Finding the optimal design of a passive microfluidic mixer.

The ability to thoroughly mix two fluids is a fundamental need in microfluidics. While a variety of different microfluidic mixers have been designed by researchers, it remains unknown which (if any) of these mixers are optimal (that is, which designs provide the most thorough mixing with the smallest possible fluidic resistance across the mixer). In this work, we automatically designed and rationally optimized a microfluidic mixer. We accomplished this by first generating a library of thousands of different randomly designed mixers, then using the non-dominated sorting genetic algorithm II (NSGA-II) to optimize the random chips in order to achieve Pareto efficiency. Pareto efficiency is a state of allocation of resources (e.g. driving force) from which it is impossible to reallocate so as to make any one individual criterion better off (e.g. pressure drop) without making at least one individual criterion (e.g. mixing performance) worse off. After 200 generations of evolution, Pareto efficiency was achieved and the Pareto-optimal front was found. We examined designs at the Pareto-optimal front and found several design criteria that enhance the mixing performance of a mixer while minimizing its fluidic resistance; these observations provide new criteria on how to design optimal microfluidic mixers. Additionally, we compared the designs from NSGA-II with some popular microfluidic mixer designs from the literature and found that designs from NSGA-II have lower fluidic resistance with similar mixing performance. As a proof of concept, we fabricated three mixer designs from 200 generations of evolution and one conventional popular mixer design and tested the performance of these four mixers. Using this approach, an optimal design of a passive microfluidic mixer is found and the criteria of designing a passive microfluidic mixer are established

Induced Ferromagnetic Order of Graphdiyne Semiconductors by Introducing a Heteroatom

To date, the realization of ferromagnetism in two-dimensional carbon semiconductors containing only sp electrons has remained a challenge for spintronics. Here, we utilize the atomic-level functionalization strategy to obtain three carbon matrix materials by accurately introducing different light elements (H, F, Cl) into graphdiyne's benzene ring. Their magnetic and conductive characteristics are thoroughly clarified via physical property measurements and DFT calculations. All of these carbon matrix materials retain their excellent intrinsic semiconductor properties. In particular, compared with the paramagnetism of HsGDY and ClsGDY, a robust ferromagnetic ordering as well as high mobility of up to 320 cm2 V−1 s −1 was observed in FsGDY, successfully realizing a ferromagnetic semiconductor. Through theory calculations, this unique ferromagnetic coupling can be attributed to the most striking charge transfer between carbon and fluorine atoms, demonstrating the advantages of controllable fabrication. These results not only reveal the important role of atomic-scale doping/substitution in optimizing graphdiyne material but also create new possibilities for manipulating spins and charges in 2D carbon materials.This study was supported by the National Natural Science Foundation of China (51802324, 21790050, 21790051, 51822208, 21771187), the Frontier Science Research Project (QYZDB-SSW-JSC052) of the Chinese Academy of Sciences, and the Taishan Scholars Program of Shandong Province (tsqn201812111)

Facet-dependent growth of InAsP quantum wells in InP nanowire and nanomembrane arrays

Selective area epitaxy is a powerful growth technique that has been used to produce III-V semiconductor nanowire and nanomembrane arrays for photonic and electronic applications. The incorporation of a heterostructure such as quantum wells (QWs) brings new functionality and further broadens their applications. Using InP nanowires and nanomembranes as templates, we investigate the growth of InAsP QWs on these pure wurtzite nanostructures. InAsP QWs grow both axially and laterally on the nanowires and nanomembranes, forming a zinc blende phase axially and wurtzite phase on the sidewalls. On the non-polar {1100} sidewalls, the radial QW selectively grows on one sidewall which is located at the semi-polar 〈112〉 A side of the axial QW, causing the shape evolution of the nanowires from hexagonal to triangular cross section. For nanomembranes with {1100} sidewalls, the radial QW grows asymmetrically on the {1100} facet, destroying their symmetry. In comparison, nanomembranes with {1120} sidewalls are shown to be an ideal template for the growth of InAsP QWs, thanks to the uniform QW formation. These QWs emit strongly in the near IR region at room temperature and their emission can be tuned by changing their thickness or composition. These findings enrich our understanding of the QW growth, which provides new insights for heterostructure design in other III-V nanostructures.National Natural Science Foundation of China (No. 61974166, 51702368 and 61874141); Hunan Provincial Natural Science Foundation of China (2018JJ3684); Open Project of the State Key Laboratory of Luminescence and Applications (SKLA-2018-07); and The Australian Research Council (ARC) are acknowledged for financial support

