Eutrophication is a major environmental problem in reservoirs, particularly in mountainous regions where shallow inflows and agricultural runoff increase nutrient loading. Floating Treatment Wetlands (FTWs), as a general nature-based treatment technology, have been investigated for nutrient removal. This study evaluated Floating Treatment Islands (FTIs) for improving water quality in the Zhaveh Dam reservoir, Iran, targeting total phosphorus (TP), total nitrogen (TN), and organic matter. Experiments were conducted under contrasting hydraulic conditions in barrel, pool, canal, and reservoir-edge systems. Results showed reductions in TP, TN, and organic matter, with observed removal efficiencies varying across hydraulic conditions and generally tending to be higher under longer retention times and lower flow conditions. Native species such as Sparganium erectum demonstrated high adaptability and effective nutrient uptake under the tested conditions. The findings indicate that FTIs may provide a sustainable approach for eutrophication control and reservoir water quality improvement. This study presents a comparative multi-condition evaluation of FTIs under contrasting hydraulic conditions in a reservoir transition zone.
Solvents derived from renewable biomass are often viewed as inherently greener and more sustainable alternatives to petrochemicals. However, their bio-origin does not always guarantee these attributes, as they can still be energy-intensive to produce, toxic, and poorly biodegradable, with enduring trade-offs related to land competition, resource use, and technological maturity. This contribution critically examines selected commercial biosolvents for which sufficient life cycle data are available and underscores the need to verify green claims on solvents through a life cycle approach. It further challenges the assumption that structurally identical bio-based solvents are inherently greener, demonstrating that upstream environmental impacts may still occur. Common neoteric solvents, such as ionic liquids and deep eutectic solvents, are also examined, highlighting the importance of measuring unresolved environmental and toxicological data. Furthermore, water, often proposed as a green solvent due to its abundance and ability to dissolve many substances, is discussed, with attention to the challenges associated with its disposal. Ultimately, this article is a call to fill the critical knowledge gap in life cycle solvent data and emphasizes that solvent greenness and sustainability cannot be presumed. Instead, they require a holistic approach that moves beyond reliance on simplified green narratives and integrates rigorous life cycle assessment, ethical feedstock sourcing, and economic viability.
Achieving efficient and stable hydrogen evolution reaction (HER) with earth-abundant electrocatalysts is pivotal for boosting the efficiency of alkaline water electrolysis. Here, we report an oxygen vacancy (O-v)-rich Cu2O/NiO heterostructure, which triggers a peculiar interfacial charge transfer from NiO to Cu2O, creating catalytically active Ni & sup3; (+)-Cu0/+ dual sites to synergistically promote water dissociation and hydrogen adsorption. The Cu2O/NiO heterostructure exhibits a low overpotential of 19.7 mV at 10 mA cm(-)& sup2; with Tafel slope of 36 mV dec(-)& sup1; , outperforming most of the reported catalysts. The anion exchange membrane (AEM) electrolyzer equipped Cu2O/NiO electrode enables 1.78 V to reach 1.0 A cm(-)& sup2; for >200 h of continuous operation. Thorough characterizations including HRTEM/XPS/EPR/XANES and DFT calculations exemplify the interfacial charge transfer dynamics in the Cu2O/NiO heterostructure during HER, offering a new paradigm for rational design of noble metal-free HER electrocatalysts for AEM water electrolysis.
Resource-efficient, low-depth implementations of quantum circuits remain a promising strategy for achieving reliable and scalable computation on quantum hardware, as they reduce gate resources and limit the accumulation of noisy operations. Here, we propose a low-depth implementation of a class of Hadamard test circuits, complemented by the development of a parameterized quantum ansatz specifically tailored for variational algorithms that exploit the underlying Hadamard test framework. Our findings demonstrate a significant reduction in single- and two-qubit gate counts, suggesting a reliable circuit architecture for noisy intermediate-scale quantum devices. Building on this foundation, we tested our low-depth scheme to investigate the expressive capacity of the proposed parameterized ansatz in simulating nonlinear Burgers' dynamics. The resulting variational quantum states faithfully capture the shockwave feature of the turbulent regime and maintain high overlaps with classical benchmarks, underscoring the practical effectiveness of our framework. Furthermore, we evaluate the effect of hardware noise by modeling the error properties of real quantum processors and by executing the variational algorithm on a trapped-ion-based IBEX Q1 device. The outcomes of our demonstrations highlight the resilience of our low-depth scheme in the turbulent regime, consistently preparing high-fidelity variational states that exhibit strong agreement with classical benchmarks. Our work contributes to the advancement of resource-efficient strategies for quantum computation, offering a robust framework for tackling a range of computationally intensive problems across numerous applications.
