Engineering

Abstract: The design of multipurpose processes in rural agroindustry considers quality criteria, environmental sustainability, and economic feasibility. The problem arises from the limited integration between process simulation and environmental assessment in traditional production systems of granulated panela (GP) and sugarcane honey (SH) in Pastaza, Ecuador. The objective was to propose a methodology for the design of sustainable multipurpose processes through simulation and the application of the GREENSCOPE tool. The methodology combined mass and energy balances, quality attribute analysis under sigma level, economic evaluation using net present value (NPV), internal rate of return (IRR), and discounted payback period (DPP), along with environmental analysis through efficiency, energy, economic, and environmental indicators. Different production scenarios were simulated with percentage combinations of GP and SH in batches of 10, 120, and 1560 units. Results show that the alternative consisting of 60% GP and 40% SH in 120 batches achieved the highest profitability, with an NPV of 141,014.59 USD and an IRR of 45.80%, while meeting technical and quality criteria. The GREENSCOPE analysis identified environmental impacts mainly associated with emissions from biomass combustion. The multipurpose production of 60% granulated panela and 40% sugarcane honey in 120 batches was identified as the best technological and economic alternative for the analyzed rural agroindustry.

Abstract: Large-scale water infrastructure projects require timely commissioning to generate economic returns and recover invested capital. Delays in reservoir impoundment can significantly reduce project performance by increasing capital lockup, deferring revenue generation, and amplifying financing costs. This study presents an engineering economics evaluation and forensic financial audit of the Zarima–Mayday Dam Project in northern Ethiopia, which was constructed with an initial investment of ETB 13.0 billion (approximately USD 541.67 million at 24 ETB/USD) to irrigate a 40,000-ha commercial sugarcane estate. Owing to delayed reservoir impoundment following completion of civil works, the project remained largely non-operational for approximately ten years. An engineering economics framework based on discounted cash-flow analysis was applied to quantify the economic impacts of project delay. The assessment evaluated the present value of locked capital, annual foregone agricultural revenue, Net Present Value (NPV), Internal Rate of Return (IRR), Benefit–Cost Ratio (BCR), and Capital Recovery Factor (CRF), while accounting for compound interest, inflation, and exchange-rate depreciation using an updated benchmark of 180 ETB/USD. The results indicate a cumulative economic loss of approximately ETB 378.51 billion (about USD 2.1 billion), comprising ETB 155.39 billion in compounded capital lockup and ETB 223.12 billion in foregone agricultural revenue. The Benefit–Cost Ratio declined from 1.45 to 0.28, while the Internal Rate of Return fell below the minimum acceptable discount rate, indicating a substantial deterioration in economic viability. The proposed framework provides a quantitative basis for evaluating delayed infrastructure projects and supports improved commissioning strategies, investment planning, and financial management of future large-scale dam and irrigation developments.

Abstract: This methodological case study demonstrates how a human-guided AI expert system applies heuristic reasoning to synthetic signals representative of those from an onboard battery-management system, using the LiFePO₄ single-particle electrochemical model as an analytical test bed. The work is conducted as a structured dialogue between a human domain expert and an AI expert system. The framework grounds the bivariate kernel V = μ + W — equilibrium chemical potential μ plus non-equilibrium reaction work W — in the Mahler bivariate first law of nonequilibrium thermodynamics, exploits the regular-solution symmetry of LiFePO₄ at c = 1/2 to identify W as a directly observable thermodynamic field, and develops a reference logic and three-stage attribution heuristic discriminating concentration-polarization memory, phase morphology change, and thermal feedback contributions to the measured W under GITT protocol. A lumped enthalpy balance runs alongside as a local thermal-constraint instrument on the convective heat-transfer coefficient, returning a per-iteration constraint margin and flag rather than a terminal verdict; the joint report combines the mechanism attribution with the local thermal-constraint flag as two independent, non-terminal diagnostic signals. An integral solver/model energy-closure check gates each candidate simulation for admissibility before the thermal-constraint and iterative-feasibility stages, so only energetically consistent candidates are interpreted.

