Sea Anemone-Inspired Slippery Liquid-Infused Porous Surface (SLIPS) with Bionic Cilia for Responsive 4D Antifouling.

The formation process of biofouling is actually a 4D process with both spatial and temporal dimensions. However, most traditional antifouling coatings, including slippery liquid-infused porous surface (SLIPS), are limited to performing antifouling process in the 2D coating plane. Herein, inspired by the defensive behavior of sea anemones' wielding toxic tentacles, a "4D SLIPS" (FSLIPS) is constructed with biomimetic cilia via a magnetic field self-assembly method for antifouling. The bionic cilia move in 3D space driven by an external magnetic field, thereby preventing the attachment of microorganisms. The FSLIPS releases the gaseous antifoulant (nitric oxide) at 1D time in response to light, thereby achieving a controllable biocide effect on microorganisms. The FSLIPS regulates the movement of cilia via the external magnetic field, and controls the release of NO overtime via the light response, so as to adjust the antifouling modes on demand during the day or night. The light/magnetic response mechanism endow the FSLIPS with the ability to adjust the antifouling effect in the 4D dimension of 1D time and 3D space, effectively realizing the intelligence, multi-dimensionality and precision of the antifouling process.

Pearl-Inspired Intelligent Marine Hetero Nanocomposite Coating Based on "Brick&Mortar" Strategy: Anticorrosion Durability and Switchable Antifouling.

Corrosion activities and biofouling pose significant challenges for marine facilities, resulting in substantial economic losses. Inspired by the "brick&mortar" structure of pearls, a novel nanocomposite coating (Pun-HJTx) with long-lasting anticorrosion and intelligent antifouling modes is fabricated by integrating a compatible MoS2/MXene heterostructure as the "brick" into a polyurea-modified PDMS (Pun) acting as "mortar." Notably, the presence of multiple hydrogen bonds within the coating effectively reduces the pinholes resulted from solution volatilizing. In the dark, where fouling adhesion and microbial corrosion activities are weakened, the MoS2/MXene plays a role in contact bactericidal action. Conversely, during daylight when fouling adhesion and microbial corrosion activities intensify, the coating releases reactive oxygen species (such as hydroxyl radicals and superoxide ions) to counteract fouling adhesion. Additionally, the coating exhibits multisource self-healing performance under heated or exposed to light (maximum self-healing rate can reach 99.46%) and proves efficient self-cleaning performance and adhesion strength (>2.0 Mpa), making it highly suitable for various practical marine applications. Furthermore, the outstanding performance of the Pun-HJT1 is maintained for ≈180 days in real-world marine conditions, which proving its practicality and feasibility in real shallow sea environments.

Slippery Porous-Liquid-Infused Porous Surface (SPIPS) with On-Demand Responsive Switching between "Defensive" and "Offensive" Antifouling Modes.

Slippery liquid-infused porous surfaces (SLIPS) have received widespread attention in the antifouling field. However, the reduction in antifouling performance caused by lubricant loss limits their application in marine antifouling. Herein, inspired by the skin of a poison dart frog which contains venom glands and mucus, a porous liquid (PL) based on ZIF-8 is prepared as a lubricant and injected into a silicone polyurethane (SPU) matrix to construct a new type of SLIPS for marine antifouling applications: the slippery porous-liquid-infused porous surface (SPIPS). The SPIPS consists of a responsive antifoulant-releasing switch between "defensive" and "offensive" antifouling modes to intelligently enhance the antifouling effect after lubricant loss. The SPIPS can adjust antifouling performance to meet the antifouling requirements under different light conditions. The wastage of antifoulants is reduced, thereby effectively maintaining the durability and service life of SLIPS materials. The SPIPS exhibits efficient lubricant self-replenishment, self-cleaning, anti-protein, anti-bacterial, anti-algal, and self-healing (97.48%) properties. Furthermore, it shows satisfactory 360-day antifouling performance in actual marine fields during boom seasons, demonstrating the longest antifouling lifespan in the field tests of reported SLIPS coatings. Hence, the SPIPS can effectively promote the development of SLIPS for neritic antifouling.

A Facile Strategy to Construct Anti-Swelling, Antibacterial, and Antifogging Coatings for Protection of Medical Goggles.

