Courses

Course Introduction: Computational Organic Optoelectronics (Fall 2025)

Organic optoelectronics is a rapidly evolving field that bridges chemistry, physics, and engineering to develop innovative electronic and photonic devices based on organic materials. This course, Computational Organic Optoelectronics, focuses on the theoretical and computational techniques used to analyze and optimize the performance of organic semiconductors and optoelectronic devices.

Students will explore quantum mechanical modeling, Density Functional Theory (DFT), Molecular Dynamics (MD), and other computational methods to investigate the electronic structure, charge transport, and optical properties of organic materials. The course will also cover the design and simulation of organic optoelectronic devices such as organic solar cells, light-emitting diodes (OLEDs), photodetectors, and optical amplifiers.

By integrating fundamental concepts with hands-on computational simulations, students will develop a deep understanding of organic optoelectronic materials and their applications in next-generation technologies. This course is ideal for students pursuing careers in photonics, materials science, nanotechnology, and computational physics.

Course Contents

Part 1: Introduction to Computational Organic Optoelectronics

1. Introduction to Organic Optoelectronics

1. • Definition and scope of organic optoelectronics

   • Key applications (e.g., OLEDs, organic photovoltaics, organic photodetectors)

   • Advantages and challenges compared to inorganic optoelectronics

2. Computational Methods in Organic Optoelectronics

2. • Overview of computational techniques (DFT, molecular dynamics, device simulations)

   • Role of simulations in understanding and designing organic optoelectronic devices

   • Introduction to Python for scientific computing

3. Setting Up the Computational Environment

3. • Installing and configuring Python, DFT software (e.g., Quantum ESPRESSO, VASP), and gpvdm

   • Overview of Python libraries for computational science (NumPy, SciPy, Matplotlib, ASE)

Part 2: Fundamentals of Organic Optoelectronics

4. Materials in Organic Optoelectronics

4. • Conjugated polymers and small molecules

   • Charge transport mechanisms in organic materials

   • Python example: Simulating molecular structures using RDKit

5. Optoelectronic Properties of Organic Materials

5. • Absorption and emission spectra

   • Exciton dynamics and energy transfer

   • Python example: Calculating optical properties from experimental data

6. Device Physics of Organic Optoelectronics

6. • Working principles of organic devices (OLEDs, OPVs, organic photodetectors)

   • Charge injection, transport, and recombination

   • Python example: Modeling current-voltage characteristics

Part 3: Computational Techniques and Simulations

7. Density Functional Theory (DFT) for Organic Materials

7. • Basics of DFT and its application to organic materials

   • Calculating electronic structure, band gaps, and optical properties

   • Python example: Using ASE (Atomic Simulation Environment) for DFT calculations

8. Molecular Dynamics Simulations

8. • Simulating molecular motion and interactions

   • Applications in understanding material stability and morphology

   • Python example: Running molecular dynamics simulations with LAMMPS or GROMACS

9. Device Simulations with gpvdm

9. • Introduction to gpvdm for simulating organic optoelectronic devices

   • Modeling OLEDs, OPVs, and organic photodetectors

   • Python example: Automating gpvdm simulations and analyzing results

Part 4: Advanced Topics and Applications

10. Nanostructured Organic Optoelectronics

10. • Role of nanostructures in enhancing device performance

    • Python example: Simulating nanostructured materials using DFT and gpvdm

11. Machine Learning in Organic Optoelectronics

11. • Introduction to machine learning for material discovery and device optimization

    • Python libraries (Scikit-learn, TensorFlow, PyTorch)

    • Case study: Predicting material properties using ML

12. Sustainability and Recycling in Organic Optoelectronics

12. • Environmental impact of organic optoelectronics

    • Strategies for sustainable production and recycling

    • Python example: Life cycle analysis of organic devices

Part 5: Hands-On Projects

13. Project 1: Designing an OLED

13. • Material selection and device simulation

    • Python example: Optimizing OLED efficiency using gpvdm

14. Project 2: Building a Simple Organic Solar Cell Model

14. • Components and assembly

    • Python example: Analyzing solar cell performance with gpvdm

15. Project 3: Simulating an Organic Photodetector

15. • Modeling photodetector response to different light conditions

    • Python example: Visualizing photodetector data

Reference Books

• Ostroverkhova, Oksana, ed. Handbook of organic materials for optical and (opto) electronic devices: properties and applications, Elsevier, 2013.

• Adrian Kitai, Principles of Solar Cells, LEDs and Diodes: The role of the PN junction, John Wiley, 2011.

• Köhler, Anna, and Heinz Bässler. Electronic processes in organic semiconductors: An introduction. John Wiley & Sons, 2015.

• Nisato, Giovanni, Donald Lupo, and Simone Ganz, eds. Organic and Printed Electronics: Fundamentals and Applications. CRC Press, 2016 

Instructor Biography

Prof. Dr. Muhammad Hassan Sayyad possesses wide multidisciplinary experience of (1) teaching physics, electronics, lasers, optics and Photonics at Bachelor, Master and PhD students, (2) research supervision to BS, MS/M.Phil and PhD students at the Government College University Lahore and the GIK Institute of Engineering Science and Technology. He has published 100 plus research articles, supervised 100 plus BS, MS and PhD students in research.

He has been honored with the Pak-US and Pak-China research projects, focusing on advancing next-generation solar cell technologies, and has served as a visiting scientist in prestigious universities in the United States, China, and Malaysia.

To see the Instructor CV, please click the following link:

https://sites.google.com/view/drmhsayyad/home