Nonflammable Lithium Metal Full Cells with Ultra-high Energy Density Based on Coordinated Carbonate Electrolytes

Coupling thin Li metal anodes with high-capacity/high-voltage cathodes such as LiNi0.8Co0.1Mn0.1O2 (NCM811) is a promising way to increase lithium battery energy density. Yet, the realization of high-performance full cells remains a formidable challenge. Here, we demonstrate a new class of highly coordinated, nonflammable carbonate electrolytes based on lithium bis(fluorosulfonyl)imide (UFSI) in propylene carbonate/fluoroethylene carbonate mixtures. Utilizing an optimal salt concentr ation (4 M LiFSI) of the electrolyte results in a unique coordination structure of Li+-FSI-solvent cluster, which is critical for enabling the formation of stable interfaces on both the thin Li metal anode and high-voltage NCM811 cathode. Under highly demanding cell configuration and operating conditions (Li metal anode = 35 mu m, areal capacity/charge voltage of NCM811 cathode = 4.8 mAh cm(-2)/4 .6 V, and anode excess capacity [relative to the cathode] = 0.83), the Li metal-based full cell provides exceptional electrochemical performance (energy densities = 679 Wh kg(cell)(-1)/1,024 Wh L-cell(-1)) coupled with nonflammability

Seismic evaluation of asymmetric wall systems using a modified three-dimensional capacity spectrum method

This paper proposes a modified three-dimensional capacity spectrum method to efficiently evaluate the seismic behavior of a building structure with asymmetric walls, where twisting is induced due to lateral loading. This method utilizes the demand surfaces and capacity curves that are created based on the inelastic earthquake response and seismic capacity of the asymmetric wall system, respectively. These two parameters are calculated from the displacement, torsional rotation angle and force coordinates of the structure under seismic loading. The seismic retrofit strategy of existing structures can be effectively determined by applying the proposed three-dimensional capacity spectrum method. In this procedure, a new performance point indicating the enhanced performance of the structure can be easily found by the modification of demand surfaces or capacity curves. The seismic evaluation and retrofitting strategies based on this approach are also discussed

Lattice-patterned LC-polymer composites containing various nanoparticles as additives

In this study, we show the effect of various nanoparticle additives on phase separation behavior of a lattice-patterned liquid crystal [LC]-polymer composite system and on interfacial properties between the LC and polymer. Lattice-patterned LC-polymer composites were fabricated by exposing to UV light a mixture of a prepolymer, an LC, and SiO2 nanoparticles positioned under a patterned photomask. This resulted in the formation of an LC and prepolymer region through phase separation. We found that the incorporation of SiO2 nanoparticles significantly affected the electro-optical properties of the lattice-patterned LC-polymer composites. This effect is a fundamental characteristic of flexible displays. The electro-optical properties depend on the size and surface functional groups of the SiO2 nanoparticles. Compared with untreated pristine SiO2 nanoparticles, which adversely affect the performance of LC molecules surrounded by polymer walls, SiO2 nanoparticles with surface functional groups were found to improve the electro-optical properties of the lattice-patterned LC-polymer composites by increasing the quantity of SiO2 nanoparticles. The surface functional groups of the SiO2 nanoparticles were closely related to the distribution of SiO2 nanoparticles in the LC-polymer composites, and they influenced the electro-optical properties of the LC molecules. It is clear from our work that the introduction of nanoparticles into a lattice-patterned LC-polymer composite provides a method for controlling and improving the composite's electro-optical properties. This technique can be used to produce flexible substrates for various flexible electronic devices

Grouping-matrix based Graph Pooling with Adaptive Number of Clusters

Graph pooling is a crucial operation for encoding hierarchical structures within graphs. Most existing graph pooling approaches formulate the problem as a node clustering task which effectively captures the graph topology. Conventional methods ask users to specify an appropriate number of clusters as a hyperparameter, then assume that all input graphs share the same number of clusters. In inductive settings where the number of clusters can vary, however, the model should be able to represent this variation in its pooling layers in order to learn suitable clusters. Thus we propose GMPool, a novel differentiable graph pooling architecture that automatically determines the appropriate number of clusters based on the input data. The main intuition involves a grouping matrix defined as a quadratic form of the pooling operator, which induces use of binary classification probabilities of pairwise combinations of nodes. GMPool obtains the pooling operator by first computing the grouping matrix, then decomposing it. Extensive evaluations on molecular property prediction tasks demonstrate that our method outperforms conventional methods.Comment: 10 pages, 3 figure

Data-driven risk assessment of the incursion of African swine fever virus via pig products brought illegally into South Korea by travelers based on the temporal relationship between outbreaks in China

