Third-party food delivery services (TPFDs) have reshaped how consumers experience restaurant meals. Although a substantial body of research on TPFDs exists, measurement of the Off‑Premise Dining Experience (OPDineX) remains fragmented across levels of abstraction in variables measured (high-order vs attribute-based), discrete journey stages, and measures from other contexts. Addressing this gap, this study develops and validates the OPDineX scale as a unified, journey‑based measure capturing customers’ holistic experience with salient attributes across pre‑meal, in‑meal, and post‑meal phases. The study followed a four-stage scale development process, and qualitative item generation and refinement were combined with four quantitative studies conducted in Australia and Singapore. The resulting OPDineX scale comprises eight dimensions and demonstrates strong reliability, convergent, discriminant, and predictive validity, as well as measurement invariance across contexts. By operationalising customer experience at the attribute level while preserving a coherent journey structure, OPDineX advances the measurement of customer experience and provides a robust diagnostic tool for TPFD research and managerial decision‑making.
Coal gasification fine slag (CGFS) contains considerable residual carbon, but its separation is challenging due to fine particle size and complex phase associations. This study compares conventional flotation and enhanced gravity separation for CGFS, integrating response surface methodology and machine learning to predict combustible recovery and analyze parameter effects. Results show that flotation achieved only similar to 54% combustible recovery even at high reagent dosages, while enhanced gravity separation reached up to 96.8% under optimized conditions (20 Hz frequency, 0.020 MPa pressure, 30 g/L solid concentration). Fuerstenau curves confirm higher separation efficiency (1.587 vs. 1.288) for gravity separation. The machine learning model achieved superior prediction accuracy (R-2 = 0.95) compared to RSM (R-2 = 0.85), revealing parameter influence order: frequency > pressure > concentration. This study demonstrates that enhanced gravity separation offers a reagent-free, highly effective alternative for CGFS upgrading, while data-driven modeling provides significant advantages over conventional regression methods for complex separation processes.
In-situ hydrogen (H2) generation accompanying carbon dioxide (CO2) mineralization in basalt offers a promising dual pathway for renewable energy generation and geological carbon storage. Currently, the interactive effects of thermodynamics, hydrochemistry, and reservoir parameters on CO2 sequestration and H2 generation mechanisms remain unclear. Therefore, a two-dimensional multiphysics reactive transport model, combined with an L25(56) orthogonal design, is developed to assess the sensitivity of six key factors (porosity, horizontal permeability, permeability anisotropy ratio, temperature, pressure, and pH) on the coupled CO2 mineralization-H2 production process. Simulations reveal that the injected CO2 induces the dissolution and redox reactions of Fe-rich minerals (e.g., olivine), generating substantial in-situ H2 while converting CO2 into stable carbonate minerals (e.g., magnesite and siderite). The spatial distribution of these reactions is controlled by the acidic fluid migration. Sensitivity analysis indicates that reservoir temperature is the primary controlling factor for both CO2 mineralization efficiency and total H2 production, with statistical significance far exceeding other factors. pH serves as a critical secondary factor for H2 output, where acidic environments significantly enhance H2 generation. Reservoir pressure determines the H2 phase transition behavior by regulating the solubility threshold. Furthermore, porosity exhibits distinct control effects: it correlates negatively with CO2 mineralization, while adequate porosity is a prerequisite for the formation of free-phase H2 gas caps. This study demonstrates that the optimal geological conditions for CO2 mineralization and H2 production do not fully overlap, providing a differentiated scientific basis for engineering site selection to balance carbon reduction and energy production.
Underground hydrogen storage (UHS) in depleted gas fields offers a promising solution for addressing the intermittency of renewable energy at the GWh-TWh scale. However, due to the inevitable mixing between injected hydrogen and residual methane, accurately predicting mixture composition during hydrogen cycling is crucial. In this study, we modelled hydrogen cycling and quantified the effects of gravity segregation, molecular diffusion, and mechanical dispersion on mixture composition. Two synthetic three-dimensional reservoir models with dip angles of 3 degrees and 15 degrees were simulated using a commercial reservoir simulator. Results show that gravity segregation drives hydrogen upward, causing a contamination from the remaining methane. Molecular diffusion plays a minor role in hydrogen purity due to its slow kinetics, while mechanical dispersion contributed to local mixing near the wellbore without significantly affecting cycle-averaged hydrogen purity. A steeper dip angle (15 degrees vs. 3 degrees) promotes hydrogen confinement near the crest, increasing purity and recovery factor by 10% (reaching 70%) after 10 cycles. Moreover, higher injection rates (10 & times; base) or thinner formations (40 m vs. 100 m) can improve purity by up to 20% by suppressing gravitational effects, rendering dip angle irrelevant under such conditions. These findings provide practical guidance for optimizing UHS operations, underscoring the importance of integrating reservoir geometry, formation thickness, and injection strategy in maximizing hydrogen purity during cyclic storage.
To address the high carbon emissions associated with traditional preparation of inorganic solidified foam used in coal mines, the present study developed a fully solid waste-based alkali-activated Janus-type solidified foam (WAJF) for preventing spontaneous combustion of coal. To this end, ground granulated blast furnace slag (GGBS) and fly ash (FA) were used as precursors, whereas liquid sodium silicate (LSS) was employed as an alkali activator. Additionally, highly stable aqueous foam (AF) was used as an expanding agent. First, highly stable Janustype foams were screened under alkaline conditions (pH of 9.54). Second, the effects of LSS modulus and content of Na2O were investigated on the fluidity, setting time, and compressive strength of WAJF. The results showed that the aqueous foam prepared from hydrophilic polyvinyl alcohol (PVA) and H18 hydrophobic nano-SiO2 (content of 1.4 wt%) did not incur any precipitation after 24 h, exhibiting the largest normalized foam volume, the smallest change in the bubble size, and the longest stability time. The study also found that the amount of C (N)-A-S-H gel increased with the increase in the content of Na2O. As the modulus increased from 1.2 to 1.5 and then further to 1.8, the content of C(N)-A-S-H first increased and then decreased. More specifically, at M1.5N6, the maximum compressive strength of WAJF was 12.71 MPa. Meanwhile, the intensity normalized cost of WAJF was 49.26 CNY & sdot;m-3 & sdot;MPa-1, whereas the intensity normalized carbon emissions were 17.93 kg & sdot;m-3 & sdot;MPa-1. Moreover, ESR results showed that, compared with raw coal, the free radical concentration (Ng) of coal samples treated with M1.5N6 WAJF was reduced, with a maximum reduction of 28.19% at 20 degrees C. This study provides a new paradigm for the development of low-carbon solidified foams to prevent spontaneous combustion of coal.
