Water/Ethanol-Soluble NDI-Based Polymer Acceptors for Eco-Friendly and Air-Stable All-Polymer Solar Cells

이승진,김영웅,Ziang Wu,이창연,오승진,Nguyen Thanh Luan,이준복,정다현,Kai Zhang,Fei Huang,Taek-Soo Kim,우한영,김범준 한국고분자학회 2020 한국고분자학회 학술대회 연구논문 초록집 Vol.45 No.2

Fluorine-Substituted Dithienylbenzodiimide-Based n-Type Polymer Semiconductors for Organic Thin-Film Transistors

Feng, Kui,Zhang, Xianhe,Wu, Ziang,Shi, Yongqiang,Su, Mengyao,Yang, Kun,Wang, Yang,Sun, Huiliang,Min, Jie,Zhang, Yujie,Cheng, Xing,Woo, Han Young,Guo, Xugang American Chemical Society 2019 ACS APPLIED MATERIALS & INTERFACES Vol.11 No.39

<P>Imide functionalization is one of the most effective approaches to develop electron-deficient building blocks for constructing n-type organic semiconductors. Driven by the attractive properties of imide-functionalized dithienylbenzodiimide (TBDI) and the promising device performance of TBDI-based polymers, a novel acceptor with increased electron affinity, fluorinated dithienylbenzodiimide (TFBDI), was designed with the hydrogen replaced by fluorine on the benzene core, and the synthetic challenges associated with this highly electron-deficient fluorinated imide building block are successfully overcome. TFBDI showed suppressed frontier molecular orbital energy levels as compared with TBDI. Copolymerizing this new electron-withdrawing TBDI with various donor co-units afforded a series of n-type polymer semiconductors TFBDI-T, TFBDI-Se, and TFBDI-BSe. All these TFBDI-based polymers exhibited a lower-lying lowest unoccupied molecular orbital (LUMO) energy level than the polymer analogue without fluorine. When applied in organic thin-film transistors, three polymers showed unipolar electron transport with large on-current/off-current ratios (<I>I</I><SUB>on</SUB>/<I>I</I><SUB>off</SUB>) of 10<SUP>5</SUP>-10<SUP>7</SUP>. Among them, the selenophene-based polymer TFBDI-Se with the deepest-positioned LUMO and optimal chain stacking exhibited the highest electron mobility of 0.30 cm<SUP>2</SUP> V<SUP>-1</SUP> s<SUP>-1</SUP>. This result demonstrates that the new TFBDI is a highly attractive electron-deficient unit for enabling n-type polymer semiconductors, and the fluorination of imide-functionalized arenes offers an effective approach to develop more electron-deficient building blocks in organic electronics.</P> [FIG OMISSION]</BR>

Aqueous-Soluble Naphthalene Diimide-Based Polymer Acceptors for Efficient and Air-Stable All-Polymer Solar Cells

Lee, Seungjin,Kim, Youngwoong,Wu, Ziang,Lee, Changyeon,Oh, Seung Jin,Luan, Nguyen Thanh,Lee, Junbok,Jeong, Dahyun,Zhang, Kai,Huang, Fei,Kim, Taek-Soo,Woo, Han Young,Kim, Bumjoon J. American Chemical Society 2019 ACS APPLIED MATERIALS & INTERFACES Vol.11 No.48

<P>Aqueous-processed all-polymer solar cells (aq-APSCs) are reported for the first time by developing a series of water/ethanol-soluble naphthalenediimide (NDI)-based polymer acceptors [P(NDIDEG-T), P(NDITEG-T), and P(NDITEG-T2)]. Polymer acceptors are designed by using the backbones of NDI-bithiophene and NDI-thiophene in combination with nonionic hydrophilic oligoethylene glycol (OEG) side chains that facilitate processability in water/ethanol mixtures. All three polymers exhibit sufficient solubility (20-50 mg mL<SUP>-1</SUP>) in the aqueous medium. The P(NDIDEG-T) polymer with shorter OEG side chains is the most crystalline with the highest electron mobility, enabling the fabrication of efficient aq-APSCs with the maximum power conversion efficiency (PCE) of 2.15%. Furthermore, these aq-APSCs are fabricated under ambient atmosphere by taking advantage of the eco-friendly aqueous process and, importantly, the devices exhibit outstanding air-stability without any encapsulation, as evident by maintaining more than 90% of the initial PCE in the air after 4 days. According to a double cantilever beam test, the interfacial adhesion properties between the active layer and electron/hole transporting layers were remarkably improved by incorporating the hydrophilic OEG-attached photoactive layer, which hinders the delamination of the constituent layers and prevents the increase of series resistance, ultimately leading to enhanced durability under ambient conditions. The combination of increased device stability and minimal environmental impact of these aq-APSCs demonstrates them to be worthy candidates for continued development of scalable polymer solar cells.</P> [FIG OMISSION]</BR>

