Density Functional Tight-Binding Models for Band Structures of Transition-Metal Alloys and Surfaces across the d -Block.
Filippo BalzarettiJohannes VossPublished in: Journal of chemical theory and computation (2024)
First-principles electronic structure simulations are an invaluable tool for understanding chemical bonding and reactions. While machine-learning models such as interatomic potentials significantly accelerate the exploration of potential energy surfaces, electronic structure information is generally lost. Particularly in the field of heterogeneous catalysis, simulated electron band structures provide fundamental insights into catalytic reactivity. This ab initio knowledge is preserved in semiempirical methods such as density functional tight binding (DFTB), which extend the accessible computational length and time scales beyond first-principles approaches. In this paper we present Shell-Optimized Atomic Confinement (SOAC) DFTB electronic-part-only parametrizations for bulk and surface band structures of all d -block transition metals that enable efficient predictions of electronic descriptors for large structures or high-throughput studies on complex systems outside the computational reach of density functional theory.
Keyphrases
- density functional theory
- high resolution
- machine learning
- high throughput
- molecular dynamics
- transition metal
- blood brain barrier
- healthcare
- human health
- biofilm formation
- artificial intelligence
- risk assessment
- dna binding
- mass spectrometry
- big data
- health risk
- transcription factor
- staphylococcus aureus
- heavy metals
- drinking water
- monte carlo
- climate change
- crystal structure