Search for: All records

We demonstrate electronic sensing of DNA nanostar (NS) condensate. Specifically, we use electrokinetic nanofluidics to observe and interpret how temperature-induced NS condensation affects nanochannel current. The increase in current upon filling a nanochannel with NS condensate indicates that its electrophoretic mobility is about half that of a single NS and its effective ionic strength is ∼ 35% greater than that of 150 mM NaCl in phosphate buffer. 𝜁 -potential measurements before and after exposure to NS show that condensate binds the silica walls of a nanochannel more strongly than individual NS do under identical conditions. This binding increases electroosmotic flow, possibly enough to completely balance, or even exceed, the electrophoretic velocity of NS condensate. Although the current through a flat nanochannel is erratic in the presence of NS condensate, tilting the nanochannel to accumulate NS condensate at one entrance (and away from the other) results in a robust electronic signature of the NS phase transition at temperatures 𝑇𝑐= 𝑓 ([NaCl]) that agree with those obtained by other methods. Electrokinetic nanofluidic detection and measurement of NS condensate thus provides a foundation for novel biosensing technologies based on liquid–liquid phase separation. 

This study aims to detect in which microstructure conditions the Mori–Tanaka scheme is inappropriate to calculate the effective stiffness of a two-phase matrix-inclusion system.We analyze the discrepancy between numerical and Mori–Tanaka stiffness estimates in two-dimensional (2D) solids with crack-like flat cavities. The maximum transfer entropy that occurs between a microstructure feature and a stiffness component discrepancy cannot only detect the phase change between a Mori–Tanaka-like cracked solid to a non-Mori–Tanaka-like cracked solid, but also reveal at which load step that phase change first occurs and which microstructure features most affect that phase change. Further analysis with a binary classifier based on a support vector machine (SVM) algorithm shows that the systematic calculation of nine microstructure features based on six statistical crack network descriptors at each step of a loading path can inform the detection of a microstructure transition. The microstructure features identified here could thus be used to trigger the transition from one homogenization scheme to another during incremental stiffness updates, for example, during the simulation of a load path. 

Building community resilience is vital due to climate change and more frequent extreme weather events, which often force people to choose between evacuating or sheltering in place. The prevalence of stay-at-home orders and quarantine practices emerging from the COVID-19 pandemic highlights the need to understand how households access resources when mobility is restricted. This research investigates peer-to-peer resource-exchanging behavior during a shelterin- place response to a flooding event amid the pandemic through an online stated response survey (n=600). Latent class analysis reveals six distinct segments based on respondents’ resource sharing and accepting behaviors. Several household and social context variables help explain these behavioral clusters. Younger individuals and individuals with lower household income are generally more reluctant to accept resources from neighbors, while larger households are more inclined to share essential items. Additionally, social resources, trust in neighbors, and preparedness level can significantly influence individuals’ resource-exchanging behaviors. The findings highlight gaps for governmental agencies and nonprofit organizations to help address, emphasizing the need to ensure sufficient allocation of resources, especially for private items such as backup power sources, communication devices, and shelter, which respondents are least willing to share. This research offers valuable insights for future disaster preparedness programs and resource allocation strategies, aiming to improve community resilience and minimize negative impacts during shelter-in-place responses.