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.

As hydrogen gains momentum as a clean and versatile energy carrier for decarbonizing hard-to-abate sectors, ensuring the safety of hydrogen infrastructure becomes critical for its widespread adoption. This review draws on peer-reviewed literature, industrial reports, and international standards for hydrogen technologies. It systematically examines safety risks across the hydrogen value chain, from production to end-of-life and assesses the effectiveness of existing mitigation strategies as well as identifying key research gaps. Common risks such as hydrogen leaks, over-pressurization, and material degradation are present at nearly every stage. Less frequent but potentially severe hazards include the risk of ice formation or equipment damage from cryogenic hydrogen leaks, and toxic exposures from chemical carriers like ammonia or hydrides used for hydrogen storage and transport. The mitigation technologies evaluated include leak detection systems, quick-release valves, emergency ventilation, and both material-based and physical barrier systems. While these safety solutions provide considerable protective potential, their long-term effectiveness depends on real-time responsiveness, and regulatory enforcement. The review also highlights critical gaps in predictive modeling, material durability under extreme conditions exacerbated by climate change, and human error analysis. Emerging technologies, such as AI-enabled safety systems and digital twins, remain underexplored, and current hydrogen safety frameworks have a limited understanding of hydrogen combustion behavior and effective fire suppression strategies. To support the safe and scalable deployment of hydrogen infrastructure, the study calls for targeted research, stakeholder education, and harmonized safety standards. This review provides a timely synthesis of risks and controls to guide future development, policy, and innovation in hydrogen safety. This review will support industry stakeholders, and researchers in developing safer, more reliable, and standardized hydrogen infrastructure.

The increasing demand for sustainable wastewater treatment methods has driven interest in biochar as an economical and eco-friendly adsorbent. Among various biomass sources, mesquite, an invasive species prevalent in arid and semi-arid areas represents a renewable yet underexploited material for biochar synthesis. This review critically examines the use of mesquite-based biochar for wastewater purification. Particular attention is given to how production parameters, including pyrolysis temperature, heating rate, and particle size, influence material properties and treatment performance reported in the literature. Mesquite biochar displays high surface area generally ranging from 50 to >800 m2/g, alkalinity, and porosity, facilitating the effective removal of heavy metals, organic contaminants, and nutrients through mechanisms like electrostatic attraction, ion exchange, and surface complexation. Chemical activation, especially using alkaline agents, further enhances its adsorption efficiency. However, adsorption performance varies considerably between studies, largely due to differences in production conditions and the absence of consistent testing methodologies. In addition to pollutant elimination, mesquite biochar aids in carbon sequestration and soil fertility improvement, contributing to wider ecological benefits. Economic feasibility and sustainability considerations are also discussed, alongside persistent research gaps related to large-scale production, regeneration efficiency, and long-term use. Overall, mesquite biochar shows strong potential as a sustainable and efficient adsorbent for wastewater management, supporting global goals for resource recovery and circular economy. The development of metal-modified biochars with iron functionalization represents a new direction for wastewater treatment because these systems combine adsorption with redox and photocatalytic functions.

The epoxidation of allyl alcohol with H 2 O 2 over titanium silicalite-1 (TS-1) is an environmentally friendly route for producing glycidol. However, the catalytic activity and stability of TS-1 is not satisfactory. In this study, strip-shaped TS-1 was hydrothermally treated by TPAOH solution, change theTi coordination states and diffusion property, thereby enhancing its catalytic performance. The influences of TPAOH concentration and treating time on the physical chemical property and catalytic performance were studied systematically. It was found that the SiO 2 agglomerant was dissolved and crystallized during the treatment, resulting in an increased Si content on the external surface. The tetrahedrally coordinated Ti was transformed to pentahedrally and octahedrally coordinated Ti, which possess higher catalytic activity for selective oxidation. The treatment also leads to the formation of cavities in the TS-1 crystals, which can shorten the diffusion pathway of substates and improve the diffusion property. Both the chemical property and microstructure enhance the catalytic activity for allyl alcohol epoxidation.

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.

Accurately modeling steady-state two-phase flow is critical for the design and operation of systems in the oil and gas industry; however, traditional models often struggle to adapt to specific field conditions. This study introduces a novel, end-to-end differentiable framework that integrates physics-informed neural networks with a Neural Ordinary Differential Equation (Neural ODE) formulation to predict pressure and temperature profiles. By leveraging automatic differentiation, the entire simulation functions as a trainable model, allowing for the simultaneous optimization of data-driven components and the automated tuning of physical parameters directly from field data. Our results demonstrate that this approach achieves superior accuracy in pressure prediction compared to tuned industry-standard correlations. We found that a transfer learning strategy, pretraining on a large experimental dataset to establish a robust physical foundation, followed by fine-tuning on sparse field data, significantly outperforms models trained on field data alone. Furthermore, the differentiable nature of the framework enabled seamless application to inverse problems, demonstrated via Randomized Maximum Likelihood (RML) for uncertainty quantification. These findings illustrate the effectiveness of bridging the domain gap between experimental and real-world conditions, presenting a powerful new paradigm for creating self-calibrating, data-driven simulation tools with significant potential for digital twin applications.

