Amination of enzymes to improve biocatalyst performance: coupling genetic modification and physicochemical tools

Improvement of the features of an enzyme is in many instances a pre-requisite for the industrial implementation of these exceedingly interesting biocatalysts. To reach this goal, the researcher may utilize different tools. For example, amination of the enzyme surface produces an alteration of the isoelectric point of the protein along with its chemical reactivity (primary amino groups are the most widely used to obtain the reaction of the enzyme with surfaces, chemical modifiers, etc.) and even its “in vivo” behavior. This review will show some examples of chemical (mainly modifying the carboxylic groups using the carbodiimide route), physical (using polycationic polymers like polyethyleneimine) and genetic amination of the enzyme surface. Special emphasis will be put on cases where the amination is performed to improve subsequent protein modifications. Thus, amination has been used to increase the intensity of the enzyme/support multipoint covalent attachment, to improve the interaction with cation exchanger supports or polymers, or to promote the formation of crosslinkings (both intra-molecular and in the production of crosslinked enzyme aggregates). In other cases, amination has been used to directly modulate the enzyme properties (both in immobilized or free form). Amination of the enzyme surface may also pursue other goals not related to biocatalysis. For example, it has been used to improve the raising of antibodies against different compounds (both increasing the number of haptamers per enzyme and the immunogenicity of the composite) or the ability to penetrate cell membranes. Thus, amination may be a very powerful tool to improve the use of enzymes and proteins in many different areas and a great expansion of its usage may be expected in the near future.

Simultaneous synthesis of heat exchanger networks with pressure recovery: optimal integration between heat and work

The optimal integration between heat and work may significantly reduce the energy demand and consequently the process cost. This paper introduces a new mathematical model for the simultaneous synthesis of heat exchanger networks (HENs) in which the pressure levels of the process streams can be adjusted to enhance the heat integration. A superstructure is proposed for the HEN design with pressure recovery, developed via generalized disjunctive programming (GDP) and mixed-integer nonlinear programming (MINLP) formulation. The process conditions (stream temperature and pressure) must be optimized. Furthermore, the approach allows for coupling of the turbines and compressors and selection of the turbines and valves to minimize the total annualized cost, which consists of the operational and capital expenses. The model is tested for its applicability in three case studies, including a cryogenic application. The results indicate that the energy integration reduces the quantity of utilities required, thus decreasing the overall cost.

Applying reactive models to column experiments to assess the hydrogeochemistry of seawater intrusion: optimising ACUAINTRUSION and selecting cation exchange coefficients with PHREEQC

Three sets of laboratory column experimental results concerning the hydrogeochemistry of seawater intrusion have been modelled using two codes: ACUAINTRUSION (Chemical Engineering Department, University of Alicante) and PHREEQC (U.S.G.S.). These reactive models utilise the hydrodynamic parameters determined using the ACUAINTRUSION TRANSPORT software and fit the chloride breakthrough curves perfectly. The ACUAINTRUSION code was improved, and the instabilities were studied relative to the discretisation. The relative square errors were obtained using different combinations of the spatial and temporal steps: the global error for the total experimental data and the partial error for each element. Good simulations for the three experiments were obtained using the ACUAINTRUSION software with slight variations in the selectivity coefficients for both sediments determined in batch experiments with fresh water. The cation exchange parameters included in ACUAINTRUSION are those reported by the Gapon convention with modified exponents for the Ca/Mg exchange. PHREEQC simulations performed using the Gains-Thomas convention were unsatisfactory, with the exchange coefficients from the database of PHREEQC (or range), but those determined with fresh water – natural sediment allowed only an approximation to be obtained. For the treated sediment, the adjusted exchange coefficients were determined to improve the simulation and are vastly different from those from the database of PHREEQC or batch experiment values; however, these values fall in an order similar to the others determined under dynamic conditions. Different cation concentrations were simulated using two different software packages; this disparity could be attributed to the defined selectivity coefficients that affect the gypsum equilibrium. Consequently, different calculated sulphate concentrations are obtained using each type of software; a smaller mismatch was predicted using ACUAINTRUSION. In general, the presented simulations by ACUAINTRUSION and PHREEQC produced similar results, making predictions consistent with the experimental data. However, the simulated results are not identical to the experimental data; sulphate (total S) is overpredicted by both models, most likely due to such factors as the kinetics of gypsum, the possible variations in the exchange coefficients due to salinity and the neglect of other processes.

