Mask-Enabled Topography Contrast on Aluminum Surfaces.

Patterned solid surfaces with wettability contrast can enhance liquid transport for applications such as electronics thermal management, self-cleaning, and anti-icing. However, prior work has not explored easy and scalable blade-cut masking to impart topography patterned wettability contrast on aluminum (Al), even though Al surfaces are widely used for thermal applications. Here, we demonstrate mask-enabled topography contrast patterning and quantify the resulting accuracy of the topographic pattern resolution, spatial variations in surface roughness, wettability, drop size distribution during dropwise condensation, and thermal emissivity of patterned Al surfaces.

Rapid In Situ Thermal Decontamination of Wearable Composite Textile Materials.

Pandemics stress supply lines and generate shortages of personal protective equipment (PPE), in part because most PPE is single-use and disposable, resulting in a need for constant replenishment to cope with high-volume usage. To better prepare for the next pandemic and to reduce waste associated with disposable PPE, we present a composite textile material capable of thermally decontaminating its surface via Joule heating. This material can achieve high surface temperatures (>100 °C) and inactivate viruses quickly (<5 s of heating), as evidenced experimentally with the surrogate virus HCoV-OC43 and in agreement with analytical modeling for both HCoV-OC43 and SARS-CoV-2.

Mitigating Contamination with Nanostructure-Enabled Ultraclean Storage.

Airborne hydrocarbon contamination hinders nanomanufacturing, limits characterization techniques, and generates controversies regarding fundamental studies of advanced materials; consequently, we urgently need effective and scalable clean storage techniques. In this work, we propose an approach to clean storage using an ultraclean nanotextured storage medium as a getter. Experiments show that our proposed approach can maintain surface cleanliness for more than 1 week and can even passively clean initially contaminated samples during storage.

A wearable textile-based pneumatic energy harvesting system for assistive robotics.

Wearable assistive, rehabilitative, and augmentative devices currently require bulky power supplies, often making these tools more of a burden than an asset. This work introduces a soft, low-profile, textile-based pneumatic energy harvesting system that extracts power directly from the foot strike of a user during walking. Energy is harvested with a textile pump integrated into the insole of the user's shoe and stored in a wearable textile bladder to operate pneumatic actuators on demand, with system performance optimized based on a mechano-fluidic model.

Logic-enabled textiles.

Textiles hold great promise as a soft yet durable material for building comfortable robotic wearables and assistive devices at low cost. Nevertheless, the development of smart wearables composed entirely of textiles has been hindered by the lack of a viable sheet-based logic architecture that can be implemented using conventional fabric materials and textile manufacturing processes. Here, we develop a fully textile platform for embedding pneumatic digital logic in wearable devices.

Necrobotics: Biotic Materials as Ready-to-Use Actuators.

Designs perfected through evolution have informed bioinspired animal-like robots that mimic the locomotion of cheetahs and the compliance of jellyfish; biohybrid robots go a step further by incorporating living materials directly into engineered systems. Bioinspiration and biohybridization have led to new, exciting research, but humans have relied on biotic materials-non-living materials derived from living organisms-since their early ancestors wore animal hides as clothing and used bones for tools. In this work, an inanimate spider is repurposed as a ready-to-use actuator requiring only a single facile fabrication step, initiating the area of "necrobotics" in which biotic materials are used as robotic components.

Efficacy and self-similarity of SARS-CoV-2 thermal decontamination.

Dry heat decontamination has been shown to effectively inactivate viruses without compromising the integrity of delicate personal protective equipment (PPE), allowing safe reuse and helping to alleviate shortages of PPE that have arisen due to COVID-19. Unfortunately, current thermal decontamination guidelines rely on empirical data which are often sparse, limited to a specific virus, and unable to provide fundamental insight into the underlying inactivation reaction. In this work, we experimentally quantified dry heat decontamination of SARS-CoV-2 on disposable masks and validated a model that treats the inactivation reaction as thermal degradation of macromolecules.

Effect of daily temperature fluctuations on virus lifetime.

Epidemiological studies based on statistical methods indicate inverse correlations between virus lifetime and both (i) daily mean temperature and (ii) diurnal temperature range (DTR). While thermodynamic models have been used to predict the effect of constant-temperature surroundings on virus inactivation rate, the relationship between virus lifetime and DTR has not been explained using first principles. Here, we model the inactivation of viruses based on temperature-dependent chemical kinetics with a time-varying temperature profile to account for the daily mean temperature and DTR simultaneously.

A predictive model of the temperature-dependent inactivation of coronaviruses.

The COVID-19 pandemic has stressed healthcare systems and supply lines, forcing medical doctors to risk infection by decontaminating and reusing single-use personal protective equipment. The uncertain future of the pandemic is compounded by limited data on the ability of the responsible virus, SARS-CoV-2, to survive across various climates, preventing epidemiologists from accurately modeling its spread. However, a detailed thermodynamic analysis of experimental data on the inactivation of SARS-CoV-2 and related coronaviruses can enable a fundamental understanding of their thermal degradation that will help model the COVID-19 pandemic and mitigate future outbreaks.