(707i) Maintaining Atomic Precision in Thiolate-Protected Alloy Nanoclusters

Thiolate-protected metal nanoclusters (TPNCs) have attracted great interest as a unique class of atomically precise nanomaterials with a wide range of applications, which includes sensing, imaging, and catalysis. Due to their high stability at magic size compositions (M_n(SR)_m), TPNCs are often regarded as inorganic-organic hybrid molecules, thus differentiating them from larger metal nanoparticles. With a growing catalogue of structures, TPNCs make up the ideal "playground" to distill fundamental nanomaterials properties from data-driven analyses¹. Recent efforts in the field have sought to modulate TPNC properties through heterometal doping, achieving enhanced catalytic activity and realization of new magic sizes. However, with the increase in structural complexity, new challenges arise in structural determination with atomic precision. The problem is only magnified at larger TPNC sizes (> 100 metal atoms), which offer a massive configuration space of potential alloy chemical orderings (i.e. how the metals position themselves in a TPNC). Herein, we introduce a computational framework to predict thermodynamically favorable dopant positions and concentrations in alloy TPNCs. We first performed Density Functional Theory calculations on Ag-doped Au TPNCs that range in size (36- to 279-metal atoms), metal composition, and chemical ordering. Our efforts yielded a rich dataset of 360 optimized alloy TPNC structures. Next, we extended the Bond-Centric Model² (which determines metal nanoparticle stability) to capture alloy LPNC stability. Importantly, we coupled data science with our domain TPNC knowledge to develop physics-based tuning parameters that were trained and validated with our extensive dataset. The resulting model accurately predicts thermodynamic stability across LPNC size, shape, metal composition, and ligand type. Finally, we incorporated our model into our previously developed nanoparticle genetic algorithm² to conduct a high-throughput screening across the alloy TPNC space. The analysis produced a vast population of hypothetical alloy TPNCs, enabling us to determine structure-based metal mixing behavior of ligated nanostructures.

1. Cowan, M. J.; Mpourmpakis, G., Towards elucidating structure of ligand-protected nanoclusters. Dalton Trans. 2020, 49 (27), 9191-9202.

2. Dean, J.; Cowan, M. J.; Estes, J.; Ramadan, M.; Mpourmpakis, G., Rapid Prediction of Bimetallic Mixing Behavior at the Nanoscale. ACS Nano 2020, 14 (7), 8171–8180.