The advent of intelligent image-activated cell sorting (iIACS) has enabled high-throughput intelligent image-based sorting of single live cells from heterogeneous populations. iIACS is an on-chip ...microfluidic technology that builds on a seamless integration of a high-throughput fluorescence microscope, cell focuser, cell sorter, and deep neural network on a hybrid software-hardware data management architecture, thereby providing the combined merits of optical microscopy, fluorescence-activated cell sorting (FACS), and deep learning. Here we report an iIACS machine that far surpasses the state-of-the-art iIACS machine in system performance in order to expand the range of applications and discoveries enabled by the technology. Specifically, it provides a high throughput of ∼2000 events per second and a high sensitivity of ∼50 molecules of equivalent soluble fluorophores (MESFs), both of which are 20 times superior to those achieved in previous reports. This is made possible by employing (i) an image-sensor-based optomechanical flow imaging method known as virtual-freezing fluorescence imaging and (ii) a real-time intelligent image processor on an 8-PC server equipped with 8 multi-core CPUs and GPUs for intelligent decision-making, in order to significantly boost the imaging performance and computational power of the iIACS machine. We characterize the iIACS machine with fluorescent particles and various cell types and show that the performance of the iIACS machine is close to its achievable design specification. Equipped with the improved capabilities, this new generation of the iIACS technology holds promise for diverse applications in immunology, microbiology, stem cell biology, cancer biology, pathology, and synthetic biology.
The upgraded version of intelligent image-activated cell sorting (iIACS) has enabled higher-throughput and more sensitive intelligent image-based sorting of single live cells from heterogeneous populations.
High-performance single-photon sources (SPSs) are essential components for quantum information technology and have been realized by strong coupling between a single quantum emitter and an optical ...cavity. However, the configurations of conventional SPSs are not ideal for long-distance quantum communication as they are intrinsically incompatible with optical fibers. Here we propose and design a strong-coupling system based on a single quantum emitter directly coupled with an in-fiber microcavity. The in-fiber microcavity not only achieves a high coupling efficiency of 83% and a high Purcell factor of 360, but also pushes the coupling system to enter the strong-coupling region with a vacuum Rabi splitting up to 4.35 meV. This enables a high quantum efficiency of 99% for a SPS. Our work presents a promising platform for realizing high-performance SPSs for long-distance quantum communication.
Flexible, slit, and rigid barriers are common countermeasures to mitigate natural geophysical mass flows, but presently, quantitative comparisons of their performance are lacking, due to the ...challenges involved in accurately representing the multi‐body and multi‐phase interactions. This study presents a numerical appraisal on this issue using a physics‐based coupled computational fluid dynamics and discrete element method (CFD‐DEM). A geophysical flow is considered as a mixture of discrete gap‐graded particles (DEM) and a continuous viscous slurry (CFD), whereas a permeable and deformable barrier structure can be modeled by DEM. The in‐flow multiphase interactions and flow‐barrier interactions can be rigorously modeled by a coupling scheme between DEM and CFD. Our numerical simulations reasonably capture both field and experimental observations on key features of flow‐barrier interactions and barrier responses. The different intercepting mechanisms of three barriers via pile‐up and runup modes are revealed by qualitative and quantitative characterizations. Flexible barriers perform the best under runup mode regarding much larger peak load reduction ratios (up to 89%) due to their high permeability and Fr‐dependent load‐deflection behavior. We further compile a barrier‐specific design diagram that suggests existing analytical models calibrated by limited experiments may underestimate the peak impact for slit and rigid barriers due to their neglect of large solid particles in the impinging flows while leading to overestimations for flexible barriers owing to inappropriate representations of barrier permeability and structural deformability. Our findings may offer a basis for model improvements and developments in practical barrier selection and design.
