Practical Materials Informatics: Designing Molecules, Formulations, and Devices
Practical Materials Informatics: Designing Molecules, Formulations, and Devices
Details
Available Languages
Chinese, English, Japanese, Korean
Duration
4 weeks / ~15 hours to complete
Level
Introductory
Cost
$600 for non-student users
$160 for student / post-doc
Course Timeframe
When registering for the course, you will be able to choose your preferred start and end date. Within those dates, you will have asynchronous access to the course to work on your preferred schedule
Overview
Materials informatics brings machine learning to every stage of materials and device design, from predicting a single molecule’s properties to optimizing multi-component formulations to guiding device-level performance. This course teaches you to build and apply Machine Learning (ML) models using Schrödinger’s Materials Science Maestro (MS Maestro) interface, with no coding required.
You’ll work hands-on with real property-prediction datasets spanning small organic and organometallic molecules, ionic liquids, catalysts, polymers, inorganic solids, and formulated products. Then, you will extend that workflow to device design. By the end of the course, you will independently build, evaluate and apply ML models for a real-world design problem.
This materials informatics course offers an effective and efficient approach to learn practical data-driven workflows for materials science:
- Work hands-on with Schrödinger’s industry-leading MS Maestro software
- Jump start your research program by learning methods that can be directly applied to ongoing projects
- Perform a completely independent case study to demonstrate mastery of the course content
- Benefit from review and feedback from Schrödinger Education Team experts for course assignments and course-related queries
- Work on the course materials on your own schedule whenever convenient for you
This course comes with access to a web-based version of Schrödinger software with the necessary licenses and compute resources for the course:
Requirements
- Working knowledge of general chemistry
- No coding or machine learning background required – all workflows are conducted through the MS Maestro graphical interface
- A computer with reliable high speed internet access (8 Mbps or better)
- A mouse and/or external monitor (recommended but not required)
Certification
- A certificate signed by the Schrödinger course lead
- A badge that can be posted to social media, such as LinkedIn
What you will learn
The basics of materials informatics & the MS Maestro interface
Learn the basics of materials informatics and how to use an industry-leading interface for data-driven materials science modeling. No coding or scripting required to run modeling workflows
Molecule-to-material property prediction
Learn how to build, train, validate, and apply models for structure-property relationships across diverse chemistries and applications
Formulation informatics
Learn how to build, train, validate and apply models for formulation-property relationships of multi-component mixtures across diverse chemistries and applications
Device-level informatics
Learn how to build, train, validate and apply models for device-property relationships of layered devices with a focus on organic light-emitting diodes (OLEDs) devices
Modules
Module 1
2 Hours
Introduction to materials informatics
Video
Introduction to materials informatics
Video tutorial
Introduction to materials science (MS) Maestro
Honor code agreement and checkpoint
Module 2
4 Hours + Compute Time
Predicting properties: From molecules to materials
Video
Introduction to structure-property relationships
Tutorials
- Machine learning property prediction
- Machine learning for singlet-triplet-gap of TADF molecules
- Machine learning for ionic conductivity of ionic liquids
- Machine learning for glass transition temperature of polymers
- Machine learning for bulk modulus of inorganic solids
- Machine learning for sweetness of small organic molecules
- Machine learning for reaction rate constants of homogeneous catalysts
- Machine learning for viscosity of organic liquids
End of module checkpoint
Module 3
4 Hours + Compute Time
Formulation informatics & design
Video
Introduction to formulation machine learning
Tutorials
- Formulation ML for compressive strength of concrete geopolymers
- Formulation ML for glass transition temperature of copolymers
- Formulation ML for motor octane number of oil and gas hydrocarbons
- Formulation ML for selectivity of heterogeneous catalysts in methanol dehydrogenation
- Formulation ML for temperature-dependent drug solubility
- Formulation ML for temperature-dependent solvent viscosity
- Formulation ML for viscosity of shampoo
End of module checkpoint
Module 4
2 Hours + Compute Time
Device-level informatics: OLED applications
Video
Introduction to machine learning for OLED devices
Tutorials
- Machine learning for OLED device design
- Optoelectronics device designer
End of module checkpoint
Module 5
3 Hours + Compute Time
Independent case study
Assignment A
Developing a QSAR Model for Aqueous Solubility
Assignment B
Optimizing the Solubility and Cost of Drug-Solvent Formulations
Assignment C
Designing an OLED Device with a Target Emission Color
End of module checkpoint
Self-paced video lessons on materials modeling
Videos on practical theory break down complex scientific concepts (e.g. Molecular Quantum Mechanics)
Access cloud-based computing resources to perform calculations yourself
Hands-on step-by-step tutorials (e.g. Pharmaceutical Formulations course, pKa prediction)
Hands-on modeling in the web-based graphical user interface (e.g. Polymeric Materials course, Diffusion tutorial)
Videos on practical theory break down complex scientific concepts (e.g. Molecular Dynamics)
On-demand video lessons on materials modeling
Access cloud-based computing resources to perform calculations yourself
Perform case studies with expert feedback (e.g. Organic Electronic Course, Independent Case Study)
Video on practical theory break down complex scientific concepts (e.g. Machine Learning for Chemistry)
Videos on practical theory break down complex scientific concepts (e.g. Periodic Quantum Mechanics)
Videos on practical theory break down complex scientific concepts (e.g. Coarse-Graining)
Need help obtaining funding for a Schrödinger Online Course?
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Show off your newly acquired skills with a course badge and certificate
When you complete a course with us in molecular modeling and are ready to share what you learned with your colleagues and employers, you can share your certificate and badge on your LinkedIn profile.
Frequently asked questions
How much does the Practical Materials Informatics: Designing Molecules, Formulations, and Devices online course cost?
Pricing varies by each course and by the participant type. For students wishing to take this, we offer a student price of $160, and $600 for non-students.
What time are the lectures?
Once the course session begins, all lectures are asynchronous and you can view the self-paced videos, tutorials, and assignments at your convenience. When registering for the course you will select the start and end date. Within those dates, you will have asynchronous, on-demand access to the course material and virtual workstation to work on the course when it best suits your schedule.
What time are the lectures?
Once the course session begins, all lectures are asynchronous and you can view the self-paced videos, tutorials, and assignments at your convenience.
How could I pay for this course?
Interested participants can pay for the course by completing their registration and using the credit card portal for an instant sign up. Please note that a credit card is required as we do not accept debit cards. Additionally, we can provide a purchase order upon request, please email online-learning@schrodinger.com if you are interested in this option. If you have any questions regarding how to pay for the course, please visit our funding options page.
Are there any scholarship opportunities available for students?
Schrödinger is committed to supporting students with limited resources. Schrödinger’s mission is to improve human health and quality of life by transforming the way therapeutics and materials are discovered. Schrödinger proudly supports the next generation of scientists. We have created a scholarship program that is open to full-time students or post-docs to students who can demonstrate financial need, and have a statement of support from the academic advisor. Please complete the application form if you qualify for our scholarship program!
Will material still be available after a course ends?
While access to the software will end when the course closes, some of the material within the course (slides, papers, and tutorials) are available for download so that you can refer back to it after the course. Other materials, such as videos, quizzes, and access to the software, will only be available for the duration of the course.
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