Engineering

Abstract: Thermodynamic equilibrium modeling is a useful approach for predicting gas production during supercritical water gasification (SCWG) of wet biomass; however, Gibbs energy minimization can be computationally demanding for repeated process simulations. This study developed an artificial neural network (ANN) surrogate model to predict the equilibrium yields of H₂, CO, CO₂, and CH₄ during SCWG of açaí residual biomass from Maranhão, Brazil. Four biomass samples collected under different geographical and seasonal conditions were characterized by ultimate analysis and used to generate a thermodynamic database with 1,000 simulations per sample using the TeS-Thermo PyPI Python library. The ANN comprised 10 input variables, two hidden layers with 12 and 6 neurons, and 4 output neurons, and was trained using the Levenberg–Marquardt algo-rithm. The selected ANN achieved R² values of 0.99989, 0.99553, 0.99957, and 0.99963 for H₂, CO, CO₂, and CH₄, respectively. External validation using an independent biomass composition provided evidence of the ANN's generalization capability within the in-vestigated compositional domain, with R² values above 0.98 for all four species. Sensi-tivity analyses further demonstrated that the ANN reproduced the effects of temperature (700–1100 K), water-to-biomass molar ratio (3–6 mol mol⁻¹), and pressure (230–260 bar), with low deviations from TeS-Thermo predictions. These results demonstrate that the ANN provides an accurate and computationally efficient surrogate model for rapid thermo-dynamic screening, sensitivity analysis and process optimization of SCWG biomass processes.

Abstract: The catalytic utilization of carbon dioxide (CO₂) and methane (CH₄) provides a sustainable pathway for the simultaneous conversion of two greenhouse gases into value-added fuels and chemicals. This study presents a steady-state simulation of a dimethyl ether (DME) production process using an integrated three-reactor system developed in ChemCAD. The process comprises dry reforming of methane over a Ni/Al₂O₃ catalyst to generate synthesis gas, catalytic methanol synthesis over a Cu/ZnO/Al₂O₃ catalyst, and methanol dehydration over γ-Al₂O₃ to produce DME. Thermodynamic calculations were performed using the Non-Random Two-Liquid (NRTL) model coupled with the latent-heat enthalpy method, while reactor performance was represented using literature-based Arrhenius kinetic expressions. The downstream process incorporated staged heat recovery, flash separation, gas compression, chilled condensation, and a primary distillation column for crude DME recovery. Under the simulated operating conditions, the integrated process produced 237.05 kg h⁻¹ of crude DME, with the primary distillation column recovering up to 93% of the DME present in the condensed liquid stream, leaving only 0.03 kg h⁻¹ in the column bottoms. The combination of staged compression and low-temperature flash separation significantly enhanced DME recovery by promoting the condensation of condensable species while rejecting non-condensable gases. The proposed process demonstrates the technical feasibility of integrating reaction engineering and separation technologies for efficient DME production from CO₂ and CH₄ and establishes a robust process platform for future optimization and industrial-scale implementation.

Abstract: This study evaluates the feasibility of microbial upcycling of thermoplastic starch-based bioplastics (TPS-BP) by converting them into lactic acid (LA). To enhance the accessibility of the starch fraction within the bioplastic matrix, microwave-assisted pretreatments were optimized using a 2^4⁻1 fractional factorial design. Optimal pretreatment conditions were identified as 150 °C with 0.1% H₂SO₄ for 30 min, which enabled the release of 17.5 g L⁻¹ glucose within 24 h of saccharification. Among the evaluated strains, Heyndrickxia coagulans was identified as the superior producer at pH 6.0, achieving a maximum volumetric productivity of 8.25 g L⁻¹ h⁻¹ and a yield of 0.91 g g⁻¹. To enhance carbon availability and overcome the low starch content (≈20%) of commercial TPS-BP, a co-fermentation strategy with rice straw was implemented. While separate hydrolysis and fermentation (SHF) were limited by carbon catabolite repression, simultaneous saccharification and fermentation (SSF) intensified production. By utilizing TPS-BP pretreatment slurry as the liquid phase for rice straw saccharification, a final LA concentration of 55.1 ± 0.7 g L⁻¹ was achieved. This co-valorization strategy demonstrates a feasible route for integrating bioplastic waste into circular biorefineries while effectively mitigating the seasonal availability of agricultural residues.