Abstract: Nitric acid production is among the most significant industrial point sources of nitrous oxide, which is a greenhouse gas with a global warming potential approximately 298 times that of carbon dioxide, yet the large installed base of legacy dual-pressure plants continues to operate with non-selective catalytic tail gas treatment systems that offer limited greenhouse gas abatement and impose rigid thermal constraints on the gas turbine cycle. A steady-state digital twin of an industrial dual-pressure nitric acid plant producing 52 t per hour of 60 wt.% nitric acid is developed, validated against measured plant data, and used to evaluate two selective catalytic retrofit configurations. The first heats raw tail gas to catalyst ignition temperature using the existing process heater, then raises the purified gas to turbine inlet conditions by mixing with flue gas from a newly installed combustion chamber. The second achieves the required temperature rise internally through catalytic fuel gas oxidation within an additional catalyst shelf in a two-bed reactor, eliminating supplementary combustion equipment entirely. The first configuration reduces total greenhouse gas emissions by 37% in carbon dioxide equivalent terms, eliminates ammonia slip, and enables a 5% production capacity increase worth 5.75 million EUR per year, at a capital cost of 4.77 million EUR and a discounted payback period of 16 months. The second achieves a 43% emissions reduction at a capital cost of 1.34 million EUR, reduces annual utility costs by 1.75 million EUR, and recovers its investment within 2.6 months without increasing electricity demand. The results demonstrate that selective catalytic tail gas treatment retrofit is a value-generating investment rather than a compliance cost. Projected across the global fleet of unabated dual-pressure plants, equivalent adoption could reduce sectoral nitrous oxide emissions by more than 21 Mt of carbon dioxide equivalent per year, representing over half the identified global industry mitigation potential.

Abstract: Process optimization can improve the environmental and economic performance of biorefineries, yet its social consequences remain largely unexamined. In this study, we apply a prospective, screening-level social life cycle assessment (S-LCA) to a thermal-extractive avocado oil biorefinery. We compare a baseline configuration (S0) with three optimization scenarios, namely green chemistry (S1), heat integration (S2), and water integration (S3). The assessment relies on the Social Impact Weighting Method, and it uses SOCA v3 and PSILCA v3.1.1 background data on the ecoinvent 3.10 structure in openLCA 2.3. Results are expressed as medium-risk worker-hour equivalents per 1 kg of avocado oil under a cradle-to-gate boundary. In total, five indicators (fair salary, weekly hours of work, unemployment, contribution to economic development, and promoting social responsibility) are covered across four stakeholder groups, together with a 1000-iteration Monte Carlo analysis. In most configurations, the oil-processing stage was the leading social hotspot, because it embeds the extraction solvent and the other reagents. Of the three levers, only green chemistry worsened the social profile. It raised every worker-hour indicator by 24% to 92% relative to the baseline, most markedly for unemployment, since the substituted solvent supply chain adds upstream worker-hours. Heat integration and water integration, by contrast, both reduced the social risk, by 15% to 29% and by 10% to 31%, respectively. In addition, the Monte Carlo analysis showed that green chemistry was clearly separated from the other configurations. When these findings are read together with the environmental and economic assessment of the same system, heat integration and water integration appear to improve all three sustainability pillars at once. Green chemistry is therefore the single strategy in which an environmental motivation conflicts with the social dimension, which underlines the value of adding the social pillar to biorefinery optimization.

Abstract: Hydrogen sulfide (H₂S), a high-volume by-product of the hydrodesulfurization of fossil fuels, can be valorized by thermolysis to recover both molecular hydrogen and elemental sulfur, rather than being oxidized as in the conventional Claus process. The viability of this route depends on quantitative knowledge of the reaction mechanism and of the energy costs of dissociation, which are difficult to obtain experimentally at the temperatures involved. Here we study H₂S thermolysis by reactive molecular dynamics (RMD) with the ReaxFF potential for systems of 1000 H₂S molecules at 1 atm, addressing three coupled questions: the simulation parameters required for dilute gases, the energetics of dissociation, and the elementary reaction mechanism. The interaction cutoff radius proved critical: the original 10 Å value, parametrized for condensed systems, misses about 23 eV of attractive non-bonded interaction energy in the gaseous system and fails to capture dissociation at 3000 K within 20 ns, whereas radii of 30–40 Å converge. Using a 40 Å cutoff at 2500, 3000 and 3500 K, atom-resolved species-transition records reveal a free-radical chain mechanism with temperature-invariant elementary steps: S–H homolysis initiates the chain, hydrogen abstraction (H• + H₂S → H₂ + HS•) is essentially the exclusive source of H₂ (persistent H•+H• recombination contributed only 1, 13 and 17 events, below 0.5% of the abstraction count), and a slow sulfur-condensation stage (S₂ → S₃ → S₄) limits the net conversion, which reached 8.7%, 26.7% and 46.3%. The enthalpy of the system rises linearly with the number of H₂S molecules consumed (R² ≥ 0.99), defining energy costs of 2.41 ± 0.07, 3.03 ± 0.06 and 3.89 ± 0.18 eV per molecule that increase with temperature by ≈1.36 eV per 1000 K; at 3500 K the cost is statistically indistinguishable from the complete-dissociation limit of 3.90 eV obtained independently from Kirchhoff's law and the experimental H–SH bond energy. These results provide a thermochemically validated, molecular-level basis for engineering the valorization of residual H₂S as a source of green hydrogen.