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.

Industrial plate heat exchangers for cooling of complex, condensing gas mixtures are possible to operate in a self-cleaning mode if a stable flow of small, spherical-like, motile drops can be realized over the heat transfer surfaces. Here, we investigate the effects of adding an amphiphilic component (benzoic acid) to a pure air/water system in terms of providing the necessary prerequisites for such a functionality. The equilibrium apparent (static) advancing and receding contact angles are measured experimentally at varying inclinations and used to inform multiphase direct numerical simulations using the Volume-of-Fluid method. The simulations enable quantification of the distortion of drops caused by the combined gas-liquid-plate interaction in the presence of flow. It is found that the addition of benzoic acid lowers the apparent contact angles, and that the magnitude of this effect is dependent on the plate surface treatment – being more pronounced on a hydrophobically modified plate than on a hydrophilically modified one. The addition of benzoic acid increases the wetting of the drop on the surface and decreases the flow-exposed gas-liquid interface, although both these effects are relatively modest in magnitude. It is suggested that two-phase heat exchangers relying on self-cleaning mechanisms are relatively immune to the presence of low concentrations of amphiphilic impurities that are chemically similar to benzoic acid. The present work thus highlights the role of combined experimental-numerical approaches to gain insight into process phenomena that are not readily amenable to only experiments or only modeling.

Methanol synthesis is one of the most hydrogen-intensive chemical processes, making its decarbonization a critical step toward climate-aligned chemical production. In this study, Aspen Plus® process simulation and techno-economic assessment (TEA) were applied to evaluate and compare four hydrogen production configurations for natural-gas-based methanol synthesis with capacity of 5,000 tons/day: (i) a conventional partial oxidation (POx)- water-gas shift reaction (WGS) base case, (ii) advanced reforming of methane (ARM) with integrated CO 2 utilization and multi-walled carbon nanotube (MWCNT) co-production, (iii) methane pyrolysis coupled with reverse water–gas shift reaction (RWGS), and (iv) POx supplemented with renewable hydrogen and oxygen from alkaline water electrolysis (AWE). Each configuration was assessed for syngas composition, carbon intensity (CI), capital and operating expenditures, net present value (NPV), internal rate of return (IRR), levelized cost of fuel (LCOF), and marginal abatement cost (MAC). Both ARM and Methane Pyrolysis + RWGS achieved net-negative CI (−0.47 and −0.57 kg CO 2 /kg MeOH, respectively), while AWE + POx reduced CI by 75% compared with the baseline and exhibited the lowest indirect emissions. ARM provided the highest profitability (NPV ≈ $20.2 B, IRR ≈ 118%/year) due to MWCNT revenues, whereas AWE-integrated delivered the lowest LCOF (≈$296/ton) and a negative MAC (≈−$137/ton CO 2 e), representing a cost-saving “no-regrets” decarbonization pathway. Methane pyrolysis and RWGS offered the deepest CO 2 reduction but were more sensitive to natural gas and electricity prices. These results identify clear deployment niches: ARM in regions with robust carbon co-product markets, methane pyrolysis + RWGS where CO 2 supply is abundant and valorization is feasible, and AWE-integrated where low-cost renewable electricity is accessible. Two-way sensitivity maps further delineate viability domains as a function of gas and methanol prices, providing a compact decision-support tool for investors.

Gasification is a technology that can produce high-value fuels and chemicals from waste biomass, with challenges mainly associated to energy required and scaling up. At the same time, solar-driven gasification can tackle the problems associated to the energy required by allothermal systems, but its feasibility requires not only technological maturation, but also a strategic location. This work analyses the potential of solar gasification in Mexico using thermodynamic simulations, based on the Gibb’s Free Energy method, and geographical and demographic information. Results indicate that states with large waste biomass production (e.g., Sinaloa and Veracruz) are better suited for solar gasification than states with a large direct normal irradiance (e.g., Sonora), particularly when based on the H 2 /CO ratio of the syngas. An index (Per capita Energy Self-sufficiency Index, PESI) was defined to establish a metric for the potential of different states for solar gasification, and it was found that several states (for example, Sinaloa with 480% and Sonora with 245%) can produce more energy from solar gasification than their per capita consumption.