Porous copper (Cu) current collectors show promise in stabilizing Li metal anodes (LMAs). However, insufficient lithiophilicity of pure Cu and limited porosity in three-dimensional (3D) porous Cu structures led to an inefficient Li-Cu composite preparation and poor electrochemical performance of Li-Cu composite anodes. Herein, we propose a porous Cu-CuZn (DG-CCZ) host for Li composite anodes to tackle these issues. This architecture features a pore size distribution and lithiophilic-lithiophobic characteristics designed in a gradient distribution from the inside to the outside of the anode structure. This dual-gradient porous Cu-CuZn exhibits exceptional capillary wettability to molten Li and provides a high porosity of up to 66.05%. This design promotes preferential Li deposition in the interior of the porous structure during battery operation, effectively inhibiting Li dendrite formation. Consequently, all cell systems achieve significantly improved cycling stability, including Li half-cells, Li-Li symmetric cells, and Li-LFP full cells. When paired synergistically with the double-coated LiFePO4 cathode, the pouch cell configured with multiple electrodes demonstrates an impressive discharge capacity of 159.3 mAh g-1 at 1C. We believe this study can inspire the design of future 3D Li anodes with enhanced Li utilization efficiency and facilitate the development of future high-energy Li metal batteries.

Increased levels of extracellular nicotinamide phosphoribosyltransferase (eNAMPT) are increasingly recognized as a highly useful biomarker of inflammatory disease and disease severity. In preclinical animal studies, a monoclonal antibody that neutralizes eNAMPT has been generated to successfully reduce the extent of inflammatory cascade activation. Thus, the rapid detection of eNAMPT concentration in plasma samples at the point of care (POC) would be of great utility in assessing the benefit of administering an anti-eNAMPT therapeutic. To determine the feasibility of this POC test, we conducted a particle immunoagglutination assay on a paper microfluidic platform and quantified its extent with a flow rate measurement in less than 1 min. A smartphone and cloud-based Google Colab were used to analyze the flow rates automatically. A horizontal flow model and an immunoagglutination binding model were evaluated to optimize the detection time, sample dilution, and particle concentration. This assay successfully detected eNAMPT in both human whole blood and plasma samples (diluted to 10 and 1%), with the limit of detection of 1-20 pg/mL (equivalent to 0.1-0.2 ng/mL in undiluted blood and plasma) and a linear range of 5-40 pg/mL. Furthermore, the smartphone POC assay distinguished clinical samples with low, mid, and high eNAMPT concentrations. Together, these results indicate this POC assay, which utilizes low-cost materials, time-effective methods, and a straightforward immunoassay (without surface immobilization), may reliably allow rapid determination of eNAMPT blood/plasma levels to advantage patient stratification in clinical trials and guide ALT-100 mAb therapeutic decision-making.

Complex fibrillar networks mediate liquid-liquid phase separation of biomolecular condensates within the cell. Mechanical interactions between these condensates and the surrounding networks are increasingly implicated in the physiology of the condensates and yet, the physical principles underlying phase separation within intracellular media remain poorly understood. Here, we elucidate the dynamics and mechanics of liquid-liquid phase separation within fibrillar networks by condensing oil droplets within biopolymer gels. We find that condensates constrained within the network pore space grow in abrupt temporal bursts. The subsequent restructuring of condensates and concomitant network deformation is contingent on the fracture of network fibrils, which is determined by a competition between condensate capillarity and network strength. As a synthetic analog to intracellular phase separation, these results further our understanding of the mechanical interactions between biomolecular condensates and fibrillar networks in the cell.

