Hydrogenated Graphene Based Organic Thin Film Transistor Sensor for Detection of Chloride Ions as Corrosion Precursors

Corrosion monitoring and management has been at the center of structural health monitoring protocols due to its damaging effects on metallic structures. Current corrosion prevention and management programs often fail to include environmental factors such as Cl− ions and surface wetness. Early detection of these environmental factors can prevent the onset of corrosion and reduce repair and maintenance-related expenses. There is growing interest in creating solution-processed thin film environmental sensors with high sensitivity to corrosion precursors, low-cost fabrication, and small footprint, rendering them viable candidates for investigation as potential corrosion sensors that could be easily integrated into existing structures and screen printed or patterned directly into surface coatings. In this work, we have implemented C60-based n-type organic thin film transistors (OTFTs) with functionalized graphene oxide for humidity sensing and functionalized graphene nanoparticles for Cl− ion detection, using low-cost solution processing techniques. The reduced graphene oxide (rGO)-coated OTFT humidity sensor is designed for the qualitative estimation of surface moisture levels and high levels of humidity, and it exhibits a relative responsivity for dry to surface wetness transition of 122.6% to surface wetness, within a response time of 20 ms. We furthermore implemented an in-house synthesized hydrogenated graphene coating in conjunction with a second OTFT architecture for Cl− ions sensing which yielded a sensitivity of 4%/ppm to ultrafine ionic concentrations, over an order of magnitude lower than the range identified to cause corrosion in aircraft structures.

Culinary Properties of Raw Versus Conventional Soy Sauce during Tuna Preparation

Soy sauce is a traditional Japanese seasoning made from fermented soybeans. As global demand grows, identifying novel soy sauce applications and benefits must become a priority. While conventional soy sauce undergoes heat-sterilization, filter-sterilization produces a lighter-colored (raw) soy sauce with preserved mold enzyme activities. As the impact of raw soy sauce during food (especially seafood) preparation remains unstudied, the present study compared the differential impact of raw and conventional soy sauce on tuna culinary properties. First, soy sauce color and protease activity were assessed. Next, tuna was marinated in soy sauce and non-alcoholic mirin for 0, 10, 35, or 60 min. Finally, marinated tuna properties (mass, salt content, surface salt penetration, color, rupture load, surface wetness, and protein content) were objectively assessed, and subjective sensory evaluation (appearance, aroma, wetness, softness, saltiness, umami, and overall taste) was performed by a blinded panel. Findings confirmed the lighter color of and the preservation of protease activity in raw soy sauce. Raw soy sauce significantly enhanced surface tenderization, salt penetration, and wetness, while both soy sauces increased surface firmness via salt-induced dehydration. Respondents significantly preferred the appearance and saltiness level of raw soy sauce-marinated tuna, and the umami and overall taste of tuna marinated in raw soy sauce for 60 min. The findings of this study, to our knowledge, demonstrate for the first time the potential culinary superiority of raw soy sauce in certain applications, and support future research to further define such applications.

An Investigation on Shenzhen Urban Green Space Changes and Their Effect on Local Eco-Environment in Recent Decades

Rapid urbanization and population growth impact enormous pressures on urban natural, economic and social environments. The quantitative analysis of urban green space (UGS) landscape dynamics and their impact on the urban eco-environment is of great significance for urban planning and eco-environment protection. Taking Shenzhen as an example, the UGS landscape changes and their impact on urban heat islands (UHI), surface wetness, air pollution and carbon storage were comprehensively investigated with Landsat and MODIS images. Results showed a large number of lands transferring from UGS to non-UGS from 1978 to 2018, especially for cropland. Built-up regions have adverse influences on eco-environment factors, and then they suffer high SUHI and AOD and low humidity and carbon storage. The growth of built-up areas not only enlarges the area of SUHI, but also enhances the intensity of heat islands. On the contrary, UGS patches have beneficial influences on all eco-environment factors and then enjoy a better eco-environment, including low SUHII, high surface wetness, high carbon storage and low AOD. It is expected that this study could provide scientific support for UGS plans and for conserving and sustainable urban development for developing cities.

Sensitivity Analysis of the Dust-Generation Algorithm in ADAM3 by Incorporating Surface-Wetness Effects

This study examined the surface-wetness effects in calculating dust generation in source regions, using Asian dust aerosol model version 3 (ADAM3; the control run; CNTL). Model sensitivity experiment was conducted in such a way that the dust generation in CNTL is compared against three ADAM3 versions with various surface-wetness effect schemes. The dust-generation algorithm in ADAM_RAIN utilizes precipitation, while the scheme in ADAM3_SM1 and ADAM3_SM2 employs soil water content to account for the surface-wetness effects on dust generation. Each run was evaluated for the spring (March–May) of 2020. ADAM3_SM1 shows the best performance for the dust source region in East Asia based on the root-mean-square error and the skill score, followed by ADAM3_SM2 and ADAM3_RAIN. Particularly, incorporation of the surface-wetness effects improves dust generation mostly in wet cases rather than dry cases. The three surface-wetness-effect runs reduce dust generation in the source regions compared to CNTL; hence, the inclusion of surface-wetness effects improves dust generation in the regions where CNTL overestimates dust generation.

