ACS Engineering Au最新文献

Methanol reforming has emerged as a leading pathway for on-demand hydrogen production, particularly for applications in portable power and fuel cells. This review offers a comprehensive analysis of methanol steam reforming (MSR), partial oxidation (POX), autothermal reforming (ATR), and recent integration strategies with renewable systems and fuel cells. Emphasis is placed on catalyst design, reaction mechanisms, reactors, operational parameters, and recent nanostructured catalyst innovations, such as single-atom catalysts (SACs), bimetallic, carbon nanotubes, perovskites, and alloy nanomaterials. This review critically evaluates recent progress, highlighting how tailored catalyst morphologies, metal–support interactions, and synthesis methods translate into enhanced methanol conversion, H₂ selectivity, and CO suppression. Notably, low-temperature SACs and Zn-modified bimetallic systems exhibit remarkable performance metrics, pointing toward viable pathways for clean hydrogen production. Furthermore, emerging approaches like plasma-assisted dry reforming and chemical looping integration present promising solutions for CO₂ utilization. Recent applications of artificial intelligence (AI) in catalyst screening and reaction modeling also show potential to accelerate the discovery of high-efficiency systems. By synthesizing these findings and identifying the gaps in current research, this review outlines future directions for scalable, low-emission methanol reforming technologies, aiming to support the global transition toward a hydrogen-based energy economy.

Increasing dynamics in surface water bodies and all-time low groundwater levels, both a consequence of global warming, put high stress on the water supply chain and require a re-evaluation of all water uses. Industry uses a significant amount of water for cooling, often in open cooling towers. We developed a digital twin for an evaporative open cooling tower, focusing on the hydrochemistry to optimize water consumption and use of inhibitor chemicals to prevent scaling. The model is based on the USGS hydrochemical standard model PhreeqC, which is controlled by Python scripts. The digital twin implements evaporation in the cooling tower, recharge of water with added inhibitors, and desalination to avoid corrosion. In contrast to previous operation strategies, which rely on a thickening ratio that can be measured using the electrical conductivity, the model allows prediction of the behavior of the cooling tower based on the saturation index for the mineral precipitates. Additionally, the digital twin offers the option of controlling the cooling tower. We present a workflow to adapt the digital twin to the actual cooling tower and to parametrize the chemicals used for the prevention of mineral scaling. The optimization objectives were to reduce the consumption of inhibitors while maintaining stable hydrochemical conditions and a benign corrosion behavior. Additionally, the digital twin should reveal possibilities for demand-driven load balancing. After site-specific adaptation of flow and evaporation rates, volumes, temperatures, and equilibrium constants for the inhibitors, the model was able to forecast the hydrochemical conditions in the cooling tower. The parameter and sensitivity analyses revealed that the total volume of water in the system and the thickening ratio have a large effect on water consumption. While slightly increased concentrations of the inhibitor would allow for significantly higher thickening ratios and slightly lower water consumption, the corrosion stability of the materials in the cooling system puts limits on this approach. Evaporation remains the main factor in water consumption. For the reference site, the digital twin revealed that the implemented operation scheme was already close to optimal conditions, considering water consumption and the use of inhibitors.