Discovery of New Plasmonic Metals via High‐Throughput Machine Learning. Issue 18 (4th August 2022)

• Record Type: Journal Article
• Authors: Shapera, Ethan P.; Schleife, André
• Is Part Of: Advanced optical materials. Volume 10:Issue 18(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-08-04
• Subjects: high throughput -- machine learning -- plasmonics; Optical materials -- Periodicals; Photonics -- Periodicals; 620.11295
• DOI: 10.1002/adom.202200158
• Languages: English
• ISSNs: 2195-1071

Abstract

Abstract: The field of plasmonics aims to manipulate and control light through nanoscale structuring and choice of materials. Finding materials with low‐loss response to an applied optical field while exhibiting collective oscillations due to intraband transitions is an outstanding challenge. This is viewed as a materials selection problem that bridges the gap between the large number of candidate materials and the high computational cost to accurately compute their individual optical properties. To address this, online databases that compile computational data for numerous properties of tens to hundreds of thousands of materials are combined with first‐principles simulations and the Drude model. By means of density functional theory (DFT), a training set of geometry‐dependent plasmonic quality factors for ≈1000 materials is computed and subsequently random‐forest regressors are trained on these data. Descriptors are limited to symmetry, quantities obtained using the chemical formula, and the Mendeleev database, which allows to rapidly screen 7445 candidates on Materials Project. Using DFT to compute quality factors for the 233 most promising materials, AlCu3, ZnCu, and ZnGa3 are identified as excellent potential new plasmonic metals. This finding is substantiated by analyzing their electronic structure and interband optical properties in detail. Abstract : Machine‐learning models are constructed, validated, and applied to search an online database for new plasmonic materials. AlCu3, ZnCu, and ZnGa3 are identified as the most promising candidates. Calculated strengths of the interband optical transitions in ZnCu are plotted. ZnCu shows no interband optical absorption below 1.9 eV, rendering it a potentially promising plasmonic metal.