Conference Agenda

Peruvian mining, crucial to the national economy, faces the challenge of optimizing gold recovery from depleted leach pads (DLPs), such as those at the Shahuindo mine in Cajamarca. This study evaluated the injection leaching method as an innovative solution to reactivate these residual resources. The research, conducted in two phases, began with a geophysical electrical resistivity tomography diagnosis that identified unleashed areas in Pad 1A, followed by the design of 31 injection wells and metallurgical tests that established 350 ppm of cyanide as the optimal concentration. Phase II (2023) covered the operational implementation of the process, with cell assembly, filter cleaning and controlled well rinsing. During the pilot phase (Dec. 2021-June 2022), 2,110 ounces of gold were recovered, bringing the overall recovery from the pad from 77.3% to 79.2%. In the operational phase (Dec. 2022-Mar. 2023), an additional 1,317 ounces were obtained. Comparison with conventional methods demonstrated the superiority of Injection Leaching, achieving higher recovery with 15 times less cyanide consumption (350 ppm vs. >2,300 ppm). In addition, the re-leaching operation in 2023 generated a return of more than USD 2.4 million, albeit with lower metallurgical efficiency. The injection leaching method is a viable, sustainable, and profitable technology that maximizes the extraction of residual gold through controlled, three-dimensional injection, positioning itself as the optimal alternative for exploiting value in historic stockpiles. Keywords-- Injection leaching, re-leaching, PADs, recovery, gold, optimization.

This study evaluated the use of saponins from Chenopodium quinoa Willd. to formulate natural cleaners from used cooking oil (UCO). The objective was to extract saponins from three quinoa varieties (Real, Sajama Blanca, and Blanca de Juli), quantify them using the standard afrosymetric method, and evaluate the stability and pH of the cleaners made with UCO. The saponins were obtained by physical extraction (scarification with 600-grit sandpaper), achieving yields of 9.2–11.8 mg of extract/g of quinoa. Saponin quantification was performed using the afrosymetric method, estimating contents of 2.4852% for Blanca de Juli, 0.0953% for Real, and 0.0060% for Sajama Blanca, which allowed for the selection of Real and Blanca de Juli for formulation. The UCO was purified by washing with water, decantation, filtration with cotton/activated carbon, and deodorization with dried mandarin peels. Formulations with and without oil were prepared, and pH and stability were evaluated. The cleaners showed no phase separation after two weeks, exhibited good consistency, and the pH ranged from 4.36 to 5.92, amenable to adjustment with a mild buffer. Overall, the results confirm the technical feasibility of using quinoa saponins as natural surfactants to valorize ACU in cleaning formulations.

This work presents a student-centered learning strategy with an interdisciplinary and international approach, developed in the Microbiology course of the Environmental Engineering program at the Technological University of Bolívar (UTB), Cartagena, Colombia, within the framework of the UTB Linked Class pedagogical strategy, implemented since 2020. The activity consisted of the students making artisanal wine, to gain a hands-on understanding of the key role of microorganisms and the biochemical processes involved in alcoholic fermentation. This experience, carried out during a partial mirrored class, enabled students to apply previous knowledge on yeasts, microbial metabolism, and the transformation of sugars into ethanol, thus strengthening the connection between theory and practice. Students organoleptically assessed the final product (taste, aroma, texture) and considered the relevance of microbiology in the real world and in the context of industry. Results obtained from field observation and perceptual surveys show significant learning and increased motivation to study microbiological processes. The strategy has been implemented as a didactic learning tool promoting scientific knowledge acquisition in an active, collaborative and interactive way.

Chemical engineering has progressively expanded from its traditional focus on unit operations and large-scale petrochemical processes to a broader interaction with biotechnology, nanotechnology, and sustainability-oriented practices. In parallel, artificial intelligence (AI) has transformed industrial systems through enhanced process optimization, predictive modeling, and the integration of smart and adaptive production environments. This paper examines the intersection of these developments by conducting a bibliometric analysis of publications indexed in Scopus between 2015 and 2024, complemented with a foresight perspective to anticipate future trajectories. The results identify five thematic clusters—adsorption and material characterization, process optimization and prediction, computational chemistry, neural networks and chemometrics, and chemical process automation—together illustrating the breadth of AI applications across the discipline. A temporal review highlights the transition from early applications in process control and multivariate analysis to recent advances in biotechnological, pharmaceutical, and materials engineering contexts. The study also situates these global trends within the Peruvian industrial environment, characterized by limited diversification and high dependence on raw material exports, but with emerging opportunities in mining analytics, agro-industry, and pharmaceutical innovation. The conclusions emphasize the strategic relevance of integrating AI into chemical engineering education and research as a means to enhance competitiveness and guide sustainable development pathways.

This study evaluates the technical and industrial feasibility of producing rum from sugarcane molasses in Honduras as a strategy for agroindustrial diversification and circular economy integration. Laboratory-scale fermentation, distillation, and accelerated aging were experimentally evaluated using molasses as the primary substrate. Fermentation achieved an ethanol yield of 77% of theoretical conversion, while batch distillation produced a heart fraction with 42% v/v ethanol. Accelerated aging was simulated using a controlled reflux system with selected wood chips, generating distinct sensory profiles in significantly reduced time.

To assess industrial scalability, the process was modeled in Aspen Plus, integrating fermentation, multistage distillation, and energy balances. Simulation results indicate that an industrial plant processing 9,650 t·y⁻¹ of molasses could produce 2.5 million liters of rum annually while meeting international quality standards for volatile compounds. Sensitivity analyses of distillation columns optimized reflux ratios and feed stages to maximize ethanol recovery and minimize impurities.

The combined experimental and simulation results demonstrate that molasses valorization into rum is technically feasible, economically promising, and aligned with sustainable industrial development objectives in sugarcane-producing regions.

The essential objective of this study is to evaluate the effect of KOH concentration (7.5, 12.5, and 25 %) g/L on the modification of the physical, chemical, and mechanical properties of individual fibers and composites obtained from Sansevieria trifasciata leaves. The fibers were extracted using the water retting method and selected via stereoscopy for the alkaline process, mechanical treatment, and physical and chemical testing. Characterization comprised the quantification of lignin, cellulose, and hemicellulose, surface analysis and cross-sectional measurement via scanning electron microscopy, and uniaxial tensile testing. The results show that increasing the percentage of KOH altered the chemical composition of the fibers, decreasing the percentages of lignin and hemicellulose and increasing the percentage of cellulose. In conclusion, ANOVA analyses indicate that treatment of the fibers with KOH significantly influences the mechanical characteristics and tensile strength of the fiber.