During the COVID-19 (Corona Virus Disease 2019) pandemic, traditional medical goggles are not only easy to attach bacteria and viruses in long-term exposure, but easy to fogged up, which increases the risk of infection and affects productivity. Bacterial adhesion and fog can be significantly inhibited through the hydrogel coatings, owing to super hydrophilic properties. On the one hand, hydrogel coatings are easy to absorb water and swell in wet environment, resulting in reduced mechanical properties, even peeling off. On the other hand, the hydrogel coatings don't have intrinsic antibacterial properties, which still poses a potential risk of bacterial transmission. Herein, an anti-swelling and antibacterial hydrogel coating is synthesized by 2-hydroxyethyl methacrylate (HEMA), acrylamide (AM), dimethylaminoethyl acrylate bromoethane (IL-Br), and poly(sodium-p-styrenesulfonate) (PSS). Due to the self-driven entropy reduction effect of polycation and polyanion, an ion cross-linking network is formed, which endows the hydrogel coating with excellent antiswelling performance. Moreover, because of the synergistic effect of highly hydrated surfaces and the active bactericidal effect from quaternary ammonium cations, the hydrogel coating exhibits outstanding antifouling performances. This work develops a facile strategy to fabricate anti-swelling, antifouling, and antifogging hydrogel coatings for the protection of medical goggles, and also for biomedical and marine antifouling fields.

Structural Engineering of Hierarchical Aerogels Hybrid Networks for Efficient Thermal Comfort Management and Versatile Protection.

In recent years, growing concerns regarding energy efficiency and heat mitigation, along with the critical goal of carbon neutrality, have drawn human attention to the zero-energy-consumption cooling technique. Passive daytime radiative cooling (PDRC) can be an invaluable tool for combating climate change by dispersing ambient heat directly into outer space instead of just transferring it across the surface. Although significant progress has been made in cooling mechanisms, materials design, and application exploration, PDRC faces challenges regarding functionality, durability, and commercialization. Herein, a silica nanofiber aerogels (SNAs) functionalized poly(vinylidene fluoride-co-hexafluoropropene) (P(VDF-HFP)) membrane (SFP membrane), inspired by constructional engineering is constructed. As-prepared membranes with flexible network structure combined hierarchical structure design and practicability principal. As the host material for thermal comfort management (TCM) and versatile protection, the SFP membrane features a large surface area, porous structure, and a robust skeleton that can render excellent mechanical properties. Importantly, the SFP membrane can keep exceptional solar reflectivity (0.95) and strong mid-infrared emittance (0.98) drop the temperature to 12.5 °C below ambient and 96 W m-2 cooling power under typical solar intensities over 910 W m-2 . This work provides a promising avenue for high performance aerogel membranes that can be created for use in a wide variety of applications.

Dense Residual LSTM-Attention Network for Boiler Steam Temperature Prediction with Uncertainty Analysis.

Flexible operation of large-scale boilers for electricity generation is essential in modern power systems. An accurate prediction of boiler steam temperature is of great importance to the operational efficiency of boiler units to prevent the occurrence of overtemperature. In this study, a dense, residual long short-term memory network (LSTM)-attention model is proposed for steam temperature prediction. In particular, the residual elements in the proposed model have a great advantage in improving the accuracy by adding short skip connections between layers. To provide overall information for the steam temperature prediction, uncertainty analysis based on the proposed model is performed to quantify the uncertainties in steam temperature variations. Our results demonstrate that the proposed method exhibits great performance in steam temperature prediction with a mean absolute error (MAE) of less than 0.6 °C. Compared to algorithms such as support-vector regression (SVR), ridge regression (RIDGE), the recurrent neural network (RNN), the gated recurrent unit (GRU), and LSTM, the prediction accuracy of the proposed model outperforms by 32, 16, 12, 10, and 11% in terms of MAE, respectively. According to our analysis, the dense residual LSTM-attention model is shown to provide an accurate early warning of overtemperature, enabling the development of real-time steam temperature control.

Squid inspired elastomer marine coating with efficient antifouling strategies: Hydrophilized defensive surface and lower modulus.

