Graphene/Ionic Liquid Ultracapacitors: Does Ionic Size Correlate with Storage Energy Performance?

An electric double layer ultracapacitor stores energy in an electric double layer formed near its electrolyte/electrode interfaces. Graphene-based ultracapacitors, because of their outstanding performance, have attracted significant research interest. Optimization of ultracapacitor performance requires understanding the correlation of molecular characteristic of the device (such as structure, inter-ionic and ion-electrode interactions) with its macroscopic properties. Herein, we report molecular dynamics study of how an ionic volume impacts a double-layer capacitance. Four systems were probed: large cation + large anion, large cation + small anion, small cation + large anion, small cation + small anion. Our results show that the structuring of the ionic liquid is driven by the electrolyte-electrode interactions in the ultracapacitor, which are predominantly of the van der Waals type. Storage density energies are similar for all ultracapacitors, being in the range of 24 to 28 J cm-3 at 5.0V. Our results present a comparative analysis of the performances of four different ILs confined between two graphene electrodes. Although the best performance has been observed for the IL with ions (cations and anions) of equal sizes, no definite conclusion about the correlation of the performance to the ionic size ratio can be made from the present study.Instituto de Ciência e Tecnologia, Universidade Federal de São Paulo, São José dos Campos, SP, BrazilP.E.S., Vasilievsky Island, Saint Petersburg, Leningrad Oblast, Russian FederationDepartment of Physics, St. Petersburg State University, St. Petersburg, Russian FederationInstituto de Ciência e Tecnologia, Universidade Federal de São Paulo, São José dos Campos, SP, Brazi

Online Intelligent Controllers for an Enzyme Recovery Plant: Design Methodology and Performance

This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4) is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that cover dynamic and nonlinear processes. The design methodology and a comparative study on the performance of fuzzy-PI, neurofuzzy, and neural network intelligent controllers are presented. To tune the fuzzy PI Mamdani controller, various universes of discourse, rule bases, and membership function support sets were tested. A neurofuzzy inference system (ANFIS), based on Takagi-Sugeno rules, and a model predictive controller, based on neural modeling, were developed and tested as well. Using a Fieldbus network architecture, a coolant variable speed pump was driven by the controllers. The experimental results show the effectiveness of fuzzy controllers in comparison to the neural predictive control. The fuzzy PI controller exhibited a reduced error parameter (ITAE), lower power consumption, and better recovery of enzyme activity

Qualidade do café arábica em diferentes altitudes no Espírito Santo.

Este trabalho teve como objetivo avaliar a influência de diferentes altitudes na qualidade do café arabica, avaliada pela análise sensorial. Para tanto, foram avaliados grãos de três cultivares de café arábica colhidos em três ambientes com altitudes diferentes, ou seja, a 700 m, 950 m e 1100 m, nos municípios de Venda Nova do Imigrante, Domingos Martins e Santa Maria do Jetiba, respectivamente. Os cafés foram secos em terreiro suspenso coberto até que alcançassem 12% de umidade. A classificação sensorial foi realizada por um provador especializado, sem prévio conhecimento das amostras. Verificou-se que cafés cultivados em maiores altitudes originaram melhores bebidas. Não houve diferença significativa entre as cultivares Rubi, Catuai Vermelho IAC 44 e Catuai Vermelho IAC 81 para a qualidade da bebida

Detection and on-line prediction of leak magnitude in a gas pipeline using an acoustic method and neural network data processing

Considering the importance of monitoring pipeline systems, this work presents the development of a technique to detect gas leakage in pipelines, based on an acoustic method, and on-line prediction of leak magnitude using artificial neural networks. On-line audible noises generated by leakage were obtained with a microphone installed in a 60 m long pipeline. The sound noises were decomposed into sounds of different frequencies: 1 kHz, 5 kHz and 9 kHz. The dynamics of these noises in time were used as input to the neural model in order to determine the occurrence and the leak magnitude. The results indicated the great potential of the technique and of the developed neural network models. For all on-line tests, the models showed 100% accuracy in leak detection, except for a small orifice (1 mm) under 4 kgf/cm² of nominal pressure. Similarly, the neural network models could adequately predict the magnitude of the leakages.14515

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This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4) is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that cover dynamic and nonlinear processes. The design methodology and a comparative study on the performance of fuzzy-PI, neurofuzzy, and neural network intelligent controllers are presented. To tune the fuzzy PI Mamdani controller, various universes of discourse, rule bases, and membership function support sets were tested. A neurofuzzy inference system (ANFIS), based on Takagi-Sugeno rules, and a model predictive controller, based on neural modeling, were developed and tested as well. Using a Fieldbus network architecture, a coolant variable speed pump was driven by the controllers. The experimental results show the effectiveness of fuzzy controllers in comparison to the neural predictive control. The fuzzy PI controller exhibited a reduced error parameter (ITAE), lower power consumption, and better recovery of enzyme activity

Effect of conductivity, viscosity, and density of water-in-salt electrolytes on the electrochemical behavior of supercapacitors: Molecular dynamics simulations and: In situ characterization studies

We report here molecular dynamics simulations combined with in situ experimental studies to understand the advantages and disadvantages of replacing conventional (salt-in-water, SiWE) aqueous-based electrolytes with very concentrated (water-in-salt, WiSE) systems in supercapacitors. Atomistic molecular dynamics simulations were employed to investigate the energetic, structural, and transport properties of aqueous electrolytes based on sodium perchlorate (NaClO4). Simulations covered the concentrations range of 1 mol dm-3 (1 mol kg-1) to 8 mol dm-3 (15 mol kg-1), demonstrating a significant increase in viscosity and density and reduction in ionic conductivity as the concentration reaches the WiSE conditions. A carbon-based symmetric supercapacitor filled with WiSE showed a larger electrochemical stability window (ESW), allowing to span the cell voltage and specific energy. Larger ESW values are possible due to the formation of a solvent blocking interface (SBI). The formation of ionic aggregates owing to the increasing cohesive energy in WiSE disturbs the hydrogen-bond network resulting in physicochemical changes in the bulk liquid phase. In addition, the molal ratio between water and ions is decreased, resulting in a low interaction of the water molecules with the electrode at the interface, thus inhibiting the water-splitting considerably.Fil: Da Silva, Débora A. C.. Universidade Estadual de Campinas; BrasilFil: Pinzón, Manuel J.. Universidade Estadual de Campinas; BrasilFil: Messias Da Silva, Andresa. Universidad Federal do Abc; Brasil. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; ArgentinaFil: Fileti, Eudes E.. Universidade de Sao Paulo; BrasilFil: Pascon, Aline. Universidade Estadual de Campinas; BrasilFil: Franco, Débora V.. University of Jequitinhonha e Mucuri's Valley; BrasilFil: Da Silva, Leonardo Morais. University of Jequitinhonha e Mucuri's Valley; BrasilFil: Zanin, Hudson G.. Universidade Estadual de Campinas; Brasi