Galo Antonio Carrillo Le Roux

Dynamic simulation of distillation columns and chemical reactors remains essential for plant design, controllability analysis, and economic optimization. High-purity separations of close-boiling mixtures present significant computational challenges due to nonlinear thermodynamic behavior and stiff differential-algebraic equation (DAE) systems. This work presents a unified Python/JAX framework integrating four computational modules: (1) Peng-Robinson thermodynamics with complex-step differentiation, (2) nonlinear solvers (Newton, Broyden, Newton-Krylov) with automatic Curtis-Reid scaling, (3) DAE solver with Radau IIA collocation and intelligent auto-selection, and (4) constrained optimization using the Augmented Lagrangian Method with JAX automatic differentiation. The framework leverages JAX’s just-in-time compilation (JIT), vectorization (vmap), and automatic differentiation (AD) to achieve near-compiled-language performance. Validation includes: nonlinear solver benchmarks with Newton-Krylov achieving 100% success across seven problems (n=2 to 5000), Williams-Otto reactor optimization with 0.06% deviation from published literature and 1325× real-time speedup, and a 180-stage propylene-propane splitter with 18× real-time performance under three concurrent disturbances. The framework shows that is possible to have an open-source alternative suitable for real-time optimization, operator training, and advanced process control applications.

We present a steady-state, optimization-based techno-economic study of a continuous fluidized temperature-swing adsorption (TSA) system for post-combustion CO2 capture from biomass-derived flue gas, using two adsorption stages and one desorption stage with integrated heat-pump thermal management. The GAMS/CONOPT4 model couples molar and energy balances, Toth adsorption equilibrium, fluidized-bed hydrodynamics and literature cost correlations. Optimization yields CO2 purity of 96% v/v and 95.5% recovery at low, safe pressures with particle Reynolds numbers of 2-11, indicating near-minimum-fluidization operation. The nominal capture cost is 87 USD/tonCO2 with an internal rate of return of 42%; utilities comprise 49% of annualized costs and the adsorption compressor dominates equipment capital. Disabling the heat pump increases modeled capture cost to 124 USD/tonCO2, highlighting the heat pump’s decisive role in reducing energy demand and costs. Adding adsorption stages lowers modeled cost further but produces impractically shallow beds, revealing a trade-off between mass-transfer performance and feasible bed geometry. A sensitivity analysis demonstrated a linear positive correlation between electricity cost and capture cost, with capture costs potentially as low as 50 USD/tonCO2 and an internal rate of return as high as 64%. While results demonstrate the technical and economic plausibility of a heat-pump-assisted fluidized TSA under the stated assumptions, the study recommends including flue contaminants, refined heat-exchanger and pressure-drop models, and experimental validation for scale-up.

Water supply in the countryside of São Paulo state, Brazil, is based on groundwater resources that can be contaminated with substances such as heavy metals or fluoride, requiring the usage of water treatment technologies such as Reverse Osmosis (RO); however, RO systems create a stream of high-salinity brine, with negative environmental consequences. Besides, regulatory constraints demand that well operations must be interrupted for a daily contiguous period. In this work, a Mixed-Integer Linear program (MILP) was implemented to define water network topologies and well exploitation schedules, under these downtime constraints, aiming the minimization of RO plant capacity (and, therefore, of brine discharges). This model was then applied to the water supply of a small city in the São Paulo countryside, with around 8000 inhabitants, where high fluoride concentrations warranted the implementation of an RO system. Demand variations between weekdays and weekends (with demands 52.7% higher) were modeled using a multi-scenario formulation. This model was optimized under different conditions of tank capacity and membrane technologies. Different membrane systems (with salt retention rates varying from 85% to 99.5%) associated with different storage tanks (with volumes between 50 and 1000 m³) led to different system topologies, and a trade-off was observed between plant capacity, tank capacity, and operating pressure: while a low pressure system with a small tank capacity required larger plant capacities (up to 44.02 m³/h), high pressure systems associated with large storage tanks required smaller plants for treatment (with a capacity as small as 11.15 m³/h).