In antifouling applications for the marine industry, low surface energy coatings entail turbulent water flow to release marine biofouling, which presents a substantial challenge for antifouling in the static situation. The traditional solution is to add environmentally friendly antifouling agents, but it has the problem of exhaustion. Therefore, the low surface energy elastic antifouling coating without antifoulants has high research value. Herein, inspired by soft body and epidermal mucus of squid, the stable polyvinylpyrrolidone (PVP) hydrophilic segments were introduced to modify the polydimethylsiloxane-based polyurethane (PDMS-PU), realizing low surface energy elastomer coatings with hydrophilized defensive surface and reduced elastic modulus (<1.1 MPa). In an aqueous environment, the tailored surface exposed sufficient stable hydrophilic segments, exerting excellent antifouling performance, which improved the anti-adsorption effect on biological proteins, bacteria (antibacterial rate 95.24%) and algae (cover rate <3%). The coating exhibited excellent marine antifouling performance within 150 days and also gave a new impetus to developing an eco-friendly and sustainable solution for no-antifoulant marine antifouling applications.

Vibration Separation Methodology Compensated by Time-Varying Transfer Function for Fault Diagnosis of Non-Hunting Tooth Planetary Gearbox.

Due to planetary movement of planet gears, the vibration signal perceived by a stationary sensor is modulated and difficult to diagnose. This paper proposed a vibration separation methodology compensated by a time-varying transfer function (TVTF-VS), which is a further development of the vibration separation (VS) method in the diagnosis of non-hunting tooth planetary gearboxes. On the basis of VS, multi-teeth VS is proposed to extract and synthesize the meshing signal of a planet gear using a single transducer. Considering the movement regularity of a planetary gearbox, the time-varying transfer function (TVTF) is represented by a generalized expression. The TVTF is constructed using a segment of healthy signal and an evaluation indicator is established to optimize the parameters of the TVTF. The constructed TVTF is applied to overcome the amplitude modulation effect and highlight fault characteristics. After that, experiments with baseline, pitting, and compound localized faults planet gears were conducted on a non-hunting tooth planetary gearbox test rig, respectively. The results demonstrate that incipient failure on a planet gear can be detected effectively, and relative location of the local faults can be determined accurately.

Uncertainty investigation of plume-chasing method for measuring on-road NOx emission factors of heavy-duty diesel vehicles.

The plume-chasing method has shown great advantages in measuring on-road emission factors (EFs) compared with regulatory methods like dynamometer and portable emission measurement systems (PEMS). In this study, a new on-board measurement system incorporating ultrasonic anemometers and solid-state Lidar was developed to investigate the uncertainties of on-road emission factors measured by plume-chasing method due to variables such as on-road wind velocity, chasing speed, chasing distance, and turbulent kinetic energy (TKE). A series of PEMS-chasing experiments for heavy-duty diesel vehicles (HDDVs) were conducted on both highways and local roadways in Beijing, China. Our analysis demonstrated that the differences in EF estimations between concurrent plume-chasing and PEMS measurement decreased with increasing chasing speed as a result of greater vehicle-induced TKE in the wake between HDDV and the mobile platform, whereas the effect of chasing distance on EF estimations appeared insignificant within the tested distance range (12-22 m). In the case of strong crosswinds, overprediction of chasing-based EFs was observed due to convective plume mixing from surrounding vehicular sources. The findings of this study contribute greatly to interpret emission factors measured by the plume-chasing method, and also calls for a future study to develop real-time EF correction algorithms for large-scale mobile chasing measurements.

Signal Identification of Gear Vibration in Engine-Gearbox Systems Based on Auto-Regression and Optimized Resonance-Based Signal Sparse Decomposition.

As an essential part of the transmission system, gearboxes are considered as a major source of vibration. Signal identification of gear vibration is necessary for online monitoring of the mechanical systems. However, in engine-gearbox systems, the ignition impact of the engine is strong, so that the gear vibration is generally submerged. To overcome this issue, the resonance-based signal sparse decomposition (RSSD) method is used in this paper based on different oscillatory behaviors of the gear meshing impact and the engine ignition impact. To improve the accuracy of RSSD under interferences, the meshing frequency energy ratio (MF-ER) index is introduced into RSSD to adaptively choose the decomposition parameters. Before applying the RSSD method, the auto-regression (AR) model is used as a pre-whitening step to eliminate the normal gear meshing vibration, which improves the decomposition performance of RSSD. The effectiveness of the proposed AR-ORSSD (AR-based optimized RSSD) algorithm is tested using both simulated signals and measured vibration signals from an engine-gearbox system in a forklift. Comparisons were made with the RSSD algorithm based on a genetic algorithm. Experimental results indicate that the AR-ORSSD algorithm is superior at identifying gear vibration signals especially when under strong interferences.

