Semiempirical Methods for Molecular Systems in Strong Magnetic Fields.

Area of Science:

• Computational Chemistry
• Quantum Chemistry
• Theoretical Chemistry

Background:

• Semiempirical methods offer computational efficiency but often struggle to accurately incorporate magnetic field effects.
• Accurate simulation of molecular systems in magnetic fields is crucial for understanding phenomena in diverse fields, from materials science to astrochemistry.
• Existing methods for calculating magnetic field effects can be computationally prohibitive for large systems.

Purpose of the Study:

• To develop a computationally efficient general scheme for extending semiempirical methods to include arbitrary strength magnetic fields.
• To adapt the density-functional tight-binding method GFN1-xTB to accurately model magnetic field interactions.
• To provide a tool for studying the structure, conformation, and dynamics of large systems in magnetic fields.

Main Methods:

• Introduction of a London atomic orbital (LAO) basis set.
• Inclusion of field-dependent kinetic energy corrections to the model Hamiltonian.
• Incorporation of spin-Zeeman interaction energy terms.
• Development of two variants: GFN1-xTB-M0 (single-basis) and GFN1-xTB-M1 (dual-basis).

Main Results:

• The GFN1-xTB-M1 approach accurately predicts magnetizabilities and nuclear magnetic resonance shielding constants even for strong magnetic fields.
• Exotic magnetic phenomena, such as the para- to diamagnetic transition in BH and preferred orientations of benzene, were reproduced.
• Conformer searches for cyclooctatetraene demonstrated GFN1-xTB-M1's ability to capture field-induced conformational changes, consistent with more demanding methods.
• Magnetically induced currents in benzene and infinitene were well described, highlighting the method's flexibility and efficiency.

Conclusions:

• The GFN1-xTB-M1 method provides a computationally efficient and accurate way to study molecular systems in magnetic fields at the semiempirical level.
• This approach is valuable for preoptimization in ab initio calculations, enabling efficient exploration of complex potential energy surfaces and reactivity.
• GFN1-xTB-M1 offers a practical tool for investigating large systems under external magnetic field conditions.