Pablo A. López-Pérez

Study of the interplay between N-graphene defects and small Pd clusters for enhanced hydrogen storage via a spill-over mechanism.

The hydrogen spill-over mechanism was studied by applying Density Functional Theory. We used small palladium clusters to act as the catalyst supported on the substrate (comprised of pyridinic and pyrrolic nitrogen doped graphene), in order to study hydrogen dissociation, migration and diffusion. Charge transfer and strong binding between the catalyst and the substrate lead to dissociated states of H2 and prevent clusters from detaching and coalescing. In dissociated cases of H2 on Pd clusters, energy barriers below 0.6 eV were found. Likewise, concerning hydrogen migration from the catalyst to the substrate, energy barrier values of 0.8 eV (pyridinic defect) and 0.5 eV (pyrrolic defect) were apparent in the case of the Pd4 cluster at full hydrogen saturation. This indicates that hydrogen dissociation and migration may occur spontaneously at room temperature. This result shows that the interaction between the defects and the small metal clusters may explain the role that defects play in hydrogen migration from the catalyst to the substrate. Subsequently, it was found that thermal desorption does not limit chemisorbed hydrogen diffusion on the substrate. This work may thus help to determine experimental strategies with the capacity to enhance hydrogen storage.

Reduction of Cr(VI) utilizing biogenic sulfide: an experimental and mathematical modeling approach

AbstractThe aim of this work was to analyze the performance of a wastewater system for Cr(VI) and sulfate compounds reduction via mathematical modeling. The considered process is coupled to chemical reactors to achieve its tasks. The first stage of the considered process is a biological sulfate-reducing reactor, by which sulfate compounds can be reduced to biogenic sulfide; then, in the second stage, the above-mentioned biogenic sulfide is fed to a second reactor in which the Cr(VI) is reduced, allowing high Cr(VI) concentration removal. The kinetic model of the biological sulfate-reducing process and the Cr(VI) reduction via biogenic sulfide reactions were experimentally corroborated and employed as a benchmarck for the wastewater process analysis via numerical simulations to achieve several feasible operation conditions, under the system’s constraints. The mathematical model was extended to a continuous operation, where numerical experiments were carried out predicting an excellent removal of 99% of Cr(...

Uniformly Bounded Error Estimator for Bioprocess with Unstructured Cell Growth Models

In this paper, we proposed a uniformly bounded error estimator for a common class of bioreactor models. The biomass and other products are estimated by means of substrate concentration measurements employing the characteristics of the unstructured cell growth models, which are linearly dependent. The estimation methodology is based on a suitable change of variable which allows generating artificial variables to infer the remaining mass concentrations constructing a differential-algebraic structure. The proposed methodology is applied to a class of Monod unstructured kinetic model with success. Some remarks about the convergence characteristics of the proposed estimator are given and numerical simulations show its satisfactory performance.

Comparison Tools for Parametric Identification of Kinetic Model for Ethanol Production using Evolutionary Optimization Approach

Abstract Living cells, type of substrate, enzymatic hydrolysis play an important role in the efficiency of ethanol production; however, the kinetic parameters of biochemical reactions necessary for modelling these processes are often not accessible directly through experiments. In this context, for the implementation of suitable operational strategies, it is necessary to have kinetic models able to describe the process as realistically as possible. This paper proposes a comparative study of two nonlinear techniques for parametric identification of a kinetic model for ethanol production from recycled paper sludge in order to improve process performance. The parameters of the model are optimized by two methods: using the Levenberg–Marquardt optimization approach and Genetic Algorithms. The performances of both techniques are evaluated using a numerical simulation. The optimal value of these parameters have been obtained based on Genetic Algorithm. Finally, the effect of parametric adjustment and dilution rate on productivity was demonstrated by changing the batch operation to the continuous operating model. The maximum ethanol concentration was about 13.25 g/l in batch process and about 13.9 g/l at Dilution rate: 0.005 1/h corresponding to a productivity of 0.327 in continuous process.

Nonlinear controller design with application to a continuous bioreactor

The goal of this work is to present a mathematical model of a sulfate-reducing bioreactor where a proposed nonlinear controller is applied to regulate the dynamics of the process. The corresponding kinetic model, experimentally corroborated, is extended to simulate continuous operation, and a class of smooth controllers, under the frame of sliding modes, is proposed to control the sulfate concentration into the bioreactor employing the dilution rate as control input, with successes. The proposed controller avoids the named chattering phenomena for its smooth structure, and its performance is compared with a well tuned proportional-integral and high-order sliding-mode controllers in order to analyze their corresponding closed-loop behavior. A sketch of proof of the closed-loop stability is provided.