A microbial fuel cell (MFC) biosensor with an anode as a sensing element is often unreliable at low or significantly fluctuating organic matter concentrations. To remove this limitation, this work demonstrates capillary action-aided carbon source delivery to an anode-sensing MFC biosensor for use in carbon-depleted environments, e.g., potable water. First, different carbon source delivery configurations using several thread types, silk, nylon, cotton, and polyester, are evaluated. Silk thread was determined to be the most suitable material for passive delivery of a 40 g L-1 acetate solution. This carbon source delivery system was then incorporated into the design of an MFC biosensor for real-time detection of toxicity spikes in tap water, providing an organic matter concentration of 56 ± 15 mg L-1. The biosensor was subsequently able to detect spikes of toxicants such as chlorine, formaldehyde, mercury, and cyanobacterial microcystins. The 16S sequencing results demonstrated the proliferation of Desulfatirhabdium (10.7% of the total population), Pelobacter (10.3%), and Geobacter (10.2%) genera. Overall, this work shows that the proposed approach can be used to achieve real-time toxicant detection by MFC biosensors in carbon-depleted environments.

Desert sandgrouse, such as the Namaqua sandgrouse, nest up to 30 km away from watering holes. Adult male desert sandgrouse have specially adapted feathers on their bellies that hold water, even during flight, allowing the birds to transport water back to the chicks at the nest. The structure of the belly feathers and aspects of the mechanism by which they hold water was first described by Cade and Maclean (Cade, Maclean 1967 Condor 69, 323-343 (doi:10.2307/1366197)). Here, we use scanning electron microscopy and micro-computed tomography as well as videography to characterize the geometry of different components of the belly feathers and to show how differences in their bending stiffnesses contribute to the water-holding mechanism. The results of this study will be used in a companion paper to model computationally water uptake by the feather.

We conceived a novel approach to screen oil types on a wax-printed paper-based microfluidic platform. Various oil samples spontaneously flowed through a micrometer-scale channel via capillary action while their components were filtered and partitioned. The resulting capillary flow velocity profile fluctuated during the flow, which was used to screen oil types. Raspberry Pi camera captured the video clips, and a custom Python code analyzed them to obtain the capillary flow velocity profiles. 106 velocity profiles (each with 125 frames for 5 s) were recorded from various oil samples to build a training database. Principal component analysis (PCA), support vector machine (SVM), and linear discriminant analysis (LDA) were used to classify the oil types into heavy-to-medium crude, light crude, marine fuel, lubricant, and diesel oils. The second-order polynomial SVM model with PCA as a pre-processing step showed the highest accuracy: 90% in classifying crude oils and 81% in classifying non-crude oils. The assay took less than 30 s from the sample to answer, with 5 s of the capillary action-driven flow. This simple and effective assay will allow rapid preliminary screening of oil types, enable early tracking, and reduce the number of suspect samples to be analyzed by laboratory fingerprinting analysis.

Coal mine in arid and semi-arid area is one of the most severely degraded ecosystems on the earth. The continuous decrease in groundwater level caused by coal mining will inevitably affect biogeochemical environment of the vadose zone, and then lead to the replacement of surface vegetation. Yimin open-pit coal mine was taken as an example to reveal the relationship between the groundwater depth and soil water content (SWC), soil salt content, soil electrical conductivity (SEC), soil organic matter (SOM), soil available potassium (SAK), soil available nitrogen (SAN), vegetation coverage, aboveground biomass and species richness. The results show that, the change of groundwater depth can affect soil properties and then change the characteristics of surface vegetation, and the change of surface vegetation can also react on soil properties. Vegetation coverage and aboveground biomass are negatively correlated with groundwater depth, and positively correlated with SWC, SEC, SOM and SAK. The shallow groundwater table is conducive to the accumulation of SOM, so that the surface biomass and vegetation coverage are high. The higher the surface biomass, the more the SAN is absorbed. Under natural conditions, the relative strength of biological nitrogen fixation and plant absorption determine the content of SAN. In the research area, when the depth of groundwater is less than 0.4 m will cause soil salinization, then lead to low species richness; Species richness is exponentially correlated with groundwater depth and decreases with the increase in groundwater depth.