As the world recognizes the need for more sustainable practices, greater effort has been put into improving the economic viability of bioprocesses. Fields like metabolic engineering explore strategies to improve the production of bioproducts of industrial relevance, such as the use of alternative carbon sources. Regarding the performance assessment of a bioprocess, the product yield can be helpful, but other parameters like product titer and productivity (rate of production) are just as important. Furthermore, the highest performance may not come from a scenario with the highest yield, titer or productivity, but from a titer, rate, yield (TRY) set that maximizes profitability when the production costs are considered. Our previous work introduced the DySEEP approach, which uses an economic metric based on TRY parameters for evaluation of the potential of bioprocesses. This work expands the DySEEP program in key areas such as adding the possibility of exploring fed-batch processes and using strain design algorithms. Taking batch and fed-batch poly-3-hydroxybutyrate (PHB) production with E. coli as the case study, the scenarios that would lead to economic viability and the theoretical maximum performance for three different carbon sources, glucose, glycerol, and xylose, were identified. The results were then set in a strain design algorithm using Minimal Cut Sets (MCS) to find genetic interventions that could achieve the desired performance. The genetic interventions found with the MCS algorithm successfully led to strains that achieve the economic viability scenario, based on in silico simulations. This work illustrates how the expanded approach can be used to guide metabolic engineering strategies to improve the production of important bioproducts.

By capturing carbon dioxide from biomass flue gases, energy processes with negative carbon footprint are achieved. Among carbon capture methods, the fluidized temperature swing adsorption (TSA) column is a promising low-pressure alternative, but it has been developed on small scales. This work aims to model, simulate and optimize a fluidized TSA multi-stage equilibrium system to obtain a cost estimate and a conceptual design for future process scale up. A mathematical model described adsorption in multiple stages, each with a heat exchanger, coupled to the desorption operation. The model was based on elementary macroscopic molar and energy balances, coupled to pressure drops in a fluidized bed designed to operate close to the minimum fluidization velocity, and coupled to thermodynamics of adsorption equilibrium of a mixture of carbon dioxide and nitrogen in solid sorbents (the Toth equilibrium isotherm was used). The complete fluidized TSA process has been optimized to minimize costs, considering equilibrium in each stage. The optimal configuration for heat exchangers was determined and a unit cost for carbon dioxide capture was estimated. It was found that a small number of stages is required to meet captured carbon specification at 95% molar purity, while process cost per metric ton of CO2 was within range of other capture technologies. These findings show that the methodology developed here is useful for guiding the conceptual design of fluidized TSA process for carbon capture.

Concerns with sustainability have led to increasing interest in bioprocesses in the last decades. In particular, environmental problems with plastic disposal have been a major issue. Bioplastics such as poly-3-hydroxybutyrate (PHB) are potential substitutes since they are biodegradable and less toxic. However, their production costs are high and optimization is required. Many works have therefore aimed to build strains capable of higher product yields. But in the case of products that share a precursor with biomass and in the case of intracellular metabolites, a trade-off may occur. Not only yield but also final biomass, titer, and productivity have to be considered. Therefore, this work presents an approach named Dynamic Simulations for Evaluation of Economic Potential (DySEEP), which uses dynamic flux balance analysis (DFBA) and an economic metric as a function of the bioprocess parameters for evaluation of the production of bioproducts of industrial interest. As a case study, the PHB production potential of recombinant Cupriavidus necator, Escherichia coli, and Saccharomyces cerevisiae was analyzed. While some key polymer properties cannot be predicted due to the nature of DFBA simulations, the PHB production is a good case study to highlight the trade-off between biomass and product formation. It was identified that for growth-associated production with recombinant E. coli and the NADPH-dependent PHB synthesis pathway, the scenario that starts positive cash flows is when a yield of 0.37 g/g and its respective final biomass, titer, and productivity is achieved, and the maximum theoretical profit would be achieved when a yield of 0.50 g/g and its respective parameters is reached. Furthermore, comparison between the internal flux distribution of the best scenario identified and the flux distributions of a simulation constrained with experimental data from the literature allowed the suggestion of genetic modifications that could enhance PHB production, such as knockouts for interruption of the oxidative phase of the pentose phosphate pathway, of the acetate production reaction, and of the reaction catalyzed by the 2-oxoglutarate dehydrogenase enzyme or downregulation of the TCA cycle, setting therefore potential targets for metabolic engineering strategies. For nongrowth-associated production with both recombinant E. coli and C. necator, the scenario at which cash flow starts to become positive is when 40% (mol) of the available glucose is used in the growth phase and the remaining 60% is used in the production phase, and the scenario that leads to the maximum theoretical profit, within a realistic maximum PHB content, is when 20% (mol) is used in the growth phase and the remaining 80% in the production phase, information that sets targets for bioreactor operation strategies such as defining the moments for nutrient limitation and for synthetic biology by showing when to activate genetic toggle-switches.