Plain Language Summary
Engineers commonly use flexible, open‐type, and closed‐type barriers to reduce the adverse impacts of natural geophysical mass flows. However, the selection and design of barriers mainly rely on engineering experience and simplified models. We present a numerical study based on the coupled fluid‐solid modeling to offer quantitative reference on this issue. The numerical framework employed enables a unified description of a geophysical flow as a mixture of solid particles and a continuous viscous slurry and any of the three barrier types, offering a consistent comparison basis. We compare the different intercepting mechanisms of three types of barriers in resisting an impinging flow and identify their intertwined dependence of incoming flow characteristics, barrier deformability and passing ability, and peak impact loads. A flexible barrier is found to outperform the other two in achieving better peak load reduction ratios (up to 89%) with a runup mode, due to its high passing ability and load‐deflection behavior. The compilation of a unified barrier‐specific design diagram highlights the influences of barrier passing ability, structure deformability, and large solid particles on the peak impacts. This work could help for developing better analytical models on specific barrier design to mitigate natural geohazards caused by geophysical mass flows.
Key Points
Coupled fluid‐solid simulations of geophysical flows against flexible, slit and rigid barriers reveal their distinct intercepting mechanisms
The flexible barrier performs the best under runup mode owing to its high permeability and Fr‐dependent load‐deflection behavior
Compilation of a barrier‐specific design diagram highlights the effects of large particles, barrier permeability, and structure deformability
Intensification of short‐duration rainfall extremes contributes to increased urban flood risk. Yet, it remains unclear how upper‐tail rainfall statistics could change with regional warming. Here, we ...characterize the non‐stationarity of rainfall extremes over durations of 1–24 hr for the rapidly developing coastal megalopolis of the Greater Bay Area, China. Using high‐resolution, multi‐source, merged and gridded data we observe greater increases in rainfall intensities over the north‐central part of the region compared with the southern coastal region. Our results show, for the first time, that urbanization nonlinearly increases rainfall intensities at different durations and return periods. Over short durations (≤3‐hr) and short return periods (2‐yr), urban areas have the greatest scaling rates (≥19.9%/°C). However, over longer durations (≥9‐hr) rural areas have greater scaling rates, with a lower degree of dependency on both durations and return periods.
Plain Language Summary
Short‐duration (sub‐daily) rainfall extremes are major drivers of flash floods and hence significant disruptions to society. Previous modeling and statistical studies show that urbanization intensifies short‐duration rainfall extremes. However, there has been less attention to regional variations in rates of rainfall intensification under a warming climate, particularly for extreme events with return periods that are comparable to or longer than the years of record. In this study, we investigate changes in rainfall extremes over the Greater Bay Area, China using long records of high‐resolution data merged from gauge networks, satellite observations, and reanalysis products. This enables us to evaluate changes in low‐frequency rainfall extremes (2‐ to 100‐yr return periods) over different land surfaces, under a warming climate. We find that increases in rainfall extremes significantly depend on the duration and return period of events, with the largest scaling occurring for short‐duration “nuisance” rainfall intensities over urban areas.
Key Points
Non‐stationarities of sub‐daily rainfall extremes over a coastal megalopolis exhibit marked land cover and duration dependencies
Urban areas show more prominent intensification of events over short durations and short return periods compared with rural areas
Rural areas show smaller nonstationary variabilities across durations and return periods and a lower peak scaling rate than urban areas
Positioning a single quantum emitter in the vicinity of a plasmonic antenna is a fundamental step in constructing a coupling system for quantum information applications. In the strong-coupling ...regime, optical forces beyond perturbative Rayleigh gradient forces are dominant in positioning and trapping the quantum emitter but are rarely explored by including the electronic contribution of the quantum emitter. Here we study the optical forces induced by the strong exciton-plasmon coupling between a single quantum dot and a plasmonic nanoantenna. Interestingly, both attractive and repulsive optical forces can be generated, which are fully controllable and tunable by engineering both excitons and plasmons.
