Optimal synthesis of Fenton reactor networks for phenol degradation

There is an increasing need to treat effluents contaminated with phenol with advanced oxidation processes (AOPs) to minimize their impact on the environment as well as on bacteriological populations of other wastewater treatment systems. One of the most promising AOPs is the Fenton process that relies on the Fenton reaction. Nevertheless, there are no systematic studies on Fenton reactor networks. The objective of this paper is to develop a strategy for the optimal synthesis of Fenton reactor networks. The strategy is based on a superstructure optimization approach that is represented as a mixed integer non-linear programming (MINLP) model. Network superstructures with multiple Fenton reactors are optimized with the objective of minimizing the sum of capital, operation and depreciation costs of the effluent treatment system. The optimal solutions obtained provide the reactor volumes and network configuration, as well as the quantities of the reactants used in the Fenton process. Examples based on a case study show that multi-reactor networks yield decrease of up to 45% in overall costs for the treatment plant. (C) 2010 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Optimal synthesis of anaerobic digester networks

The objective of this paper is to develop a mathematical model for the synthesis of anaerobic digester networks based on the optimization of a superstructure that relies on a non-linear programming formulation. The proposed model contains the kinetic and hydraulic equations developed by Pontes and Pinto [Chemical Engineering journal 122 (2006) 65-80] for two types of digesters, namely UASB (Upflow Anaerobic Sludge Blanket) and EGSB (Expanded Granular Sludge Bed) reactors. The objective function minimizes the overall sum of the reactor volumes. The optimization results show that a recycle stream is only effective in case of a reactor with short-circuit, such as the UASB reactor. Sensitivity analysis was performed in the one and two-digester network superstructures, for the following parameters: UASB reactor short-circuit fraction and the EGSB reactor maximum organic load, and the corresponding results vary considerably in terms of digester volumes. Scenarios for three and four-digester network superstructures were optimized and compared with the results from fewer digesters. (C) 2009 Elsevier B.V. All rights reserved.

Multisite phosphorylation in (bio-)chemical reaction networks : multistationarity and robustness

Magdeburg, Univ., Fak. für Elektro- und Informationstechnik, Diss., 2014

Characterisation of a cavity transfer mixer as a chemical reactor

This research project examined the feasibility of using a cavity transfer mixer (CTM) as a continuous reactor to perform reactions between either solid or liquid reagents and polymer melt; reactions which have previously been typically carried out in batch reactor systems. Equipment has been developed to allow uniform and reproducible introduction of reagents into the polymer melt. Reactions have also been performed using batch processing equipment to enable comparison with the performance of the CTM. It was concluded that: a) there are certain reactions which cannot be carried out in a CTM, but which can be performed in a batch system such as a mill or a sigma blade mixer. This was found to be the case for some neutralisation reactions where the product was quasi crosslinked. b) the reactions that can be carried out in a CTM are performed more efficiently in a CTM than on a batch process. For example, when monomers were to be grafted onto polymers, this was more safely and efficiently performed in the CTM than in a mill or a sigma blade mixer. Residence time distributions (RTDs) for three CTMs were studied in order to gain an insight into the effect of CTM geometry on RTD, polymer melt flow pattern and reactor performance. A mathematical model has been developed to predict the influence of process parameters on RTD and the results compared with experimentally observed trends. The comparison was good. A programme of research has been drawn up to form the basis of an industrially based sponsored development project of the CTM reactor. This work programme was successfully marketed to companies with commercial interest in modified rubber and plastics as an integral part of the research programme of this thesis and the sponsored research programme has paralleled the work reported here.

