Webinar: Modeling Defects in Solids with DFT, doped and ShakeNBreak
- khollingsworth9
- 6 hours ago
- 3 min read
First-principles simulations of atomic and electronic structure in solids offer a powerful route to predict and understand material properties. This is particularly relevant for point defects, which can dramatically affect material properties yet remain challenging to characterize experimentally.
Recent years have seen significant advances in both computational methodologies and associated toolkits for modeling defect behaviour. In this webinar, we’ll introduce the typical defect modeling workflow using Density Functional Theory (DFT) and explore collaborative efforts that are making defect calculations more robust, reproducible, and efficient.
The webinar will cover the ShakeNBreak approach for navigating complex defect configurational landscapes and identifying ground-state defect structures, as well as doped, a Python package designed for robust and reproducible defect supercell calculations. We’ll also explore the modeling of non-radiative charge capture processes at defects in semiconductors.
Time permitting, we’ll finish with a look at recent efforts to accelerate these workflows using machine-learning approaches—highlighting their exciting potential while also considering current limitations in accuracy and reliability.
What you will learn:
How DFT is used to model point defects in solids
The key steps in a typical computational defect modeling workflow
How ShakeNBreak helps identify ground-state defect structures and navigate complex configurational landscapes
How doped enables robust and reproducible charged-defect supercell calculations
How first-principles methods can model non-radiative charge capture at semiconductor defects
Where machine learning can accelerate defect calculations—and where challenges remain
Who should attend:
This webinar will be valuable for materials scientists, computational chemists, physicists, semiconductor researchers, DFT practitioners, graduate students, and R&D professionals interested in point defects, electronic structure, materials modeling, and computational materials discovery.
Webinar Sessions
Tuesday, September 1st:
Live Q&A
10:00 AM PDT (USA) 1:00 PM EDT (USA)19:00 CEST (EUROPE)
Wednesday, September 2nd:
Live Q&A
07:00 AM PDT (USA) 10:00 AM EDT (USA)16:00 CEST (EUROPE)19:30 IST (INDIA)
Thursday, September 3rd:
Live Q&A
08:00 CEST (EUROPE)11:30 IST (INDIA)14:00 CST (CHINA)15:00 JST (JAPAN)
Note: Please select a day and time that best fits your schedule. This one-hour webinar is offered multiple times to accommodate participants worldwide. Note: All of our scientific webinars are free to attend.
Dr. Seán Kavanagh
Dr. Seán Kavanagh is an Assistant Professor in Simulation of Energy Materials, at the Department of Chemistry in the University of Cambridge. He earned his undergraduate at Trinity College Dublin in his native Ireland, PhD at University College London and Imperial College London, and a Fellowship at the Harvard University Center for the Environment. Seán was awarded the 2024 IOP and APS Computational Physics thesis prizes, the 2025 RSC Energy Sector Thesis Prize and named a 2025 JPhys Energy Emerging Leader. He serves as an Editorial Board Member for Physical Review Materials, an Assessor for Innovate UK and a Modeling & Simulation Steering Group Member at the Henry Royce Institute.
Seán heads the Simulation of Advanced Materials (SAM) lab, studying defects and disorder in materials, including methodological/software developments such as the doped and ShakeNBreak defect modeling toolkits – and machine-learning approaches.
Dr. Shubham Pandey
Dr. Shubham Pandey is a Support and Application Scientist in the support team at Materials Design. Shubham holds a PhD degree in Materials Science and Engineering from the University of Florida. Shubham is an experienced researcher with expertise in density functional theory calculations of materials including metal-organic frameworks, metallic alloys, and inorganic crystals. Shubham also has experience with deep learning for solid-state systems from his postdoctoral research at Colorado School of Mines.
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