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Thiolate-protected metal nanoclusters (TPNCs) have attracted great interest in the last few decades due to their high stability, atomically precise structure, and compelling physicochemical properties. Among their various applications, TPNCs exhibit excellent catalytic activity for numerous reactions; however, recent work revealed that these systems must undergo partial ligand removal in order to generate active sites. Despite the importance of ligand removal in both catalysis and stability of TPNCs, the role of ligands and metal type in the process is not well understood. Herein, we utilize Density Functional Theory to understand the energetic interplay between metal–sulfur and sulfur–ligand bond dissociation in metal–thiolate systems. We first probe 66 metal–thiolate molecular complexes across combinations of M = Ag, Au, and Cu with twenty-two different ligands (R). Our results reveal that the energetics to break the metal–sulfur and sulfur–ligand bonds are strongly correlated and can be connected across all complexes through metal atomic ionization potentials. We then extend our work to the experimentally relevant [M 25 (SR) 18 ] − TPNC, revealing the same correlations at the nanocluster level. Importantly, we unify our work by introducing a simple methodology to predict TPNC ligand removal energetics solely from calculations performed on metal–ligand molecular complexes. Finally, a computational mechanistic study was performed to investigate the hydrogenation pathways for SCH 3 -based complexes. The energy barriers for these systems revealed, in addition to thermodynamics, that kinetics favor the break of S–R over the M–S bond in the case of the Au complex. Our computational results rationalize several experimental observations pertinent to ligand effects on TPNCs. Overall, our introduced model provides an accelerated path to predict TPNC ligand removal energies, thus aiding towards targeted design of TPNC catalysts. 

Ligand-protected metal nanoclusters (NCs) are organic–inorganic nanostructures, exhibiting high stability at specific “magic size” compositions and tunable properties that make them promising candidates for a wide range of nanotechnology-based applications. Synthesis and characterization of these nanostructures has been achieved with atomic precision, offering great opportunities to study the origin of new physicochemical property emergence at the nanoscale using theory and computation. In this Frontier article, we highlight the recent advances in the field of ligand-protected metal NCs, focusing on stability theories on monometallic and heterometal doped NCs, and NC structure prediction. Furthermore, we discuss current challenges on predicting previously undiscovered NCs and propose future steps to advance the field through applying first principles calculations, machine learning, and data-science-based approaches. 

Since their discovery, thiolate-protected gold nanoclusters (Au n (SR) m ) have garnered a lot of interest due to their fascinating properties and “magic-number” stability. However, models describing the thermodynamic stability and electronic properties of these nanostructures as a function of their size are missing in the literature. Herein, we employ first principles calculations to rationalize the stability of fifteen experimentally determined gold nanoclusters in conjunction with a recently developed thermodynamic stability theory on small Au nanoclusters (≤102 Au atoms). Our results demonstrate that the thermodynamic stability theory can capture the stability of large, atomically precise nanoclusters, Au 279 (SR) 84 , Au 246 (SR) 80 , and Au 146 (SR) 57 , suggesting its applicability over larger cluster size regimes than its original development. Importantly, we develop structure–property relationships on Au nanoclusters, connecting their ionization potential and electron affinity to the number of gold atoms within the nanocluster. Altogether, a computational scheme is described that can aid experimental efforts towards a property-specific, targeted synthesis of gold nanoclusters.