Abstract: This article presents a summary of recent theoretical investigations on the residence time distribution (RTD) of particles in laminar flow tubes, based on stochastic simulation of particles trajectories, and also a formerly unpublished comparison of the numerical simulation results with experimental data. The RTD depends on the flow velocity profile of the fluid. For the two extreme flow types, plug or uniform flow (UF) and fully developed or parabolic flow (PF), the RTD is a function of two dimensionless numbers: the particle diffusivity, D, and the tube aspect ratio, a. A third additional dimensionless variable, the Reynolds number, Re, should also be considered when the stationary fluid velocity profile gradually develops along the tube (steady transition flow, TF). The role of D can be split up into two contributions: one due to diffusion along the main fluid flow direction, the other to cross-stream diffusion; the first moment of the RTD depends on the product aD in the first case, but only on D in the second one. In the ideal case in which the fluid velocity is constant throughout the tube (plug flow) and particle axial diffusion is absent, the particle RTD coincides with that of the fluid. In any other circumstances the RTD of the particles shifts to smaller residence times in comparison with the RTD of the fluid: the mean particle residence time in the tube is smaller than that of the fluid. This surprising outcome is explained in terms of the particle survival probability, the mean particle radial coordinate and the mean axial displacement of the particles per unit time along the tube. In the last section of the paper, theoretical particle survival probability and residence time distribution are both favorably compared with the presently available experimental results.

Abstract: Polymeric membrane systems have emerged as an effective approach for water separa-tions due to their high separation efficiency, simplicity, and adaptability to a wide range of water treatment applications. However, traditional membrane fabrication processes often rely on toxic organic solvents, such as N-methyl-2-pyrrolidone (NMP) and dime-thylacetamide (DMAc), which pose environmental and health risks. Eco-friendly solvents have been investigated as an alternative to traditional toxic solvents. This study inves-tigates the fabrication and performance of polymeric membranes using eco-friendly solvent systems, with a focus on bilayer membranes designed to improve separation performance over traditional single-layer membranes. Membranes were fabricated using eco-friendly solvents, Rhodiasolv^© PolarClean and gamma-valerolactone in combination with polymers polysulfone (PSf) and poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP). Membranes were fabricated using non-solvent induced phase separation (NIPS) through doctor blade extrusion (DBE) and slot-die coating (SDC) methods in order to compare traditional laboratory-scale casting methods (DBE) with scalable fabrication techniques (SDC). Bilayer membranes were found to overcome the inherent limitations presented by single-layer membranes, such as mechanical stability, with polydopamine (PDA) being incorporated as an adhesion-promoting additive to enhance bonding be-tween polymer layers. Membrane characterization included scanning electron micros-copy (SEM), contact angle measurements, and tensile strength tests, along with per-meability and solute rejection tests to investigate membrane performance. Results showed that membranes fabricated at higher concentrations and through the SDC method per-formed at a higher level than the other membranes, exhibiting improved solute rejection rates and less variability in pore structure distribution.

Abstract: This paper reviews requirements for water supply rate for life support of human crews on deep space missions such as Mars, and methods to provide that water supply. The literature on required water supply flow rate to support human crews on deep space missions is inadequate, typically with a few terse estimates lacking analysis or explication. These estimates were generated in an era where saving mass was critical and the allocations were skimpy. Here, we provide new, updated estimates of suggested water supply flow rate (at three levels of comfort) to support human crews on deep space missions in an era where mass in deep space is far more affordable. The total mass of water required for the mission is significant, but appropriate in the era of huge launch vehicles like the Starship. It was widely believed that water recycling systems are necessary to reduce mission mass in the era of high launch costs. However, the reliability of recycling technology is poor, as evidenced by experience on the International Space Station. Use of spares to replace subsystems that fail was proposed to greatly improve reliability, and that works good on paper as shown by probabilistic analysis, but the logistics of implementation are problematic. Bringing water from Earth is the best way to supply crew requirements for limited missions likely to be the first human landings on Mars. For futuristic missions of great extent, either recycling or use of indigenous water from Mars would be needed. In any mission, if possible, bringing a survival level of water from Earth is strongly recommended.

