Optimization and Characterization of a Layer-by-Layer, Fully Printed, Secondary Zn-MnO2 Battery with an Ionic Liquid Gel Polymer Electrolyte for Internet of Things Applications

Advancements in manufacturing for printed electronics have brought with it a demand for printed, rechargeable batteries capable of powering these devices. This research aims to meet this demand by characterizing and optimizing components and performance of a printed, rechargeable Zn-MnO2 cell with an ionic liquid gel polymer electrolyte.The cathode and anode are comprised of manganese dioxide (MnO2) and zinc (Zn) respectively. The ionic liquids 1-butyl-3-methylimidazolium trifluoromethanesulfonate ([BMIM]+[OTf]-) and 1-ethyl-3-methylimidazolium trifluoromethanesulfonate ([EMIM]+[OTf]-) with the dissolved salt zinc trifluoromethanesulfonate (Zn(OTf)2) are used as the electrolyte. These nonaqueous electrolytes have been shown to enable rechargeable zinc chemistries as well as compatibility with solution-cast polymer membranes to form gel polymer electrolytes (GPEs). When combined with poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) that is dissolved in n-methyl-2-pyrrolidone, a printable separator membrane capable of ionic conductance is produced. This separator membrane can then be incorporated into a layer-by-layer additive manufacturing process to produce a fully printed battery.To produce consistent fully printed cells and to prevent catastrophic cell degradation and failure, additional variables must be considered and optimized. The printed electrode composition must be optimized for surface profile, rheology, and electric conductivity in order to enable uniform and dense separator layers. The ionic liquid electrolyte composition and gel polymer electrolyte morphology must be controlled in order to optimize mass transport and reaction kinetics. Furthermore, the mass transport and kinetic properties of Zn deposition and dissolution in ionic liquid electrolytes and gel polymer electrolytes must be characterized and understood. To characterize these aspects, battery components were produced via stencil casting, doctor blade coating, and solution casting. Electrochemical properties were characterized by cyclic voltammetry, chronoamperometry, and electrochemical impedance spectroscopy. Physical and electric properties were characterized by rheometry, profilometry, four point probe resistivity, and scanning electron microscopy. Cell performance was characterized by galvanostatic and potentiostatic cycle life testing and pulsed current discharging, and differential capacity analysis was performed for further insights.Ball milling and mechanical sieving was found to be an effective method to improve printed electrode surface profile, reducing waviness and roughness each by a factor of 4 compared to unoptimized electrodes while retaining similar conductivity. Zn deposition and dissolution were found to be kinetically (rather than mass transport) limited and therefore quasireversible in both ionic liquids. Zn2+ diffusivity ranged from 1.42-3.38e-9 cm2/s in [BMIM]+[OTf]- electrolytes and from 1.64-4.87e-9 cm2/s in [EMIM]+[OTf]- electrolytes, decreasing with higher concentrations of Zn(Otf)2 salt. [EMIM]+[OTf]- electrolytes were found to provide higher Zn diffusivity, ionic conductivity, and redox kinetics, but were also more prone to forming electrical shorts through the GPE and offered lower discharge capacities than [BMIM]+[OTf]- electrolytes. The polymer structure in the GPE was found to be highly dependent on processing temperature and pressure.Fully printed cells were produced that prevented catastrophic cell failure from delamination of the cathode, resulting in at least a 20x improvement in cycle life compared to mechanically assembled cells. Average discharge capacities for fully printed cells ranged from 1.8-3.6 mAh/cm3, and cells were cycled at least 200 times without catastrophic failure. Critical cell failure mechanisms including phase transformations of MnO2 and deposition of Zn within poor GPE microstructures were identified. Finally, printed cells were discharged under a pulsed current discharge regime typical of those found in Internet of Things devices for 650 cycles without signs of degradation.This research has successfully produced and characterized fully printed, rechargeable, Zn-MnO2 cells with an ionic liquid gel polymer electrolyte for printed electronics and the Internet of Things. The results presented herein seek to further understanding of Zn interactions with ionic liquid gel polymer electrolytes and additive manufacturing methods for printed energy storage devices