Abstract: The efficient recovery of methanol is essential for improving the overall performance and economic viability of integrated carbon dioxide utilization processes. This study presents the process simulation, separation performance and techno-economic assessment of a methanol recovery section within an integrated CO2/CH4 co-valorization process for dimethyl ether production using ChemCAD. A rigorous equilibrium-based distillation model was developed following preliminary shortcut column design to evaluate the recovery of methanol from the methanol-rich stream obtained after dimethyl ether separation. The separation train consisted of flash separation followed by rigorous staged distillation, with operating conditions selected to maximize methanol recovery while maintaining stable column operation. The developed model achieved a methanol recovery of 98.39%, producing 420.73 kg h⁻¹ of methanol in the distillate while effectively rejecting water to the bottoms stream. The selected operating conditions required a reboiler duty of 900.86 MJ h⁻¹ and a condenser duty of 1050.86 MJ h⁻¹, corresponding to a specific energy consumption of 4.64 MJ kg⁻¹ of recovered methanol. Techno-economic analysis estimated a total installed cost of US$312,818, with the distillation column accounting for the largest share of the capital investment. The annual utility cost was estimated at US$118,164, with steam representing more than 90% of the operating expenditure, identifying thermal energy consumption as the principal target for future process optimization. The results demonstrate that the proposed methanol recovery section provides an efficient and economically attractive purification strategy for integrated CO₂ utilization processes while providing a practical basis for future process intensification and industrial scale-up.

Abstract: Vacuum contact drying of small spherical beads in a rotating drum with a hot wall was studied using the discrete element method (DEM). Both the mechanical and thermal interactions between particles were described. The drying rate was supposed to be entirely controlled by heat transfer, either between the particles and the hot wall or between adjacent particles. For modelling purposes, the drying process was divided in three steps: 1) initial heating up of the particles, 2) free liquid water vaporization within the particles at constant temperature, 3) bounded water desorption. The standard EDEM software routines were customized by the authors in order to take into account the coupling between the mass and heat balance of the particle and to handle its water content evolution. The test product was a bed of several hundred, millimetric size, spherical beads made of micro-crystalline cellulose, initially water saturated and frozen. The test dryer was a small scale horizontal rotary drum with a hot peripheral wall. Overall (averaged over all beads) and individual (one singular bead) water content and temperature profiles were simulated. The overall drying rate curve was derived from the average water content time profile. By extracting and plotting the time evolution of the minimal, maximal and average beads water content, the dispersion of beads’ water contents within the bed was globally assessed. For given operating conditions, these simulations can provide the processing time required to obtain a batch where every single particle has a water content below the required limit.

Abstract: Fifth metacarpal shaft fractures account for a large share of hand trauma and often re-quire operative internal fixation, yet conventional dorsal plates and cannulated screws present a stiffness mismatch with native bone and mechanically preclude active, piezo-electric coatings. This study presents the design, fabrication, and functional characteri-sation of a low-profile, 4D piezoelectric dorsal plate for the fifth metacarpal bone. A curved, 0.5 mm plate was modelled in SolidWorks and overlaid with a randomised De-launay lattice in Meshmixer, achieving 73.6% porosity and quasi-isotropic yield behav-iour via a 70% mesh-reduction strategy. Finite element analysis under a 300 N load, using MED610 biocompatible resin properties, confirmed structural integrity with a 4.083 mm peak deflection and no localised buckling. Implants were manufactured by masked stereolithography (Anycubic Photon Mono, 20 μm layers), achieving 98.75% average dimensional accuracy. A barium titanate precursor was synthesised via the propionate route and deposited through a three-cycle, low-temperature submersion process. FTIR confirmed molecular bonding between cations and the polymer matrix, while micros-copy verified a continuous, pore-preserving coating. Under cyclic compressive loading (1–2 N), the implant generated an alternating open-circuit voltage of 0.3–0.7 V. These results demonstrate an accessible stereolithography route to active, self-stimulating or-thopaedic hardware.