Abstract: The Zeta-Minimizer Theorem (ZMT) furnishes a rigorous axiomatic foundation for thermodynamics through three principles—strict concave entropy maximization, uniform Gibbs free energy landscapes with spectral minima, and irreducibility enforced by perpetual bounded oscillations—augmented by helical geometry in which prime numbers emerge as indivisible cycle lengths. The multi-component grand-partition function Z(s) is constructed and establish its universal categorical invariance under functorial mappings, thereby providing a parameter-free backbone for equilibrium and dynamical phenomena. From this structure the thermodynamic conjugate pairs and variational Maxwell relations, the emergence of chemical equilibrium and the equilibrium constant are deductively derived directly from the grand potential, explicit fugacity coefficients, and a variational reaction-rate law governed by the analytical scalar Hessian of the gas-phase reaction coordinate. For heterogeneous systems solid–fluid interface continuity conditions, marginal stability criteria via the covariant fugacity Hessian are obtained, and—crucially—the first-principles deductive origin of linear scaling relations and Sabatier volcano plots from closed prime functions, without empirical parameters. A complete methodology is developed for ammonia-synthesis loop analysis and catalyst optimization. Central to this methodology is the vapor–solid (V/S) locus, which incorporates inert effects, promoter-induced shifts in effective black-box constants, and distinct operating regimes of Fe- versus Ru-based catalysts. Numerical integrations and Hessian-based kinetic analyses quantitatively recover industrial third-bed behavior, elucidate the lab–industry gap in recent low-pressure studies, and furnish predictive guidelines for next-generation catalyst and process design. The ZMT framework thereby bridges number-theoretic structure with practical chemical engineering, offering zero-adjustable-parameter predictions for sustainable ammonia production.

Abstract: Cobalt-based electrocatalysts are promising alternatives to costly noble metal OER catalysts, yet they suffer poor conductivity, insufficient active sites and severe structural degradation during electrolysis. Herein, hollow Co₃O₄ microspheres were fabricated via solvothermal synthesis and calcination, followed by gas-phase phosphorus doping and controlled NaBH₄ reduction to prepare a series of defective Co₃O₄/P−B electrocatalysts. Multiple characterizations including XRD, SEM, TEM, EPR and XPS confirm that 1 h mild reduction retains the intact hollow spherical framework while introducing abundant lattice defects. P doping and reduction jointly adjust the electron density of Co and P atoms without altering oxygen’s chemical state. Electrochemical tests in 1.0 M KOH reveal that Co₃O₄/P−B1 delivers optimal OER performance: an overpotential of 282 mV at 10 mA·cm⁻² and a small Tafel slope of 88.7 mV·dec⁻¹. It maintains negligible current decay over 70000 s chronoamperometry measurement. Post-catalysis XPS verifies that surface adsorbed *OOH species act as core active sites. This work proposes a facile morphology-defect co-regulation strategy to design high-stability hollow cobalt-based alkaline OER electrocatalysts.

Abstract: This study develops a computer-aided molecular design (CAMD) framework to select solvents for extracting octacosanol from multicomponent sugarcane wax. The solvent-selection problem is formulated as a mixed-integer nonlinear programming problem in which candidate solvents are generated from UNIFAC functional groups and evaluated using the net distribution coefficient and net solvent selectivity. Four metaheuristic solvers—ant-colony optimization (ACO), simulated annealing (SA), efficient ant-colony optimization (EACO), and efficient simulated annealing (ESA)—are compared to assess solvent quality and computational efficiency. EACO and ESA incorporate Hammersley sequence sampling to improve multidimensional sampling uniformity relative to conventional pseudo-random sampling. The results show that all four solvers consistently identify the same highest-ranked candidate solvent. ACO and EACO require substantially fewer objective-function evaluations than SA and ESA, while SA-based methods provide greater diversity among lower-ranked candidates. EACO reduces the computational cost relative to ACO while retaining the same top-ranked solvents, whereas ESA provides only a modest efficiency improvement over SA. Overall, the proposed CAMD framework reliably identifies promising solvents for nutraceutical extraction, and quasi-random sampling improves the efficiency of metaheuristic solvent design.

