Abstract

This study investigates the effect of low-salinity waterflooding on enhanced oil recovery, focusing on how different cation types (Na+, Ca2+, Mg2+) and their concentrations influence the interfacial structure and viscoelastic properties of stearic acid monolayers at the oil-water interface. The results demonstrate that low-salinity waterflooding significantly improves microscopic sweep efficiency by enhancing the stability and rigidity of the oil-water interface. This enhancement is achieved through ion-regulated modifications of the interfacial film, particularly through the formation of hydration-bridged structures. Surface pressure-area isotherms, interfacial dilational rheology, and Zeta potential measurements show that the interfacial properties are highly dependent on the type and concentration of cations. Specifically, Mg2+ produces the most significant effects, leading to the highest collapse pressure (53.7 mN·m-1), elastic modulus (19.71 mN·m-1), and a significantly reduced Zeta potential (-13.77 mV), indicating a more stable and rigid interfacial film. These effects are attributed to the stronger interactions between Mg2+ and the carboxyl groups of stearic acid, which promote tighter molecular packing and interfacial elasticity. Furthermore, the increased interfacial elasticity observed at deformation frequencies between 0.025 and 0.1 Hz supports the formation of a viscoelastic nanomembrane that resists localized deformation under flow. This enhanced interfacial structure helps suppress viscous fingering, stabilize the displacement front, and improve displacement efficiency. As a result, low-salinity waterflooding, particularly with optimized cation concentrations, significantly enhances oil recovery by improving microscopic sweep efficiency in heterogeneous reservoirs. The study provides valuable insights into the mechanisms behind low-salinity waterflooding and highlights the critical role of ionic regulation in optimizing oil recovery processes.

Abstract

This study investigates how DC electric fields (0-15 V) regulate interfacial properties and compositional evolution in crude oil–water systems. By integrating IFT and interfacial viscosity measurements with aqueous chemical analysis, SARA fractionation, GC, and FTIR, we reveal correlations between aqueous electrochemistry and molecular restructuring of crude oil. Electrolysis at the cathode increased aqueous pH to 12.97, promoting ionization of native acids and in-situ formation of carboxylates; correspondingly, IFT dropped from 12.63 to 0.08 mN·m-1. Interfacial viscosity decreased sharply with voltage, while SARA and molecular analyses showed depletion of asphaltenes, ~eightfold growth of polar resins, ~9.6% rise in branched alkanes, and ~32% increase in the CH3/CH2 ratio. These coupled aqueous–oil transformations explain the collapse of interfacial film strength under DC electrolysis and suggest a dual mechanism: aqueous alkalinization activates the interface, while electrochemically induced molecular restructuring weakens it. The findings directly inform electrochemical EOR and demulsification strategies.

Abstract

The global promotion of decarbonization and the circular economy (CE) calls for a new perspective on
waste reduction and energy management in an integrated way. Single-use plastics, especially beverage
containers, remain a major contributor to resource inefficiencies and environmental impacts, and life cycle
assessment (LCA) and material flow analysis (MFA) studies have quantified their environmental impact
(Busch et al., 2021; Chairat et al., 2023; Liang et al., 2023). On the other hand, policies such as the EU’s
Single-Use Plastics Directive and the Deposit Return Scheme (DRS) have achieved some results (European
Commission, 2020; OECD, 2022), political conflicts and difficulties in institutional adjustment have become
apparent in the social implementation stage (UK Government, 2024; BBC, 2024). Additionally, IoT-based
technologies such as smart collection devices and refill vending machines enhance resource circulation while
increasing overall facility electricity consumption, creating energy management challenges (Islam et al.,
2021; Ruan et al., 2022). Recent research has shown the effectiveness of integrating CE with energy efficiency
measures (Seljak et al., 2023), but there is a lack of design frameworks that link device-level power loads and
consumer behavior. In this study, we propose the “Material–Energy–Behavior Tri-loop Framework” to fill
this research gap. This framework simultaneously deals with the three elements of (1) material loop, (2) energy
management, and (3) behavior loop, and integrates usage data and energy data through IT and IoT platforms. This will redefine waste reduction from a “resource problem” to a “system design issue that connects energy and action” and provide new design guidelines for researchers and policymakers.

Abstract

Fossil fuel exporters such as Qatar are seeking ways to adapt to a world that aims to shift away from unabated fossil fuels. In this regard, clean hydrogen production is viable for harnessing the nation’s natural resources while addressing environmental concerns. Nonetheless, uncertainties surrounding the hydrogen market add complexity to hydrogen strategy development. Hence, the present study accounts for said uncertainties while deploying a probabilistic approach via a Bayesian Belief Network (BBN) to obtain evidence that can support decision-makers in generating Qatar’s potential hydrogen strategy. Outcomes indicate that if Qatar aims to become a major exporter of clean commodities, its current H2 production will require a minor expansion. However, to position itself as a leading hydrogen exporter, Qatar would need to act more decisively, since several other countries are ahead, as reflected by the 2050 projections, which indicate that Qatar will face less than a 40% probability to satisfy a demand as high as 20 MTPA.

