Merlin Alvarado-Morales

Conventional continuous plants use fixed‐capacity equipment, resulting in high capital risk and suboptimal performance under fluctuating demands. To address these, this study proposes an integrated framework for modular process design and supervisory control capable of adapting to demand uncertainty for long‐term economic viability. Market uncertainty is modeled using two scenarios: fixed‐rate compound annual growth rate (CAGR) to capture long‐term growth trends, and time‐dependent CAGR to account for annual fluctuations within those trends. Using ibuprofen manufacturing, we compare a conventional plant against a modular facility featuring standardized reactor modules. Supervisory control strategy dynamically selects the number of active modules to maintain optimal performance. Economic performance is evaluated using the levelized cost of production (LCOP) calculated across stochastic demand trajectories. Results demonstrate that while the conventional design is sensitive to market uncertainty, the modular configuration exhibits superior economic resilience, achieving lower mean LCOP and minimized risk of economic ruin.

The decarbonization of pharmaceutical manufacturing is critical for achieving the industry’s net-zero targets, and electrochemistry is emerging as a promising green technology that could play a key role in this transition. This work evaluates a continuous-flow electrochemical route for ibuprofen synthesis through electrochemical carboxylation of 1-chloro-(4-isobutylphenyl) ethane as a low-carbon alternative that can be directly coupled with renewable electricity. Experimental studies have demonstrated the selective formation of ibuprofen using a silver cathode in the ionic liquid N-methyl-N-propylpiperidinium bis(trifluoromethanesulfonyl)imide (PP13 TFSI). While the reaction mechanism is based on laboratory-scale, batch experiments, this study develops a conceptual design and scale-up methodology for the continuous route to provide an evaluation of the industrial feasibility of this electrochemical pathway through a rigorous plant-wide simulation in AVEVA® Process Simulation. Global sensitivity analysis is employed to identify key operating variables and evaluate their impact on reactor and process performance, energy consumption, and ionic liquid recovery. These insights provide a robust foundation for informed decision-making in process intensification, demonstrating the technical viability and scalability of continuous flow electrosynthesis as a sustainable alternative to conventional API manufacturing.

Continuous manufacturing processes offer significant advantages over batch processes, including easier scalability, reduced costs, lower raw material and solvent consumption, and improved energy efficiency. A robust techno-economic assessment is therefore essential to evaluate and facilitate the adoption of such technologies, as well as to guide process development. We present a novel framework that integrates stochastic optimization with rigorous process simulation for uncertainty-aware techno-economic assessment. This framework combines conceptual process design and simulation, global sensitivity analysis, stochastic optimization, and economic evaluation under uncertainty in a unified workflow. We apply the framework to the continuous manufacturing of ibuprofen, which is predominantly manufactured through established batch processes, and benchmark its performance against a conventional deterministic optimization approach. While the deterministic optimization converges more rapidly to a lower levelized cost of production (LCOP), the stochastic approach provides a more conservative, robust solution, reflecting real-world process variability. The resulting optimized design remains economically competitive, with an LCOP below current market prices, while ensuring greater reliability under uncertainty. By capturing variability in economic parameters, our approach enhances decision-making and facilitates exploration of conceptual design performance under uncertainty. This comparison highlights the importance of integrating uncertainty quantification into technology shifts and strategic process development.

Succinic acid (SA) is a valuable platform chemical that can be converted into biodegradable plastics, resins, solvents, etc. The emerging biological routes for SA production are gaining more attention because they exploit the natural abilities of bacteria to fixate carbon dioxide (CO₂). On the other hand, an inexpensive organic carbon source that can fulfill the energetic requirements of the microbial strain is also a significant challenge for industrial SA production. The current work presents a holistic techno-economic analysis of SA production using sugar-rich residual streams and biogas as raw materials. Simulation results showed that by establishing an integrated process, high SA production can be simultaneously achieved with biogas upgrading. The CO₂ provided from biogas and carbohydrates, which are provided from organic by-products is converted into two products: biomethane (CH₄ > 95%, a clean biofuel), and SA. The mass and energy balances and techno-economic indicators were simulated and calculated using SuperPro Designer^®. The total capital investment and the total production cost for a facility producing 1000 tSA/year were estimated to be EUR 5,211,000 and EUR 2,339,000 per year, respectively. The total revenue was calculated to be EUR 2,811,000 per year, while the revenue due to biomethane produced, namely, 198,150 Nm³ corresponded to EUR 205,284 per year. The return on investment, payback period, and internal rate of return of the project were found to be 11.68%, 8.56 years, and 11.11%, respectively.

Biological biogas upgrading with H₂ derived from excess renewable electricity was modeled and simulated in PROII^® (AVEVA Group plc, Cambridge, UK). An economic analysis was performed for a biogas plant processing 100,000 tons of biomass (substrate) per year. The biogas and biomethane production simulation results were validated with laboratory experimental data, as well as full-scale data obtained from biogas plants. A biomethane production cost of 0.47 €/Nm³ was calculated, while the minimum biomethane selling price for NPV = 0 was equal to 0.66 €/Nm³, considering a H₂ price of 1.0 €/kg. The feasibility analysis indicated that the H₂-related costs were the major contributor to the capital and operation costs due to high expenses associated with the in-situ H₂ storage facility and the purchasing of H₂, respectively. Compared to conventional upgrading methods, biological biogas upgrading has a higher capital and production cost, which can be reduced by increasing the plant capacity. The sensitivity analysis showed that the profitability is very sensitive to biomethane prices, capital investment, and the H₂ price.