Graphene, a two-dimensional (2D) carbon nanomaterial, has attracted worldwide attention owing to its fascinating properties. One of critical bottlenecks on some important classes of applications, such as printed electronics, conductive coatings, and composite fillers, is the lack of industrial-scale methods to produce high-quality graphene in the form of liquid suspensions, inks, or dispersions. Since 2008, when liquid-phase exfoliation (LPE) of graphene via sonication was initiated, huge progress has been made in the past decade. This review highlights the latest progress on the successful preparation of graphene in various media, including organic solvents, ionic liquids, water/polymer or surfactant solutions, and some other green dispersants. The techniques of LPE, namely sonication, high-shear mixing, and microfluidization are reviewed subsequently. Moreover, several typical devices of high-shear mixing and exfoliation mechanisms are introduced in detail. Finally, we give perspectives on future research directions for the development of green exfoliation media and efficient techniques for producing high-quality graphene. This systematic exploratory study of LPE will potentially pave the way for the scalable production of graphene, which can be also applied to produce other 2D layered materials, such as BN, MoS₂, WS₂, etc.

Urban water distribution systems face growing challenges from energy inefficiencies caused by hydraulic anomalies, such as pipe aging, bursts, demand variability, and suboptimal pump and valve operations. This review systematically evaluates current technologies for energy-efficient management of WDNs under such conditions, structured around both basic and applied technologies. Basic technologies include real-time monitoring, data acquisition, and hydraulic modeling with CFD simulation. Applied technologies focus on demand forecasting, pressure management for energy optimization, and leakage anomaly detection. Case studies demonstrate the practical value of these approaches. Despite recent advances, challenges persist in data interoperability, real-time optimization complexity, scalability, and forecasting uncertainty. Future research should emphasize adaptive AI algorithms, integration of digital twin platforms with control systems, hybrid optimization frameworks, and renewable energy recovery technologies. This review provides a comprehensive foundation for the development of intelligent, energy-efficient, and resilient urban water distribution systems through integrated, data-driven management strategies.