A Low-Computation Indirect Model Predictive Control for Modular Multilevel Converters

Ma, Wenzhong,Sun, Peng,Zhou, Guanyu,Sailijiang, Gulipali,Zhang, Ziang,Liu, Yong The Korean Institute of Power Electronics 2019 JOURNAL OF POWER ELECTRONICS Vol.19 No.2

The modular multilevel converter (MMC) has become a promising topology for high-voltage direct current (HVDC) transmission systems. To control a MMC system properly, the ac-side current, circulating current and submodule (SM) capacitor voltage are taken into consideration. This paper proposes a low-computation indirect model predictive control (IMPC) strategy that takes advantages of the conventional MPC and has no weighting factors. The cost function and duty cycle are introduced to minimize the tracking error of the ac-side current and to eliminate the circulating current. An optimized merge sort (OMS) algorithm is applied to keep the SM capacitor voltages balanced. The proposed IMPC strategy effectively reduces the controller complexity and computational burden. In this paper, a discrete-time mathematical model of a MMC system is developed and the duty ratio of switching state is designed. In addition, a simulation of an eleven-level MMC system based on MATLAB/Simulink and a five-level experimental setup are built to evaluate the feasibility and performance of the proposed low-computation IMPC strategy.

A Low-Computation Indirect Model Predictive Control for Modular Multilevel Converters

Wenzhong Ma,Peng Sun,Guanyu Zhou,Gulipali Sailijiang,Ziang Zhang,Yong Liu 전력전자학회 2019 JOURNAL OF POWER ELECTRONICS Vol.19 No.2

The modular multilevel converter (MMC) has become a promising topology for high-voltage direct current (HVDC) transmission systems. To control a MMC system properly, the ac-side current, circulating current and submodule (SM) capacitor voltage are taken into consideration. This paper proposes a low-computation indirect model predictive control (IMPC) strategy that takes advantages of the conventional MPC and has no weighting factors. The cost function and duty cycle are introduced to minimize the tracking error of the ac-side current and to eliminate the circulating current. An optimized merge sort (OMS) algorithm is applied to keep the SM capacitor voltages balanced. The proposed IMPC strategy effectively reduces the controller complexity and computational burden. In this paper, a discrete-time mathematical model of a MMC system is developed and the duty ratio of switching state is designed. In addition, a simulation of an eleven-level MMC system based on MATLAB/Simulink and a five-level experimental setup are built to evaluate the feasibility and performance of the proposed low-computation IMPC strategy.

Development, Validation and Comparison of Artificial Neural Network and Logistic Regression Models Predicting Eosinophilic Chronic Rhinosinusitis With Nasal Polyps

Zhou Huiqin,Fan Wenjun,Qin Danxue,Liu Peiqiang,Gao Ziang,Lv Hao,Zhang Wei,Xiang Rong,Xu Yu 대한천식알레르기학회 2023 Allergy, Asthma & Immunology Research Vol.15 No.1

Purpose: Chronic rhinosinusitis with nasal polyps (CRSwNP) can be classified into eosinophilic CRSwNP (eCRSwNP) and non-eosinophilic CRSwNP (non-eCRSwNP) by tissue biopsy, which is difficult to perform preoperatively. Clinical biomarkers have predictive value for the classification of CRSwNP. We aimed to evaluate the application of artificial neural network (ANN) modeling in distinguishing different endotypes of CRSwNP based on clinical biomarkers. Methods: Clinical parameters were collected from 109 CRSwNP patients, and their predictive ability was analyzed. ANN and logistic regression (LR) models were developed in the training group (72 patients) and further tested in the test group (37 patients). The output variable was the diagnosis of eCRSwNP, defined as tissue eosinophil count > 10 per high-power field. The receiver operating characteristics curve was used to assess model performance. Results: A total of 15 clinical features from 60 healthy controls, 60 eCRSwNP and 49 non-eCRSwNP were selected as candidate predictors. Nasal nitric oxide levels, peripheral eosinophil absolute count, total immunoglobulin E, and ratio of bilateral computed tomography scores for the ethmoid sinus and maxillary sinus were identified as important features for modeling. Two ANN models based on 4 and 15 clinical features were developed to predict eCRSwNP, which showed better performance, with the area under the receiver operator characteristics significantly higher than those from the respective LR models (0.976 vs. 0.902, P = 0.048; 0.970 vs. 0.845, P = 0.011). All ANN models had better fits than single variable prediction models (all P < 0.05), and ANN model 1 had the best predictive performance among all models. Conclusions: Machine learning models assist clinicians in predicting endotypes of nasal polyps before invasive detection. The ANN model has the potential to predict eCRSwNP with high sensitivity and specificity, and is superior to the LR model. ANNs are valuable for optimizing personalized patient management.