Acoustic Classification of Mosquitoes using Convolutional Neural Networks Combined with Activity Circadian Rhythm Information

Many researchers have used sound sensors to record audio data from insects, and used these data as inputs of machine learning algorithms to classify insect species. In image classification, the convolutional neural network (CNN), a well-known deep learning algorithm, achieves better performance than any other machine learning algorithm. This performance is affected by the characteristics of the convolution filter (ConvFilter) learned inside the network. Furthermore, CNN performs well in sound classification. Unlike image classification, however, there is little research on suitable ConvFilters for sound classification. Therefore, we compare the performances of three convolution filters, 1D-ConvFilter, 3×1 2D-ConvFilter, and 3×3 2D-ConvFilter, in two different network configurations, when classifying mosquitoes using audio data. In insect sound classification, most machine learning researchers use only audio data as input. However, a classification model, which combines other information such as activity circadian rhythm, should intuitively yield improved classification results. To utilize such relevant additional information, we propose a method that defines this information as a priori probabilities and combines them with CNN outputs. Of the networks, VGG13 with 3×3 2D-ConvFilter showed the best performance in classifying mosquito species, with an accuracy of 80.8%. Moreover, adding activity circadian rhythm information to the networks showed an average performance improvement of 5.5%. The VGG13 network with 1D-ConvFilter achieved the highest accuracy of 85.7% with the additional activity circadian rhythm information

The Role of Epigenetic Changes in the Progression of Alcoholic Steatohepatitis

Alcoholic steatohepatitis (ASH) is a progression hepatitis with severe fatty liver and its mortality rate for 30-days in patients are over 30%. Additionally, ASH is well known for one-fifth all alcoholic related liver diseases in the world. Excessive chronic alcohol consumption is one of the most common causes of the progression of ASH and is associated with poor prognosis and liver failure. Alcohol abuse dysregulates the lipid homeostasis and causes oxidative stress and inflammation in the liver. Consequently, metabolic pathways stimulating hepatic accumulation of excessive lipid droplets are induced. Recently, many studies have indicated a link between ASH and epigenetic changes, showing differential expression of alcohol-induced epigenetic genes in the liver. However, the specific mechanisms underlying the pathogenesis of ASH remain elusive. Thus, we here summarize the current knowledge about the roles of epigenetics in lipogenesis, inflammation, and apoptosis in the context of ASH pathophysiology. Especially, we highlight the latest findings on the roles of Sirtuins, a conserved family of class-III histone deacetylases, in ASH. Additionally, we discuss the involvement of DNA methylation, histone modifications, and miRNAs in ASH as well as the ongoing efforts for the clinical translation of the findings in ASH-related epigenetic changes

Mutual authentication protocol for low-cost RFID.

Abstract-Radio frequency identification (RFID) is the latest technology to play an importan