Noble metal nanoparticle-loaded catalytic membrane reactors (CMRs) have emerged as a promising method for water decontamination. In this study, we proposed a convenient and green strategy to prepare ...gold nanoparticle (Au NPs)-loaded CMRs. First, the redox-active substrate membrane (CNT-MoS2) composed of carbon nanotube (CNT) and molybdenum disulfide (MoS2) was prepared by an impregnation method. Water-diluted Au(III) precursor (HAuCl4) was then spontaneously adsorbed on the CNT-MoS2 membrane only through filtration and reduced into Au(0) nanoparticles in situ, which involved a “adsorption–reduction” process between Au(III) and MoS2. The constructed CNT-MoS2@Au membrane demonstrated excellent catalytic activity and stability, where a complete 4-nitrophenol transformation can be obtained within a hydraulic residence time of <3.0 s. In addition, thanks to the electroactivity of CNT networks, the as-designed CMR could also be applied to the electrocatalytic reduction of bromate (>90%) at an applied voltage of −1 V. More importantly, by changing the precursors, one could further obtain the other noble metal-based CMR (e.g., CNT-MoS2@Pd) with superior (electro)catalytic activity. This study provided new insights for the rational design of high-performance CMRs toward various environmental applications.
Geophysical mass flows impacting flexible barriers can create complex flow patterns and multiway solid‐fluid‐structure interactions, wherein estimates of impact loads rely predominantly on analytical ...or simplified solutions. However, an examination of the fundamental relations, applicability, and underlying mechanisms of these solutions has been so far elusive. Here, using a coupled continuum‐discrete method, we systematically examine the physical laws of multiphase, multiway interactions between geophysical flows of variable natures, and a permeable flexible ring net barrier system. This model well captures the essential physics observed in experiments and field investigations. Our results reveal for the first time that unified bi‐linear laws underpin widely used analytical and simplified solutions, with inflection points caused by the transitions from trapezoid‐shaped to triangle‐shaped dead zones. Specifically, the peak impact load increases bi‐linearly with increasing Froude number, peak cable force, or maximum barrier deformation. Flow materials (wet vs. dry) and impact dynamics (slow vs. fast) jointly drive the patterns of identified bi‐linear correlations. These findings offer a physics‐based, significant improvement over existing solutions to impact problems for geophysical flows.
Plain Language Summary
Flexible barriers are increasingly used worldwide to mitigate debris flows, debris/rock/snow avalanches, and rockfalls. Although many methods exist to estimate critical design factors of flexible barriers, a systematic examination of their applicability and underlying relations remains elusive. The status quo has been largely caused by the challenges of capturing and quantifying the multiphase, multiway flow‐barrier interactions. Here, we perform a series of hybrid solid‐fluid simulations to explore the impact of debris flows/avalanches and rock avalanches on a flexible barrier system. Our numerical predictions of critical physical processes show reasonable consistency with experimental and field observations. For the first time, the physics‐based numerical measures of the flow‐barrier forces, in‐barrier forces, and barrier load‐deformation relations reveal the unified bi‐linear laws behind widely used methods. We find that the flow‐specific turning points of the bi‐linear laws are due to the changes from trapezoid‐shaped to triangle‐shaped jammed regions formed upstream of the barrier. Our findings quantitatively explain how flow properties (e.g., wet vs. dry and slow vs. fast) control the obtained bi‐linear laws. This study provides a crucial improvement over widely used methods for geohazard scientists and engineers to impact problems for geophysical flows.