Evaluation of Polarimetric Eigenvector Based Decomposition for Types of Wetland Mapping

ContextThe Kosi mega fan landscape is an alluvial deposited site that have led to several devastating floods. A considerable portion of the land comprises of different types of wetlands and persistent surface wetness. Detection of these wet patches is important in terms of understanding morphology of this sediment deposited fan.ObjectivesThis study identifies different wetland patches in monsoon time with critical reaches of rail-road and waterlogged intersections.MethodsSAR Polarimetry based H-A-Alpha decomposition and Wishart classification is used to identify different backscatter intensities of vegetated wetland, wet soil and open water using dual-pol Sentinel-1 10m data.ResultsThis study showed that Wishart classification offers a good potential for herbaceous waterbody mapping. The presence of a varieties types of wetlands is identified based on their scattering properties. Preliminary it has identified wet soil, low land, marshy patches as well as open water. Though at some places it mistakenly classified vegetation covered water as forest land. Some dry soil also exhibits low entropy volume scattering which is similar to certain type of vegetation cover. This study also identifies the vulnerable zone of waterlogging to existing rail and road network.

Logistic Models derived using Lasso Methods for Quantifying the Risk of Natural Contamination of Maize Grain with Deoxynivalenol

Models were developed to quantify the risk of deoxynivalenol (DON; ppm) contamination of maize grain based on weather, cultural practices, hybrid resistance, or Gibberella ear rot (GER) intensity. Data on natural DON contamination of 15-16 hybrids and weather were collected from 10 Ohio locations over four years. Logistic regression with 10-fold cross-validation was used to develop models to predict the risk of DON ≥ 1 ppm. The presence and severity of GER predicted DON risk with an accuracy of 0.81 and 0.87, respectively. Temperature, relative humidity, surface wetness, and rainfall were used to generate 37 weather-based predictor variables summarized over each of six 15-day windows relative to maize silking (R1). With these variables, LASSO followed by all-subsets variable selection, and logistic regression with 10-fold cross-validation were used to build single-window weather-based models, from which 11 with one or two predictors were selected based on performance metrics and simplicity. LASSO-logistic regression was also used to build more complex multi-window models with up to 22 predictors. The performance of the best single-window models was comparable to that of the best multi-window models, with accuracy ranging from 0.81 to 0.83 for the former and 0.83 to 0.87 for the latter group of models. These results indicated that the risk of DON ≥ 1 ppm can be accurately predicted with relatively simple models built using temperature- and moisture-based predictors from a single window. These models will serve as the foundation for developing tools to predict the risk of DON contamination of maize grain.

Life in a Droplet: Microbial Ecology in Microscopic Surface Wetness

While many natural and artificial surfaces may appear dry, they are in fact covered by thin liquid films and microdroplets invisible to the naked eye known as microscopic surface wetness (MSW). Central to the formation and the retention of MSW are the deliquescent properties of hygroscopic salts that prevent complete drying of wet surfaces or that drive the absorption of water until dissolution when the relative humidity is above a salt-specific level. As salts are ubiquitous, MSW occurs in many microbial habitats, such as soil, rocks, plant leaf, and root surfaces, the built environment, and human and animal skin. While key properties of MSW, including very high salinity and segregation into droplets, greatly affect microbial life therein, it has been scarcely studied, and systematic studies are only in their beginnings. Based on recent findings, we propose that the harsh micro-environment that MSW imposes, which is very different from bulk liquid, affects key aspects of bacterial ecology including survival traits, antibiotic response, competition, motility, communication, and exchange of genetic material. Further research is required to uncover the fundamental principles that govern microbial life and ecology in MSW. Such research will require multidisciplinary science cutting across biology, physics, and chemistry, while incorporating approaches from microbiology, genomics, microscopy, and computational modeling. The results of such research will be critical to understand microbial ecology in vast terrestrial habitats, affecting global biogeochemical cycles, as well as plant, animal, and human health.

Long-term and recent ecohydrological dynamics of patterned peatlands in north-central Quebec (Canada)

Peatlands are natural ecosystems that provide archives of the hydrological cycle, ecological processes and terrestrial carbon dynamics. In the north-central region of Quebec (eastern Canada), patterned peatlands developed in topographic depressions of the Precambrian Shield following the Laurentide Ice Sheet retreat. These peatlands display characteristics similar to appa mires and other peatlands that developed at the ecotone between the open (taiga) and closed boreal forest biomes of the Northern Hemisphere, and also correspond to the biogeographic limit between ombrotrophic and minerotrophic peatlands. During the Neoglacial cooling period in northeastern Canada, patterned peatlands, mainly oligotrophic fens, registered a hydrological disequilibrium expressed by an increase in surface wetness as aquatic microforms expanded to the detriment of terrestrial surfaces. Ecohydrological trajectories were reconstructed from a detailed study of two patterned peatlands in order to document their sensitivity to climate variations. To do this, plant macrofossil and testate amoeba data were combined with peat carbon accumulation rates, C:N ratios, 210Pb and 14C chronologies. Data show that peatlands initiated ca 6500 cal. y BP as ombrotrophic or minerotrophic systems depending on site-specific conditions, followed by a general increase in surface wetness during the Neoglacial cooling until the end of the Little Ice Age. A relatively synchronous ecosystem state shift from oligotrophic to more ombrotrophic conditions was registered at the beginning of the 20th century in central and lateral cores of both study sites, evoking the likely influence of recent warming on peat accumulation. These results suggest a potential northward migration of the biogeographic limit of the ombrotrophic peatland distribution during the 20th century, which could have implications for the role of these ecosystems as C sinks at the continental scale. Overall, these peatlands have stored a mean carbon mass of ca 100 kg m− 2.