Caractérisation morphologique de l'usure des freins

Lors du dimensionnement d'un système de freinage, la géométrie de la garniture est modélisée classiquement avec une surface de contact plane. Hors dans la réalité la surface des garnitures des plaquettes présente une morphologie fortement hétérogène et stochastique. Cette hétérogénéité provient, directement de la constitution et du mode de fabrication de ces dernières. De plus, en service, les garnitures de freins s'usent. Les mécanismes d'usures sont complexes et ne seront pas abordés dans cette étude. Il en résulte une modification continue de la surface de la plaquette tout au long de sa vie en service. L'objectif de ce travail était de mettre en place une méthode de caractérisation de l'état de surface des plaquettes de frein. Cette méthode doit permettre de caractériser, la morphologie d'une part à grande échelle (l'échelle de la plaquette) et d'autre part à plus petite échelle (l'échelle de la rugosité). Pour notre étude nous avions à disposition trois jeux de quatre plaquettes utilisées dans le système de freinage du train de roues de devant d'un véhicule. Un premier jeu constitué de plaquettes neuves. Les deux autres jeux sont issus de tests réalisés chez Hyundai Motors. La procédure est inspirée du test standardisé SAE J2521 (Disc and Drum Brake Dynamometer Squeal Noise Test Procedure). Le nombre de freinage est de 400 pour le premier jeu de plaquettes et de 2600 pour le second. Pour la morphologie à grande échelle, nous avons utilisé un système optique à variation de focus (InfiniteFocus, Alicona?) en utilisant un faible grossissement. Cet appareil nous a permis de mesurer la morphologie sur une grande surface : typiquement, une demi plaquette (29 cm²). Cette surface est reconstruite par assemblage d'images avec chevauchement. Cette méthode de reconstruction d'image est appelée ""stitching"". Pour la rugosité à petite échelle, nous avons effectué les mesures sur un interféromètre en lumière blanche (NewView7300, Zygo ?). Un grossissement 5 fois plus important est utilisé. Sur chaque demie-plaquette nous avons mesuré neufs zones de 5x5 mm² constituées chacune de 30X22 images individuelles se chevauchant (méthode de ""stiching""). Les surfaces ont été choisies pour quadriller d'une façon homogène la plaquette.   Les mesures des morphologies réalisées par variation de focus nous ont permis d'accéder aux profils des garnitures des plaquettes de frein. Ces mesures ont également mis en évidence différentes zones morphologiques sur la surface d'une même plaquette. En interférométrie les mesures ont été traités avec le logiciel MesRug. Cette analyse multi-échelle a permis de classer les différentes zones de la plaquette et de ressortir le paramètre de rugosité (norme ISO 25178) caractéristique

Controlled DNA double-strand break induction in mice reveals post-damage transcriptome stability

DNA double-strand breaks (DSBs) and their repair can cause extensive epigenetic changes. As a result, DSBs have been proposed to promote transcriptional and, ultimately, physiological dysfunction via both cell-intrinsic and cell-non-autonomous pathways. Studying the consequences of DSBs in higher organisms has, however, been hindered by a scarcity of tools for controlled DSB induction. Here, we describe a mouse model that allows for both tissue-specific and temporally controlled DSB formation at ∼140 defined genomic loci. Using this model, we show that DSBs promote a DNA damage signaling-dependent decrease in gene expression in primary cells specifically at break-bearing genes, which is reversed upon DSB repair. Importantly, we demonstrate that restoration of gene expression can occur independently of cell cycle progression, underlining its relevance for normal tissue maintenance. Consistent with this, we observe no evidence for persistent transcriptional repression in response to a multi-day course of continuous DSB formation and repair in mouse lymphocytes in vivo. Together, our findings reveal an unexpected capacity of primary cells to maintain transcriptome integrity in response to DSBs, pointing to a limited role for DNA damage as a mediator of cell-autonomous epigenetic dysfunction

Extracting Knowledge from the Geometric Shape of Social Network Data Using Topological Data Analysis

Topological data analysis is a noble approach to extract meaningful information from high-dimensional data and is robust to noise. It is based on topology, which aims to study the geometric shape of data. In order to apply topological data analysis, an algorithm called mapper is adopted. The output from mapper is a simplicial complex that represents a set of connected clusters of data points. In this paper, we explore the feasibility of topological data analysis for mining social network data by addressing the problem of image popularity. We randomly crawl images from Instagram and analyze the effects of social context and image content on an image’s popularity using mapper. Mapper clusters the images using each feature, and the ratio of popularity in each cluster is computed to determine the clusters with a high or low possibility of popularity. Then, the popularity of images are predicted to evaluate the accuracy of topological data analysis. This approach is further compared with traditional clustering algorithms, including k-means and hierarchical clustering, in terms of accuracy, and the results show that topological data analysis outperforms the others. Moreover, topological data analysis provides meaningful information based on the connectivity between the clusters.https://doi.org/10.3390/e1907036

Optimization and Characterization of a Layer-by-Layer, Fully Printed, Secondary Zn-MnO2 Battery with an Ionic Liquid Gel Polymer Electrolyte for Internet of Things Applications