Traditionally, specific bioreceptors such as antibodies have rapidly identified bacterial species in environmental water samples. However, this method has the disadvantages of requiring an additional process to conjugate or immobilize bioreceptors on the assay platform, which becomes unstable at room temperature. Here, we demonstrate a novel mix-and-match method to identify bacteria species by loading the bacterial samples with simple bacteria interacting components (not bioreceptors), such as lipopolysaccharides, peptidoglycan, and bovine serum albumin, and carboxylated particles, all separately on multiple channels. Neither covalent conjugation nor surface immobilization was necessary. Interactions between bacteria and the above bacteria interacting components resulted in varied surface tension and viscosity, leading to various flow velocities of capillary action through the paper fibers. The smartphone camera and a custom Python code recorded multiple channel flow velocity, each loaded with different bacteria interacting components. A multi-dimensional data set was obtained for a given bacterial species and concentration and used as a machine learning training model. A support vector machine was applied to classify the six bacterial species: Escherichia coli, Salmonella Typhimurium, Pseudomonas aeruginosa, Staphylococcus aureus, Enterococcus faecium, and Bacillus subtilis. Under optimized conditions, the training model predicts the bacterial species with an accuracy of > 85% of the six bacteria species.

Respiratory viruses, especially coronaviruses, have resulted in worldwide pandemics in the past couple of decades. Saliva-based paper microfluidic assays represent an opportunity for noninvasive and rapid screening, yet both the sample matrix and test method come with unique challenges. In this work, we demonstrated the rapid and sensitive detection of SARS-CoV-2 from saliva samples, which could be simpler and more comfortable for patients than existing methods. Furthermore, we systematically investigated the components of saliva samples that affected assay performance. Using only a smartphone, an antibody-conjugated particle suspension, and a paper microfluidic chip, we made the assay user-friendly with minimal processing. Unlike the previously established flow rate assays that depended solely on the flow rate or distance, this unique assay analyzes the flow profile to determine infection status. Particle-target immunoagglutination changed the surface tension and subsequently the capillary flow velocity profile. A smartphone camera automatically measured the flow profile using a Python script, which was not affected by ambient light variations. The limit of detection (LOD) was 1 fg/μL SARS-CoV-2 from 1% saliva samples and 10 fg/μL from simulated saline gargle samples (15% saliva and 0.9% saline). This method was highly specific as demonstrated using influenza A/H1N1. The sample-to-answer assay time was <15 min, including <1-min capillary flow time. The overall accuracy was 89% with relatively clean clinical saline gargle samples. Despite some limitations with turbid clinical samples, this method presents a potential solution for rapid mass testing techniques during any infectious disease outbreak as soon as the antibodies become available.

The sensing field has shed light on an urgent necessity for field-deployable, user-friendly, sensitive, and scalable platforms that are able to translate solutions into the real world. Here, we attempt to meet these requests by addressing a simple, low-cost, and fast electrochemical approach to provide sensitive assays that consist of dropping a small volume (0.5 μL) of off-the-shelf alcohols on pyrolyzed paper-based electrodes before adding the sample (150 μL). This method was applied in the detection of phosphate after the formation of the phosphomolybdate complex (250-860 nm in size). Prior drops of isopropanol allow for the fast penetration of the sample through pores of this hydrophobic paper, delivering hindrance-free redox reactions across increasing active areas and ultimately improving the detection performance. The sensitivity (-1.9 10-6 mA cm-2 ppb-1) and limit of detection (1.1 ppb) were improved, respectively, by factors of 33 and 99 over the data achieved without the addition of isopropanol, listing among the lowest values when compared with those results reported in the literature for phosphate (expressed in terms of the concentration of phosphorus). The approach enabled the quantification of this analyte in real samples with accuracies ranging from 87 to 103%. Furthermore, preliminary measurements demonstrated the successful performance of the electrodes with prior addition of other widely used alcohols, that is, methanol and ethanol. These results may extend the applicability of the method. In special, the scalability and eco-friendly character of the electrode fabrication combined with the sensitivity and simplicity of the analyses make the developed platform a promising alternative that may help to pave the way for a new generation of disposable sensors toward the daily monitoring of phosphate in water samples, thus contributing to prevent ecological side effects.