Controlling a class of chaotic quantum system under disturbances and noisy measurements: Application to 1D Bose-Einstein condensate

In this paper, a robust nonlinear feedback control scheme with adaptive gain is proposed to control the chaotic behavior in a Bose–Einstein condensate (BEC). The control goal concerns the track or regulation purposes. The BEC system is represented as stochastic ordinary differential equations with measured output perturbed by Gaussian noise, which represents the nature of the quantum systems. The convergence of the BEC control law is analyzed under the frame of the Lyapunov stability theory. Numerical experiments show an adequate performance of the proposed methodology under the required conditions. The results are applicable when the shape of the condensate is sufficiently simple.

Improving Bioethanol Production via Nonlinear Controller with Noisy Measurements

A bioprocess operation is commonly determined off-line, in which the measurements contain noise and can affect the controller performance. In this work, a nonlinear controller based on a generalized hyperbolic tangent feedback in the control error was designed, proving reduction of the negative effects caused by noise in the bioreactor measurement output. This was applied to regulate the substrate concentration in a continuous bioreactor for the simultaneous saccharification and fermentation of starch to ethanol. The proposed controller stability was demonstrated by Lyapunov theory. Numerical results showed a good performance by the controller scheme, despite the bounded additive noise in the substrate measurements, and it achieved high ethanol production in comparison with other control laws.

Changes to the dissociation barrier of H2 due to buckling induced by a chemisorbed hydrogen on a doped graphene surface

AbstractAn effectiveway of enhancing hydrogen storage on adsorbent materials can be induced by the hydrogen spill-over mechanism, although to date there is no general consensus which satisfactorily explains the mechanism. In this work, a possible reaction path to explain hydrogen adsorption is shown. Density-functional calculations were used to study the dissociation of molecular hydrogen near to a stressed region, as a consequence of chemisorbed hydrogen at the graphene-nitrogen surface. We found that as a result of the buckling induced by the chemisorbed hydrogen, the dissociation barrier of molecular hydrogen diminished by 0.84 eV. The chemisorbed hydrogen is the final state in the spill-over mechanism on a graphene-nitrogen decorated with palladium clusters. This effect helps to create hydrogen nanoislands that may change the diffusion and detrapping of H. An electronic structure analysis suggests that these systems occasionally present metallic or semiconductor behavior. Graphical AbstractHydrogen dissociation and adsorption process via buckling defect

Development of a Novel Kinetic Model for Cocoa Fermentation Applying the Evolutionary Optimization Approach

Abstract Traditional Mexican cocoa fermentation performed in batch was studied by applying kinetic modelling with experimental validation. Similar microbiological behaviour was observed up to 60 h, with a temperature increase at 72 h that remained constant (50 °C) until 156 h. Metabolite-production kinetics (ethanol and acetic acid) from degradable mucilage (glucose) was explored. Exploration involved applying different combinations of unstructured growth models, in order to consider the effect of temperature when predicting the concentration of metabolites in these microorganisms. Two methods were used to optimize model parameters: the Levenberg–Marquardt optimization approach and Genetic Algorithms (GAs). GAs which could be used to scale up the fermentation process indicated the applicability of this model for predicting fermentation quality. The maximum specific rate average for μmax and saturation constant (Ks) were 0.0961 h−1 and 1.4 mg/g m.s., respectively. The results obtained indicate the expediency of this technique for future application in the design and control of batch fermentation.

Estimation of plasmid concentration in batch culture of Escherichia coli DH5α via simple state observer

The aim of this paper is to present an alternative state observer structure for online estimation purposes of the key dynamical variables in a class of batch culture for plasmid production; the latter has been extremely attractive to be used as DNA vaccines or gene therapy. A mathematical model for culture of Escherichia coli DH5α-harboring plasmid was considered a benchmark system for the application of the proposed estimation methodology. Local observability analysis revealed that the system is partially observable for plasmid concentration considering only the biomass concentration in the batch culture as the measured variable. The proposed observer is designed with a simple proportional–integral feedback of the measured biomass concentration, where under the proposed design, the observer gain´s array can compensate the main nonlinearities of the estimation error dynamics. The convergence of estimated variables to the real ones is mathematically analyzed, reaching an asymptotic behavior. Numerical experiments were performed, where a comparison with a standard extended Luenberger observer was done and the proposed estimation methodology revealed a satisfactory performance.