Abstract: Industrial process safety systems are predominantly reactive: alarms activate after limits are crossed, faults are diagnosed after deviations develop, and HAZOP knowledge remains offline during operation. This paper proposes Predictive Operational Safety Engineering (POSE) as an emerging research paradigm in which operational safety is treated as a continuously forecastable state rather than a post-event classification, shifting the operational question from what has gone wrong? to how much safe operating time remains, and which intervention is most urgent? Four integrated predictive safety metrics anchor the framework: Remaining Safety Margin (RSM), quantifying the normalized distance between the predicted process trajectory and the nearest safety boundary; Remaining Safe Operating Time (RSOT), estimating when that boundary will be crossed under the current trajectory; the Operational Vulnerability Index (OVI), combining margin depletion rate, safeguard availability, and consequence severity into a single intervention-urgency signal; and Predictive Safety Confidence (PSC), the probability that a specific named operator intervention can be executed to completion before the predicted safety boundary is crossed, coupling prediction uncertainty with action execution time. The Predictive Operational Safety Twin (POST) is proposed as a three-layer reference architecture implementing POSE through predictive process intelligence, predictive safety intelligence, and human safety intelligence. The paper synthesizes six research streams, positions POSE against seven adjacent disciplines, states ten guiding principles, and formulates a research agenda. As a conceptual narrative review, the paper does not claim empirical validation of POSE. Instead, it establishes the foundational vocabulary, reference architecture, and research agenda required to advance predictive operational safety from an emerging concept toward benchmarked and industrially validated practice.

Abstract: An entropy-based solubility parameter-translated Soave-Redlich-Kwong equation of state (eSPT-SRK EoS) was developed that incorporates two correction parameters which can be linearly correlated with the critical compressibility factor of pure substances. The correlated results gave an average relative deviation (ARD) value of 5.4 % at the critical density for a database of 28 widely-used chemicals. Estimation of liquid densities at standard temperature and pressure conditions gave ARD values of 5.8 % compared with the original SRK EoS of 22.2 %. The eSPT-SRK EoS was applied to calculate thermodynamic properties (entropy, fugacity, cohesive energy density) and was found to be reliable for estimating entropy-based Hansen-type solubility parameters (eHSP). The eSPT-SRK EoS was compared with a corrected form of the entropy-based solubility parameter-traslated Peng-Robinson EoS (eSPT-PR EoS) and both functional forms were found to give reliable eHSP values. Therefore, the formulation methodology can be applied to other cubic equations of state for specialized fluid mixtures.

Abstract: Catalyst deactivation shifts the optimal operating region of exothermic fixed-bed reactors, yet most reactor digital twins focus on monitoring rather than catalyst-state-aware operating decisions. This work presents a self-optimizing digital twin integrating a physics-based reactor model, a moving-window constrained activity estimator, and a target-optimization layer, demonstrated through simulation for o-xylene oxidation to phthalic anhydride in a vanadia-titania heat-exchanged fixed-bed reactor. Sparse axial temperature and conversion measurements are reconciled to estimate an axial catalyst activity profile; gas and coolant inlet temperatures are then updated subject to a hot-spot safety constraint. The estimator achieved an activity-profile RMSE of 0.075, an outlet-conversion RMSE of 0.99 percentage points, and an outlet-temperature RMSE of 1.85K. Under the baseline noisy-measurement scenario, estimated-activity optimization raised the mean phthalic anhydride yield from 46.3% under fixed targets to 61.9%, within 0.14 percentage points of the true-activity optimum, while maintaining the maximum reactor temperature below 730K. This corresponds to recovering approximately 99.1% of the yield improvement available with perfect catalyst-state knowledge. The policy remained superior to fixed-target operation across all tested noise levels, sensor configurations, and kinetic pre-exponential perturbations, although plant validation is still required to quantify structural model error. The findings demonstrate the value of linking catalyst-state estimation to operating-target adaptation in a reproducible catalytic-reactor digital-twin workflow.

Abstract: The rapid growth of electric mobility, renewable energy storage, and portable electronics has sharply increased global lithium demand, highlighting the environmental and socio economic drawbacks of conventional extraction methods such as hard rock mining and brine evaporation. These processes are land intensive, slow, water consumptive, and carbon intensive, underscoring the need for next generation materials that enable selective, circular and sustainable lithium recovery. Zeolite based adsorbents have emerged as strong candidates, due to their crystalline frameworks, tunable pore architectures, ion exchange functionality, and exceptional thermal and chemical stability. This review covers recent advances in natural and synthetic zeolites, and zeolite-based composites for lithium capture, with emphasis on guiding design principles governing Li⁺ adsorption capacity and selectivity, transport behavior, and adsorption mechanisms across diverse feedstocks such as brines, geothermal fluids, seawaters, and battery recycling leachates. Lastly, we discuss current challenges and emerging opportunities that will guide future research aimed at advancing zeolite-based adsorbents toward sustainable, next-generation lithium recovery technologies.

