journal article·2016-12

Quantifying losses and thermodynamic limits in nanophotonic solar cells

Sander A. Mann, Sebastian Z. Oener, Alessandro Cavalli, Jos E. M. Haverkort, Erik P. A. M. Bakkers, Erik C. Garnett

Nature Nanotechnology· Volume 11· Issue 12
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Abstract

Nanophotonic engineering shows great potential for photovoltaics: the record conversion efficiencies of nanowire solar cells are increasing rapidly and the record open-circuit voltages are becoming comparable to the records for planar equivalents. Furthermore, it has been suggested that certain nanophotonic effects can reduce costs and increase efficiencies with respect to planar solar cells. These effects are particularly pronounced in single-nanowire devices, where two out of the three dimensions are subwavelength. Single-nanowire devices thus provide an ideal platform to study how nanophotonics affects photovoltaics. However, for these devices the standard definition of power conversion efficiency no longer applies, because the nanowire can absorb light from an area much larger than its own size. Additionally, the thermodynamic limit on the photovoltage is unknown a priori and may be very different from that of a planar solar cell. This complicates the characterization and optimization of these devices. Here, we analyse an InP single-nanowire solar cell using intrinsic metrics to place its performance on an absolute thermodynamic scale and pinpoint performance loss mechanisms. To determine these metrics we have developed an integrating sphere microscopy set-up that enables simultaneous and spatially resolved quantitative absorption, internal quantum efficiency (IQE) and photoluminescence quantum yield (PLQY) measurements. For our record single-nanowire solar cell, we measure a photocurrent collection efficiency of >90% and an open-circuit voltage of 850 mV, which is 73% of the thermodynamic limit (1.16 V).
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Research context

OpenAlex topics: Nanowire Synthesis and Applications · Thin-Film Transistor Technologies · Chalcogenide Semiconductor Thin Films

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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