Colorimetric transition pathway mapping in polydiacetylene by hyperspectral microscopy

The structural variance of polydiacetylene (PDA) at the nanoscale even under the same fabrication conditions is one of the origins of its poor reproducibility in chemo/biosensing. In this work, we present a spatial map of such structural distributions within a single crystal by taking an advantage of the recent development of hyperspectral microscopy in visible wavelength. Hyperspectral microscopy provides the distribution of absorption spectra at the spatial resolution of the standard optical microscopy. By track-ing the blue-to-red transition via this technique, we found that the heat application leaves a fingerprint in the transition pathways

Effects of hardware design and operation conditions on PEM fuel cell water flooding

In this paper, membrane electrode assemblies were constructed using catalyst-coated membranes to investigate proton-exchange membrane fuel cell water flooding. Two major fuel cell hardware variations, namely flowfield design and Teflon loading of the gas diffusion layer (GDL), were tested to explore their effects on water flooding. A flowfield with triple serpentine flow channels showed heavier water flooding than that with single serpentine flow channels. Increasing the Teflon loading in the GDL reduced water flooding effectively. Several fuel cell operating conditions, including air stoichiometry, current density, relative humidity (RH), backpressure, and temperature, were also tested to identify their effects on water flooding. It was observed that the water flooding severity increased with decreasing air stoichiometry, as well as with increasing temperature, RH, backpressure, and current density. Among these operation conditions, air stoichiometry (or air flow rate) and RH played more important roles in reducing water flooding.Peer reviewed: YesNRC publication: Ye

Soft-Templated Synthesis Of Lightweight, Elastic, And Conductive Nanotube Aerogels

Conductive polymer (CP) nanotubes are fascinating nanostructures with high electrical conductivity, fast charge/discharge capability, and high mechanical strength. Despite these attractive physical properties, progress in the synthesis of CP nanotube hydrogels is still limited. Here, we report a facile and effective approach for the synthesis of polypyrrole (PPy) nanotube hydrogels by using the weakly interconnected network of self-assembled nanotubes of lithocholic acid as a soft template. The PPy nanotube hydrogels are then converted to aerogels by freeze drying, in which PPy nanotubes form elastic and conductive networks with a density of 38 mg/cm3 and an electrical conductivity of 1.13 S/m. The PPy nanotube aerogels are able to sustain a compressive strain as high as 70% and show an excellent cyclic compressibility due to their robust nanotube networks and hierarchically porous structures, which allow the compressive stress to be easily dissipated. Furthermore, PPy nanotube aerogels show negative strain-dependent electrical resistance changes under compressive strains. The lightweight, elastic, and conductive PPy nanotube aerogels may find potential applications in strain sensors, supercapacitors, and tissue scaffolds

DrawGAN: Multi-view Generative Model Inspired By The Artist's Drawing Method

We present a novel approach for modeling artists' drawing processes using an architecture that combines an unconditional generative adversarial network (GAN) with a multi-view generator and multi-discriminator. Our method excels in synthesizing various types of picture drawing, including line drawing, shading, and color drawing, achieving high quality and robustness. Notably, our approach surpasses the existing state-of-the-art unconditional GANs. The key novelty of our approach lies in its architecture design, which closely resembles the typical sequence of an artist's drawing process, leading to significantly enhanced image quality. Through experimental results on few-shot datasets, we demonstrate the potential of leveraging a multi-view generative model to enhance feature knowledge and modulate image generation processes. Our proposed method holds great promise for advancing AI in the visual arts field and opens up new avenues for research and creative practices

Dual nano-friction force microscopy/fluorescence microscopy imaging reveals the enhanced force sensitivity of polydiacetylene by pH and NaCl

Polydiacetylene (PDA) is a popular mechanochromic material often used in biosensing. The effect of its headgroup-headgroup interactions on the thermochromism such as pH or salt concentration dependency has been extensively studied before, yet, their effect on mechanochromism at nanoscale is left unstudied. In this work, the nano-friction force microscopy and the fluorescence microscopy were combined to study the effect of pH and ionic strength on the polydiacetylene (PDA) force-sensitivity at the nanoscale. We found that the increase in pH from 5.7 to 8.2 caused an enhancement in the force sensitivity by 8 folds. The elevation of NaCl concentration from 10 mM to 200 mM also made the PDA 5 times more force-sensitive. These results suggest that the PDA force sensitivity at the nanoscale can be conveniently enhanced by “pre-stimulation” with pH or ionic strength

The Effect of Cooling Rate on Microstructure and Mechanical Properties of the Zr-4Hf-3Nb (wt%) Alloy

The mechanical properties of Zr-based alloys, such as strength and elongation, are heavily dependent on the cooling rate during heat treatment. Understanding the phase transformation and microstructural evolution in various cooling media can establish the connection between the cooling rate and mechanical properties. The effect of the cooling rate on the phase, microstructure, and tensile properties of Zr-4Hf-3Nb (wt%) alloy is studied in this paper. The results show that the phase composition of the samples transforms from α+β to α+β+ω, and, finally, to α+α’+ω, while the average grain size of α phase decreases from 3.73 μm to 1.96 μm, and the distribution varies from compact to scattering as the cooling rate increases. Hf tends to distribute in β phase, and the slower cooling rate is beneficial to the existence of Hf. The strength and microhardness enhances monotonously, while the elongation ascends first, then decreases as the cooling rate increases. The high strength of water-cooling samples is attributed to the reduction in average grain size and volume fraction of α phase, and the lath α’ martensite and granular ω phase. The fracture pattern of Zr-4Hf-3Nb (wt%) alloy is ductile fracture, and the plasticity gets better with decreasing cooling rate

HSE: Hybrid Species Embedding for Deep Metric Learning

Deep metric learning is crucial for finding an embedding function that can generalize to training and testing data, including unknown test classes. However, limited training samples restrict the model's generalization to downstream tasks. While adding new training samples is a promising solution, determining their labels remains a significant challenge. Here, we introduce Hybrid Species Embedding (HSE), which employs mixed sample data augmentations to generate hybrid species and provide additional training signals. We demonstrate that HSE outperforms multiple state-of-the-art methods in improving the metric Recall@K on the CUB-200 , CAR-196 and SOP datasets, thus offering a novel solution to deep metric learning's limitations

Cathode Contamination Modeling

NRC publication: Ye

Data_Sheet_1_Identifying individual-specific microbial DNA fingerprints from skin microbiomes.ZIP

Skin is an important ecosystem that links the human body and the external environment. Previous studies have shown that the skin microbial community could remain stable, even after long-term exposure to the external environment. In this study, we explore two questions: Do there exist strains or genetic variants in skin microorganisms that are individual-specific, temporally stable, and body site-independent? And if so, whether such microorganismal genetic variants could be used as markers, called “fingerprints” in our study, to identify donors? We proposed a framework to capture individual-specific DNA microbial fingerprints from skin metagenomic sequencing data. The fingerprints are identified on the frequency of 31-mers free from reference genomes and sequence alignments. The 616 metagenomic samples from 17 skin sites at 3-time points from 12 healthy individuals from Integrative Human Microbiome Project were adopted. Ultimately, one contig for each individual is assembled as a fingerprint. And results showed that 89.78% of the skin samples despite body sites could identify their donors correctly. It is observed that 10 out of 12 individual-specific fingerprints could be aligned to Cutibacterium acnes. Our study proves that the identified fingerprints are temporally stable, body site-independent, and individual-specific, and can identify their donors with enough accuracy. The source code of the genetic identification framework is freely available at https://github.com/Ying-Lab/skin_fingerprint.</p