Semi-algebraic methods for symbolic analysis of complex reaction networks

The identification of chemical mechanism that can exhibit oscillatory phenomena in reaction networks are currently of intense interest. In particular, the parametric question of the existence of Hopf bifurcations has gained increasing popularity due to its relation to the oscillatory behavior around the fixed points. However, the detection of oscillations in high-dimensional systems and systems with constraints by the available symbolic methods has proven to be difficult. The development of new efficient methods are therefore required to tackle the complexity caused by the high-dimensionality and non-linearity of these systems. In this thesis, we mainly present efficient algorithmic methods to detect Hopf bifurcation fixed points in (bio)-chemical reaction networks with symbolic rate constants, thereby yielding information about their oscillatory behavior of the networks. The methods use the representations of the systems on convex coordinates that arise from stoichiometric network analysis. One of the methods called HoCoQ reduces the problem of determining the existence of Hopf bifurcation fixed points to a first-order formula over the ordered field of the reals that can then be solved using computational-logic packages. The second method called HoCaT uses ideas from tropical geometry to formulate a more efficient method that is incomplete in theory but worked very well for the attempted high-dimensional models involving more than 20 chemical species. The instability of reaction networks may lead to the oscillatory behaviour. Therefore, we investigate some criterions for their stability using convex coordinates and quantifier elimination techniques. We also study Muldowney's extension of the classical Bendixson-Dulac criterion for excluding periodic orbits to higher dimensions for polynomial vector fields and we discuss the use of simple conservation constraints and the use of parametric constraints for describing simple convex polytopes on which periodic orbits can be excluded by Muldowney's criteria. All developed algorithms have been integrated into a common software framework called PoCaB (platform to explore bio- chemical reaction networks by algebraic methods) allowing for automated computation workflows from the problem descriptions. PoCaB also contains a database for the algebraic entities computed from the models of chemical reaction networks.

Water-assisted Flow of Heavy Oil in a Vertical Pipe: Pilot-scale Experiments

The use of the core-annular flow pattern, where a thin fluid surrounds a very viscous one, has been suggested as an attractive artificial-lift method for heavy oils in the current Brazilian ultra-deepwater production scenario. This paper reports the pressure drop measurements and the core-annular flow observed in a 2 7/8-inch and 300 meter deep pilot-scale well conveying a mixture of heavy crude oil (2000 mPa.s and 950 kg/m3 at 35 C) and water at several combinations of the individual flow rates. The two-phase pressure drop data are compared with those of single-phase oil flow to assess the gains due to water injection. Another issue is the handling of the core-annular flow once it has been established. High-frequency pressure-gradient signals were collected and a treatment based on the Gabor transform together with neural networks is proposed as a promising solution for monitoring and control. The preliminary results are encouraging. The pilot-scale tests, including long-term experiments, were conducted in order to investigate the applicability of using water to transport heavy oils in actual wells. It represents an important step towards the full scale application of the proposed artificial-lift technology. The registered improvements in terms of oil production rate and pressure drop reductions are remarkable.

Thermal Runaway in Tubular Reactor Systems with n-th Order Kinetics

This paper addresses the problem of predicting the critical parameters that characterize thermal runaway in a tubular reactor with wall cooling, introducing a new view of the n-th order kinetics reactions. The paper describes the trajectories of the system in the temperature-(concentration)n plane, and deduces the conditions for the thermal risk.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

