Global health organizations recommend the use of cloth face coverings to slow the spread of COVID-19. Seemingly overnight, companies whose primary business is in no way related to healthcare or personal protective equipment—from mattresses manufacturers to big box stores—transitioned into the “mask business.” Many companies advertise antimicrobial masks containing silver, copper, or other antimicrobials. Often, the techniques used to load such antimicrobials onto mask fibers are undisclosed, and the potential for metal leaching from these masks is yet unknown. We exposed nine so-called “antimicrobial” face masks (and one 100% cotton control mask) to deionized water, laundry detergent, and artificial saliva to quantify the leachable silver and copper that may occur during mask washing and wearing. Leaching varied widely across manufacturer, metal, and leaching solution, but in some cases was as high as 100% of the metals contained in the as-received mask after 1 h of exposure.

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Abstract

To efficiently design new adsorption systems, industrial scale fixed beds are often scaled down to bench‐top experiments and/or modeled using computational fluid dynamics (CFD). While there has been considerable work exploring adsorption of volatile organics onto activated carbon fixed beds in the literature, this article attempts to reckon with the high variability of adsorption capacities observed at small scales and improve small‐scale experiments for industrial scale reactor design. This study integrates experimental results with CFD simulations, which can explicitly model system heterogeneities and their influence on adsorption by resolving local packing densities and flow paths. Activated carbon physical properties were determined through surface area analysis, proximate analysis, and toluene adsorption (measured via mass spectroscopy). Variability in the small‐scale systems was not attributed to surface area or carbon content, as is often stated, but instead was due to local packing density variations and the heterogeneity of particle size distributions.

Biofuels produced via thermochemical conversions of waste biomass could be sustainable alternatives to fossil fuels but currently require costly downstream upgrading to be used in existing infrastructure. In this work, we explore how a low-cost, abundant clay mineral, bentonite, could serve as an in situ heterogeneous catalyst for two different thermochemical conversion processes: pyrolysis and hydrothermal carbonization (HTC). Avocado pits were combined with 20 wt% bentonite clay and were pyrolyzed at 600 °C and hydrothermally carbonized at 250 °C, commonly used conditions across the literature. During pyrolysis, bentonite clay promoted Diels–Alder reactions that transformed furans to aromatic compounds, which decreased the bio-oil oxygen content and produced a fuel closer to being suitable for existing infrastructure. The HTC bio-oil without the clay catalyst contained 100% furans, mainly 5-methylfurfural, but in the presence of the clay, approximately 25% of the bio-oil was transformed to 2-methyl-2-cyclopentenone, thereby adding two hydrogen atoms and removing one oxygen. The use of clay in both processes decreased the relative oxygen content of the bio-oils. Proximate analysis of the resulting chars showed an increase in fixed carbon (FC) and a decrease in volatile matter (VM) with clay inclusion. By containing more FC, the HTC-derived char may be more stable than pyrolysis-derived char for environmental applications. The addition of bentonite clay to both processes did not produce significantly different bio-oil yields, such that by adding a clay catalyst, a more valuable bio-oil was produced without reducing the amount of bio-oil recovered.

Early phases of green material development can be accelerated by identifying driving factors that control material properties to understand potential tradeoffs. Full investigation of fabrication variables is often prohibitively expensive. We propose a pared-down design of experiments (DOE) approach to identify driving variables in limited data scenarios using tunable polydimethylsiloxane (PDMS) foams made via sacrificial templating as an example system. This new approach systematically determines the dependencies of porosity, transparency, and fluid flow by varying the template particle size and packing while using a more sustainable solvent. Factor screening identified template particle size and packing density as the driving factors for foam performance by controlling pore size and interconnectivity. The framework developed provides a robust, foundational understanding of how to green and tune a novel material's properties using an efficient and effective exploration of the design space. Recommendations for applying this method to a broad suite of experiments are provided.

Global health organizations recommend the use of cloth face coverings to slow the spread of COVID-19. Seemingly overnight, companies whose primary business is in no way related to healthcare or personal protective equipment – from mattresses manufacturers to big box stores – transitioned into the “mask business.” One of many options on the market are antimicrobial face masks, some of which contain silver and/or copper that may leach out of these masks. We exposed ten face masks to deionized water, laundry detergent, and artificial saliva to quantify the leachable silver and copper as a result of mask washing and wearing. Leaching varied widely across brand, metal, and leaching solution, but in some cases was as high as 100% of the metals contained in the as-received mask after 1 hour of exposure. This could lead to a total adult body metal exposure of up to 900 µg/kg of silver and 75 µg/kg of copper by wearing a given mask over an 8-hour workday. While this exposure could be minimized by pre-washing the cloth masks, this would seem to eliminate any (perceived) antimicrobial properties as the metals are eliminated into wastewater and/or graywater.

Aminopolymer-based adsorbents are commonly investigated for CO2 direct air capture (DAC). In the presence of high temperature and O2, which could happen during process upset, oxidative degradation can significantly contribute to limiting the adsorbent lifetime. Here, we demonstrate the use of a portable, benchtop NMR sensor to collect proton relaxometry profiles to track the degradation of a PEI/Al2O3 sample exposed to controlled accelerated oxidation conditions and correlate the extent of oxidation as measured by loss in amine efficiency with T2 (spin-spin) relaxation times. We hypothesize that T2 relaxation accurately tracks oxidative degradation in aminopolymers because of reduced polymer mobility resulting from radical-induced crosslinking that can occur during the oxidation process. The advantage of using NMR relaxometry as a non-destructive technique to probe degradation is demonstrated on a 1-inch square-channel monolith adsorbent exposed to actual DAC service conditions, highlighting the potential for using this technique as a rapid and non-destructive method of probing adsorbent health.