Modeling the path to >30% power conversion efficiency in perovskite solar cells with plasmonic nanoparticles.

Mixed organic-inorganic halide perovskite solar cells (PSCs) are a promising technology with increasing power conversion efficiency (PCE), low-cost material constituents, simple scalability, and a low-temperature solution fabrication process. Recent developments have seen energy conversion efficiencies increase from 3.8% to over 20%. However, to further improve PCE and reach the target efficiency of over 30%, light absorption through plasmonic nanostructures is a promising approach. In this work, we present a thorough quantitative analysis of the absorption spectrum of a methylammonium lead iodide (CH3NH3PbI3) perovskite solar cell using a nanoparticle (NP) array. Our multiphysics simulations using finite element methods (FEM) show that an array of Au nanospheres can increase average absorption >45%, compared to only 27.08% for the baseline structure without any NPs. Furthermore, we investigate the combined effect of engineered enhanced absorption on electrical and optical solar cell performance parameters using the one-dimensional solar cell capacitance software (SCAPS 1-D), which shows a PCE of ∼30.4%, significantly higher than the PCE of ∼21% for cells without NPs. Our findings demonstrate the potential of plasmonic perovskite research for next-generation optoelectronic technologies.

Graphene based hyperbolic metamaterial for tunable mid-infrared biosensing.

Plasmonic biosensors, operating in the mid-infrared (mid-IR) region, are well-suited for highly specific and label-free optical biosensing. The principle of operation is based on detecting the shift in resonance wavelength caused by the interaction of biomolecules with the surrounding medium. However, metallic plasmonic biosensors suffer from poor signal transduction and high optical losses in the mid-IR range, leading to low sensitivity. Here, we introduce a hyperbolic metamaterial (HMM) biosensor, that exploits the strong, tunable, mid-IR localization of graphene plasmons, for detecting nanometric biomolecules with high sensitivity. The HMM stack consists of alternating graphene/Al2O3 multilayers, on top of a gold grating structure with rounded corners, to produce plasmonic hotspots and enhance sensing performance. Sensitivity and figure-of-merit (FOM) can be systematically tuned, by varying the structural parameters of the HMM stack and the doping levels (Fermi energy) in graphene. Finite-difference time-domain (FDTD) analysis demonstrates that the proposed biosensor can achieve sensitivities as high as 4052 nm RIU-1 (refractive index unit) with a FOM of 11.44 RIU-1. We anticipate that the reported graphene/Al2O3 HMM device will find potential application as a mid-IR, highly sensitive plasmonic biosensor, for tunable and label-free detection.

Transport in nanoribbon interconnects obtained from graphene grown by chemical vapor deposition.

We study graphene nanoribbon (GNR) interconnects obtained from graphene grown by chemical vapor deposition (CVD). We report low- and high-field electrical measurements over a wide temperature range, from 1.7 to 900 K. Room temperature mobilities range from 100 to 500 cm(2)·V(-1)·s(-1), comparable to GNRs from exfoliated graphene, suggesting that bulk defects or grain boundaries play little role in devices smaller than the CVD graphene crystallite size. At high-field, peak current densities are limited by Joule heating, but a small amount of thermal engineering allows us to reach ∼2 × 10(9) A/cm(2), the highest reported for nanoscale CVD graphene interconnects. At temperatures below ∼5 K, short GNRs act as quantum dots with dimensions comparable to their lengths, highlighting the role of metal contacts in limiting transport. Our study illustrates opportunities for CVD-grown GNRs, while revealing variability and contacts as remaining future challenges.

Scaling of high-field transport and localized heating in graphene transistors.

We use infrared thermal imaging and electrothermal simulations to find that localized Joule heating in graphene field-effect transistors on SiO(2) is primarily governed by device electrostatics. Hot spots become more localized (i.e., sharper) as the underlying oxide thickness is reduced, such that the average and peak device temperatures scale differently, with significant long-term reliability implications. The average temperature is proportional to oxide thickness, but the peak temperature is minimized at an oxide thickness of ∼90 nm due to competing electrostatic and thermal effects. We also find that careful comparison of high-field transport models with thermal imaging can be used to shed light on velocity saturation effects. The results shed light on optimizing heat dissipation and reliability of graphene devices and interconnects.