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The efficiency of nanoparticle (NP) solar cells has grown impressively inrecent years, exceeding 16%. However, the carrier mobility in NP solar cells,and in other optoelectronic applications remains low, thus critically limitingtheir performance. Therefore, carrier transport in NP solids needs to be betterunderstood to further improve the overall efficiency of NP solar celltechnology. However, it is technically challenging to simulate experimentalscale samples, as physical processes from atomic to mesoscopic scales allcrucially impact transport. To rise to this challenge, here we report thedevelopment of TRIDENS: the Transport in Defected Nanoparticle SolidsSimulator, that adds three more hierarchical layers to our previously developedHINTS code for nanoparticle solar cells. In TRIDENS, we first introduced planardefects, such as twin planes and grain boundaries into individual NP SLs thatcomprised the order of 10^3 NPs. Then we used HINTS to simulate the transportacross tens of thousands of defected NP SLs, and constructed the distributionof the NP SL mobilities with planar defects. Second, the defected NP SLs wereassembled into a resistor network with more than 10^4 NP SLs, thus representingabout 10^7 individual NPs. Finally, the TRIDENS results were analyzed by finitesize scaling to explore whether the percolation transition, separating thephase where the low mobility defected NP SLs percolate, from the phase wherethe high mobility undefected NP SLs percolate drives alow-mobility-to-high-mobility transport crossover that can be extrapolated tomacroscopic length scales. For the theoretical description, we adapted theEfros-Shklovskii bimodal mobility distribution percolation model. Wedemonstrated that the ES bimodal theory's two-variable scaling function is aneffective tool to quantitatively characterize thislow-mobility-to-high-mobility transport crossover.

Describing transport in defected nanoparticle solids using a new, hierarchical, simulation tool, TRIDENS