Exploring coordination-driven self-assembly with autonomous chemical robots

The work presented herein focused on the automation of coordination-driven self assembly, exploring methods that allow syntheses to be followed more closely while forming new ligands, as part of the fundamental study of the digitization of chemical synthesis and discovery. Whilst the control and understanding of the principle of pre-organization and self-sorting under non-equilibrium conditions remains a key goal, a clear gap has been identified in the absence of approaches that can permit fast screening and real-time observation of the reaction process under different conditions. A firm emphasis was thus placed on the realization of an autonomous chemical robot, which can not only monitor and manipulate coordination chemistry in real-time, but can also allow the exploration of a large chemical parameter space defined by the ligand building blocks and the metal to coordinate. The self-assembly of imine ligands with copper and nickel cations has been studied in a multi-step approach using a self-built flow system capable of automatically controlling the liquid-handling and collecting data in real-time using a benchtop MS and NMR spectrometer. This study led to the identification of a transient Cu(I) species in situ which allows for the formation of dimeric and trimeric carbonato bridged Cu(II) assemblies. Furthermore, new Ni(II) complexes and more remarkably also a new binuclear Cu(I) complex, which usually requires long and laborious inert conditions, could be isolated. The study was then expanded to the autonomous optimization of the ligand synthesis by enabling feedback control on the chemical system via benchtop NMR. The synthesis of new polydentate ligands has emerged as a result of the study aiming to enhance the complexity of the chemical system to accelerate the discovery of new complexes. This type of ligand consists of 1-pyridinyl-4-imino-1,2,3-triazole units, which can coordinate with different metal salts. The studies to test for the CuAAC synthesis via microwave lead to the discovery of four new Cu complexes, one of them being a coordination polymer obtained from a solvent dependent crystallization technique. With the goal of easier integration into an automated system, copper tubing has been exploited as the chemical reactor for the synthesis of this ligand, as it efficiently enhances the rate of the triazole formation and consequently promotes the formation of the full ligand in high yields within two hours. Lastly, the digitization of coordination-driven self-assembly has been realized for the first time using an in-house autonomous chemical robot, herein named the ‘Finder’. The chemical parameter space to explore was defined by the selection of six variables, which consist of the ligand precursors necessary to form complex ligands (aldehydes, alkineamines and azides), of the metal salt solutions and of other reaction parameters – duration, temperature and reagent volumes. The platform was assembled using rounded bottom flasks, flow syringe pumps, copper tubing, as an active reactor, and in-line analytics – a pH meter probe, a UV-vis flow cell and a benchtop MS. The control over the system was then obtained with an algorithm capable of autonomously focusing the experiments on the most reactive region (by avoiding areas of low interest) of the chemical parameter space to explore. This study led to interesting observations, such as metal exchange phenomena, and also to the autonomous discovery of self assembled structures in solution and solid state – such as 1-pyridinyl-4-imino-1,2,3-triazole based Fe complexes and two helicates based on the same ligand coordination motif.

An Evaluation of Different Bioreactor Configurations with Immobilized Yeast for Bioethanol Production

The bioethanol industry expects a huge expansion and new technologies are being implemented with the aim of optimizing the fermentation process. The behavior of cells of Saccharomyces cerevisiae immobilized in PVA-LentiKats, during the production of bioethanol in two reactor systems, was studied. The entrapped cell in LentiKats lenses showed a different profile using stirred tank reactor (STR) and packed column reactor (PCR). Low free cells accumulation in the medium was observed for the STR after 72 h of fermentation. On the other hand, no free cells accumulation was observed, probably due to the absence of mechanical agitation in PCR configuration. Better fermentation results were obtained working with STR (final cellular concentration = 13 g.L-1, Pf = 28 g.L-1, Qp = 1.17 g.L-1.h-1,and Yp/s = 0.3 g.g-1) in comparison to PCR (final cellular concentration = 11.4 g.L-1, Pf = 20 g.L-1, Qp = 0.83 g.L-1.h-1,and Yp/s = 0.25 g.g-1). Such results are probably due to the mechanical agitation of the medium provided by STR configuration, which permitted a better heat and mass transference.

