Accurate prediction of the rheological behavior of heavy crude oil mixtures is essential for pipeline transport under cold climate conditions. This study presents a physically based non-Newtonian rheological model that incorporates the coupled effects of temperature and mixture composition through temperature- and concentration-dependent expressions for the consistency coefficient and flow behavior index. The model was calibrated and validated using 88 experimental rheological measurements on binary mixtures of heavy Severo-Komsomolskoye and light Vankor crudes over a temperature range of 5C–60 °C, heavy-oil concentrations of 0%–100%, and shear rates of 1–300 s -1 . The proposed model predicts shear stress with a mean relative deviation of 8.7% and a root mean square error below 0.95 Pa, outperforming conventional Arrhenius, Refutas, and classical power-law correlations by a factor of 2–3. The model accurately captures the transition from non-Newtonian to near-Newtonian behavior with increasing temperature and dilution, providing a practical tool for hydraulic calculations and flow assurance design in cold-region pipeline systems.

Increasing environmental concerns caused by vehicular emissions have intensified the search for the design and development of non-noble metal catalysts for catalytic converter devices as potential replacements for conventional Pt-, Pd-, and Rh-based noble metal catalysts. This research highlights the development and evaluation of an alternative to conventional catalysts through the synthesis of non-noble metal perovskite-based catalysts and the design modification of a catalytic converter. A non-noble metal catalyst, La 0 . 8 Sr 0 . 2 Co 0 . 8 Fe 0 . 2 O 3 (LSCF), was synthesized by co-precipitation, coated onto a ceramic monolith of a catalytic converter, and examined for effectiveness under petrol fuel laboratory test setup. The synthesized catalyst was also analyzed using SEM, XRD, and EDX to study surface morphology and confirm the crystal structure. The catalytic converter housing assembly was modified by integrating design modifications and analyzed through computational simulations to investigate velocity profile, pressure distribution, and reaction behavior. Among the three catalytic converter design configurations with diffuser cone angles of 8°, 10°, and 14°, the first was selected as it showed a favorable gas flow pattern, pressure distribution, and velocity profile. The entire module was then experimentally evaluated on a petrol fuel laboratory test setup to assess emission performance under varying loads and speeds. Experimental emission tests revealed a significant reduction in hydrocarbon (HC) and carbon monoxide (CO) emissions compared to engines without a catalytic converter. The results demonstrate that the synthesized La 0 . 8 Sr 0 . 2 Co 0 . 9 Fe 0 . 1 O 3 -δ non-noble metal catalyst, combined with the modified catalytic converter design, effectively reduces vehicular emissions and provides an alternative and practical approach to noble metal catalysts. A noticeable reduction in CO and HC exhaust emissions was achieved using the LSCF catalyst for an automotive catalytic converter.

The government of the state of Espírito Santo, Brazil, has established that minimizing emissions, by considering the natural gas as the best fossil fuel during the energy transition period, and energy efficiency are two of the four strategies for industries to competitively achieve the energy transition and decarbonization. In this framework, a major chocolate factory currently meets its chilled-water demand with electricity from the national grid and its hot-water demand with natural gas boilers. This study evaluates alternative configurations based on the integration of Organic Rankine Cycle (ORC) and/or Vapor Compression Refrigeration (VCR) systems, simultaneously generating electricity, chilled water and/or hot water. Three scenarios are proposed and comparatively evaluated using a 4E (energy, exergy, environmental, and economic) assessment. Thermodynamic and environmental modeling of the current and proposed scenarios was conducted using nominal and operational data, with simulations performed in EES software. Mass, energy, and exergy balances were carried out, along with associated CO 2 emissions. The economic analysis considered both operational costs and capital investments, the latter estimated through parametric equations for equipment sizing and costing. Feasibility indicators were applied, such as payback, net present value (NPV), and internal rate of return (IRR). The results indicate the VCR configuration, without ORC, as the most advantageous performance. This scenario requires an investment of US$ 2,679,612.19, resulting a payback period of 2 years and 3 months, an IRR of 51.40% and achieving the lowest CO 2 emissions (0.467 ton/h) due to the elimination of natural gas boilers, using total electrification of the process. Given the relatively low emission factors of the Brazilian interconnected electric grid and the competitive electricity tariffs, electrification of industrial utilities emerges as the most promising decarbonization pathway. Specifically, in this case, VCR simultaneously produces chilled and hot water with high efficiency and reduced environmental impact. Building on the conclusion that electrification is the most favorable option, new insights for research opportunities arise. Future studies could investigate the use of Photovoltaic Thermal (PVT) hybrid solar collectors for the simultaneous production of electricity and hot water, thereby reducing emissions, as well as the integration of energy storage systems to further enhance emission reductions.

