We present an optimization strategy for atom-specific spin-polarization constants within the spin-polarized GFN2-xTB framework, aiming to enhance the accuracy of molecular simulations. We compare a sequential and global optimization of spin parameters for hydrogen, carbon, nitrogen, oxygen, and fluorine. Sensitivity analysis using Sobol indices guides the identification of the most influential parameters for a given reference dataset, allowing for a nuanced understanding of their impact on diverse molecular properties. In the case of the W4-11 dataset, substantial error reduction was achieved, demonstrating the potential of the optimization. Transferability of the optimized spin-polarization constants over different properties, however, is limited, as we demonstrate by applying the optimized parameters on a set of singlet-triplet gaps in carbenes. Further studies on ionization potentials and electron affinities highlight some inherent limitations of current extended tight-binding methods that can not be resolved by simple parameter optimization. We conclude that the significantly improved accuracy strongly encourages the present re-optimization of the spin-polarization constants, whereas the limited transferability motivates a property-specific optimization strategy.
Department of Chemistry, Karmanos Cancer Institute (KCI), Integrative Biosciences (Ibio), Wayne State University, Detroit, Michigan 48202, United States.
NMR hyperpolarization dramatically improves the detection sensitivity of magnetic resonance through the increase in nuclear spin polarization. Because of the sensitivity increase by several orders of magnitude, additional applications have been unlocked, including imaging of gases in physiologically relevant conditions. Hyperpolarized Xe gas recently received FDA approval as the first inhalable gaseous MRI contrast agent for clinical functional lung imaging of a wide range of pulmonary diseases.
The cluster-based Mean Field method (cMF) and it is second order perturbative correction was introduced by Jiménez-Hoyos and Scuseria to reduce the cost of modeling strongly correlated systems by dividing an active space up into small clusters, which are individually solved in the mean-field presence of each other. In that work, clusters with unpaired electrons are treated by allowing the α and β orbitals to spin polarize. While that provided significant energetic stabilization, the resulting cMF wave function was spin-contaminated, making it difficult to use as a reference state for spin-pure post-cMF methods.
Regulating the spin states in transition-metal (TM)-based single-atom catalysts (SACs), such as the TM-NC configurations, is crucial for improving the catalytic activity. However, the role of spin in single Ni atoms facilitating the electrochemical CO reduction reaction (CORR) has been largely overlooked. Using first-principles simulations, we investigated the electrocatalytic performance of Ni-N-C SACs vertically stacked on the O-terminated MXene nanosheets for the CORR.
We present an optimization strategy for atom-specific spin-polarization constants within the spin-polarized GFN2-xTB framework, aiming to enhance the accuracy of molecular simulations. We compare a sequential and global optimization of spin parameters for hydrogen, carbon, nitrogen, oxygen, and fluorine. Sensitivity analysis using Sobol indices guides the identification of the most influential parameters for a given reference dataset, allowing for a nuanced understanding of their impact on diverse molecular properties.
Actinide +IV complexes with six nitrates [An(NO)] (An = Th, U, Np, and Pu) have been studied by N and O NMR spectroscopy in solution and first-principles calculations. Magnetic susceptibilities were evaluated experimentally using the Evans method and are in good agreement with the ab initio values. The evolution in the series of the crystal field parameters deduced from ab initio calculations is discussed.
