Al–Au Thin Films for Thermally Stable and Highly Sensitive Plasmonic Sensors

Abstract

Plasmonic sensors provide label-free detection of bio and chemical targets with ultrahigh sensitivity and accuracy. However, they usually lack the ability to operate at high temperatures, producing large measurement errors due to perturbations. Here, we report a surface plasmon resonance sensor based on Al–Au thin films, which outperforms its conventional Au counterpart by providing a temperature-stable response. We fabricate six metallic samples via the co-sputtering depositing method, obtaining four bimetallic thin films and two pure metals. Through spectroscopic ellipsometry, transmission measurements, and scanning electron microscopy images, we obtain their dielectric function and film morphology from room temperature to 200 °C, showing that the films containing Al do not undergo significant changes with increasing temperature. We experimentally and theoretically establish the dispersion relation of Al–Au alloys by varying the film chemical composition. Using the transfer matrix method, we evaluate the performance of the sensors by studying their response in the refractive index measurement of air, water, and a biological environment. We show that all alloys outperform their pure counterparts, achieving maximum theoretical sensitivities of 42411 nm/RIU and 162.7 °/RIU for a Au0.62Al0.38-based wavelength-dependent sensor and a Au0.85Al0.15-based angular-dependent sensor, respectively. We find that Au0.85Al0.15 is a particularly promising candidate for both wavelength- and angular-dependent sensors due to its high sensitivity (18967 nm/RIU and 162.7 °/RIU) and good peak definition. Furthermore, using partial density-of-state calculations assisted by machine learning, we obtain the dielectric function of the films, showing an excellent agreement with our experimental results. The alloying approach assisted by computational prediction of the samples’ physical properties has the potential to accelerate the discovery of novel materials for plasmonic sensors with high sensitivity and excellent functioning capabilities at elevated temperatures.

Revisiting semiconductor bulk hamiltonians using quantum computers

“…Over the last few decades, materials science has developed with help of digital simulations on supercomputers. Such developments have enabled several new applications by manipulating the structure, composition, and atomic arrangement, of a broad range of materials [1]. We observe a paradigm change when the scientific community started primarily simulating the material's response, predicting the desired behaviors, and subsequently moving to the laboratory to produce new devices with outstanding properties [1].…”

“…Such developments have enabled several new applications by manipulating the structure, composition, and atomic arrangement, of a broad range of materials [1]. We observe a paradigm change when the scientific community started primarily simulating the material's response, predicting the desired behaviors, and subsequently moving to the laboratory to produce new devices with outstanding properties [1]. The screening of material and structural properties is highly bound to the balance between the systems we can simulate and the computational time invested in the modeling [2].…”

“…Hence, approximations should be employed in the models to ease the complexity. The density functional theory (DFT) is an example of success in the materials science area still albeit at the expense of time-consuming simulations [1]. The rate at which computational power is increased appears insufficient to meet the demands of simulating new systems with desired properties [2].…”