Mathematical programming model for heat exchanger design through optimization of partial objectives

Mathematical programming can be used for the optimal design of shell-and-tube heat exchangers (STHEs). This paper proposes a mixed integer non-linear programming (MINLP) model for the design of STHEs, following rigorously the standards of the Tubular Exchanger Manufacturers Association (TEMA). Bell–Delaware Method is used for the shell-side calculations. This approach produces a large and non-convex model that cannot be solved to global optimality with the current state of the art solvers. Notwithstanding, it is proposed to perform a sequential optimization approach of partial objective targets through the division of the problem into sets of related equations that are easier to solve. For each one of these problems a heuristic objective function is selected based on the physical behavior of the problem. The global optimal solution of the original problem cannot be ensured even in the case in which each of the sub-problems is solved to global optimality, but at least a very good solution is always guaranteed. Three cases extracted from the literature were studied. The results showed that in all cases the values obtained using the proposed MINLP model containing multiple objective functions improved the values presented in the literature.

Effect of the intercalated cation-exchanged on the properties of nanocomposites prepared by 2-aminobenzene sulfonic acid with aniline and montmorillonite

Polymer/montmorillonite nanocomposites were prepared. Intercalation of 2-aminobenzene sulfonic acid with aniline monomers into montmorillonite modified by cation was followed by subsequent oxidative polymerization of monomers in the interlayer spacing. The clay was prepared by cation exchange process between sodium cation in (M–Na) and copper cation (M–Cu). XRD analyses show the manifestation of a basal spacing (d-spacing) for M–Cu changes depending on the inorganic cation and the polymer intercalated in the M–Cu structure. TGA analyses reveal that polymer/M–Cu composites is less stable than M–Cu. The conductivity of the composites is found to be 103 times higher than that for M–Cu. The microscopic examinations including TEM picture of the nanocomposite demonstrated an entirely different and more compatible morphology. Remarkable differences in the properties of the polymers have also been observed by UV–Vis and FTIR, suggesting that the polymer produced with presence of aniline has a higher degree of branching. The electrochemical behavior of the polymers extracted from the nanocomposites has been studied by cyclic voltammetry which indicates the electroactive effect of nanocomposite gradually increased with aniline in the polymer chain.

MINLP Model for the Synthesis of Heat Exchanger Networks with Handling Pressure of Process Streams

This paper introduces a new mathematical model for the simultaneous synthesis of heat exchanger networks (HENs), wherein the handling pressure of process streams is used to enhance the heat integration. The proposed approach combines generalized disjunctive programming (GDP) and mixed-integer nonlinear programming (MINLP) formulation, in order to minimize the total annualized cost composed by operational and capital expenses. A multi-stage superstructure is developed for the HEN synthesis, assuming constant heat capacity flow rates and isothermal mixing, and allowing for streams splits. In this model, the pressure and temperature of streams must be treated as optimization variables, increasing further the complexity and difficulty to solve the problem. In addition, the model allows for coupling of compressors and turbines to save energy. A case study is performed to verify the accuracy of the proposed model. In this example, the optimal integration between the heat and work decreases the need for thermal utilities in the HEN design. As a result, the total annualized cost is also reduced due to the decrease in the operational expenses related to the heating and cooling of the streams.

Retrofit of heat exchanger networks with pressure recovery of process streams at sub-ambient conditions

This paper presents a new mathematical programming model for the retrofit of heat exchanger networks (HENs), wherein the pressure recovery of process streams is conducted to enhance heat integration. Particularly applied to cryogenic processes, HENs retrofit with combined heat and work integration is mainly aimed at reducing the use of expensive cold services. The proposed multi-stage superstructure allows the increment of the existing heat transfer area, as well as the use of new equipment for both heat exchange and pressure manipulation. The pressure recovery of streams is carried out simultaneously with the HEN design, such that the process conditions (streams pressure and temperature) are variables of optimization. The mathematical model is formulated using generalized disjunctive programming (GDP) and is optimized via mixed-integer nonlinear programming (MINLP), through the minimization of the retrofit total annualized cost, considering the turbine and compressor coupling with a helper motor. Three case studies are performed to assess the accuracy of the developed approach, including a real industrial example related to liquefied natural gas (LNG) production. The results show that the pressure recovery of streams is efficient for energy savings and, consequently, for decreasing the HEN retrofit total cost especially in sub-ambient processes.