Abstract: Zein protein nanoparticles are fabricated in two anionic polysaccharides Sodium carboxymethyl cellulose (CMC) and Xanthan gum (XG) using the anti-solvent method. The rheological behavior and surface-active properties of dispersions of Zein nanoparticles in polysaccharides are investigated. Two sets of experiments are carried out. In one set, the Zein concentration is fixed at 1 wt% and the concentrations of the polysaccharides varied from 0 to 1 wt% in increments of 0.2 wt%. In the second set of experiments, the Zein concentration varies from 1 to 5 wt% at a fixed polysaccharide concentration of 0.5 wt%. The SEM images clearly show the formation of Zein nanoparticles in polysaccharides. Polysaccharide solutions and Zein nanoparticle-polysaccharide dispersions exhibit shear-thinning rheological behavior and follow the power-law model adequately. With the addition of Zein, the consistency of Zein nanoparticle-CMC dispersions increases, and they become more shear-thinning in comparison to pure CMC solutions. With the increase in Zein concentration at a fixed CMC concentration, the consistency rises sharply up to 4 wt% Zein concentration and then drops substantially with further increase in Zein concentration. The addition of Zein to XG solutions exhibits a more complex rheological behavior. The consistency index decreases with the addition of Zein to XG solutions when XG concentration is less than 0.7 wt%. At higher XG concentrations, the consistency index increases with the addition of Zein to XG solutions. With the increase in Zein concentration at a fixed XG concentration, the consistency decreases substantially over the full range of Zein concentration investigated. The surface tension of CMC solutions is strongly affected by the addition of Zein nanoparticles. It decreases substantially with the addition of Zein to CMC solutions. The surface tension behavior of Zein nanoparticle-XG dispersions is like that of Zein nanoparticle-CMC dispersions. The transitions in rheological and surface-active properties of Zein nanoparticle-polysaccharide dispersions are explained in terms of microstructure of the dispersions.

Abstract: Industrial steam methane reforming remains the dominant large-scale route for hydrogen production, yet most reactor models neglect catalyst aging during long operating campaigns or rely on tube wall temperature measurements that are rarely available in continuous operation. This work presents a hybrid phenomenological-empirical model for an industrial top-fired steam methane reformer that integrates a one-dimensional pseudo-homogeneous reactor model with a time-dependent catalyst activity model and an empirical wall temperature model accounting for furnace thermal inertia. Catalyst deactivation was described by a residual activity power-law model with Arrhenius temperature dependence, while the wall temperature was estimated from continuously monitored process variables using exponentially smoothed thermal-state variables. All model parameters were estimated simultaneously from more than 1,000 days of industrial operating data using a hybrid particle swarm optimization and interior-point strategy, and parameter uncertainty was quantified by residual bootstrap. The proposed framework accurately reproduced methane conversion and reformer outlet temperature with mean absolute percentage errors below 5% and negligible systematic bias in outlet temperature throughout the operating campaign, while consistently describing the coupled evolution of furnace thermal response and catalyst aging. The estimated deactivation parameters were consistent with sintering-dominated behavior of Ni-based catalysts. The proposed methodology provides a practical framework for long-term process monitoring, catalyst health assessment, campaign analysis, and predictive maintenance of industrial steam methane reformers.

Abstract: Reverse electrodialysis (RED) is an emerging process intensification technology for sustainable energy generation from the salinity gradient between concentrated brines and dilute streams. Concentrated brines, generated in large volumes by seawater reverse osmosis (SWRO) desalination, mining operations, and saltworks, represent an abundant and underutilised resource whose energetic valorisation via RED can simultaneously reduce brine disposal impacts and contribute to decarbonising the water-energy nexus. This review critically examines existing simulation and modelling approaches for RED systems applied to concentrated brines, covering ion transport models, thermodynamic and exergy frameworks, semi-empirical stack models, multi-physics computational fluid dynamics (CFD), and data-driven machine learning (ML) methods. The review identifies the principal knowledge gaps limiting large-scale deployment: the incomplete description of multicomponent, multivalent ion transport in real brines; the translation of validated laboratory models to pilot and industrial stacks; and the absence of techno-economic and life-cycle analysis integrated with process models. Future research should focus on hybrid models that couple high-fidelity electrochemical simulation with experimental calibration, ML-accelerated parametric studies, and system-level integration of RED with reverse osmosis and membrane distillation. This work provides a structured assessment of current modelling capabilities and a roadmap for simulation-driven optimisation of RED technology.