Since 2018, Asian countries have been affected by the African swine fever (ASF) virus, with major socioeconomic consequences. Moreover, the number of people traveling in Asian countries has been increasing, leading to an inevitable increase in the risk of ASF spread through livestock products carried by travelers. China and South Korea have close geo-economic ties and numerous international travelers. After the ASF outbreak in China in 2018, many illegally imported pig products (IIPPs) that were confiscated from travelers from China at the port of entry in South Korea tested positive for ASF. The detection of ASF virus (ASFV)-positive IIPPs highlights the need to further assess the risk of incursion by travelers and review the existing prevention strategies. Here, we investigated the temporal relationship between ASF outbreaks in China and the detection of ASFV-positive IIPPs in randomly confiscated samples from all ports of entry, such as flights and ships to South Korea, from 2018 to 2019 using a cross-correlation analysis. Based on the significantly correlated temporal lags between the bivariate time-series data, a risk assessment model, using the Bayesian framework, was built to estimate the distribution of the parameters for the risk assessment model and the monthly probability of ASF being introduced via IIPPs from China to South Korea. ASF outbreaks in China were significantly associated with the detection of ASFV-positive IIPPs in South Korea 5 months later. Hence, the monthly probability of ASFV-infected pig products imported from China via a traveler to South Korea was estimated to be 2.00 × 10−5, corresponding to a 0.98 mean monthly probability of at least one ASF-infected pig product arriving at ports of entry via travelers, from 2018 to 2019. To our knowledge, this study is the first attempt to estimate the risk of ASF introduction via pig products carried by international travelers to all ports from neighboring countries in the Asian region using commonly exchanged observed data. The data presented in this study can be used to refine the intervention strategies to combat the spread of transboundary animal diseases

Sex- and Age-Related Changes in Connexin 43 Expression in Normal Rat Bladder

Purpose Gap junctions are intercellular channels to facilitate electrical and metabolic communication between adjacent cells. Connexin 43 is the most predominant type of connexin expressed on rat detrusor muscle cells. We investigated the connexin 43 expressions in various age groups of either sex in normal rats. Methods Eighty Sprague-Dawley rats were used for analysis. Each group was quantified by 8 rats at 1 week, 2 weeks, 1 month, 3 months, and 6 months of age in either sex. In each animal, bladder was removed without any kind of intervention and fresh-frozen in liquid nitrogen. Total RNA extraction was done with easy-BLUE total RNA extraction kit. Reverse transcription polymerase chain reaction was done for connexin 43 and glyceraldehyde-3-phosphate dehydrogenase as an internal control using ImProm-II Reverse Transcription System. Results In female rats, no age-related change was detected in connexin 43 expressions. In male rats, connexin expression at 3 months of age showed significant decrease compared with 1 week, 2 weeks, and 6 months of age (P<0.05). When connexin expression at the same age in male and female were compared, only 3 months group in male showed significant decrease than the same age group in female. Conclusions Our data suggest that the expressions of connexin 43 mRNA in normal detrusor muscle cell showed age-related changes especially in male rats. Although it is difficult to interpret these findings at this stage, age should be considered as a possible compounding factor affecting connexin 43 expressions in male rats

3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation

Pretraining molecular representations from large unlabeled data is essential for molecular property prediction due to the high cost of obtaining ground-truth labels. While there exist various 2D graph-based molecular pretraining approaches, these methods struggle to show statistically significant gains in predictive performance. Recent work have thus instead proposed 3D conformer-based pretraining under the task of denoising, which led to promising results. During downstream finetuning, however, models trained with 3D conformers require accurate atom-coordinates of previously unseen molecules, which are computationally expensive to acquire at scale. In light of this limitation, we propose D&D, a self-supervised molecular representation learning framework that pretrains a 2D graph encoder by distilling representations from a 3D denoiser. With denoising followed by cross-modal knowledge distillation, our approach enjoys use of knowledge obtained from denoising as well as painless application to downstream tasks with no access to accurate conformers. Experiments on real-world molecular property prediction datasets show that the graph encoder trained via D&D can infer 3D information based on the 2D graph and shows superior performance and label-efficiency against other baselines.Comment: 16 pages, 5 figure

Molecular orientation of liquid crystal on polymer blends of coumarin and naphthalenic polyimide

Photo-induced liquid crystal alignment layers were prepared by blending polyimides and photoreactive polymers followed by polarized UV irradiation. Polyimides are selected for the purpose of improving the thermal stability of the molecular orientation of the photoreactive groups. The thermal stability of the LC alignment layer was enhanced regardless of the type of the polyimide while the direction of LC orientation was dependent on the type of polyimide. The photoreactivity of the polyimide governs the LC orientation in the blend alignment layers. © 2008 Springer-Verlag.1

Nest entry shape change may cause nest abandonment in urban cavity-nesting species: a case study of the Tree Sparrow Passer montanus

The threat of predation is the main cause of bird nest abandonment, with such behaviour imposing considerable energetic costs on breeding birds. However, for several species, nest abandonment can be a less costly alternative to complete brood failure. In this study, we examined nest abandonment among Eurasian Tree Sparrows (Passer montanus) by surveying 71 Tree Sparrow nests with various types of entry holes and conducted artificially manipulating some of the entrance shapes. We found that nest abandonment was caused by changes to the nest entry shape in seven cases and by human interference in two cases. Nest abandonments occurred throughout the breeding season, and breeding pairs attempted to breed again immediately after nest abandonment. The results of the artificial nest entry shape manipulation experiment showed that nine of twelve nests (75.0%) were abandoned where the nest entrance holes were widened, and six of eleven nests (54.5%) were abandoned where the nest entrance holes were narrowed. However, none of the nests were abandoned where the entry shape was unchanged. Thus, nest abandonment by Tree Sparrows is correlated with nest entry shape manipulation and is more likely to occur when the energy cost of breeding again is less than that of abandoning the nest