Residual Stress Distribution Design for Gear Surfaces Based on Genetic Algorithm Optimization.

The rolling contact fatigue of gear surfaces in a heavy loader gearbox is investigated under various working conditions using the critical plane-based multiaxial Fatemi-Socie criterion. The mechanism for residual stress to increase the fatigue initiation life is that the compressive residual stress has a negative normal component on the critical plane. Based on this mechanism, the genetic algorithm is used to search the optimum residual stress distribution that can maximize the fatigue initiation life for a wide range of working conditions. The optimum residual stress distribution is more effective in increasing the fatigue initiation life when the friction coefficient is larger than its critical value, above which the fatigue initiation moves from the subsurface to the surface. Finally, the effect on the fatigue initiation life when the residual stress distribution deviates from the optimum distribution is analyzed. A sound physical explanation for this effect is provided. This yields a useful guideline to design the residual stress distribution.

The impact of air filtration units on primary school students' indoor exposure to particulate matter in China.

The air quality in classrooms is a critical factor that affects students' daily exposure. Although air filtration units (AFUs) are often used to reduce exposure to air pollution in China, the effectiveness of installing AFUs in Chinese classrooms have not been quantitatively studied. Hence, we carried out concurrent air quality experiments in two identical classrooms where one room was equipped with commercial AFUs and the other one relied on the natural introduction of outside air. Measurements were taken during regular school days in the winter at a primary school in Hangzhou, China. Three AFU ventilation modes, i.e., fresh air, mixed air and recirculation mode were evaluated, respectively. We found that classrooms equipped with AFU showed significant PM2.5 reductions, but this was accompanied by CO2 build-ups. In classroom with AFUs on internal recirculation, nearly 70% of the PM2.5 concentration at the beginning of the class was reduced by the end of a 40-min class. However, the CO2 concentration was observed to reach levels that were six times greater than that of the ambient due to inadequate air change rate (<1 h-1). To mitigate the issue of excessive in-classroom CO2 accumulation when using AFUs, filtered outside air must be brought in during their operation. In comparison with the internal recirculation mode, we demonstrated that the fresh air mode that draws the supply air from outdoor can considerably lower CO2 build-ups in the classroom with a moderate increase in PM2.5 concentration of 15 ± 10 µg/m3. The findings from this study helps policy makers especially in developing countries with serious air pollution issues to determine whether or not to install AFU in primary schools and what ventilation mode is effective in reducing negative health effects.

Exploring the effects of ventilation practices in mitigating in-vehicle exposure to traffic-related air pollutants in China.

In most major cities of China, commuters inevitably spend a considerable amount of time in vehicle cabins due to the escalation of traffic congestion and a rapidly increasing vehicle population. The in-vehicle microenvironment that is in close proximity to traffic emission sources is at particular risk of increased exposure to traffic-related air pollutants (TRAPs). In this study, a mobile measurement campaign was carried out to investigate in-vehicle exposure to TRAPs in China where the elevated level of TRAPs has drawn worldwide attention in recent years. Our analysis demonstrates that vehicle ventilation mode (i.e., mechanical ventilation, natural ventilation, hybrid ventilation, and infiltration) played a critical role in determining the level of in-vehicle exposure. Although the outside air (OA) mode of mechanical ventilation provided adequate air exchange to passengers, the average in-vehicle PM2.5 and UFP concentrations (119 µg/m3 and 97,227 cm-3 on freeway, and 93 µg/m3 and 42,829 cm-3 on local roadway) during a 20-min sampling period were observed at the level that are markedly greater than those from studies conducted in the U.S., posing a serious health threat to vehicle occupants. We elaborated how our results collected in China with a significantly more polluted on-road environment differ from existing studies in terms of ventilation and driving conditions. In addition, we made the first effort to examine in-vehicle exposure under hybrid ventilation that is a common ventilation practice in everyday commute to potentially reduce symptoms similar to sick building syndrome (SBS). Our data indicate that vehicle occupants under hybrid ventilation are at much greater risk of TRAPs exposure if operating in a polluted on-road environment, and we call for future research on automated ventilation system with advanced window control especially for vans and buses with a large cabin volume.

