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| 1 | Regulating the morphology of fluorinated non-fullerene acceptor and polymer donor via binary solvent mixture for high efficiency polymer solar cells显示文摘Fluorinated non-fullerene acceptors(NFAs) usually have planar backbone and a higher tendency to crystallize compared to their non-fluorinated counterparts, which leads to enhanced charge mobility in organic solar cells(OSCs). However, this selforganization behavior may result in excessive phase separation with electron donors and thereby deteriorate device efficiency.Herein, we demonstrate an effective approach to tune the molecular organization of a fluorinated NFA(INPIC-4 F), and its phase separation with the donor PBDB-T, by varying the casting solvent. A prolonged film drying time encourages the crystallization of INPIC-4 F into spherulites and consequently results in excessive phase separation, leading to a low device power conversion efficiency(PCE) of 8.1%. Contrarily, a drying time leads to fine mixed domains with inefficient charge transport properties,resulting in a moderate device PCE of 11.4%. An intermediate film drying time results in the formation of face-on π-π stacked PBDB-T and INPIC-4 F domains with continuous phase-separated networks, which facilitates light absorption, exciton dissociation as well as balanced charge transport towards the electrode, and achieves a remarkable PCE of 13.1%. This work provides a rational guide for optimizing the molecular ordering of NFAs and electron donors for high device efficiency. | Mengxue Chen Zhuohan Zhang Wei Li Jinlong Cai Jiangsheng Yu Emma L. K. Spooner Rachel C. Kilbride Donghui Li Baocai Du Robert S. Gurney Dan Liu Weihua Tang David G. Lidzey Tao Wang | 2019 | Science China Chemistry2019，62，9： | 2 |
| 2 | Enhanced anti-HIV Efficacy of Indinavir by Metabolic Interactions with Herb Medicine and Products显示文摘 | Zhuohan Hu Jusheng Liang Jianan Wei | 2006 | Drug Metabolism Review2006，，38： | 1 |
| 3 | Energy-saving optimal control for a factual electrostatic precipitator with multiple electric-field stages based on GA显示文摘 | Zhuohan Li Cheng Shao Yi An Gaofeng Xu | 2013 | Journal of Process Control2013，，8： | 1 |
| 4 | Nitrogen-doped porous carbons from polyacrylonitrile fiber as effective CO_(2) adsorbents显示文摘In this report, nitrogen-doped porous carbons were synthesized from polyacrylonitrile fiber by a facile two-step synthesis process i.e. carbonization followed by KOH activation. Activation temperature and KOH/carbon ratio are two parameters to tune the porosity and surface chemical properties of sorbents. The as-obtained sorbents were carefully characterized.Special attention was paid concerning the change of sorbents’ morphology with respect to synthesis conditions. Under the activation temperatures of this study, the sorbents can still retain their fibrous structure when the KOH/carbon mass ratio is 1. Further increasing the KOH amount will destroy the original morphology of polyacrylonitrile fiber. CO_(2)adsorption performance tests show that a sorbent retaining the fibrous shape possesses the highest CO_(2)uptake of 3.95 mmol/g at 25℃and 1 bar. Comprehensive investigation found that the mutual effect of narrow microporosity and doped N content govern the CO_(2)adsorption capacity of these adsorbents. Furthermore, these polyacrylonitrile fiber-derived carbons present multiple outstanding CO_(2)capture properties such as excellent recyclability, high CO_(2)/N_(2)selectivity, fast adsorption kinetics, suitable heat of adsorption, and good dynamic adsorption capacity. Hence, nitrogen-doped porous carbons with fibrous structure are promising in CO_(2)capture. | Changdan Ma Jiali Bai Xin Hu Zhuohan Jiang Linlin Wang | 2023 | Journal of Environmental Sciences2023，，3： | 1 |
