formulation Webinar Materials Science
  • May 13, 2026
Integrating AI and Machine Learning to Accelerate Composite Resin Formulation

Schrödinger is excited to be hosting a webinar in collaboration with Composites World, taking place on May 13th at 11:00AM EDT.

Atomic layer deposition: Bridging theory and experiment to design a process for silicon carbonitride Webinar Materials Science
  • Mar 19, 2026
Atomic layer deposition: Bridging theory and experiment to design a process for silicon carbonitride

MAR 19, 2026 | SchrödingerとLam Researchのコラボレーション事例を通じて、計算科学(DFT)と実験(RGA、FTIR)を組み合わせ、最適な前駆体を効率的に選定するアプローチをご紹介します。

The Importance of Human Know-How in AI Execution for Materials R&D Webinar Materials Science
  • Mar 18, 2026
The Importance of Human Know-How in AI Execution for Materials R&D

Join us to explore how Schrödinger’s domain experts integrate these three pillars to streamline material optimization. 

Physics-driven ML to accelerate the design of layered multicomponent electronic devices Webinar Materials Science
  • Feb 10, 2026
Physics-driven ML to accelerate the design of layered multicomponent electronic devices

Schrödinger has developed a machine learning (ML) framework that enables users to predict key performance metrics of multilayered electronic devices from simple, intuitive descriptions of their architecture and operating conditions.

Digital forum on atomic layer deposition: Bridging theory and experiment to design a process for silicon carbonitride Webinar Materials Science
  • Nov 18, 2025
Digital forum on atomic layer deposition: Bridging theory and experiment to design a process for silicon carbonitride

Join us as we discuss how effectively theory and experiment are working together to solve the R&D challenges facing high-tech industries.

Materials Engineering Webinar Materials Science
  • Oct 2, 2025
Accelerating product development with computational materials engineering

Learn how Ansys and Schrödinger are transforming product development with Integrated Computational Materials Engineering (ICME) to accelerate material discovery and innovation.

Advanced-machine-learning-to-accelerate-materials-research_hero Webinar Materials Science
  • Oct 29, 2025
Advancing battery materials innovation using charge-aware machine learning force fields

In this webinar, we will demonstrate how Schrödinger is utilizing an integrated computational approach combining physics-based molecular modeling with machine learning force fields (MLFFs) to address key challenges in battery materials design.

難溶性薬物の放出メカニズムを解明する – ASD研究の新たなアプローチModelling amorphous solid dispersion (ASD) release mechanisms Webinar Materials Science
  • Oct 15, 2025
難溶性薬物の放出メカニズムを解明する – ASD研究の新たなアプローチModelling amorphous solid dispersion (ASD) release mechanisms

AbbVie と Schrödinger のエキスパートが、ASDにおける薬物放出やLoss of Release のメカニズムを、熱力学モデリング・分子シミュレーション・実験研究 を組み合わせた最新の研究成果を基に解説します。

Accelerating Product Development: The Industrial Shift to AI/ML-Driven Formulation Webinar Materials Science
  • Sep 18, 2025
Accelerating Product Development: The Industrial Shift to AI/ML-Driven Formulation

In this discussion, we explore the rapidly evolving role of modeling and machine learning in formulation design; from a supplementary tool to a driving force of innovation.

Events

2026 CMC Conference Event Materials Science
  • Apr 16, 2026
2026 CMC Conference

Schrödinger is excited to be participating in the 2026 CMC Conference conference taking place on April 14th – 16th in Portland, Oregon.

In-Cosmetics Global 2026 Event Materials Science
  • Apr 16, 2026
In-Cosmetics Global 2026

Schrödinger is excited to be participating in the In-Cosmetics Global 2026 conference taking place on April 14th – 16th in Paris, France.

Amplifying medicinal chemist impact with large-scale ideation, FEP+, machine learning, and retrosynthesis through LiveDesign Webinar Life Science
  • Apr 16, 2026
Amplifying medicinal chemist impact with large-scale ideation, FEP+, machine learning, and retrosynthesis through LiveDesign

Join us to see how Schrödinger’s Enterprise Informatics Platform, LiveDesign, serves as the single terminal to bridge this gap.

Webinars

Formulation ML and Optimization: Making advanced property prediction and experimental design fast and accessible Webinar Materials Science
  • Apr 22, 2026
Formulation ML and Optimization: Making advanced property prediction and experimental design fast and accessible

Join our upcoming webinar to learn how your R&D organization can remove adoption barriers, accelerate discovery cycles, and align with national AI initiatives.

Accessible and automated computational catalyst discovery and reactivity optimization Webinar Materials Science
  • May 7, 2026
Accessible and automated computational catalyst discovery and reactivity optimization

In this webinar, we will demonstrate how an end-user physics–AI platform removes barriers to entry, making this process accessible to both experts and non-experts while enabling seamless scalability.