Abstract: Catalyst activity loss reduces both the performance and operating flexibility of industrial sulfur dioxide converters, yet its consequences are rarely assessed beyond conversion decline. This work develops an activity-loss vulnerability framework for a four-bed double- contact SO₂ converter model evaluated against an industrial fresh-catalyst benchmark and applies it to four prescribed activity scenarios (a = 1.0, 0.8, 0.6, 0.4). At the reference inlet-temperature policy, reducing activity from a = 1.0 to a = 0.4 lowered conversion from 99.758% to 96.812%, increased outlet SO₂ slip from 230 to 2960 ppmv, and raised the hotspot from 613.7 to 660.3 °C, exceeding the adopted illustrative limit of 650 °C. Sensitivity, vulnerability, hotspot-risk, and feasible-region maps show that prescribed activity loss progressively shrinks the permissible operating envelope and creates a coupled productivity–emissions–thermal-safety tradeoff. A non-uniform activity profile at the same mean activity as uniform a = 0.6 produced a hotspot 9.3 °C higher, demonstrating that average activity alone is insufficient for thermal-risk assessment. Finally, a scenario-relative Operating Efficiency Reduction Index (OERI) integrates conversion loss, SO₂-slip increase, and thermal-margin loss into an illustrative scenario-screening score. The results show that catalyst activity loss should be assessed as a coupled performance, emissions, and operational-vulnerability problem rather than conversion decline alone.

Abstract: Diesel fuel forensic analysis has been accomplished to ensure the cut obtained from fractional distillation yielded the desired product. The analysis was achieved via Fourier Transform Infrared Spectrometry and Gas Chromatography Mass Spectrometry techniques. Crude oil sample obtained from Tema Oil Refinery was emulsified with sea water. The mixture was cleaned from the seawater and distilled. The cut received from the distillation at about 265 oC and a pure diesel standard sample were sent to Kwame Nkrumah University of Science and Technology chemistry laboratory for the FTIR and GC-MS analysis. The peaks provided by the GC-MS of components from the cut were compared with the peaks of the components of the pure diesel sample. Furthermore, the chemical compositions of the cut were compared with the chemical compositions of diesel samples published by other researchers. Again, the functional groups of the cuts produced by the GC-MS were related to the diesel functional groups retrieved from the publications of other researchers. Additionally, the spectrum of the cuts produced by FTIR were overlayed on the pure diesel sample spectrum for comparison. Based on the similarities of the GC-MS information and the FTIR information, it was concluded that the cut was a diesel.

Abstract: The leaching of chalcopyrite in sulfate or chloride media has been proposed to occur through a combined non-oxidative/oxidative mechanism, where H₂S forms an intermediary species, concurrently with direct oxidative leaching. Some studies have noted that elevated concentrations of Cu(II) improve chalcopyrite leaching in sulfate media. In this study, the role of Cu(II) was investigated in the non-oxidative/oxidative process through electrochemical tests on a chalcopyrite electrode, supported by bulk leach tests. The results of the electrochemical tests are consistent with the formation of H₂S through non-oxidative leaching of chalcopyrite. The H₂S subsequently reacts with Cu(II) to form intermediate cuprous sulfide species, which can be readily oxidized by dissolved oxygen. The bulk leach tests point to a synergy between Cu(II) and O₂, further confirming the catalytic role of Cu(II). The findings support the feasibility of running heap leaching of chalcopyrite-rich ores at elevated copper concentrations in either chloride or sulfate systems.

Abstract: This research aims to study by numerical simulation the optimization of a fed batch bioreactor (FBBR). The main characteristic of this reactor is that it used to produce biomass concentration (X) or a specific product concentration (P). The study of the FBBR is carried out in order to evidence the influence of the stirrer kind on the biomass growing duration inside the reactor. So, in this study, the variable to be minimized is the biomass growing or culture duration (CD) and the parameters influencing the culture duration are some type of stirrer such as Rushton turbin, six inclined blades turbin, helix and anchor. The influence of other parameters were also studied such as the initial biomass concentration (So), the final desired biomass concentration (Xf), the velocity stirring (Vr), the initial biomass concentration (Xo) and the liquid density (mv).. The obtained results show how would be these parameters values in order to minimize the biomass culture duration.