Biomass Refinery as a Renewable Complement to the Petroleum Refinery

Biomass Refinery is a sequential of eleven thermochemical processes and one biological process with two initial basic treatments: prehydrolysis for lignocellulosics and low temperature conversion for biomass with medium-to-high content of lipids and proteins. The other ten processes are: effluent treatment plant, furfural plant, biodiesel plant, cellulignin dryer, calcination, fluidized bed boiler, authotermal reforming of cellulignin for syngas production, combined cycle of two-stroke low-speed engine or syngas turbine with fluidized bed boiler heat recovery, GTL technologies and ethanol from cellulose, prehydrolysate and syngas. Any kind of biomass such as wood, agricultural residues, municipal solid waste, seeds, cakes, sludges, excrements and used tires can be processed at the Biomass Refinery. Twelve basic products are generated such as cellulignin, animal feed, electric energy, fuels (ethanol, crude oil, biodiesel, char), petrochemical substitutes, some materials (ash, gypsum, fertilizers, silica, carbon black) and hydrogen. The technology is clean with recovery of energy and reuse of water, acid and effluents. Based on a holistic integration of various disciplines Biomass Refinery maximizes the simultaneous production of food, electric energy, liquid fuels and chemical products and some materials, achieving a competitive position with conventional and fossil fuel technologies, as well as payment capacity for biomass production. Biomass Refinery has a technical economical capability to complement the depletion of the conventional petroleum sources and to capture its GHGs resulting a biomass + petroleum ""green"" combination.

Fermentation of Groundnut Shell Enzymatic Hydrolysate for Fuel Ethanol Production by Free and Sorghum Stalks Immobilized Cells of Pichia stipitis NCIM 3498

Groundnut shell (GS), after separation of pod, is readily available as a potential feedstock for production of fermentable sugars. The substrate was delignified with sodium sulfite. The delignified substrate released 670 mg/g of sugars after enzymatic hydrolysis (50 degrees C, 120 rpm, 50 hrs) using commercial cellulases (Dyadic Xylanase PLUS, Dyadic Inc. USA). The groundnut shell enzymatic hydrolysate (45.6 g/L reducing sugars) was fermented for ethanol production with free and sorghum stalks immobilized cells of Pichia stipitis NCIM 3498 under submerged cultivation conditions. Immobilization of yeast cells on sorghum stalks were confirmed by scanning electron microscopy (SEM). A maximum of ethanol production (17.83 g/L, yield 0.44 g/g and 20.45 g/L, yield 0.47 g/g) was observed with free and immobilized cells of P. stipitis respectively in batch fermentation conditions. Recycling of immobilized cells showed a stable ethanol production (20.45 g/L, yield 0.47 g/g) up to 5 batches followed by a gradual downfall in subsequent cycles.

Nanoparticles in SiH4-Ar plasma: Modelling and comparison with experimental data

Experimental and theoretical investigations for growth of silicon nanoparticles (4 to 14 nm) in radio frequency discharge were carried out. Growth processes were performed with gas mixtures of SiH4 and Ar in a plasma chemical reactor at low pressure. A distinctive feature of presented kinetic model of generation and growth of nanoparticles (compared to our earlier model) is its ability to investigate small"critical" dimensions of clusters, determining the rate of particle production and taking into account the influence of SiH2 and Si2Hm dimer radicals. The experiments in the present study were extended to high pressure (≥20 Pa) and discharge power (≥40 W). Model calculations were compared to experimental measurements, investigating the dimension of silicon nanoparticles as a function of time, discharge power, gas mixture, total pressure, and gas flow.

Advanced analysis and design methods for preparative chromatographic separation processes