Microenvironmental air quality impact of a commercial-scale biomass heating system.

Initiatives to displace petroleum and climate change mitigation have driven a recent increase in space heating with biomass combustion. However, there is ample evidence that biomass combustion emits significant quantities of health damaging pollutants. We investigated the near-source micro-environmental air quality impact of a biomass-fueled combined heat and power system equipped with an electrostatic precipitator (ESP) in Syracuse, NY. Two rooftop sampling stations with PM2.5 and CO2 analyzers were established in such that one could capture the plume while the other one served as the background for comparison depending on the wind direction. Four sonic anemometers were deployed around the stack to quantify spatially and temporally resolved local wind patterns. Fuel-based emission factors were derived based on near-source measurement. The Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry (CTAG) model was then applied to simulate the spatial variations of primary PM2.5 without ESP. Our analysis shows that the absence of ESP could lead to an almost 7 times increase in near-source primary PM2.5 concentrations with a maximum concentration above 100 µg m-3 at the building rooftop. The above-ground "hotspots" would pose potential health risks to building occupants since particles could penetrate indoors via infiltration, natural ventilation, and fresh air intakes on the rooftop of multiple buildings. Our results demonstrated the importance of emission control for biomass combustion systems in urban area, and the need to take above-ground pollutant "hotspots" into account when permitting distributed generation. The effects of ambient wind speed and stack temperature, the suitability of airport meteorological data on micro-environmental air quality were explored, and the implications on mitigating near-source air pollution were discussed.

Integrated design workflow and a new tool for urban rainwater management.

Low Impact Development (LID) practices provide more sustainable solutions than traditional piping and storm ponds in stormwater management. However, architects are not equipped with the knowledge to perform runoff calculations at early design stage. In response to this dilemma, we have developed an open-source stormwater runoff evaluation and management tool, Rainwater+. It is seamlessly integrated into computer-aided design (CAD) software to receive instant estimate on the stormwater runoff volume of architecture and landscape designs. Designers can thereby develop appropriate rainwater management strategies based on local precipitation data, specific standards, site conditions and economic considerations. We employed Rainwater+ to conduct two case studies illustrating the importance of considering stormwater runoff in the early design stage. The first case study showed that integrating rainwater management into design modeling is critical for determining LID practice at any specific site. The second case study demonstrated the need of visualizing runoff flow direction in assisting the placement of LID practices at proper locations when the terrain is of great complexity.

Quantifying the impact of traffic-related air pollution on the indoor air quality of a naturally ventilated building.

Improper natural ventilation practices may deteriorate indoor air quality when in close proximity to roadways, although the intention is often to reduce energy consumption. In this study, we employed a CFD-based air quality model to quantify the impact of traffic-related air pollution on the indoor air quality of a naturally ventilated building. Our study found that the building envelope restricts dispersion and dilution of particulate matter. The indoor concentration in the baseline condition located 10m away from the roadway is roughly 16-21% greater than that at the edge of the roadway. The indoor flow recirculation creates a well-mixed zone with little variation in fine particle concentration (i.e., 253nm). For ultrafine particles (<100nm), a noticeable decrease in particle concentrations indoors with increasing distance from the road is observed due to Brownian and turbulent diffusion. In addition, the indoor concentration strongly depends on the distance between the roadway and building, particle size, wind condition, and window size and location. A break-even point is observed at D'~2.1 (normalized distance from the roadway by the width of the road). The indoor particle concentration is greater than that at the highway where D'<2.1, and vice versa. For new building planning, the distance from the roadway and the ambient wind condition need to be considered at the early design stage whereas the size and location of the window openings, the interior layout, and the placement of fresh air intakes are important to the indoor air quality of existing buildings adjacent to roadways.

Roadside vegetation barrier designs to mitigate near-road air pollution impacts.

