Optimizing the Organic Solar Cell Manufacturing Process by Means of AFM Measurements and Neural Networks

Capizzi, Giacomo; Sciuto, Grazia Lo; Napoli, Christian; Shikler, Rafi; Woźniak, Marcin

doi:10.3390/en11051221

Cited by 22 publications

(8 citation statements)

References 29 publications

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“…In Romania, the TQM model has been analyzed in many specialized works, including Stanciu [39], Ilies [40], and Busu and Busu [41,42]. Capizzi et al [43] introduced a neural network-based model to improve the production workflow of organic solar cells (OSCs). The authors proved that the use of a neural model could be an important key for improving the OSC manufacturing process.…”

Section: Introductionmentioning

confidence: 99%

Applications of TQM Processes to Increase the Management Performance of Enterprises in the Romanian Renewable Energy Sector

Bușu

2019

Processes

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This paper focuses on total quality management (TQM) processes and their applications to increase the management performance of enterprises in the renewable energy sector (RES). TQM is a modern tool used by enterprises to increase their management performance. We start with a description of Edwards Deming’s conceptualized model, highlighting different phases of its development as described in the literature. The TQM process is then used for an application to the RES in Romania. The quantitative model analyzes the influence of TQM process implementation in achieving competitive advantage and the management performance of the undertakings in the RES. Data was collected through a survey based on a questionnaire addressed to employees and managers in the RES. Structural equation modeling (SEM) was used and the research hypotheses were tested with the partial least squares path method (PLS). Data analysis was performed with the statistical software SmartPLS 3.2.8. The main contribution of this article is to evaluate the relationship between the management performance of enterprises in the RES sector in Romania and TQM process indicators. The results underline the fact that the most important attributes of a TQM process to increase the management performance are: integrated operational processes, policies and trading strategies, integrated operational management, company social responsibility, motivated workforce, knowledge, and competencies. The conclusions of the research are in line with the latest findings in the area, underlining that management performance is the direct result of the association between a group of factors and processes, such as the integrated operational processes, trade strategies and policies, integrated operational management, corporate social responsibility (CSR), motivated workforce, knowledge, and competencies.

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Section: Introductionmentioning

confidence: 99%

Applications of TQM Processes to Increase the Management Performance of Enterprises in the Romanian Renewable Energy Sector

Bușu

2019

Processes

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“…The PCE of the OSC with IDIC-4F as an acceptor and DRCN5T2F as donor was increased to 9.36% (the PCE of the OSC based on DRCN5T/IDIC-4F is 8.02%) [18]. As shown in Figure 4, DRCN5T2F, DRCN5T4F, DRCN5T6F DRCN5T2Cl, DRCN5T6Cl, DRCN5T2Br, and DRCN5T6Br have slightly smaller dipole moments (15.23, 16.68, 14.26, 13.42, 15.96, 15.78, and 16.45 Debye, respectively) than that of DRCN5T (17.33 Debye), which may benefit a higher PCE [23,24].…”

Section: Dipole Moments Of the Halogenated Moleculesmentioning

confidence: 90%

Designing Potential Donor Materials Based on DRCN5T with Halogen Substitutions: A DFT/TDDFT Study

Xiang

Zhang

Zheng

2021

IJMS

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Experimental researchers have found that the organic solar cell (OSC) based on DRCN5T (an oligothiophene) possesses excellent power conversion efficiency (PCE) of 10.1%. However, to date, there have been few studies about halogenation of DRCN5T, and its effects on photovoltaic properties of halogenated DRCN5T are still not clear. In the present work, we first perform benchmark calculations and effectively reproduce experimental results. Then, eight halogenated DRCN5T molecules are designed and investigated theoretically by using density functional theory (DFT) and time-dependent DFT. The dipole moments, frontier molecular orbital energies, absorption spectra, exciton binding energy (Eb), singlet–triplet energy gap (ΔEST), and electrostatic potential (ESP) of these molecules, and the estimated open circuit voltages (VOCs) of the OSCs with PC71BM as acceptor are presented. We find that (1) generally, halogen substitutions would increase VOC; (2) Eb rises with more fluorine substitutions, but for Cl and Br substitutions, Eb increases firstly and then drops; (3) ΔEST keeps increasing with more halogen substitutions; (4) except for Br substitutions, the averaged ESP arises along with more halogen substitutions; (5) the absorption strength of UV–Vis spectra of DRCN5T2F, DRCN5T4F, DRCN5T6F, and DRCN5T2Cl in the visible region is enhanced with respect to DRCN5T. Based on these results, overall, DRCN5T2Cl, DRCN5T4F, and DRCN5T6F may be promising donors.

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“…A neural network [26][27][28] has excellent predictive ability and has been used by researchers in multi-step predictive control as early as the 1990s. Generally, it is employed as a predictive model to predictoutput values for rolling optimization.…”

Section: A Prediction Model Of An Aircraft Enginementioning

confidence: 99%

Hybrid Grey Wolf Optimization Nonlinear Model Predictive Control for Aircraft Engines Based on an Elastic BP Neural Network

Xiao

Yuhan

et al. 2019

Applied Sciences

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In order to deal with control constraints and the performance optimization requirements in aircraft engines, a new nonlinear model predictive control method based on an elastic BP neural network with a hybrid grey wolf optimizer is proposed in this paper. Based on the acquired aircraft engines data, the elastic BP neural network is used to train the prediction model, and the grey wolf optimization algorithm is applied to improve the selection of initial parameters in the elastic BP neural network. The accuracy of network modeling is increased as a result. By introducing the logistics chaotic sequence, the individual optimal search mechanism, and the cross operation, the novel hybrid grey wolf optimization algorithm is proposed and then used in receding horizon optimization to ensure real-time operation. Subsequently, a nonlinear model predictive controller for aircraft engine is obtained. Simulation results show that, with constraints in the control signal, the proposed nonlinear model predictive controller can guarantee that the aircraft engine has a satisfactory performance.

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Optimizing the Organic Solar Cell Manufacturing Process by Means of AFM Measurements and Neural Networks

Cited by 22 publications

References 29 publications

Applications of TQM Processes to Increase the Management Performance of Enterprises in the Romanian Renewable Energy Sector

Applications of TQM Processes to Increase the Management Performance of Enterprises in the Romanian Renewable Energy Sector

Designing Potential Donor Materials Based on DRCN5T with Halogen Substitutions: A DFT/TDDFT Study

Hybrid Grey Wolf Optimization Nonlinear Model Predictive Control for Aircraft Engines Based on an Elastic BP Neural Network

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