Simulations of HIV capsid protein dimerization reveal the effect of chemistry and topography on the mechanism of hydrophobic protein association

Recent work has shown that the hydrophobic protein surfaces in aqueous solution sit near a drying transition. The tendency for these surfaces to expel water from their vicinity leads to self assembly of macromolecular complexes. In this article we show with a realistic model for a biologically pertinent system how this phenomenon appears at the molecular level. We focus on the association of the C-terminal domain (CA-C) of the human immunodeficiency virus (HIV) capsid protein. By combining all-atom simulations with specialized sampling techniques we measure the water density distribution during the approach of two CA-C proteins as a function of separation and amino acid sequence in the interfacial region. The simulations demonstrate that CA-C protein-protein interactions sit at the edge of a dewetting transition and that this mesoscopic manifestation of the underlying liquid-vapor phase transition can be readily manipulated by biology or protein engineering to significantly affect association behavior. While the wild type protein remains wet until contact, we identify a set of in silico mutations, in which three hydrophilic amino acids are replaced with nonpolar residues, that leads to dewetting prior to association. The existence of dewetting depends on the size and relative locations of substituted residues separated by nm length scales, indicating long range cooperativity and a sensitivity to surface topography. These observations identify important details which are missing from descriptions of protein association based on buried hydrophobic surface area

Magnetic Nanocomposites and Fields for Bone and Cartilage Tissue Engineering Applications

Current stem cell research often relies on the use of growth factors to stimulate cell proliferation and differentiation for tissue engineering purposes. However, these growth factors are not only short-lived proteins but also expensive resources. Research in biodegradable magnetic nanocomposites is a promising rising field for biomedical applications due to the magnetic response properties of the materials that could provide external physical stimulations as an alternative. This project seeks to investigate the application potential of biodegradable magnetic nanocomposites for bone and cartilage tissue regeneration. Different weight percent of polyvinyl alcohol (PVA) was used to modify the surface of superparamagnetic nanoparticles to reduce aggregation and increase dispersibility in polymer solutions for the synthesis of magnetic nanocomposites. The results showed that 30 wt% of PVA coating was able to provide the best dispersibility compared to all other groups. Hydrogel-based magnetic nanocomposites were synthesized and the cytocompatibility of magnetic nanocomposite hydrogel with bone marrow-derived mesenchymal stem cells (BMSCs) was higher than pure hydrogel. However, both the hydrogel and magnetic nanocomposite hydrogel completely lost structural integrity within 24 hours of culture with BMSCs, which made it difficult for in vivo cell delivery. Another polymer, poly(glycerol sebacate) (PGS) was studied due to its reported elastomeric property. Initial study showed that magnetic PGS nanocomposites without any surface features had low cell adherence. Thus porous structures were created in magnetic PGS nanocomposites to increase cell adhesion. Different weight percent of magnetic nanoparticles (MNPs)-incorporated PGS nanocomposites were synthesized to investigate the effect of MNPs concentration on BMSC proliferation and differentiation behaviors with and without exposure to external electromagnetic field (EMF). The 3-week study showed that BMSCs cultured in magnetic PGS nanocomposite groups had slightly lower cell density but increased ALP activity, calcium deposition, protein and collagen secretion, indicating positive induction towards osteogenesis. This project presented promising porous magnetic PGS nanocomposite scaffolds for bone and cartilage tissue engineering applications

Magnetic Nanocomposites and Fields for Bone and Cartilage Tissue Engineering Applications

Current stem cell research often relies on the use of growth factors to stimulate cell proliferation and differentiation for tissue engineering purposes. However, these growth factors are not only short-lived proteins but also expensive resources. Research in biodegradable magnetic nanocomposites is a promising rising field for biomedical applications due to the magnetic response properties of the materials that could provide external physical stimulations as an alternative. This project seeks to investigate the application potential of biodegradable magnetic nanocomposites for bone and cartilage tissue regeneration. Different weight percent of polyvinyl alcohol (PVA) was used to modify the surface of superparamagnetic nanoparticles to reduce aggregation and increase dispersibility in polymer solutions for the synthesis of magnetic nanocomposites. The results showed that 30 wt% of PVA coating was able to provide the best dispersibility compared to all other groups. Hydrogel-based magnetic nanocomposites were synthesized and the cytocompatibility of magnetic nanocomposite hydrogel with bone marrow-derived mesenchymal stem cells (BMSCs) was higher than pure hydrogel. However, both the hydrogel and magnetic nanocomposite hydrogel completely lost structural integrity within 24 hours of culture with BMSCs, which made it difficult for in vivo cell delivery. Another polymer, poly(glycerol sebacate) (PGS) was studied due to its reported elastomeric property. Initial study showed that magnetic PGS nanocomposites without any surface features had low cell adherence. Thus porous structures were created in magnetic PGS nanocomposites to increase cell adhesion. Different weight percent of magnetic nanoparticles (MNPs)-incorporated PGS nanocomposites were synthesized to investigate the effect of MNPs concentration on BMSC proliferation and differentiation behaviors with and without exposure to external electromagnetic field (EMF). The 3-week study showed that BMSCs cultured in magnetic PGS nanocomposite groups had slightly lower cell density but increased ALP activity, calcium deposition, protein and collagen secretion, indicating positive induction towards osteogenesis. This project presented promising porous magnetic PGS nanocomposite scaffolds for bone and cartilage tissue engineering applications