Hydrothermal liquefaction (HTL) is a developing alternative for municipal wastewater sludge management that converts sludge into biocrude oil that can be refined into a liquid transportation fuel for the road, marine, and aviation sectors. A major byproduct of HTL is an aqueous phase (AP) high in ammonia, organic carbon, and potentially toxic compounds. This study investigated the feasibility of disposing AP through discharge into the headworks of conventional activated sludge water resource recovery facilities (WRRFs). Bench-scale, acute inhibition experiments using non-nitrifying mixed liquor indicated that a single AP exposure did not inhibit the specific oxygen uptake rates (SOUR) at pilot- and full-scale dilutions (0.03%–0.4% v/v). In contrast, post-secondary nitrifying mixed liquor showed that SOUR inhibition was linearly correlated to the AP concentration. Chronic AP exposure studies (121 days of operation) in continuous-flow, 2.25-L, non-nitrifying activated sludge reactors also indicated that SOUR was unaffected at the pilot- and full-scale AP dilutions in synthetic wastewater feed. However, repeated-measure linear-mixed models showed statistically significant lower specific dissolved organic carbon (DOC) removal rates and percentage DOC removal associated with higher AP concentration in the influent. At the full-scale AP concentration, removal rates were 25 mg DOC/g TSS-hr less and mean percent DOC removal was 40% lower than controls, despite higher DOC loading to the +AP reactors. Furthermore, ultraviolet transmittance (UVT) in the effluent of these reactors was 93% less than in the controls. The results of this study suggest that while headworks discharge of AP at pilot scale might be feasible, full-scale would require pretreatment of the AP, especially at WRRFs that use ultraviolet disinfection. The lack of detectable inhibition in non-nitrifying activated sludge via batch SOUR tests contrasted with the reduction in DOC removal detected in the continuous reactor studies. This result indicates the value of continuous studies to adequately understand the implications of AP headworks discharge on activated sludge processes. To our knowledge, this study is the first to characterize the effects of chronic exposure of mixed liquor to AP in continuous-flow activated sludge reactors.

Uranium, extensively used in nuclear power generation, military applications, and scientific research, poses significant environmental and human health risks when released into soil due to its radiotoxicity and long half-life. Conventional remediation methods such as chemical leaching, stabilization, and bioremediation often face limitations including high costs, incomplete removal, prolonged treatment durations, and the potential for secondary pollution. In contrast, electrokinetic remediation (EKR) has emerged as a promising in situ technology for addressing uranium-contaminated soils, particularly in low-permeability environments where other methods are less effective. EKR operates by applying an external electric field across the soil matrix, inducing contaminant transport via mechanisms such as electromigration (ionic movement), electroosmosis (bulk fluid flow), and electrophoresis (movement of charged particles). These processes mobilize uranium species toward electrode zones, where they can be collected and removed through various treatment strategies. This review provides a comprehensive overview of recent advances in the application of EKR for uranium remediation, including fundamental transport mechanisms, system design parameters (e.g., electrode materials, electrolyte formulations, voltage gradients), and synergistic approaches such as coupling with phytoremediation and permeable reactive barriers. The role of numerical modeling in predicting system performance and optimizing operational parameters is also highlighted, along with the emerging potential of integrating renewable energy sources to enhance sustainability. Despite encouraging results at laboratory and pilot scales, challenges remain regarding scalability, energy efficiency, electrode longevity, and field deployment under heterogeneous site conditions. Future research should prioritize the development of hybrid systems, site-specific optimization strategies, and robust monitoring frameworks. Overall, EKR represents an environmentally friendly and technically viable solution for the remediation of uranium-contaminated soils, with considerable potential for application in nuclear facility decommissioning and long-term environmental restoration.

