Search for: All records

Biofilms are complex biomaterials comprising a well-organized network of microbial cells encased in self-produced extracellular polymeric substances (EPS). This paper presents a detailed account of the implementation of optical coherence elastography (OCE) measurements tailored for the elastic characterization of biofilms. OCE is a non-destructive optical technique that enables the local mapping of the microstructure, morphology, and viscoelastic properties of partially transparent soft materials with high spatial and temporal resolution. We provide a comprehensive guide detailing the essential procedures for the correct implementation of this technique, along with a methodology to estimate the bulk Young's modulus of granular biofilms from the collected measurements. These consist of the system setup, data acquisition, and postprocessing. In the discussion, we delve into the underlying physics of the sensors used in OCE and explore the fundamental limitations regarding the spatial and temporal scales of OCE measurements. We conclude with potential future directions for advancing the OCE technique to facilitate elastic measurements of environmental biofilms. 

Debris-covered glaciers (DCGs) are globally distributed and thought to contain greater microbial diversity than clean surface continental glaciers, but the ecological characteristics of microbial communities on the surface of DCGs have remained underexplored. Here, we investigated bacterial and fungal diversity and co-occurrence networks on the supraglacial debris habitat of two DCGs (Hailuogou and Dagongba Glaciers) in the southeastern Tibetan Plateau. We found that the supraglacial debris harbored abundant microbes with Proteobacteria occupying more than half (51.5%) of the total bacteria operational taxonomic units. The composition, diversity, and co-occurrence networks of both bacterial and fungal communities in the debris were significantly different between Hailuogou Glacier and Dagongba Glacier even though the glaciers are geographically adjacent within the same mountain range. Bacteria were more diverse in the debris of the Dagongba Glacier, where a lower surface velocity and thicker debris layer allowed the supraglacial debris to continuously weather and accumulate nutrients. Fungi were more diverse in the debris of the Hailuogou Glacier, which experiences a wetter monsoonal climate, is richer in calcium, has greater debris instability, and greater ice velocity than the Dagongba Glacier. These factors may provide ideal conditions for the dispersal and propagation of fungi spores on the Hailuogou Glacier. In addition, we found an obvious gradient of bacterial diversity along the supraglacial debris transect on the Hailuogou Glacier. Bacterial diversity was lower where debris cover was thin and scattered and became more diverse near the glacial terminus in thick, slow-moving debris. No such increasing bacterial pattern was detected on the Dagongba Glacier, which implies a positive relationship of debris age, thickness, and weathering on bacterial diversity. Additionally, a highly connected bacterial co-occurrence network with low modularity was found in the debris of the Hailuogou Glacier. In contrast, debris from the Dagongba Glacier exhibited less connected but more modularized co-occurrence networks of both bacterial and fungal communities. These findings indicate that less disturbed supraglacial debris conditions are crucial for microbes to form stable communities on DCGs. 

The growing global plastic waste challenge requires development of new plastic waste management strategies, such as pyrolysis, that will help to enable a circular plastic economy. Developing optimized, scalable pyrolysis reactors capable of maximizing the yield of desired products requires a fundamental understanding of plastic pyrolysis chemistry. Accordingly, the intrinsic reaction kinetics of polypropylene pyrolysis have been evaluated by the method of pulse-heated analysis of solid reactions (PHASR), which enables time-resolved measurement of pyrolysis kinetics at high temperature absent heat and mass transfer limitations on the millisecond scale. Polypropylene pyrolysis product evolution curves were generated at 525°C–625°C, and the overall reaction kinetics were described by a lumped first-order model with an activation energy of 242.0 ± 2.9 kJ mol−1 and a pre-exponential factor of 35.5 ± 0.6 ln(s−1). Additionally, the production of solid residues formed during polypropylene pyrolysis was investigated, revealing a secondary kinetic regime. 

Abstract Hydrogel-encapsulated catalysts are an attractive tool for low-cost intensification of (bio)-processes. Polyvinyl alcohol-sodium alginate hydrogels crosslinked with boric acid and post-cured with sulfate (PVA-SA-BS) have been applied in bioproduction and water treatment processes, but the low pH required for crosslinking may negatively affect biocatalyst functionality. Here, we investigate how crosslinking pH (3, 4, and 5) and time (1, 2, and 8 h) affect the physicochemical, elastic, and process properties of PVA-SA-BS beads. Overall, bead properties were most affected by crosslinking pH. Beads produced at pH 3 and 4 were smaller and contained larger internal cavities, while optical coherence tomography suggested polymer cross-linking density was higher. Optical coherence elastography revealed PVA-SA-BS beads produced at pH 3 and 4 were stiffer than pH 5 beads. Dextran Blue release showed that pH 3-produced beads enabled higher diffusion rates and were more porous. Last, over a 28-day incubation, pH 3 and 4 beads lost more microspheres (as cell proxies) than beads produced at pH 5, while the latter released more polymer material. Overall, this study provides a path forward to tailor PVA-SA-BS hydrogel bead properties towards a broad range of applications, such as chemical, enzymatic, and microbially catalyzed (bio)-processes. 

Abstract Convective available potential energy (CAPE) is of strong interest in climate modeling because of its role in both severe weather and in model construction. Extreme levels of CAPE (>2000 J kg −1 ) are associated with high-impact weather events, and CAPE is widely used in convective parameterizations to help determine the strength and timing of convection. However, to date few studies have systematically evaluated CAPE biases in models in a climatological context, and none have addressed bias in the high tail of CAPE distributions. This work compares CAPE distributions in ~200 000 summertime proximity soundings from four sources: the observational radiosonde network [Integrated Global Radiosonde Archive (IGRA)], 0.125° reanalyses (ERA-Interim and ERA5), and a 4-km convection-permitting regional WRF simulation driven by ERA-Interim. Both reanalyses and the WRF Model consistently show too-narrow distributions of CAPE, with the high tail (>90th percentile) systematically biased low by up to 10% in surface-based CAPE and even more in alternate CAPE definitions. This “missing tail” corresponds to the most impacts-relevant conditions. CAPE bias in all datasets is driven by surface temperature and humidity: reanalyses and the WRF Model underpredict observed cases of extreme heat and moisture. These results suggest that reducing inaccuracies in land surface and boundary layer models is critical for accurately reproducing CAPE. 

Abstract Convective available potential energy (CAPE), a metric associated with severe weather, is expected to increase with warming, but we have lacked a framework that describes its changes in the populated midlatitudes. In the tropics, theory suggests mean CAPE should rise following the Clausius–Clapeyron (C–C) relationship at ∼6%/K. In the heterogeneous midlatitudes, where the mean change is less relevant, we show that CAPE changes are larger and can be well‐described by a simple framework based on moist static energy surplus, which is robust across climate states. This effect is highly general and holds across both high‐resolution nudged regional simulations and free‐running global climate models. The simplicity of this framework means that complex distributional changes in future CAPE can be well‐captured by a simple scaling of present‐day data using only three parameters.