Nanoscale Metamaterials Engineering and Manufacturing for Emerging Optoelectronics

This award aims to support research that intends to develop a novel approach to metamaterials engineering and manufacturing for emerging optoelectronics. Using a combination of state-of-the-art manufacturing tools, focused-ion-beam-assisted molecular-beam epitaxy (FiMBE) is pioneered, enabling high purity non-precious metals to be patterned and integrated with high quality semiconductors.

The new knowledge generated is expected to revolutionize nanomanufacturing, opening a new frontier for light emission and enabling the development of emerging optoelectronics, including energy-efficient image sensing, catalysis, and light harvesting, which boosts the US economy. The project involves a unique multi-disciplinary approach, with interactions between students, faculty, and scientists from several departments, universities, laboratories, and countries.

The principal investigator continues a legacy of community building and broadening participation by providing opportunities for high school students and teachers to join research cohorts and participate in local, regional, and national science fairs, leading to transformational and lasting benefits to the student-body of the school and the greater community at large. The project augments the semiconductor industry and responds to the Chips and Science Act. The award is also supported by the NNI Special Program Initiative.

This project seeks to support research that intends to develop a combined computational-experimental toolkit for nanomanufacturing, which consists of kinetic Monte Carlo simulation-guided integration of nanoparticle (NP) arrays into epitaxial growth processes, followed by electromagnetic simulation-driven metamaterials design and discovery. The ultra-clean molecular-beam epitaxy (MBE) environment enables systematic investigations of elemental (gallium) and multi-metal (gallium-indium-bismuth) nanoparticle arrays.

For both nanoparticle array formation and overgrowth, substrate chemistry/orientation, effusion cell temperature, and substrate temperature ramping and cooling rates are varied. Real-time probes, including reflection high-energy electron diffraction (RHEED), multi-beam optical stress sensor (MOSS), and spectroscopic ellipsometry (SE) are utilized to monitor array formation and overgrowth.

A machine learning approach involving convolutional neural networks is used to classify RHEED patterns, accelerating the identification of array periodicities and optimization of overgrown layer crystallinity. The macroscopic and microscopic optical responses are measured using ex-situ spectroscopic ellipsometry and photoluminescence spectroscopy, in combination with high-resolution scanning transmission electron microscopy (STEM) and high-energy resolution electron-energy loss spectra (EELS).

Finally, electromagnetic (EM) simulations are used to design structures with multiple alternating layers of NP arrays and high-crystallinity semiconductors or insulators for emerging optoelectronics. Expected outcomes of the work include new insights into nanoscale growth kinetics to enable seamless integration of metallic nanoparticle arrays with single-crystal semiconductors and insulators.

Additional outcomes include novel strategies for tuning absorption, scattering, and emission of incident electromagnetic waves, as well as controlled propagation of surface plasmons along the arrays.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.