Sitemap
A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
Published:
This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.
Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Optimization of a Pb-free all-perovskite tandem solar cell with 30.85% efficiency
Published in Optical Materials, 2022
Addressing the environmental challenges of lead-based perovskite solar cells, this study models and optimizes lead-free tandem solar cells using SCAPS software. By fine-tuning the optoelectronic properties of MAGeI3 and FASnI3 subcells, we achieve an impressive 31% efficiency. This work demonstrates the viability of eco-friendly alternatives for high-performance solar cells, paving the way for sustainable energy solutions.
Recommended citation: Duha, Arman U., and Mario F. Borunda. "Optimization of a Pb-free all-perovskite tandem solar cell with 30.85% efficiency." Optical Materials 123 (2022): 111891.
Download Paper
Two-mode squeezing in Floquet-engineered power-law interacting spin models
Published in Physical Review A, 2024
In this study, we explore the potential of Floquet-engineered power-law interacting spin-1/2 XXZ models for generating metrologically useful entanglement. By leveraging spatiotemporal control of interactions, we demonstrate Heisenberg-limited two-mode squeezing, surpassing traditional limits on sensitivity in quantum sensing. Using the discrete truncated Wigner approximation (dTWA) for numerical simulations, our results reveal universal scaling laws that unlock new possibilities for quantum platforms featuring power-law interactions.
Recommended citation: Duha, Arman, and Thomas Bilitewski. "Two-mode squeezing in Floquet-engineered power-law interacting spin models." Physical Review A 109.6 (2024): L061304.
Download Paper
Effect of uncorrelated on-site scalar potential and mass disorder on transport of two-dimensional Dirac fermions
Published in Physical Review B, 2024
This work investigates how scalar potential and mass disorder affect the transport properties of Dirac fermions in two-dimensional systems. Using a tight-binding lattice model and the Landauer formalism, we uncover a rich phase diagram encompassing insulating, metallic, and scale-invariant behaviors. These findings illuminate the interplay between disorder types and their critical thresholds, offering insights into designing systems like bilayer graphene with tunable transport properties.
Recommended citation: Duha, Arman, and Mario F. Borunda. "Effect of uncorrelated on-site scalar potential and mass disorder on transport of two-dimensional Dirac fermions." Physical Review B 110.9 (2024): 094205.
Download Paper
Machine Learning-Driven Analytical Models for Threshold Displacement Energy Prediction in Materials
Published in arXiv, 2025
The threshold displacement energy (Ed) is a fundamental parameter for understanding radiation damage in materials, yet its determination typically relies on costly experiments or computationally expensive simulations. In this work, we employ the Sure Independence Screening and Sparsifying Operator (SISSO) machine learning method to develop analytical models that predict Ed based on fundamental material properties. Our models achieve high accuracy for monoatomic materials, outperforming traditional empirical approaches. For polyatomic systems, we identify key challenges and highlight pathways for improvement with enhanced datasets. This study identifies cohesive energy and melting temperature as the dominant descriptors of Ed, providing a predictive framework for radiation damage assessment in diverse materials.
Recommended citation: Duque, Rosty B. Martinez, Arman Duha, and Mario F. Borunda. "Machine Learning-Driven Analytical Models for Threshold Displacement Energy Prediction in Materials." arXiv preprint arXiv:2502.01813 (2025).
Download Paper
talks
Lead-free All-perovskite Tandem Solar Cell
Published:
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.