Preparative liquid chromatography is one of the most selective separation techniques in the fine chemical, pharmaceutical, and food industries. Several process concepts have been developed and applied for improving the performance of classical batch chromatography. The most powerful approaches include various single-column recycling schemes, counter-current and cross-current multi-column setups, and hybrid processes where chromatography is coupled with other unit operations such as crystallization, chemical reactor, and/or solvent removal unit. To fully utilize the potential of stand-alone and integrated chromatographic processes, efficient methods for selecting the best process alternative as well as optimal operating conditions are needed. In this thesis, a unified method is developed for analysis and design of the following singlecolumn fixed bed processes and corresponding cross-current schemes: (1) batch chromatography, (2) batch chromatography with an integrated solvent removal unit, (3) mixed-recycle steady state recycling chromatography (SSR), and (4) mixed-recycle steady state recycling chromatography with solvent removal from fresh feed, recycle fraction, or column feed (SSR–SR). The method is based on the equilibrium theory of chromatography with an assumption of negligible mass transfer resistance and axial dispersion. The design criteria are given in general, dimensionless form that is formally analogous to that applied widely in the so called triangle theory of counter-current multi-column chromatography. Analytical design equations are derived for binary systems that follow competitive Langmuir adsorption isotherm model. For this purpose, the existing analytic solution of the ideal model of chromatography for binary Langmuir mixtures is completed by deriving missing explicit equations for the height and location of the pure first component shock in the case of a small feed pulse. It is thus shown that the entire chromatographic cycle at the column outlet can be expressed in closed-form. The developed design method allows predicting the feasible range of operating parameters that lead to desired product purities. It can be applied for the calculation of first estimates of optimal operating conditions, the analysis of process robustness, and the early-stage evaluation of different process alternatives. The design method is utilized to analyse the possibility to enhance the performance of conventional SSR chromatography by integrating it with a solvent removal unit. It is shown that the amount of fresh feed processed during a chromatographic cycle and thus the productivity of SSR process can be improved by removing solvent. The maximum solvent removal capacity depends on the location of the solvent removal unit and the physical solvent removal constraints, such as solubility, viscosity, and/or osmotic pressure limits. Usually, the most flexible option is to remove solvent from the column feed. Applicability of the equilibrium design for real, non-ideal separation problems is evaluated by means of numerical simulations. Due to assumption of infinite column efficiency, the developed design method is most applicable for high performance systems where thermodynamic effects are predominant, while significant deviations are observed under highly non-ideal conditions. The findings based on the equilibrium theory are applied to develop a shortcut approach for the design of chromatographic separation processes under strongly non-ideal conditions with significant dispersive effects. The method is based on a simple procedure applied to a single conventional chromatogram. Applicability of the approach for the design of batch and counter-current simulated moving bed processes is evaluated with case studies. It is shown that the shortcut approach works the better the higher the column efficiency and the lower the purity constraints are.

Systemic gut microbial modulation of bile acid metabolism in host tissue compartments

We elucidate the detailed effects of gut microbial depletion on the bile acid sub-metabolome of multiple body compartments (liver, kidney, heart, and blood plasma) in rats. We use a targeted ultraperformance liquid chromatography with time of flight mass-spectrometry assay to characterize the differential primary and secondary bile acid profiles in each tissue and show a major increase in the proportion of taurine-conjugated bile acids in germ-free (GF) and antibiotic (streptomycin/penicillin)-treated rats.Although conjugated bile acids dominate the hepatic profile (97.0 ± 1.5%) of conventional animals, unconjugated bile acids comprise the largest proportion of the total measured bile acid profile in kidney (60.0±10.4%) andheart (53.0 ± 18.5%) tissues. In contrast, in the GF animal, taurine-conjugated bile acids (especially taurocholic acid and tauro-β-muricholic acid) dominated the bile acid profiles (liver: 96.0 ± 14.5%; kidney: 96 ± 1%; heart: 93 ± 1%; plasma: 93.0 ± 2.3%), with unconjugated and glycine-conjugated species representing a small proportion of the profile. Higher free taurine levels were found in GF livers compared with the conventional liver (5.1-fold; P < 0.001). Bile acid diversity was also lower in GF and antibiotic-treated tissues compared with conventional animals. Because bile acids perform important signaling functions, it is clear that these chemical communication networks are strongly influencedbymicrobial activitiesormodulation, as evidenced by farnesoid X receptor-regulated pathway transcripts. The presence of specific microbial bile acid co-metabolite patterns in peripheral tissues (including heart and kidney) implies a broader signaling role for these compounds and emphasizes the extent of symbiotic microbial influences in mammalian homeostasis.