Fast, accurate, and tunable: Advancing battery materials innovation with Schrödinger’s Machine Learning Force Fields Webinar Materials Science
  • May 12, 2026
Fast, accurate, and tunable: Advancing battery materials innovation with Schrödinger’s Machine Learning Force Fields

Join us for live demos showcasing applications of MLFFs for accurate modeling of complex systems including liquid and solid-state electrolytes.

Documentation

  • Documentation
Complex Bilayer Builder Panel

Build single or multi-component lipid membranes with or without an embedded membrane protein.

  • Documentation
Membrane Analysis Panel

Calculate structural properties for a lipid membrane over the selected frames of a trajectory.

  • Documentation
Membrane Analysis Viewer Panel

View plots of the structural properties of a lipid over the course of a molecular dynamics trajectory, generated using the Membrane Analysis panel.

Tutorials

  • Tutorial
Introduction to Materials Science Maestro Tutorial

An introduction to Materials Science Maestro, covering basic navigation, an intro to building models and several of the key functionalities of the graphical user interface.

  • Tutorial
Disordered System Building and Molecular Dynamics Multistage Workflows

Learn to use the Disordered System Builder and Molecular Dynamics Multistage Workflow panels to build and equilibrate model systems.

  • Tutorial
Introduction to Geometry Optimizations, Functionals and Basis Sets

Perform geometry optimizations on simple organic molecules and learn basics regarding functionals and basis sets.

Training Videos

Getting Going with Materials Science Maestro Video Series Video Materials Science
Getting Going with Materials Science Maestro Video Series

A free video series introducing the basics of using Materials Science Maestro.

Schrödinger’s Materials Science Builder Series: Single Complex Builder Video Materials Science
Schrödinger’s Materials Science Builder Series: Single Complex Builder

The video demonstrates how to use the Single Complex Builder panel within Schrödinger’s Materials Science Suite to build organometallic complexes.

Schrödinger’s Materials Science Builder Series: Enumerate Adsorbates Video Materials Science
Schrödinger’s Materials Science Builder Series: Enumerate Adsorbates

The video demonstrates how to use the Enumerate Adsorbates panel within Schrödinger’s Materials Science Suite to build adsorbate structures for when a gas-phase molecule adsorbs on a solid substrate.

Publications

  • Publication
  • Jan 20, 2026
Quantum-Enhanced Neural Exchange-Correlation Functionals

Sokolov, et al. Physical Review A, 2026, 113, 012427

  • Publication
  • Jan 8, 2026
Molecular Dynamics Insights into Ibuprofen Nanocrystal Dissolution Put in the Context of Classical Nucleation Theory

Skrdla, et al. Molecular Pharmaceutics, 2026, 23(2), 1089-1100

  • Publication
  • Jan 1, 2026
Insights into electrolyte reactivity at the Li metal surface from density functional theory

Agarwal, et al. Computational Materials Science, 2026, 261, 114278

Case Studies

Advancing sustainable food processing through integrated experimental and molecular simulation approaches Case Study Materials Science
  • Jul 11, 2025
Advancing sustainable food processing through integrated experimental and molecular simulation approaches

Scientists from Schrödinger and UMass carried out comprehensive studies experimentally and computationally to investigate the key properties and extrusion performance of zein-formulated meat alternatives.

Advancing lipid nanoparticle development with structure-based modeling platform and services Case Study Life Science Materials Science
The Future of Food: Molecular Simulations and AI/ML Reshaping Product Development Case Study Materials Science

White Papers

Quick Reference Sheets

  • Quick Reference Sheet
Clean Up Structures

Get an overview of the Clean Up Structures Panel.

  • Quick Reference Sheet
Materials Science Panel Explorer

Get an overview of the Materials Science Panel Explorer panel for filtering for tools of interest.

  • Quick Reference Sheet
Coarse Grained Mapping

Get an overview of the Coarse Grained Mapping panel for mapping all-atom structures to coarse grained models.

Latest insights from Extrapolations blog

How L’Oreal Uses Digital Simulation to Explore Sustainable Product Ingredients Blog
How L’Oreal Uses Digital Simulation to Explore Sustainable Product Ingredients

Most of us could name at least one cosmetic or personal care product that’s essential to looking and feeling our best. Whether it’s a specific kind of soap, a brand of mascara, the right shade of lipstick or the shampoo that works best for our hair, these products have become a critical part of our daily routine.

Uncovering Better Materials for the Spacecraft of Tomorrow
Uncovering Better Materials for the Spacecraft of Tomorrow

When it comes to solving problems for his job, the work done by Dr. Levi Moore actually is rocket science. As a research chemist with the United States Air Force Research Laboratory, he’s tasked with helping to develop new materials that make it easier and safer to launch rockets into space.

Sustainable Food Packaging Designed at the Atomic Level
Sustainable Food Packaging Designed at the Atomic Level

Each year, an estimated 330 million metric tonnes of plastic are produced globally. A significant portion of that plastic becomes waste, clogging landfills, rivers, and the ocean for centuries, damaging ecosystems and negatively impacting human health.

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.

Free learning resources

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.