Predictive Computational Analysis of Exchange Interactions in Gd3+ Complexes with Biradical Ligands

The development of lanthanide-based molecular magnetic materials incorporating organic radicals requires a fundamental understanding of how ligand modification influences magnetic exchange interactions while preserving the coordination environment around the metal center. In this predictive computational study, the electronic structures and magnetic properties of two hypothetical Gd3+ complexes with donor–acceptor semiquinone–nitronylnitroxide biradicals, Tp2Gd(SQNN) (1) and Tp2Gd(SQPhNN) (2), were investigated using ab initio calculations and compared with the previously characterized monoradical complex Tp2Gd(SQ); Tp is hydro-tris(1-pyrazolyl)borate. For the first time, the related zinc complex TpCumZn(SQNN) (3) was also computed using its experimental geometry, providing a reference point for the reliability of the computational protocol. The inclusion of dynamic correlation at the NEVPT2 (N-Electron Valence State Perturbation Theory, 2nd order) level was essential for correctly predicting the antiferromagnetic nature of the Gd3+–biradical interaction, while the SA-CASSCF (State-Average Complete Active Space Self-Consistent Field) alone yielded a ferromagnetic ground state. The computed exchange interaction in the –2J formalism between Gd3+ and the biradical in complexes 1 and 2 (J ≈ –2.1 cm−1) is more than two times weaker than that in Tp2Gd(SQ) (J = –5.4 cm−1). The intraligand exchange parameters JSQ–NN = 690 cm−1 and JSQ–PhNN = 122 cm−1 reflect strong ferromagnetic coupling within the biradical moieties. Application of the valence bond configuration interaction model yielded electronic coupling matrix elements HDA of 15,283 cm−1 and 6546 cm−1 for the yttrium analogues of 1 and 2, respectively. The calculated magnetic susceptibility data for complexes 1 and 2 closely resemble the behavior of Tp2Gd(SQ), although the characteristic temperatures differ due to the unequal exchange coupling strengths. This study demonstrates that modern computational methods enable consistent prediction of the key magnetic characteristics of heterospin systems based on their possible molecular structures.