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Abstract Formation of mineral scale on a material surface has profound impact on a wide range of natural processes as well as industrial applications. However, how specific material surface characteristics affect the mineral-surface interactions and subsequent mineral scale formation is not well understood. Here we report the superior resistance of hexagonal boron nitride ( h BN) to mineral scale formation compared to not only common metal and polymer surfaces but also the highly scaling-resistant graphene, making h BN possibly the most scaling resistant material reported to date. Experimental and simulation results reveal that this ultrahigh scaling-resistance is attributed to the combination of h BN’s atomically-smooth surface, in-plane atomic energy corrugation due to the polar boron-nitrogen bond, and the close match between its interatomic spacing and the size of water molecules. The latter two properties lead to strong polar interactions with water and hence the formation of a dense hydration layer, which strongly hinders the approach of mineral ions and crystals, decreasing both surface heterogeneous nucleation and crystal attachment. 

Tailoring interactions between a target ion and polymer can lead to highly precise ion separations for ultrathin membranes. 

Water and wastewater infrastructure worldwide faces unprecedented demand and supply conflicts that require unconventional solutions. In this study, we develop a novel modelling framework to assess the environmental and economic implications of a hybrid water supply system that supplements a centralized surface water supply with distributed direct potable reuse (DPR) of municipal wastewater, as a strategy to address such challenges. The model is tested with real water and wastewater systems data from the City of Houston, Texas. Results show that supplementing the conventional centralized water supply with distributed DPR would reduce water age in the drinking-water distribution network and hence improve water quality; properly designed system configurations attain system-wide net energy savings even with the high energy consumption of existing technologies used for advanced treatment of the wastewater. A target energy efficiency for future advanced treatment technologies is identified to achieve net energy saving with all hybrid system configurations. Furthermore, distributed DPR remains financially competitive compared with other unconventional water supply solutions. The modelling framework and associated databases developed in this study serve an important research need for quantitatively characterizing distributed and hybrid water systems, laying the necessary foundation for rational design of integrated urban water systems. 

Abstract It is widely acknowledged that distributed water systems (DWSs), which integrate distributed water supply and treatment with existing centralized infrastructure, can mitigate challenges to water security from extreme events, climate change, and aged infrastructure. However, it is unclear which are beneficial DWS configurations, i.e., where and at what scale to implement distributed water supply. We develop a mesoscale representation model that approximates DWSs with reduced backbone networks to enable efficient system emulation while preserving key physical realism. Moreover, system emulation allows us to build a multiobjective optimization model for computational policy search that addresses energy utilization and economic impacts. We demonstrate our models on a hypothetical DWS with distributed direct potable reuse (DPR) based on the City of Houston's water and wastewater infrastructure. The backbone DWS with greater thanlink and node reductions achieves satisfactory approximation of global flows and water pressures, to enable configuration optimization analysis. Results from the optimization model reveal case‐specific as well as general opportunities, constraints, and their interactions for DPR allocation. Implementing DPR can be beneficial in areas with high energy intensities of water distribution, considerable local water demands, and commensurate wastewater reuse capacities. The mesoscale modeling approach and the multiobjective optimization model developed in this study can serve as practical decision‐support tools for stakeholders to search for alternative DWS options in urban settings.