Key Points
We present numerical measures of the impact loads of debris flows/avalanches and rock avalanches on a flexible ring net barrier system
Bi‐linear laws relate peak impact to Fr, peak cable force, or maximum barrier deformation with turning points due to shifts of dead zones
Flow materials and dynamics jointly control the obtained bi‐linear laws, which underpin widely used analytical and simplified solutions
We developed and optimized an electrocatalytic filtration system to catalytically hydrodechlorinate chlorophenolic compounds. A key part of the system was the cathode, which consisted of a filter ...constructed with electroactive carbon nanotubes (CNTs) functionalized with atomically precise gold nanoclusters (AuNCs). In the functional membrane electrode, the AuNCs attached to the CNTs functioned as a highly effective hydrodechlorination catalyst. Additionally, the ligands of the AuNCs facilitated the binding of the AuNCs with the CNT and protected the Au core from agglomeration. Atomic H* was the primary reactive species in the system, but direct reduction by cathode electrons also contributed to the elimination of 2,4-dichlorophenol (2,4-DCP) by hydrodechlorination. The generated atomic H* was able to break the C–Cl bond to achieve the rapid hydrodechlorination of 2,4-DCP into phenol, with 91.5% 2,4-DCP removal within 120 min. The AuNC catalysts attached to the CNT exceeded the best catalytic activity of larger nanoparticles (e.g., AuNPs), while the flow-through construction performed better than a standard batch reactor due to the convection-enhanced mass transport. The study provides an environmentally friendly strategy for the elimination of pervasive halogenated organic contaminants using a highly efficient, stable and recyclable system for hydrodechlorination that integrates nanofiltration and electrochemistry.
•Sediment load inflow and outflow of the TGR decreased 60% and 90% since 2003.•Cascade reservoirs in all sub-basins dominate the reduction of sediment inflow.•JRB traps sediment comparable with the ...sum of other sub-basins since 2015.•TGR only accounts for <20% of total trapped sediment in Upper Yangtze since 2015.
The construction of cascade reservoirs upstream of the Three Gorges Reservoir (TGR) has been greatly intensified in the 21st century. While research attention is dedicated to the downstream effects of the TGR, few studies have been focused on the radical change of upstream inflows to the TGR. In this study, we reveal the impact of upstream cascade reservoirs on the annual runoff and sediment load inflows to the TGR based on the data in 1956–2016. The measured sediment load at control hydrological stations shows a drastic decrease (59%) while the runoff only had a slight decrease (6%). The similarity of these characteristics for that measured at Yichang indicates the leading effects of TGR inflows on its outflow. We develop a macroscopic quantification method utilizing double mass curves to separate the contribution from climate effects and human activities. Results show that precipitation (climate factors) dominated the runoff change, while human activities were the main driving factors for sediment load reduction in the studied area. In the four sub-basins upstream of the TGR, the sediment retention induced by large reservoirs was the major reason for sediment load reduction, especially in the Jinsha River Basin and the Jialing River Basin, which contributed 70% (or 347 Mt/yr) of the total sediment retention in the whole upper Yangtze River Basin (YRB) since 2015, much larger than that of the TGR (19% or 94 Mt/yr). As the total storage capacity of the cascade reservoirs increased to more than twice the TGR’s capacity in the 2010s, the regression relationship between runoff and sediment load broke down. The unprecedented situation in the upper YRB may have profound impacts on the morphology and ecology of the TGR as well as the downstream Yangtze River including its delta.
Optofluidic time-stretch quantitative phase imaging (OTS-QPI) is a potent tool for biomedical applications as it enables high-throughput QPI of numerous cells for large-scale single-cell analysis in ...a label-free manner. However, there are a few critical limitations that hinder OTS-QPI from being widely applied to diverse applications, such as its costly instrumentation and inherent phase-unwrapping errors. Here, to overcome the limitations, we present a QPI-free OTS-QPI method that generates “virtual” phase images from their corresponding bright-field images by using a deep neural network trained with numerous pairs of bright-field and phase images. Specifically, our trained generative adversarial network model generated virtual phase images with high similarity (structural similarity index >0.7) to their corresponding real phase images. This was also supported by our successful classification of various types of leukemia cells and white blood cells via their virtual phase images. The virtual OTS-QPI method is highly reliable and cost-effective and is therefore expected to enhance the applicability of OTS microscopy in diverse research areas, such as cancer biology, precision medicine, and green energy.
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