Abstract

Electric vehicle (EV) powertrains predominantly rely on compact, high-density SiC/GaN power modules in traction inverters, on-board chargers, and DC-DC converters, where aggressive drive-cycle transients push local heat flux to 500-1000 W/cm2. These EV-specific duty constraints, tight packaging, weight/volume limits, and reliability under vibration, render conventional single-phase coolants inadequate. This study targets the EV high power electronics incorporating hybrid nanofluid spray cooling by developing a semi-analytical predictive framework for the heat-transfer coefficient (HTC) of hybrid nanofluids (HNFs) for high heat flux. The model embeds synergistic thermophysical effects such as effective conductivity, heat capacity, density/velocity ratios) and is validated against benchmark data for Al2O3-CNT, Al2O3-Ag, CNT-Ag, and GNP-Ag at mixing ratios 0.1-0.9 to 0.9-0.1 and fluxes 500 and 1000 W/cm2. The model achieves adjusted R2 = 94.5% (max R2 = 95.4%) and correctly ranks HNF chemistries for EV conditions; notably, CNT-Al2O3 (0.9-0.1) delivers the highest HTC enhancement among tested systems. By mapping HNF composition to HTC under different spray velocities, the model enables rapid coolant down-selection for EV modules to support miniaturization, lower junction temperatures, and efficiency gains. The contribution bridges material-level formulation and system-level EV thermal design, providing a tractable tool for EV thermal engineers to screen next-generation coolants for electrified drivetrains.

Abstract

This paper outlines the key activities and outcomes of the MINERVA project. This project involves the cooperation of various academic, research, and industrial partners to develop and test hybrid storage architectures for use in high-performance racing vehicles. With this aim, simulation and experimental characterisation tests have been carried out by means of an advanced and interconnected laboratory network. In this case, a bottom-up approach is proposed, starting from a single battery cell up to the whole vehicle level.

Abstract

R290 secondary-loop air conditioning heat pump
systems are a promising alternative for electric vehicles
due to their environmental friendliness and high thermal
efficiency. At ambient temperatures around 0°C, heat
exchangers are prone to frosting, which reduces heating
performance; rapid frost detection can significantly
enhance system efficiency. In this study, a deep learning
based image recognition method was developed for frost
detection in R290 heat pump systems. Experiments were
conducted to observe the frosting process and obtain
heat transfer characteristics. The results indicate that
frosting can be divided into three stages: a sharp decline
in the initial stage, a stable development stage, and a
rapid decrease during the frosting stage. A modified
deep learning approach was used to detect these stages,
achieving over 95% accuracy across different
temperatures after 150 training rounds. These results
demonstrate that the method is reliable and effective
under varying conditions.

Abstract

Currently, China’s oil and gas resources are in a state of long-term shortage, and the technology for oil and gas exploration and development still lags behind that of developed countries. There is a need to intensify research on key technologies to enhance the development efficiency of oil and gas fields, especially those with remaining oil and gas resources. Plunger gas lift technology offers high economic efficiency in the mid-to-late stages of oil and gas reservoir development, but there is still considerable room for improvement in its application. Currently, the primary factors affecting the efficiency of this technology and their interrelationships remain unclear. To investigate the impact of various factors on the efficiency of plunger lift under identical conditions, and based on real physical conditions, not assumptions, a suit of indoor experiment equipment is designed that can measure weight changes of water which lifted from tubing every plunger lift period. According to the experimental data, it can be found that: Through this technology, the efficiency of water drainage and gas production in a single well can be increased from 82% to 90%; The efficiency of plunger lifting is nonlinearly related to the wellbore inclination angle, and there is a minimum efficiency point around 10 °; The average lifting efficiency of the plunger is highest when the diameter is 60mm; PRG has higher efficiency at smaller inclination angles (0 °~20 °).

Abstract

Edge data centres and small server rooms are widely embedded in non-domestic buildings, yet their cooling systems remain energy intensive and under-optimised. This study reports the operational evidence of dew-point cooling (DPC) in a live edge data centre in Hull, the UK. The units feature a heat-and-mass exchanger, high-performance wetting medium, and intermittent water supply. Results from representative operating periods showed that the DPC system delivered stable cooling with low electrical input, achieving a Coefficient of Performance (COP) of up to 40. The monitored hourly profiles also showed important maintenance periods, with a legionella monitoring scheme as a routine risk management. These findings provide evidence to demonstrate that the DPC system is an efficient and practical cooling solution for small edge data centres and support its wider application in similar built environments.

Abstract

This paper addresses the challenges of high injection pressures, difficulty in establishing displacement systems, and low recovery rates in ultra-low permeability reservoirs by proposing an integrated development strategy that combines large-scale complex fracture network fracturing with a COâ‚‚ cooperative injection-production process based on the “injection–shut-in–production” cycle. The approach aims to enhance both oil recovery and COâ‚‚ sequestration potential through reservoir modification and crude oil property regulation. A non-intrusive embedded discrete fracture model (EDFM) is used to accurately represent the complex fracture network in three-dimensional space, overcoming the limitations of traditional methods in multi-scale fracture handling. The paper compares the effects of three development methods: conventional water injection, COâ‚‚ huff-and-puff, and COâ‚‚-water alternating injection (COâ‚‚-WAG). Key parameters such as injection timing, total COâ‚‚ volume, injection rate, and shut-in time are optimized, with carbon sequestration efficiency introduced as a core evaluation index. Simulation results show that cyclic COâ‚‚-WAG can increase recovery by 8.9% compared to conventional water injection. Key mechanisms include: COâ‚‚ reducing oil viscosity and expanding its volume during the shut-in phase, water injection controlling COâ‚‚ flow and expanding sweep volume, and periodic injection–shutdown operations restoring fracture conductivity and maintaining reservoir pressure. This method improves fluid exchange between fractured and unfractured zones, reducing recovery discrepancies. Optimized injection gas rates and timing can delay production decline and reduce fracture closure risks. From a carbon sequestration perspective, the optimized COâ‚‚-WAG scheme improves both oil recovery and COâ‚‚ sequestration efficiency, achieving synergistic optimization. This study offers an integrated method for ultra-low permeability tight oil reservoirs, providing a reliable pathway for green and efficient development.