Abstract: Nanomaterials such as fumed silica nanoparticles and nanocrystalline cellulose are emerging materials with many practical applications. One important application of these emerging materials is in the thickening and modification of the rheology of liquids. In this work, the rheological behavior of hybrid suspensions composed of fumed silica nanoparticles (T30) and nanocrystalline cellulose (NCC) was investigated to understand the combined effects of particle concentration and nanoparticle interactions on steady shear and viscoelastic properties. Steady shear measurements were conducted over a broad range of T30 concentrations, while oscillatory rheology was performed on selected high-silica formulations (7.06 and 8.1 wt% T30). All suspensions exhibited shear-thinning behavior, indicating progressive microstructural breakdown under increasing shear rate. The addition of NCC significantly increased the suspension consistency, suggesting enhanced particle–particle interactions and structural connectivity. Oscillatory measurements revealed elastic-dominated behavior (G'≫G'') across the entirely investigated frequency range for the selected formulations. The incorporation of NCC led to a substantial increase in both storage and loss moduli, with a more pronounced enhancement in the elastic response. In particular, the storage modulus increased by more than one order of magnitude (from ~210 Pa to ~8000 Pa at 1 rad/s), indicating the formation of a strongly interconnected viscoelastic network. The enhanced rheological behavior in hybrid suspensions is attributed to synergistic interactions between fumed silica aggregates and rod-like NCC particles, which promote network formation and mechanical reinforcement. Gap-dependent measurements showed negligible variation in the measured moduli, confirming the reliability of the rheological data. These findings demonstrate that small additions of NCC can transform fumed silica suspensions into strongly interconnected gel-like viscoelastic networks, which can be leveraged to enhance bulk rheological structuring and thickening of liquid systems.

Abstract: We develop a unified analytical framework for steady, fully developed, pressure-driven flow of a Carreau--Yasuda fluid in circular tubes and plane channels. Using the normalized shear rate as the independent parameter, we prove that the induced mapping from shear rate to transverse position is strictly increasing under the stated Carreau–Yasuda parameter assumptions. This establishes the global well-posedness of the parametric velocity representation without requiring pointwise inversion of the nonlinear constitutive relation. We then prove a master integration formula for the family of non-elementary integrals generated by the Carreau--Yasuda law, reducing them through explicit changes of variables to Euler's integral representation of the Gauss hypergeometric function. The master formula yields the complete velocity profile and a finite hypergeometric representation for every nonnegative integer radial moment. Each moment contains exactly one more hypergeometric term than its integer order, with coefficients determined by the binomial structure of the constitutive law. The plane-channel and circular-tube average velocities are obtained from the second- and third-order radial moments, respectively, and are therefore unified by the same moment formula.

Abstract: A practical model to forecast the removal of micropollutants and other chemical Contaminants of Emerging Concern (CECs) in Activated Sludge (AS) systems was developed. Full-scale campaigns were carried out in three AS-WWTPs to evaluate the influence of the Mixed Liquor Suspended Solids (MLSS), Hydraulic Retention Time (HRT), and nitrification conditions. The previously observed sigmoidal correlation between CEC removal and biodegradation rate (k_bio) was validated and a pseudo-first-order kinetic model was adapted to include, in addition to MLSS, HRT, k_bio, a lumped-correction factor ‘a’. The transferability of the approach was further assessed using data from two WWTPs analysed in a previous study. The “a” value ranged from 0.19 (oxidation ditch at a nitrification rate of 5.8 g N-NH₄/(kg VSS·d)) to 0.61 (A2O with 27 g N-NH₄/(kg VSS·d)), suggesting a potential influence of reactor configuration and nitrification activity. This model allows WWTP managers optimizing AS performance and assessing its combination with advanced treatments needed to comply with the 80% removal efficiency for micropollutant indicators set by the revised Urban Wastewater Treatment Directive. Increasing MLSS from 2 to 5 g/L, increases AS removal from 23% to 45% and thus decreases ozone dose from 20 to 12 g/m³.

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.