| 5 | A data-based review on norfloxacin degradation by persulfate-based advanced oxidation processes:Systematic evaluation and mechanisms显示文摘Persulfate-based advanced oxidation processes(AOPs)have obtained increasing attention due to the generation of sulfate radical(SO_(4)-)with high reactivity for organic contaminants degradation,Numerous activation methods have been used to activate two common persulfates:peroxymonosulfate(PMS)and peroxydisulfate(PDS).However,the comparisons of activation methods and two oxidants in the comprehensive degradation performance of the target contaminant are still limited.Thus,taking norfloxacin(NOR)as the target contaminant,we proposed five key parameters(the observed pseudo-first-order rate constant,kobs;average mineralization rate,rm;utilization efficiency of catalyst,Ucat;utilization efficiency of oxidant,Uox;and net utilization efficiency of oxidant,Uox')to quantify the comprehensive degradation performance of NOR.The irradiation affected target pollutants,catalysts,and oxidants,leading to an improved degradation performance of NOR.Various heterogeneous catalysts were compared in terms of the key elements contained.Fe,Co,and Mn-based materials performed better,while carbon-based catalysts performed poorly on NOR degradation.The overall degradation performance of NOR was different for PMS and PDS,which can be ascribed to their varied reaction pathways towards NOR,but stemmed from different properties of PMS and PDS.Besides,the effect of pH on the degradation efficiency of NOR was investigated.A neutral solution was optimal for PMS system,while an acidic solution worked better for PDS system.Finally,we analyzed the molecule structure of NOR by density functional theory(DFT)calculation to study the sites easy to attack.Then,we summarized four typical degradation pathways of NOR in SO_(4)^(-)-based AOP systems,including defluorination,piperazine ring cleavage,piperazine ring oxidation,and quinoline group transformation. | Pan Wang Huixuan Zhang Zhuohan Wu Xiao Zhao Ying Sun Na Duan Zhidan Liu Wen Liu | 2023 | Chinese Chemical Letters2023，34，12： | 0 |
| 6 | A machine learning method to quantitatively predict alpha phase morphology in additively manufactured Ti-6Al-4V显示文摘Quantitatively defining the relationship between laser powder bed fusion(LPBF)process parameters and the resultant microstructures for LPBF fabricated alloys is one of main research challenges.To date,achieving the desired microstructures and mechanical properties for LPBF alloys is generally done by time-consuming and costly trial-and-error experiments that are guided by human experience.Here,we develop an approach whereby an image-driven conditional generative adversarial network(cGAN)machine learning model is used to reconstruct and quantitatively predict the key microstructural features(e.g.,the morphology of martensite and the size of primary and secondary martensite)for LPBF fabricated Ti-6Al-4V.The results demonstrate that the developed image-driven machine learning model can effectively and efficiently reconstruct micrographs of the microstructures within the training dataset and predict the microstructural features beyond the training dataset fabricated by different LPBF parameters(i.e.,laser power and laser scan speed).This study opens an opportunity to establish and quantify the relationship between processing parameters and microstructure in LPBF Ti-6Al-4V using a GAN machine learning-based model,which can be readily extended to other metal alloy systems,thus offering great potential in applications related to process optimisation,material design,and microstructure control in the additive manufacturing field. | Zhuohan Cao Qian Liu Qianchu Liu Xiaobo Yu Jamie J.Kruzic Xiaopeng Li | 2023 | npj Computational Materials2023，，1： | 0 |
| 7 | Research on Coordinated Development and Optimization of Distribution Networks at All Levels in Distributed Power Energy Engineering显示文摘The uncertainty of distributed generation energy has dramatically challenged the coordinated development of distribution networks at all levels.This paper focuses on the multi-time-scale regulation model of distributed generation energy under normal conditions.The simulation results of the example verify the self-optimization characteristics and the effectiveness of real-time dispatching of the distribution network control technology at all levels under multiple time scales. | Zhuohan Jiang Jingyi Tu Shuncheng Liu Jian Peng Guang Ouyang | 2023 | Energy Engineering2023，120，7： | 0 |
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