Effect of Threshold Voltage Window and Variation of Organic Synaptic Transistor for Neuromorphic System.

Synaptic devices, which are considered as one of the most important components of neuromorphic system, require a memory effect to store weight values, a high integrity for compact system, and a wide window to guarantee an accurate programming between each weight level. In this regard, memristive devices such as resistive random access memory (RRAM) and phase change memory (PCM) have been intensely studied; however, these devices have quite high current-level despite their state, which would be an issue if a deep and massive neural network is implemented with these devices since a large amount of current-sum needs to flow through a single electrode line. Organic transistor is one of the potential candidates as synaptic device owing to flexibility and a low current drivability for low power consumption during inference. In this paper, we investigate the performance and power consumption of neuromorphic system composed of organic synaptic transistors conducting a pattern recognition simulation with MNIST handwritten digit data set. It is analyzed according to threshold voltage (VT) window, device variation, and the number of available states. The classification accuracy is not affected by VT window if the device variation is not considered, but the current sum ratio between answer node and the rest 9 nodes varies. In contrast, the accuracy is significantly degraded as increasing the device variation; however, the classification rate is less affected when the number of device states is fewer.

Common plasma protein marker LCAT in aggressive human breast cancer and canine mammary tumor.

Breast cancer is one of the most frequently diagnosed cancers. Although biomarkers are continuously being discovered, few specific markers, rather than classification markers, representing the aggressiveness and invasiveness of breast cancer are known. In this study, we used samples from canine mammary tumors in a comparative approach. We subjected 36 fractions of both canine normal and mammary tumor plasmas to highperformance quantitative proteomics analysis. Among the identified proteins, LCAT was selectively expressed in mixed tumor samples. With further MRM and Western blot validation, we discovered that the LCAT protein is an indicator of aggressive mammary tumors, an advanced stage of cancer, possibly highly metastatic. Interestingly, we also found that LCAT is overexpressed in high-grade and lymph-node-positive breast cancer in silico data. We also demonstrated that LCAT is highly expressed in the sera of advanced-stage human breast cancers within the same classification. In conclusion, we identified a possible common plasma protein biomarker, LCAT, that is highly expressed in aggressive human breast cancer and canine mammary tumor. [BMB Reports 2020; 53(12): 664-669].

Numerical and experimental analysis of thermal-flow characteristics in a pyrolysis reactor of a gas scrubber designed based on similitude theory.

With the continuous development of the semiconductor industry, interest in the technology for treating various pollutant gases in the semiconductor fabrication process has increased recently. Various gas scrubbers are being used to remove the pollutant gas from the processes. An efficient design of the pyrolysis reactor is crucial in a scrubber system due to the effective removal of pollutant sources and the overall operation stability. In this study, the thermal and flow characteristics in the reactor were examined through experiments and numerical analysis using a small-scale model of simplified pyrolysis reactor. Furthermore, a prototype model of pyrolysis reactor was designed through analysis result of small-scale model based on the similitude theory. The results of this study can be used as basic data for analyzing thermal and flow characteristics in a variety of scrubber systems.Implications: This study investigated and suggested a methodology for designing a pyrolysis reactor of the gas scrubber to overcome the design failure by using the concept of similarity, which can use the results from one system to explain phenomena in another system. We believe that our study makes a significant contribution to the literature because it provides a way to improve the performance of the gas scrubbers and test this performance with a smaller scalable model. And, we expect this study to be used as basic data when applying innovative and new design proposals in various industries.

A numerical study on the behavior of coastal waste particles in a wind-power sorting system for renewable fuel production.

In this study, a Computational Fluid Dynamics (CFD) to analyze the coastal waste particles in a wind-power sorting system is applied to produce renewable fuel using commercial CFD package (ANSYS-CFX code). The numerical methodology results predicted various coastal waste shredded inside the sorting machine. Furthermore, to identify the effect of working conditions on separation characteristics, a parametric study is performed. These study findings will offer appropriate a wind-power sorting conditions according to the purpose of using coastal waste. Under basic conditions, the characteristics of coastal waste particle behavior and the sorting of waste particles were analyzed, and the behavioral changes of diverse particles were identified by changing the airflow rate to improve the sorting performance. As a result, an appropriate airflow rate, Qair = 85 m3/min, at which the change in the airflow rate can simultaneously meet the conditions for both the recovery of the combustibles and the removal of the incombustibles, was selected with the selection efficiency rate was 92%, and the combustibles content was 99%. Based on the results of the analysis, the particle characteristics of sorting were identified to reduce and recycle the coastal waste.

Synthesis of CVD-graphene on rapidly heated copper foils.

Most chemical vapor deposition (CVD) systems used for graphene growth mainly employ convection and radiation heat transfer between the heating source and the metal catalyst in order to reach the activation temperature of the reaction, which in general leads to a long synthesis time and poor energy efficiency. Here, we report a highly time- and energy-efficient CVD setup, in which the metal catalyst (Cu) is designed to be physically contacted with a heating source to give quick heat transfer by conduction. The induced conduction heating enabled the usual effects of the pretreatment and annealing of Cu (i.e., annihilation of surface defects, impurities and contaminants) to be achieved in a significantly shorter time compared to conventional CVD. Notably, the rapid heating was observed to lead to larger grains of Cu with high uniformity as compared to the Cu annealed by conventional CVD, which are believed to be beneficial for the growth of high quality graphene. Through this CVD setup, bundles of high quality (∼252 Ω per square) and large area (over 16 inch) graphenes were able to be readily synthesized in 40 min in a significantly efficient way. When considering ease of scalability, high energy effectiveness and considerable productivity, our method is expected to be welcomed by industrialists.