My Orcid ID is 0000-0002-4882-9542
Phase behavior and surface tension of soft active Brownian particles
N. J. Lauersdorf, T. Kolb, M. Moradi, E. Nazockdast, and D. Klotsa. 2021 Soft Matter Emerging Investigators themed collection (invited) Soft Matter 17, 6337-6351 (2021)
I derive an analytical theory predicated on equilibrium statistical mechanics to predict the steady state of non-equilibrium, active Brownian (self-propelled) systems. Being able to predict the final, steady-state behavior of systems is typically reserved for traditional, equilibrium systems; therefore, knowing how our active systems should behave is incredibly unique, allowing for designing systems with a desired steady-state.
Chapter 13: Perovskites enabled highly sensitive and fast photodetectors
N. J. Lauersdorf and J. Huang. Book chapter published in “Perovskite Photovoltaics and Optoelectronics: From Fundamentals to Advanced Applications” 383-409, edited by Tsutomu Miyasaka, Wiley (2021).
This textbook chapter distills perovskites and photodetectors to an easily-digestible manner for students and scientists new to or seeking to get into the field. I summarize notable developments and provide my insight on fruitful research directions.
Tunable perovskite-based photodetectors in optical sensing
J. Wolanyk, X. Xiao, M. Fralaide, N. J. Lauersdorf, R. Kaudal, E. Dykstra, J. Huang, J. Shinar, and R. Shinar. Book chapter published in Sensors and Actuators. B 321, 1-7 (2020).
I developed the first narrow-band perovskite photodetector that can accurately differentiate photo-luminescent dyes, which is important for detecting harmful chemical or biological materials, such as COVID-19, in laboratory samples. Creating affordable detectors for this diagnostic tool is essential for providing greater access to lower-income patients.
Development of a Ross Filter Based Aluminum Line Radiation (NickAl2) Detector in Madison Symmetric Torus (MST)
N. J. Lauersdorf, L. M. Reusch, and D. Den Hartog Senior thesis internally published by UW-Madison, 1-75 (2018).
Applying a Python model that I developed, I simulated the energy emissions and measured signal from the MST to design and optimize an x-ray detector that measures Aluminum line-radiation. Previously, diagnostics would use incredibly thick filters to block the Aluminum line radiation, losing significant information in the process. Now, all diagnostics use much thinner filters and, therefore, retain significantly more information.