Machine-Learning-Enabled Design and Manipulation of a Microfluidic Concentration Gradient Generator

Microfluidics concentration gradient generators have been widely applied in chemical and biological fields. However, the current gradient generators still have some limitations. In this work, we presented a microfluidic concentration gradient generator with its corresponding manipulation process to generate an arbitrary concentration gradient. Machine-learning techniques and interpolation algorithms were implemented to help researchers instantly analyze the current concentration profile of the gradient generator with different inlet configurations. The proposed method has a 93.71% accuracy rate with a 300× acceleration effect compared to the conventional finite element analysis. In addition, our method shows the potential application of the design automation and computer-aided design of microfluidics by leveraging both artificial neural networks and computer science algorithms

Acoustic Imaging Using the Built-In Sensors of a Smartphone

Thanks to the rapid development of the semiconductor industry, smartphones have become an indispensable part of our lives with their increasing computational power, 5G connection, multiple integrated sensors, etc. The boundary of the functionalities of a smartphone is beyond our imagination again and again as the new smartphone is introduced. In this work, we introduce an acoustic imaging algorithm by only using the built-in sensors of a smartphone without any external equipment. First, the speaker of the smartphone is used to emit sound waves with a specific frequency band. During the movement of the smartphone, the accelerometer collects acceleration data to reconstruct the trajectories of the movements, while the microphones receive the reflected waves. A microphone plus an accelerometer are able to partially replace the functionality of a microphone array and to become a symmetry-imitation system. After scanning, a series of algorithms are implemented to generate a heat map, which outlines the target object. Our algorithm demonstrates the feasibility of smartphone-based acoustic imaging with minimal equipment complexity and no additional cost, which is beneficial to the promotion and popularization of acoustic imaging technology in daily applications

ANN-Based Instantaneous Simulation of Particle Trajectories in Microfluidics

Microfluidics has shown great potential in cell analysis, where the flowing path in the microfluidic device is important for the final study results. However, the design process is time-consuming and labor-intensive. Therefore, we proposed an ANN method with three dense layers to analyze particle trajectories at the critical intersections and then put them together with the particle trajectories in straight channels. The results showed that the ANN prediction results are highly consistent with COMSOL simulation results, indicating the applicability of the proposed ANN method. In addition, this method not only shortened the simulation time but also lowered the computational expense, providing a useful tool for researchers who want to receive instant simulation results of particle trajectories

Graphdiyne Ink for Ionic Liquid Gated Printed Transistor

Graphdiyne‐based electronic devices have recently attracted a lot of research interest due to their excellent performance and promising application prospects in carbon electronics. Here, graphdiyne (GDY) inks are prepared by solution processing of newly grown GDY material, which is suitable for fabricating fully printed thin‐film field‐effect transistor (FET). An ionic liquid gate dielectric is used as a gate to maintain stable on/off ratios at different V SD compared to conventional SiO2 dielectric. Significantly, the GDY network combined with ionic liquid allows a general and cheap approach to achieve printed FET devices containing 2D carbon materials. Furthermore, a flexible FET on polyethylene terephthalate is developed, which still reaches a repeatable on/off ratio of more than 102. These results enable the design of wearable or large‐area carbon‐based electronics involving graphdiyne semiconductors, suggesting a promising new carbon material for novel electronic devices.This study was supported by the National Natural Science Foundation of China (51802324, 21790050, 21790051, 51822208, 21771187), the Frontier Science Research Project (QYZDB-SSW-JSC052) of the Chinese Academy of Sciences, and the Taishan Scholars Program of Shandong Province (tsqn201812111)