-Omics technologies have emerged as powerful tools to uncover cellular diversity within tissues, and the role of cell-cell communication in tissue development, function, and disease. In this review, we will discuss recent advancements in -omics technologies that are used to interrogate the biomolecular mechanisms that underly tissue form and function. We will specifically discuss the application of -omics technologies, along with bioinformatic tools, towards identifying new cell types and cell-cell interactions within native tissues. We will then examine how insights from -omics technologies can inform the design of engineered tissues, particularly through the lens of recapitulating native cell-cell interactions. Finally, we will discuss how -omics can be employed to benchmark and analyze engineered tissues for applications that span fundamental science and translation. Overall, the integration of -omics and tissue engineering will improve our understanding of the roles of cellular diversity and cell-cell communication in regulating tissue health and disease and subsequently inform how cell-cell interactions can be leveraged to design therapies for human health applications.

This study seeks to understand the impact of uncertainties in the solvent property submodel on the design and cost of the solvent-based CO2 capture process. First, a deterministic model of the MEA-based CO2 capture process using the CEMCAP reference cement plant case was developed and validated in the CO2SIM flowsheet simulator. Subsequently, a stochastic approach using the Monte Carlo simulation framework was applied by coupling the validated process model and UQLab, a MATLAB-based uncertainty quantification toolbox. Based on this, the implications of these uncertainties on key performance indicators are derived: CO2 capture ratio, specific reboiler duty, reboiler duty, condenser duty, lean rich heat exchanger duty, and lean and rich loading. Finally, the impact of these uncertainties on equipment design and the CO2 avoidance cost are assessed and discussed. The results show that heat exchanger duty uncertainty falls within the overdesign margin commonly used in engineering practice. However, the CO2 avoidance cost exhibits significant uncertainty linked to solvent properties (∼5.2%) that are mainly linked to uncertainty in the CO2 capture ratio. Hence, a key element in reducing CO2 avoidance cost uncertainty may be to validate suitable absorber height to guarantee, with a reasonable confidence, a 90% capture ratio via pilot testing.

Sorption-enhanced dimethyl ether synthesis (SEDMES) is a powerful technology to produce dimethyl ether (DME) from captured CO2 and renewable H2. In situ water by-product removal by zeolites shifts the thermodynamic equilibrium of the reaction towards product formation. Sorption enhancement proved to provide a single-pass CO2 conversion above 90%. This work presents a modelling study of the SEDMES process to optimize its performance under varying conditions. A universal cycle was designed to fulfil the requirement of continuous DME production as well as feed and purge flows. The cycle design is based on a state-of-the-art pilot plant commissioned by TNO in 2023, located in Petten, The Netherlands. Multiple Pareto fronts were generated to express the trade-offs between DME productivity and carbon selectivity in the SEDMES process for the first time. The impact of such process parameters as operating pressure, cycle duration, amount of inert gases, tube geometry and feed flow rate was analysed. A general trend of increased carbon selectivity and productivity at higher pressure was observed and analyzed under relevant cycle durations. However, this enhanced performance comes with the negative side effect of higher DME loss associated at elevated pressure operation. The SEDMES process proved to be tolerant to high concentrations of inert gases such as N2, reducing the need for extensive pretreatment steps. A lower feed flow rate was found to positively impact carbon selectivity to DME, which is promising for operation under intermittent conditions. Finally, even a minor increase in tube diameter reduced the Gas Hourly Space Velocity (GHSV), enhancing DME selectivity in a manner comparable to the effect of lower feed flow rates. Maximum productivity increases from 2.2 kg/h with 50.2% DME selectivity at 20 bar to 3.6 kg/h with 88.5% DME selectivity at 50 bar. The optimal cycle duration for these points also increased from 113 to 233 min, respectively.

This work investigates the potential of hybrid modelling in the digitalization of the chemical and biochemical industries. Hybrid modelling combines first-principles with data-driven models and is a vital enabler for the knowledge-informed transition to Industry 4.0 and, ultimately, 5.0. By integrating data with mechanistic know-how, hybrid modelling facilitates the implementation of “smart manufacturing”. Although there have been many innovations in the field of machine learning, AI, and cloud computing, the industry is still some distance away from becoming truly digital; this is particularly true in the case of the biochemical industry, which in many ways still is in the industry 3.0 stages. This gap hinders the full realization and benefits of the digital transition, such as easier process optimization, better cost-efficiency balance, and overall improved competitiveness and sustainability. This research delves into documented examples of hybrid modeling in chemical and biochemical engineering research and industries. It aims to illustrate current motivations, implementation challenges, and practical issues that hybrid modeling can address. The goal is to derive the path towards fully implementing hybrid modeling as an effective tool and key enabler for creating true digital twins and successful digitalization.