Advancements in manufacturing for printed electronics have brought with it a demand for printed, rechargeable batteries capable of powering these devices. This research aims to meet this demand by characterizing and optimizing components and performance of a printed, rechargeable Zn-MnO2 cell with an ionic liquid gel polymer electrolyte.The cathode and anode are comprised of manganese dioxide (MnO2) and zinc (Zn) respectively. The ionic liquids 1-butyl-3-methylimidazolium trifluoromethanesulfonate ([BMIM]+[OTf]-) and 1-ethyl-3-methylimidazolium trifluoromethanesulfonate ([EMIM]+[OTf]-) with the dissolved salt zinc trifluoromethanesulfonate (Zn(OTf)2) are used as the electrolyte. These nonaqueous electrolytes have been shown to enable rechargeable zinc chemistries as well as compatibility with solution-cast polymer membranes to form gel polymer electrolytes (GPEs). When combined with poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) that is dissolved in n-methyl-2-pyrrolidone, a printable separator membrane capable of ionic conductance is produced. This separator membrane can then be incorporated into a layer-by-layer additive manufacturing process to produce a fully printed battery.To produce consistent fully printed cells and to prevent catastrophic cell degradation and failure, additional variables must be considered and optimized. The printed electrode composition must be optimized for surface profile, rheology, and electric conductivity in order to enable uniform and dense separator layers. The ionic liquid electrolyte composition and gel polymer electrolyte morphology must be controlled in order to optimize mass transport and reaction kinetics. Furthermore, the mass transport and kinetic properties of Zn deposition and dissolution in ionic liquid electrolytes and gel polymer electrolytes must be characterized and understood. To characterize these aspects, battery components were produced via stencil casting, doctor blade coating, and solution casting. Electrochemical properties were characterized by cyclic voltammetry, chronoamperometry, and electrochemical impedance spectroscopy. Physical and electric properties were characterized by rheometry, profilometry, four point probe resistivity, and scanning electron microscopy. Cell performance was characterized by galvanostatic and potentiostatic cycle life testing and pulsed current discharging, and differential capacity analysis was performed for further insights.Ball milling and mechanical sieving was found to be an effective method to improve printed electrode surface profile, reducing waviness and roughness each by a factor of 4 compared to unoptimized electrodes while retaining similar conductivity. Zn deposition and dissolution were found to be kinetically (rather than mass transport) limited and therefore quasireversible in both ionic liquids. Zn2+ diffusivity ranged from 1.42-3.38e-9 cm2/s in [BMIM]+[OTf]- electrolytes and from 1.64-4.87e-9 cm2/s in [EMIM]+[OTf]- electrolytes, decreasing with higher concentrations of Zn(Otf)2 salt. [EMIM]+[OTf]- electrolytes were found to provide higher Zn diffusivity, ionic conductivity, and redox kinetics, but were also more prone to forming electrical shorts through the GPE and offered lower discharge capacities than [BMIM]+[OTf]- electrolytes. The polymer structure in the GPE was found to be highly dependent on processing temperature and pressure.Fully printed cells were produced that prevented catastrophic cell failure from delamination of the cathode, resulting in at least a 20x improvement in cycle life compared to mechanically assembled cells. Average discharge capacities for fully printed cells ranged from 1.8-3.6 mAh/cm3, and cells were cycled at least 200 times without catastrophic failure. Critical cell failure mechanisms including phase transformations of MnO2 and deposition of Zn within poor GPE microstructures were identified. Finally, printed cells were discharged under a pulsed current discharge regime typical of those found in Internet of Things devices for 650 cycles without signs of degradation.This research has successfully produced and characterized fully printed, rechargeable, Zn-MnO2 cells with an ionic liquid gel polymer electrolyte for printed electronics and the Internet of Things. The results presented herein seek to further understanding of Zn interactions with ionic liquid gel polymer electrolytes and additive manufacturing methods for printed energy storage devices

The histone variant macroH2A1 is a splicing-modulated caretaker of genome integrity and tumor growth

The macroH2A1.2 histone variant facilitates the response to replication stress with implications for genome maintenance and cell growth. A mutually exclusive splice variant, macroH2A1.1, has opposing effects on DNA repair outcome and proliferation. Here we discuss the potential impact of splicing-modulated macroH2A1 chromatin organization for cell function and malignant transformation