With increasing evidence that exposures to air pollution near large roadways increases risks of a number of adverse human health effects, identifying methods to reduce these exposures has become a public health priority. Roadside vegetation barriers have shown the potential to reduce near-road air pollution concentrations; however, the characteristics of these barriers needed to ensure pollution reductions are not well understood. Designing vegetation barriers to mitigate near-road air pollution requires a mechanistic understanding of how barrier configurations affect the transport of traffic-related air pollutants. We first evaluated the performance of the Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry (CTAG) model with Large Eddy Simulation (LES) to capture the effects of vegetation barriers on near-road air quality, compared against field data. Next, CTAG with LES was employed to explore the effects of six conceptual roadside vegetation/solid barrier configurations on near-road size-resolved particle concentrations, governed by dispersion and deposition. Two potentially viable design options are revealed: a) a wide vegetation barrier with high Leaf Area Density (LAD), and b) vegetation-solid barrier combinations, i.e., planting trees next to a solid barrier. Both designs reduce downwind particle concentrations significantly. The findings presented in the study will assist urban planning and forestry organizations with evaluating different green infrastructure design options.

A case study of air quality above an urban roof top vegetable farm.

The effect of elevation and rooftop configuration on local air quality was investigated at the Brooklyn Grange rooftop farm during a short-term observational campaign. Using multiple particle counters and sonic anemometers deployed along vertical gradients, we found that PM2.5 concentration decayed with height above the street. Samples adjacent to the street had the highest average PM2.5 concentration and frequent stochastic spikes above background. Rooftop observations 26 m above ground showed 7-33% reductions in average PM2.5 concentration compared with the curbside and had far fewer spikes. A relationship between the vertical extinction rate of PM2.5 and atmospheric stability was found whereby less unstable atmosphere and greater wind shear led to greater PM2.5 extinction due to damped vertical motion of air.

Quantifying the effect of vegetation on near-road air quality using brief campaigns.

Many reports of trees' impacts on urban air quality neglect pattern and process at the landscape scale. Here, we describe brief campaigns to quantify the effect of trees on the dispersion of airborne particulates using high time resolution measurements along short transects away from roads. Campaigns near major highways in Queens, NY showed frequent, stochastic spikes in PM2.5. The polydisperse PM2.5 class poorly represented the behavior of discrete classes. A transect across a lawn with trees had fewer spikes in PM2.5 concentration but decreased more gradually than a transect crossing a treeless lawn. This coincided with decreased Turbulence Kinetic Energy downwind of trees, indicating recirculation, longer residence times and decreased dispersion. Simply planting trees can increase local pollution concentrations, which is a special concern if the intent is to protect vulnerable populations. Emphasizing deposition to leaf surfaces obscures the dominant impact of aerodynamics on local concentration.

Modeling multi-scale aerosol dynamics and micro-environmental air quality near a large highway intersection using the CTAG model.

A new methodology, referred to as the multi-scale structure, integrates "tailpipe-to-road" (i.e., on-road domain) and "road-to-ambient" (i.e., near-road domain) simulations to elucidate the environmental impacts of particulate emissions from traffic sources. The multi-scale structure is implemented in the CTAG model to 1) generate process-based on-road emission rates of ultrafine particles (UFPs) by explicitly simulating the effects of exhaust properties, traffic conditions, and meteorological conditions and 2) to characterize the impacts of traffic-related emissions on micro-environmental air quality near a highway intersection in Rochester, NY. The performance of CTAG, evaluated against with the field measurements, shows adequate agreement in capturing the dispersion of carbon monoxide (CO) and the number concentrations of UFPs in the near road micro-environment. As a proof-of-concept case study, we also apply CTAG to separate the relative impacts of the shutdown of a large coal-fired power plant (CFPP) and the adoption of the ultra-low-sulfur diesel (ULSD) on UFP concentrations in the intersection micro-environment. Although CTAG is still computationally expensive compared to the widely-used parameterized dispersion models, it has the potential to advance our capability to predict the impacts of UFP emissions and spatial/temporal variations of air pollutants in complex environments. Furthermore, for the on-road simulations, CTAG can serve as a process-based emission model; Combining the on-road and near-road simulations, CTAG becomes a "plume-in-grid" model for mobile emissions. The processed emission profiles can potentially improve regional air quality and climate predictions accordingly.