We have always had the belief that scripted workflows, in combination with a vast modeling library, could assist teachers and students in grasping concepts more quickly and more effectively. This is done by having access to the latest tools in computational chemistry. Imagine that an undergraduate can operate the same professional software as a researcher in a pharmaceutical company.
For professors that have bought a research license of CULGI, all licenses for teaching are free, including free licenses for home PC’s of students. A teaching license is a fully functional package.
Working with CULGI in an academic setting usually has four steps. If you would like to know more per step, please follow the link per step.
Try Culgi for free
If you are an academic from a government sponsored research institute or university, you are eligible for a free trial license. License for students in class is free, also for home PC.
Notice that we only accept requests from tenured professors.
If you are a student or post-doc, consult with your supervisor.
Step 1 – creating Workflows
Typically, undergraduate chemistry students have not been exposed to programming before. While in a traditional curriculum this is not a problem, one needs to anticipate the modern digitalization of chemical R&D, which is full of workflows and programming. Our CULGI Graphical Programming Environment is an excellent tool to learn the first steps in programming, while from the start working on a significant chemical problem. The course starts from a humble beginning that includes teaching the distinction between hardware and software, to the first steps in writing a series of commands in a workflow, until they can make a 30-40 line workflow for building a lipids bilayer.
CULGI script is a meta-language, with simple syntax and commands suitable for chemistry. The organization is through objects (molecules, calculation methods, etc.), with properties. A very sophisticated aspect is that students do not need to type in commands explicitly, but instead drag-and-drop commands to a central canvas. Also, the interface is intelligent enough to capture logical errors interactively. Help is integrated with the software.
The depicted example is a script for showing ethanol on screen. Of course, one could have done this by pressing a few buttons in a graphical modeling interface. There are many such interfaces available (in our software too). But it is so much better as a learning experience to write a script for that!
Step 2 – Make it Your Own
Instead of a pre-determined one-possible-answer hand-written exercise, as typical in old-style-curriculum, the students develop an electronic workflow as their own individual solution to a challenge. As a result, students have the feeling, sometimes for the first time in their career, that they have created something that is their own.
We have found this aspect the most valuable part of teaching through workflows. Instead of top-down imposing, the student learns bottom-up, and will not forget quickly what new concepts he or she has learned.
The enclosed workflow is a few ten lines for making a lipid bilayer. Undergraduate students learn to make the script in six sessions of each one day. The calculation takes ten minutes on a common PC, more than fast enough for a task in a practical course or home-exercise.
As the course advances, students learn to think about chemistry (what if one adds lipids with three tails?), theory and algorithms (can one write a script that speeds up the bilayer formation?), visualisation (how to make it really nice), and biology (what would happen if one adds proteins).
Step 3 – Increase complexity
In a traditional undergraduate theoretical curriculum, courses quickly specialize in a plethora of topics, such as statistical thermodynamics (physics and chemistry departments), quantum chemistry and molecular modeling (chemistry), chemical informatics (pharmaceutical department), thermodynamics (chemical engineering), and so forth. But real research in industry is about integration and collaboration, not about the dissection of methods. The artificial division is also no longer necessary. CULGI includes all modern computational chemistry. In a single undergraduate course, the student could just as easily write a workflow for calculation of molecular orbitals, a workflow for molecular modeling, chemical QSAR, or engineering thermodynamics; or any a combination.
The depicted example is from our Automated Fragmentation and Parameterization Scripts, which handle all scales simultaneously. The script is perhaps too difficult for undergraduates but easy enough for graduates and post-docs. Such advanced workflow can contain hundreds of lines of code. The scripts are also available in python, as shown.
STEP 4 – EXERCISE and EXAM
In old-style curriculum, in a theory class, a teacher poses a set of questions, and a student returns hand-written answers, as home-exercise and also at the exam.
In the new-style scripted workflow class, the student develops a workflow as a small CULGI script, that is validated by the teacher on logic and outcome.
Moreover, CULGI is easy to install, and for students working at home, free. This means that students can also do their home-exercises at their own pace, and simply send the workflow electronically to the teacher for review.
We have found that students quickly get addicted to writing workflows. They are proud to find original solutions, and they really enjoy being part of a professional community.
Get a COURSE
We have been using CULGI in undergraduate teaching for more than ten years. We have an extensive suite of theoretical introductory readers, workflows, exam questions, and take-home exercises that we can share with you. The course is suitable for undergraduate and graduate teaching. If you are interested, to receive a copy, please send us an email.
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